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The utilization of lasers in dentistry expands greatly in recent years. For instance, fs-lasers are effective for both drilling and caries prevention, while cw-lasers are useful for adhesive hardening. A cutting-edge application of lasers in dentistry is the debonding of veneers. While there are pre-existing tools for this purpose, there is still potential for improvement. Initial efforts to investigate laser assisted debonding mechanisms with measurements of the optical and mechanical properties of teeth and prosthetic ceramics are presented. Preliminary tests conducted with a laser system used for debonding that is commercially available showed differences in the output power set at the systems console to that at specified distances from the handpiece. Furthermore, the optical properties of the samples (human teeth and ceramics) were characterised. The optical properties of the ceramics should closely resemble those of teeth in terms of look and feel, but they also influence the laser assisted debonding technique and thus must be taken into account. In addition first attempts were performed to investigate the mechanical properties of the samples by means of pump-probe-elastography under a microscope. By analyzing the sample surface up to 20 ns after a fs-laser pulse impact, pressure and shock waves could be detected, which can be utilized to determine the elastic constants of specific materials. Together such investigations are needed to shape the basis for a purely optical approach of debonding of veneers utilizing acoustic waves.
This paper presents a project developed at the K.S.Rangasamy College of Technology (Tamilnadu,India) aimed at designing, implementing, and testing an autonomous multipurpose vehicle with safe, efficient, and economic operation. This autonomous vehicle moves through the crop lines of a Agricultural land and performs tasks that are tedious and/or hazardous to the farmers. First, it has been equipped for spraying, but other configurations have also been designed, such as: a seeding ,plug platform to reach the top part of the plants to perform different tasks (pruning, harvesting, etc.), and a trailer to transport the fruits, plants, and crop waste.
Modern portable electronic devices have seen component heat load increasing, while the space available for heat dissipation has decreased. This requires the thermal management system to be optimized to attain the high performance heat sink. Heat sinks plays a major role for dissipating heat in electronic devices. Phase change material (PCM) is used to enhance the heat dissipation in heat sink. This paper reports the results of an experimental investigation of the performance of Pin fin heat sinks filled with phase change materials for thermal management of electronic devices. The experimental set ups are prepared with the graphical programming language with Lab VIEW (Laboratory Virtual Instruments for Engineering Workbench. Three different types of Pin fin Heat sink with and without PCM are investigated based on different operational timings and the temperature is acquired with the help of Data Acquisition Card (DAQ). The results indicated that the inclusion of the PCM could stabilize the temperature for a longer period and reduce the heating rates and peak temperatures of heat sink with increasing the number of fins can enhance the thermal performance of electronic devices.
Signatures of the optical stark effect on entangled photon pairs from resonantly-pumped quantum dots
(2023)
Two-photon resonant excitation of the biexciton-exciton cascade in a quantum dot generates highly polarization-entangled photon pairs in a near-deterministic way. However, the ultimate level of achievable entanglement is still debated. Here, we observe the impact of the laser-induced ac-Stark effect on the quantum dot emission spectra and on entanglement. For increasing pulse-duration-to-lifetime ratios and pump powers, decreasing values of concurrence are recorded. Nonetheless, additional contributions are still required to fully account for the observed below-unity concurrence.
Strain-induced dynamic control over the population of quantum emitters in two-dimensional materials
(2023)
The discovery of quantum emitters in two-dimensional materials has triggered a surge of research to assess their suitability for quantum photonics. While their microscopic origin is still the subject of intense studies, ordered arrays of quantum emitters are routinely fabricated using static strain-gradients, which are used to drive excitons toward localized regions of the 2D crystals where quantum-light-emission takes place. However, the possibility of using strain in a dynamic fashion to control the appearance of individual quantum emitters has never been explored so far. In this work, we tackle this challenge by introducing a novel hybrid semiconductor-piezoelectric device in which WSe2 monolayers are integrated onto piezoelectric pillars delivering both static and dynamic strains. Static strains are first used to induce the formation of quantum emitters, whose emission shows photon anti-bunching. Their excitonic population and emission energy are then reversibly controlled via the application of a voltage to the piezoelectric pillar. Numerical simulations combined with drift-diffusion equations show that these effects are due to a strain-induced modification of the confining-potential landscape, which in turn leads to a net redistribution of excitons among the different quantum emitters. Our work provides relevant insights into the role of strain in the formation of quantum emitters in 2D materials and suggests a method to switch them on and off on demand.
Synthetic polymers, such as polyamide (PA), inherently possess a moderate number of surface functionalities compared to natural polymers, which negatively impacts the uniformity of metallic coatings obtained through wet-chemical methods like electroless plating. The paper presents the use of a siloxane interlayer formed from the condensation of the hydrolyzed 3-triethoxysilylpropyl succinic anhydride (TESPSA) precursor as a strategy to modify the surface properties of polyamide 6.6 (PA66) fabrics and improve the uniformity of the copper surface coating. The application of the siloxane intermediate coating demonstrates a significant improvement in electrical conductivity, up to 20 times higher than fabrics without the interlayer. The morphology of the coatings was investigated using scanning electron (SEM) and laser confocal scanning microscopy (LSM). In addition, dye adsorption, flexural rigidity, air permeability and contact angle measurements were conducted to monitor the change in the PA66 properties after the siloxane functionalization.
Experimental multi-state quantum discrimination in the frequency domain with quantum dot light
(2022)
The quest for the realization of effective quantum state discrimination strategies is of great interest for quantum information technology, as well as for fundamental studies. Therefore, it is crucial to develop new and more efficient methods to implement discrimination protocols for quantum states. Among the others, single photon implementations are more advisable, because of their inherent security advantage in quantum communication scenarios. In this work, we present the experimental realization of a protocol employing a time-multiplexing strategy to optimally discriminate among eight non-orthogonal states, encoded in the four-dimensional Hilbert space spanning both the polarization degree of freedom and photon energy. The experiment, built on a custom-designed bulk optics analyser setup and single photons generated by a nearly deterministic solid-state source, represents a benchmarking example of minimum error discrimination with actual quantum states, requiring only linear optics and two photodetectors to be realized. Our work paves the way for more complex applications and delivers a novel approach towards high-dimensional quantum encoding and decoding operations.
A quantum-light source that delivers photons with a high brightness and a high degree of entanglement is fundamental for the development of efficient entanglement-based quantum-key distribution systems. Among all possible candidates, epitaxial quantum dots are currently emerging as one of the brightest sources of highly entangled photons. However, the optimization of both brightness and entanglement currently requires different technologies that are difficult to combine in a scalable manner. In this work, we overcome this challenge by developing a novel device consisting of a quantum dot embedded in a circular Bragg resonator, in turn, integrated onto a micromachined piezoelectric actuator. The resonator engineers the light-matter interaction to empower extraction efficiencies up to 0.69(4). Simultaneously, the actuator manipulates strain fields that tune the quantum dot for the generation of entangled photons with fidelities up to 0.96(1). This hybrid technology has the potential to overcome the limitations of the key rates that plague current approaches to entanglement-based quantum key distribution and entanglement-based quantum networks. Introduction
Beyond the Four-Level Model: Dark and Hot States in Quantum Dots Degrade Photonic Entanglement
(2023)
Entangled photon pairs are essential for a multitude of quantum photonic applications. To date, the best performing solid-state quantum emitters of entangled photons are semiconductor quantum dots operated around liquid-helium temperatures. To favor the widespread deployment of these sources, it is important to explore and understand their behavior at temperatures accessible with compact Stirling coolers. Here we study the polarization entanglement among photon pairs from the biexciton–exciton cascade in GaAs quantum dots at temperatures up to ∼65 K. We observe entanglement degradation accompanied by changes in decay dynamics, which we ascribe to thermal population and depopulation of hot and dark states in addition to the four levels relevant for photon pair generation. Detailed calculations considering the presence and characteristics of the additional states and phonon-assisted transitions support the interpretation. We expect these results to guide the optimization of quantum dots as sources of highly entangled photons at elevated temperatures.
In this paper, we consider the question of data aggregation using the practical example of emissions data for economic activities for the sustainability assessment of regional bank clients. Given the current scarcity of company-specific emission data, an approximation relies on using available public data. These data are reported in different standards in different sources. To determine a mapping between the different standards, an adaptation to the Covariance Matrix Self-Adaptation Evolution Strategy is proposed. The obtained results show that high-quality mappings are found. Nevertheless, our approach is transferable to other data compatibility problems. These can be found in the merging of emissions data for other countries, or in bridging the gap between completely different data sets.
This study presents different approaches to increase the sensing area of NiO based semiconducting metal oxide gas sensors. Micro- and nanopatterned laser induced periodic surface structures (LIPSS) are generated on silicon and Si/SiO2 substrates. The surface morphologies of the fabricated samples are examined by FE SEM. We select the silicon samples with an intermediate Si3N4 layer due to its superior isolation quality over the thermal oxide for evaluating the hydrogen and acetone sensitivity of a NiO based test sensor.
Objectives: The MetabQoL 1.0 is the first disease-specific health related quality of life (HrQoL) questionnaire for patients with intoxication-type inherited metabolic disorders. Our aim was to assess the validity and reliability of the MetabQoL 1.0, and to investigate neuropsychiatric burden in our patient population. Methods: Data from 29 patients followed at a single center, aged between 8 and 18 years with the diagnosis of methylmalonic acidemia (MMA), propionic acidemia (PA) or isovaleric acidemia (IVA), and their parents were included. The Pediatric Quality of Life Inventory (PedsQoL) was used to evaluate the validity and reliability of MetabQoL 1.0.
Results: The MetabQoL 1.0 was shown to be valid and reliable (Cronbach's alpha: 0.64–0.9). Fourteen out of the 22 patients (63.6%) formally evaluated had neurological findings. Of note, 17 out of 20 patients (85%) had a psychiatric disorder when evaluated formally by a child and adolescent psychiatrist. The median mental scores of the MetabQoL 1.0 proxy report were significantly higher than those of the self report (p = 0.023). Patients with neonatal-onset disease had higher MetabQoL 1.0 proxy physical (p = 0.008), mental (p = 0.042), total scores (p = 0.022); and self report social (p = 0.007) and total scores (p = 0.043) than those with later onset disease.
Conclusions: This study continues to prove that the MetabQoL 1.0 is an effective tool to measure what matters in intoxication-type inherited metabolic disorders. Our results highlight the importance of clinical assessment complemented by patient reported outcomes which further expands the evaluation toolbox of inherited metabolic diseases.
Whether at the intramolecular or cellular scale in organisms, cell-cell adhesion adapt to external mechanical cues arising from the static environment of cells and from dynamic interactions between neighboring cells. Cell-cell adhesions need to resist detachment forces to secure the integrity and internal organization of organisms. In the past, various techniques have been developed to characterize adhesion properties of molecules and cells in vitro, and to understand how cells sense and probe their environment. Atomic force microscopy and dual-pipette aspiration, where cells are mainly present in suspension, are common methods for studying detachment forces of cell-cell adhesions. How cell-cell adhesion forces are developed for adherent and environment-adapted cells, however, is less clear. Here, we designed the Cell-Cell Separation Device (CC-SD), a microstructured substrate that measures both intercellular forces and external stresses of cells towards the matrix. The design is based on micropillar arrays originally designed for cell traction-force measurements. We designed PDMS micropillar-blocks, to which cells could adhere and be able to connect to each other across the gap. Controlled stretching of the whole substrate changed the distance between blocks and increased gap size. That allowed us to apply strains to cell-cell contacts, eventually leading to cell-cell adhesion detachment, which was measured by pillar deflections. The CC-SD provided an increase of the gap between the blocks of up to 2.4-fold, which was sufficient to separate substrate-attached cells with fully developed F-actin network. Simultaneously measured pillar deflections allowed us to address cellular response to the intercellular strain applied. The CC-SD thus opens up possibilities for the analysis of intercellular force detachments and sheds light on the robustness of cell-cell adhesions in dynamic processes in tissue development.
Power plant operators increasingly rely on predictive models to diagnose and monitor their systems. Data-driven prediction models are generally simple and can have high precision, making them superior to physics-based or knowledge-based models, especially for complex systems like thermal power plants. However, the accuracy of data-driven predictions depends on (1) the quality of the dataset, (2) a suitable selection of sensor signals, and (3) an appropriate selection of the training period. In some instances, redundancies and irrelevant sensors may even reduce the prediction quality.
We investigate ideal configurations for predicting the live steam production of a solid fuel-burning thermal power plant in the pulp and paper industry for different modes of operation. To this end, we benchmark four machine learning algorithms on two feature sets and two training sets to predict steam production. Our results indicate that with the best possible configuration, a coefficient of determination of R^2 = 0.95 and a mean absolute error of MAE=1.2 t/h with an average steam production of 35.1 t/h is reached. On average, using a dynamic dataset for training lowers MAE by 32% compared to a static dataset for training. A feature set based on expert knowledge lowers MAE by an additional 32 %, compared to a simple feature set representing the fuel inputs. We can conclude that based on the static training set and the basic feature set, machine learning algorithms can identify long-term changes. When using a dynamic dataset the performance parameters of thermal power plants are predicted with high accuracy and allow for detecting short-term problems.
Highly-sensitive single-step sensing of levodopa by swellable microneedle-mounted nanogap sensors
(2023)
Microneedle (MN) sensing of biomarkers in interstitial fluid (ISF) can overcome the challenges of self-diagnosis of diseases by a patient, such as blood sampling, handling, and measurement analysis. However, the MN sensing technologies still suffer from poor measurement accuracy due to the small amount of target molecules present in ISF, and require multiple steps of ISF extraction, ISF isolation from MN, and measurement with additional equipment. Here, we present a swellable MN-mounted nanogap sensor that can be inserted into the skin tissue, absorb ISF rapidly, and measure biomarkers in situ by amplifying the measurement signals by redox cycling in nanogap electrodes. We demonstrate that the MN-nanogap sensor measures levodopa (LDA), medication for Parkinson disease, down to 100 nM in an aqueous solution, and 1 μM in both the skin-mimicked gelatin phantom and porcine skin.
Organic acidurias (OAs), urea-cycle disorders (UCDs), and maple syrup urine disease (MSUD) belong to the category of intoxication-type inborn errors of metabolism (IT-IEM). Liver transplantation (LTx) is increasingly utilized in IT-IEM. However, its impact has been mainly focused on clinical outcome measures and rarely on health-related quality of life (HRQoL). Aim of the study was to investigate the impact of LTx on HrQoL in IT-IEMs. This single center prospective study involved 32 patients (15 OA, 11 UCD, 6 MSUD; median age at LTx 3.0 years, range 0.8–26.0). HRQoL was assessed pre/post transplantation by PedsQL-General Module 4.0 and by MetabQoL 1.0, a specifically designed tool for IT-IEM. PedsQL highlighted significant post-LTx improvements in total and physical functioning in both patients' and parents' scores. According to age at transplantation (≤3 vs. >3 years), younger patients showed higher post-LTx scores on Physical (p = 0.03), Social (p < 0.001), and Total (p =0.007) functioning. MetabQoL confirmed significant post-LTx changes in Total and Physical functioning in both patients and parents scores (p ≤ 0.009). Differently from PedsQL, MetabQoL Mental (patients p = 0.013, parents p = 0.03) and Social scores (patients p = 0.02, parents p = 0.012) were significantly higher post-LTx. Significant improvements (p = 0.001–0.04) were also detected both in self- and proxy-reports for almost all MetabQoL subscales. This study shows the importance of assessing the impact of transplantation on HrQoL, a meaningful outcome reflecting patients' wellbeing. LTx is associated with significant improvements of HrQol in both self- and parentreports. The comparison between PedsQL-GM and MetabQoL highlighted that MetabQoL demonstrated higher sensitivity in the assessment of diseasespecific domains than the generic PedsQL tool.
Long-Term outcome of infantile onset pompe disease patients treated with enzyme replacement therapy
(2024)
Background: Enzyme replacement therapy (ERT) with recombinant human alglucosidase alfa (rhGAA) was approved in Europe in 2006. Nevertheless, data on the long-term outcome of infantile onset Pompe disease (IOPD) patients at school age is still limited.
Objective: We analyzed in detail cardiac, respiratory, motor, and cognitive function of 15 German-speaking patients aged 7 and older who started ERT at a median age of 5 months.
Results: Starting dose was 20 mg/kg biweekly in 12 patients, 20 mg/kg weekly in 2, and 40 mg/kg weekly in one patient. CRIM-status was positive in 13 patients (86.7%) and negative or unknown in one patient each (6.7%). Three patients (20%) received immunomodulation. Median age at last assessment was 9.1 (7.0–19.5) years. At last follow-up 1 patient (6.7%) had mild cardiac hypertrophy, 6 (42.9%) had cardiac arrhythmias, and 7 (46.7%) required assisted ventilation. Seven patients (46.7%) achieved the ability to walk independently and 5 (33.3%) were still ambulatory at last follow-up. Six patients (40%) were able to sit without support, while the remaining 4 (26.7%) were tetraplegic. Eleven patients underwent cognitive testing (Culture Fair Intelligence Test), while 4 were unable to meet the requirements for cognitive testing. Intelligence quotients (IQs) ranged from normal (IQ 117, 102, 96, 94) in 4 patients (36.4%) to mild developmental delay (IQ 81) in one patient (9.1%) to intellectual disability (IQ 69, 63, 61, 3x < 55) in 6 patients (54.5%). White matter abnormalities were present in 10 out of 12 cerebral MRIs from 7 patients.
Measuring what matters
(2023)
Patient reported outcomes (PROs) are generally defined as ‘any report of the status of a patient's health condition that comes directly from the patient, without interpretation of the patient's response by a clinician or anyone else’. A broader definition of PRO also includes ‘any information on the outcomes of health care obtained directly from patients without modification by clinicians or other health care professionals’. Following this approach, PROs encompass subjective perceptions of patients on how they function or feel not only in relation to a health condition but also to its treatment as well as concepts such as health-related quality of life (HrQoL), information on the functional status of a patient, signs and symptoms and symptom burden. PRO measurement instruments (PROMs) are mostly questionnaires and inform about what patients can do and how they feel. PROs and PROMs have not yet found unconditional acceptance and wide use in the field of inborn errors of metabolism. This review summarises the importance and usefulness of PROs in research, drug legislation and clinical care and informs about quality standards, development, and potential methodological shortfalls of PROMs. Inclusion of PROs measured with high-quality, well-selected PROMs into clinical care, drug legislation, and research helps to identify unmet needs, improve quality of care, and define outcomes that are meaningful to patients. The field of IEM should open to new methodological approaches such as the definition of core sets of variables including PROs to be systematically assessed in specific metabolic conditions and new collaborations with PRO experts, such as psychologists to facilitate the systematic collection of meaningful data.
Why do some countries assign a major role to wind energy in decarbonizing their electricity systems, while others are much less committed to this technology? We argue that processes of (de-)legitimation, driven by discourse coalitions who strategically employ certain storylines in public debates, provide part of the answer. To illustrate our approach, we comparatively investigate public discourses surrounding wind energy in Austria and Switzerland, two countries that differ strongly in wind energy deployment. By combining a qualitative content analysis and a discourse network analysis of 808 newspaper articles published 2010–2020, we identify four distinct sets of storylines used to either delegitimize or legitimize the technology. Our study indicates that low deployment rates in Switzerland can be related to the prominence of delegitimizing storylines in the public discourse, which result in a rather low socio-political acceptance of wind energy. In Austria, by contrast, there is more consistent support for wind energy by discourse coalitions using a broad set of legitimizing storylines. By bridging the related but separate literatures of technology legitimacy and social acceptance, our study contributes to a better understanding of socio-political conflict and divergence in low-carbon technological pathways.
A step change is needed in the deployment of renewable energy if the triple challenge of ensuring climate change mitigation, energy security, and energy affordability is to be met. Yet, social acceptance of infrastructure projects and policies remains a key concern. While there has been decades of fruitful research on the social acceptance of wind energy and other renewables, much of the extant research is cross-sectional in nature, failing to capture the important dynamic processes that can make or break renewable energy projects. This paper introduces a Special Issue of Energy Policy which focuses on the neglected topic of the dynamics of social acceptance of renewable energy, drawing on contributions made at an international research conference held in St. Gallen (Switzerland) in June 2022. In addition to introducing these papers and drawing out common themes, we also seek to offer some conceptual clarity on the issue of dynamics in social acceptance, taking into account the influence of time, power, and scale in shaping decision-making processes. We conclude by highlighting a number of avenues of potential future research.
X-ray microtomography is a nondestructive, three-dimensional inspection technique applied across a vast range of fields and disciplines, ranging from research to industrial, encompassing engineering, biology, and medical research. Phasecontrast imaging extends the domain of application of x-ray microtomography to classes of samples that exhibit weak attenuation, thus appearing with poor contrast in standard x-ray imaging. Notable examples are low-atomic-number materials, like carbon-fiber composites, soft matter, and biological soft tissues.We report on a compact and cost-effective system for x-ray phase-contrast microtomography. The system features high sensitivity to phase gradients and high resolution, requires a low-power sealed x-ray tube, a single optical element, and fits in a small footprint. It is compatible with standard x-ray detector technologies: in our experiments, we have observed that single-photon counting offered higher angular sensitivity, whereas flat panels provided a larger field of view. The system is benchmarked against knownmaterial phantoms, and its potential for soft-tissue three-dimensional imaging is demonstrated on small-animal organs: a piglet esophagus and a rat heart.We believe that the simplicity of the setupwe are proposing, combined with its robustness and sensitivity, will facilitate accessing quantitative x-ray phase-contrast microtomography as a research tool across disciplines, including tissue engineering, materials science, and nondestructive testing in general.
Parametric anti-resonance is a phenomenon that occurs in systems with at least two degrees of freedom; this can be achieved by periodically exciting some parameters of the system. The effect of this properly tuned periodicity is to increase the dissipation in the system, which leads to a raising in the effective damping of vibrations. This contribution presents the design of an open-loop control to reduce the settling time using the anti-resonance concept. The control signal consists of a quasi-periodic signal capable of transferring the system’s oscillations from one mode to another mode of the system. The general averaging technique is used to characterize the dynamics, particularly the so-called slow dynamics of motion. With this analysis, the control signal is designed for the potential application of a microelectromechanical sensor arrangement; for this specific example, up to 96.8% reduction of settling time is achieved.
In this work, parametric excitation is introduced in a fully balanced flexible rotor mounted on two identical active gas foil bearings. The active gas foil bearings change the top foil shape harmonically with a specific amplitude and frequency. The deformable foil shape is approximated by an analytical function, while the gas pressure distribution is evaluated by the numerical solution of the Reynolds equation for compressible flow. The harmonic variation of the foil shape generates a respective variation in the bearings’ stiffness and damping properties and the system experiences parametric resonances and antiresonances in specific excitation frequencies. The nonlinear gas bearing forces generate bifurcations in the solutions of the system at certain rotating speeds and excitation frequencies; period doubling and Neimark-Sacker bifurcations are noticed in the examined system, and their progress is evaluated as the two bifurcation parameters (rotating speed and parametric excitation frequency) are changed, though a codimension-2 numerical continuation of limit cycles. It is found that at specific range of excitation frequency there are parametric anti-resonances and the bifurcations collide and vanish. Therefore, a bifurcation-free operating range is established and the system can operate stable at a wide speed range.
Digitalization is changing business models and operational processes. At the same time, improved data availability and powerful analytical methods are influencing controlling and increasingly require the use of statistical and information technology skills and knowledge. Using a case study from marketing controlling, the article shows the use of business analytics methods and addresses the tasks of controlling in the digital age.
By a simple femtosecond laser process, we fabricated metal-oxide/gold composite films for electrical and optical gas sensors. We designed a dripple wavelength AWG-spectrometer, matched to the plasma absorption wavelength region of the composite films. H2/CO absorptions fit well with the AWG design for multi gas detection sensor arrays
Pooled data from published reports on infants with clinically diagnosed vitamin B12 (B12) deficiency were analyzed with the purpose of describing the presentation, diagnostic approaches, and risk factors for the condition to inform prevention strategies. An electronic (PubMed database) and manual literature search following the PRISMA approach was conducted (preregistration with the Open Science Framework, accessed on 15 February 2023). Data were described and analyzed using correlation analyses, Chi-square tests, ANOVAs, and regression analyses, and 102 publications (292 cases) were analyzed. The mean age at first symptoms (anemia, various neurological symptoms) was four months; the mean time to diagnosis was 2.6 months. Maternal B12 at diagnosis, exclusive breastfeeding, and a maternal diet low in B12 predicted infant B12, methylmalonic acid, and total homocysteine. Infant B12 deficiency is still not easily diagnosed. Methylmalonic acid and total homocysteine are useful diagnostic parameters in addition to B12 levels. Since maternal B12 status predicts infant B12 status, it would probably be advantageous to target women in early pregnancy or even preconceptionally to prevent infant B12 deficiency, rather than to rely on newborn screening that often does not reliably identify high-risk children.
Grey Box models provide an important approach for control analysis in the Heating, Ventilation and Air Conditioning (HVAC) sector. Grey Box models consist of physical models where parameters are estimated from data. Due to the vast amount of component models that can be found in literature, the question arises, which component models perform best on a given system or dataset? This question is investigated systematically using a test case system with real operational data. The test case system consists of a HVAC system containing an energy recovery unit (ER), a heating coil (HC) and a cooling coil (CC). For each component, several suitable model variants from the literature are adapted appropriately and implemented. Four model variants are implemented for the ER and five model variants each for the HC and CC. Further, three global optimization algorithms and four local optimization algorithms to solve the nonlinear least squares system identification are implemented, leading to a total of 700 combinations. The comparison of all variants shows that the global optimization algorithms do not provide significantly better solutions. Their runtimes are significantly higher. Analysis of the models shows a dependency of the model accuracy on the number of total parameters.
Purpose – The purpose of this study is to explore the exogenous and endogenous drivers of the high-growth of Unicorn start-ups along their life cycle, with a particular focus on Unicorns in the fintech industry.
Design/methodology/approach – The study employs an explorative longitudinal analysis with a matched pair of two cases of Unicorns start-ups with similar antecedent features to understand holistically drivers over the longer term.
Findings – High-growth patterns over the longer term are the result of a combined industry- and company-life cycle perspective. Drivers and growth patterns vary significantly according to the time of entry in the industry and
its development status. The findings are systematised within a set of propositions to be tested in future research.
Research limitations/implications – The limitations lie in empirical evidence, as the analysis is limited to one matched-pair. The revealed Unicorns’ drivers for long-term growth might encourage future research to further investigate these drivers on a larger scale.
Practical implications – The study offers practical recommendations for start-ups with high-growth ambitions and advice to policy makers regarding the development of tailor-made support programs.
Originality/value – The study significantly extends extant work on growth and high-growth by examining endogenous and exogenous triggers over time and by linking the Unicorn-life cycle to the industry life cycle, an approach which has, to the best of the authors’ knowledge, not yet been applied.
International Entrepreneurship explains the opportunities and challenges facing internationalizing entrepreneurial ventures. The book inlcudes a thorough discussion of fundamentals as well as contemporary research findings. Numerous cases, featuring diverse contexts, illustrate theory and help classroom use.
The main aims of this work are the validation of the developed process of gluing a single-mode optical fiber array with a photonic chip and the selection of a more suitable adhesive from the two adhesives being compared. An active alignment system was used for adjusting the two optical fiber arrays to a photonics chip. The gluing was done by two compared UV curable adhesives applied in the optical path. The insertion losses of glued coupling were measured and investigated at two discrete wavelengths 1310 nm and 1550 nm during temperature testing in the climatic chamber according to Telcordia GR_1209_Corei04 [3]. The measurement, investigation, and comparison of insertion losses of the glued coupling at the spectral band from 1530 nm to 1570 nm were done immediately after gluing process and after three temperature cycles in the climatic chamber with one month delay.
In 2021, a prominent Austria dairy producer suffered from an IT attack and was completely paralysed. Without clearly defined mitigation measures in place, major disruptions were caused alongside the whole supply chain, including logistics service providers, governmental food safety bodies, as well as retailers (i.e., supermarkets and convenience stores). In this paper, we ask the question how digitisation and digital transformation impact IT security, especially when considering the complex company ecosystems of food production and food supply chains in Austria. The problem statement stems from a gap in knowledge of key differences in approaches towards IT security, resilience, risk management and especially business interfaces between food suppliers, supermarkets, distributors, logistics and other service providers. In order to answer related research questions, firstly, the authors conduct literature research, and highlight common guidelines and standardisation as well as look at state-based recommendations for critical infrastructure. In a second step, the paper describes a quantitative and qualitative survey with Austrian food companies (producers and retailers) which is described in detail in the paper. A description of recommended measures for the industry, further steps, as well as an outlook conclude the paper.
Background: Cardiovascular disease is the major cause of death worldwide. Although knowledge regarding diagnosing and treating cardiovascular disease has increased dramatically, secondary prevention remains insufficiently implemented due to failure among affected individuals to adhere to guideline recommendations. This has continued to lead to high morbidity and mortality rates. Involving patients in their healthcare and facilitating their active roles in their chronic disease management is an opportunity to meet the needs of the increasing number of cardio-vascular patients. However, simple recall of advice regarding a more preventive lifestyle does not affect sustainable behavioral lifestyle changes. We investigate the effect of plaque visualization combined with low-threshold daily lifestyle tasks using the smartphone app PreventiPlaque to evaluate change in cardiovascular risk profile. Methods: and study design: This randomized, controlled clinical trial includes 240 participants with ultrasound evidence of atherosclerotic plaque in one or both carotid arteries, defined as focal thickening of the vessel wall measuring 50% more than the regular vessel wall. A criterion for participation is access to a smartphone suitable for app usage. The participants are randomly assigned to an intervention or a control group. While both groups receive the standard of care, the intervention group has additional access to the PreventiPlaque app during the 12-month follow-up. The app includes daily tasks that promote a healthier lifestyle in the areas of smoking cessation, medication adherence, physical activity, and diet. The impact of plaque visualization and app use on the change in cardiovascular risk profile is assessed by SCORE2. Feasibility and effectiveness of the PreventiPlaque app are evaluated using standardized and validated measures for patient feedback.
The production of liquid-gas mixtures with desired properties still places high demands on process technology and is usually realized in bubble columns. The physical calculation models used have individual dimensionless factors which, depending on the application, are only valid for small ranges consisting of flow velocity, nozzle geometry and test setup. An iterative but time-consuming design of such dispersion processes is used in industry for producing a liquid-gas mixture according to desired requirements. In the present investigation, we accelerate the necessary design loops by setting up a physical model, which consists of several subsystems that are enriched by dedicated experiments to realize liquid-gas dispersions with low volume fraction and small air bubble diameters in oil. Our approach allows the extraction of individual dimensionless factors from maps of the introduced subsystems. These maps allow for targeted corrective measures of a production process for keeping the quality. The calculation-based approach avoids the need for performing iterative design loops. Overall, this approach supports the controlled generation of liquid-gas mixtures.
Creating a schedule to perform certain actions in a realworld environment typically involves multiple types of uncertainties. To create a plan which is robust towards uncertainties, it must stay flexible while attempting to be reliable and as close to optimal as possible. A plan is reliable if an adjustment to accommodate for a new requirement causes only a few disruptions. The system needs to be able to adapt to the schedule if unforeseen circumstances make planned actions impossible, or if an unlikely event would enable the system to follow a better path. To handle uncertainties, the used methods need to be dynamic and adaptive. The planning algorithms must be able to re-schedule planned actions and need to adapt the previously created plan to accommodate new requirements without causing critical disruptions to other required actions.
The usage of data gathered for Industry 4.0 and smart factory scenarios continues to be a problem for companies of all sizes. This is often the case because they aim to start with complicated and time-intensive Machine Learning scenarios. This work evaluates the Process Capability Analysis (PCA) as a pragmatic, easy and quick way of leveraging the gathered machine data from the production process. The area of application considered is injection molding. After describing all the required domain knowledge, the paper presents an approach for a continuous analysis of all parts produced. Applying PCA results in multiple key performance indicators that allow for fast and comprehensible process monitoring. The corresponding visualizations provide the quality department with a tool to efficiently choose where and when quality checks need to be performed. The presented case study indicates the benefit of analyzing whole process data instead of considering only selected production samples. The use of machine data enables additional insights to be drawn about process stability and the associated product quality.
Tap or swipe
(2023)
Demand-side management approaches that exploit the temporal flexibility of electric vehicles have attracted much attention in recent years due to the increasing market penetration. These demand-side management measures contribute to alleviating the burden on the power system, especially in distribution grids where bottlenecks are more prevalent. Electric vehicles can be defined as an attractive asset for distribution system operators, which have the potential to provide grid services if properly managed. In this thesis, first, a systematic investigation is conducted for two typically employed demand-side management methods reported in the literature: A voltage droop control-based approach and a market-driven approach. Then a control scheme of decentralized autonomous demand side management for electric vehicle charging scheduling which relies on a unidirectionally communicated grid-induced signal is proposed. In all the topics considered, the implications on the distribution grid operation are evaluated using a set of time series load flow simulations performed for representative Austrian distribution grids. Droop control mechanisms are discussed for electric vehicle charging control which requires no communication. The method provides an economically viable solution at all penetrations if electric vehicles charge at low nominal power rates. However, with the current market trends in residential charging equipment especially in the European context where most of the charging equipment is designed for 11 kW charging, the technical feasibility of the method, in the long run, is debatable. As electricity demand strongly correlates with energy prices, a linear optimization algorithm is proposed to minimize charging costs, which uses next-day market prices as the grid-induced incentive function under the assumption of perfect user predictions. The constraints on the state of charge guarantee the energy required for driving is delivered without failure. An average energy cost saving of 30% is realized at all penetrations. Nevertheless, the avalanche effect due to simultaneous charging during low price periods introduces new power peaks exceeding those of uncontrolled charging. This obstructs the grid-friendly integration of electric vehicles.
Alleviating the curse of dimensionality in minkowski sum approximations of storage flexibility
(2023)
Many real-world applications require the joint optimization of a large number of flexible devices over some time horizon. The flexibility of multiple batteries, thermostatically controlled loads, or electric vehicles, e.g., can be used to support grid operations and to reduce operation costs. Using piecewise constant power values, the flexibility of each device over d time periods can be described as a polytopic subset in power space. The aggregated flexibility is given by the Minkowski sum of these polytopes. As the computation of Minkowski sums is in general demanding, several approximations have been proposed in the literature. Yet, their application potential is often objective-dependent and limited by the curse of dimensionality. In this paper, we show that up to 2d vertices of each polytope can be computed efficiently and that the convex hull of their sums provides a computationally efficient inner approximation of the Minkowski sum. Via an extensive simulation study, we illustrate that our approach outperforms ten state-of-the-art inner approximations in terms of computational complexity and accuracy for different objectives. Moreover, we propose an efficient disaggregation method applicable to any vertex-based approximation. The proposed methods provide an efficient means to aggregate and to disaggregate typical battery storages in quarter-hourly periods over an entire day with reasonable accuracy for aggregated cost and for peak power optimization.
In the era of digital transformation an evolution takes place. Following this, new perspectives concerning leadership are required, especially in virtual teams. Shared Leadership is a promising leadership form to meet the challenges in a virtual team setting. Particularly, studies show that shared leadership increases performance, team creativity and innovative behavior. Moreover, the responsibility is distributed among several, not one individual. Nevertheless, it is unclear, which skills are needed in shared leadership teams and how they could be trained. Therefore, we develop a conceptual framework to pave the way for an empirical inquiry of the skills for and the role of shared leadership. Moreover, we encourage the discussion, whether the current leadership development is still viable and offer practical implications to develop shared leadership.
A model is presented that allows for the calculation of the success probability by which a vanilla Evolution Strategy converges to the global optimizer of the Rastrigin test function. As a result a population size scaling formula will be derived that allows for an estimation of the population size needed to ensure a high convergence security depending on the search space dimensionality.
Effective lead management
(2023)
In the last few years the global interest on lead management has increased. This classic topic for marketing and sales departments is aimed at converting potential customers into sales. The following thesis identifies the challenges and solutions for marketing and sales departments in order to process effective lead management. Using data from a literature review and qualitative empirical research, conducted with representatives of marketing and sales departments, the results showed overall and task specific challenges and solutions. The research indicates that overall challenges and solutions regarding the gap between marketing and sales, new processes and data management including data quality, software and silos emerge. In addition task specific challenges and solutions concerning lead generation including purchased leads, lead qualification, lead nurturing and sales specific challenges and solutions conclusively the focus on existing customers, time famine and lead routing were identified. This thesis provides a framework for further studies regarding the challenges and solutions for marketing and sales departments processing lead management.
The thorny issue of time
(2023)
This study aims to address the research gap surrounding the role of leadership in the formation of high-performance teams within startup companies. While there is existing research on high-performing teams, limited attention has been given to leadership in this environment. To bridge this gap, the study combines a literature review and qualitative analysis through semi-structured interviews with diverse stakeholders in startups, with the goal of providing practical guidance for startup executives based on the research findings. The study uncovers key aspects of leadership in high-performance teams, emphasizing the importance of skills such as motivation and support for team members, fostering psychological safety and trust, and effectively managing uncertainty. In addition to resource constraints and high expectations, the study sheds light on the challenges faced by leaders in startup and high-performance team environments, particularly the blurring of traditional leadership roles as team members seek autonomy and decision-making authority. These findings present opportunities for future research to explore this progressive leadership style. Overall, this study contributes to our understanding of leadership dynamics within high-performance teams operating in the context of startups. It offers valuable insights that can help startup executives navigate the complexities of leadership and foster the development of successful and high-performing teams.
In an oversaturated market, companies are required to use innovative and, above all, creative advertising methods to capture their customers’ attention, and thus differentiate themselves from rival businesses. To this end, companies have been increasingly relying on the use of humor, a phenomenon that remains highly subjective and is perceived differently by each individual. This master’s thesis, which was completed as part of the International Marketing and Sales program at the FH Vorarlberg, focuses on this phenomenon of humor as well as its impact on advertising perception. With the aid of three different theories, the term “humor” is defined. Furthermore, this study explains and researches the so-called vampire effect, wherein various factors (in this case humor) draw attention away from the actual advertising message. In addition, this thesis takes a closer look at involvement, as a person’s involvement or interest in a brand or product can influence brand and product recall and recognition. An online survey was conducted to determine whether the vampire effect caused by humor is able to influence brand and product recall. In other words, this concerns whether the viewer can still remember the brand and product afterward or whether the humor employed triggers the vampire effect. Furthermore, this thesis explored whether the vampire effect caused by humor is able to influence brand and product recognition. Recall is the retrieval of information from memory without direct cues, whereas recognition refers to the recognition of information when it is presented again. Furthermore, within this context, it was discovered that brand and product recall varies with low and high involvement viewers of the advertisement. In other words, this means that the strength of the vampire effect caused by humor changes depending on the strength of the viewer’s involvement. During the course of this research, it was further observed that the humor employed significantly affects the perception of the advertising message, thus confirming the existence of the vampire effect. This effect also influences both brand as well as product recall and recognition. In both cases, participants in the survey were less able to remember the product and brand in the humorous advertising. Furthermore, it was proven that people with low involvement in the advertised product group are more heavily affected by the vampire effect. As such, they are more likely to not remember the product or brand after seeing the advertisement.
The presented master thesis of the study subject International Management and Leadership at the University of Applied Science Vorarlberg in Dornbirn handles the potential future influence of the EU Corporate Sustainability Due diligence on SMEs. First this thesis introduces the most important regulations that might come into place with this Due Diligence Act and gives a theoretical input when and how it will come into place, and also who it will affect directly and who will be affected indirectly. The empirical data resulted of several qualitative expert interviews and a following quantitative research. The expert interviews are split in two different groups, first the topic experts from institutions like chamber of commerce or chamber of labour and second experts from highly successful Austrian companies which are already handling the topic and the future challenges. Expected outcome of the qualitative interviews was a better view on the actual situation especially the impact on small and medium enterprises. On the basis of this results the quantitative survey was produced. In the quantitative survey the goal was to see, how much entrepreneurs and companies in the small and medium sector already are aware of the upcoming legal challenges throughout the supply chain. With all this collected data the practical outcome of this thesis is the Checklist, which helps entrepreneurs to find out if and how much they will be affected by the Act. And finally, the most important part is the Guideline, which introduces first risk assessment tools, that will help companies to prepare for future legislation and bring undoubtedly a certain advantage for the upcoming challenges.
Digital twin as enabler of business model innovation for infrastructure construction projects
(2023)
Emerging technologies and methods are becoming an important element of the construction industry. Digital Twins are used as a base to store data in BIM models and make use out of the data respectively make the data visible. The transparency in all phases of the lifecycle of building and infrastructure assets is crucial in order to get a more efficient lifecycle of planning, construction and maintenance. Whereas other industries increased performance in these phases by making use out of the data, construction industry is stuck in traditional methods and business models. In this paper we propose a concept that focuses on the digital production twin. The comparison of planning data with As-Is production data can empower a data driven continuous improvement process and support the decision making process of future innovations and suitable business models. This paper outlines the possibility to use the data stored in a digital twin with regards to the evaluation of possible business models.
Although workplace climate has been already extensively studied, the research has not led to firm conclusions regarding leadership trainings referring to the awareness of psychological safety in a company and its influence on existing teams and the general work climate. The author used the already existing model of Carr, Schmidt, Ford, & DeShon (2003) and adjusted it with psychological safety as 4th climate item to develop hypothesen which can also be seen as a path analytic model. The model posied that climate affects individual level outcomes through its impact on cognitive and affective states. Therefore, the author wants to show the correlation between the 4 higher order facets of climate affect the individual levels of job performance, psychological well-being and withdrawal through their impact on orangizational commitment and job saitsfaction (Carr, Schmidt, Ford, & DeShon, 2003).
This thesis investigates the role of leadership behaviours of C-level executives in the context of post-M&A integration processes. The primary focus is on understanding the impact of specific leadership behaviours on inspiring desirable follower effects and facilitating emotional acceptance during organizational change. Drawing on the frameworks presented in “Six- Dimension Integrative Model of Leadership” and "The Six Domains of Leadership" developed by Sitkin et al., the study conducts expert interviews with managers from middle management who have recently experienced M&A integration. The answers are analysed in depth to identify the most effective leadership behaviours, highlighting those mentioned most frequently and those capable of triggering multiple follower effects simultaneously. The result is a list of behaviours that can serve as a guideline for C-level executives who want to foster desirable follower effects throughout the M&A integration journey.
Through mandatory ESG (environmental, social, governance) reporting large companies must disclose their ESG activities showing how sustainability risks are incorporated in their decision-making and production processes. This disclosure obligation, however, does not apply to small and medium-sized enterprises (SME), creating a gap in the ESG dataset. Banks are therefore required to collect sustainability data of their SME customers independently to ensure complete ESG integration in the risk analysis process for loans. In this paper, we examine ESG risk analysis through a smart science approach laying the focus on possible value outcomes of sustainable smart services for banks as well as for their (SME) customers. The paper describes ESG factors, how services can be derived from them, targeted metrics of ESG and an ESG Service Creation Framework (business ecosystem building, process model, and value creation). The description of an exemplary use case highlighting the necessary ecosystem for service creation as well as the created value concludes the paper.
The role of entrepreneurs and intrapreneurs in the current zeitgeist is to drive innovation, re-shape rigid, established processes in business as well as for consumers. They use new viewpoints to pioneer new (business) models which focus on ‘smartness’ rather than the purely monetary and short-sighted models of yesteryear. Fostering and supporting the culture of this current zeitgeist is a mayor challenge for entre- and intrapreneurial support infrastructures, namely startup centres and innovation hubs of universities and other public institutions as well as innovation centres of private companies. Hereby, support may range from access to funding over provision of resources such as offices or computing hardware to coaching in the development of business ideas and strategic roadmaps for product and service deployment. In this paper, we focus on describing the status-quo of afore- mentioned support infrastructures in Vorarlberg and the Lake Constance region, then extend the scope to existing (international) approaches for aiding founders and inno- vators in the development of smart services. An analysis of success stories of the Vorarlberg startup centre ‘startupstube’ and other initiatives including their compar- ison to international counterparts builds the basis for a methodological framework for (service science) coaching in entre- and intrapreneurial support infrastructures. The paper is concluded by the description of a framework for choosing the right methods and tools to create service value in entre-/intrapreneurship based upon tested, proven know-how and for defining support infrastructure needs based upon pre-defined stakeholder and target groups as well as the (industry) sectors of the innovators.
In this paper, a 256-channel, 10-GHz arrayed waveguide gratings demultiplexer for ultra-dense wavelength division multiplexing was designed using an in-house developed tool called AWG-Parameters. The AWG demultiplexer was designed for a central wavelength of 1550 nm and the structure was simulated in PHASAR tool from Optiwave. Two different AWG designs were developed and the influence of the design parameters on the AWG performance was studied.
Design, simulation, and optimization of the 1×4 optical three-dimensional multimode interference splitter using IP-Dip polymer as a core and polydimethylsiloxane (PDMS) Sylgard 184 as a cladding is demonstrated. The splitter was simulated by using beam propagation method in BeamPROP simulation module of RSoft photonic tool and optimized for an operating wavelength of 1.55 μm . According to the minimum insertion loss, the dimensions of the splitter were optimized for a waveguide with a core size of 4×4 μm2 . The objective of the study is to create the design for fabrication by three-dimensional direct laser writing optical lithography.
The control measures for the COVID-19 pandemic, early 2020, caused a chain reaction that eventually led to a shortage of components in the electronic manufacturing industry. A lack of components meant that the production and sales were interrupted or even stopped. For many electronic manufacturing firms, this was seen as a crisis. A crisis is mostly divided into three phases called the pre-crisis phase, crisis management and post-crisis phase. The pre-crisis phase involves an environmental assessment and setting up of crisis management teams, and plan. The crisis management phase has to do with the collection and interpretation of information and the mitigation of the crisis. The post-crisis phase looks at learnings from the crisis. In this paper it was investigated how the electronic manufacturing firms in Vorarlberg managed the crisis in the period between 2020 and 2022. The overall aim was to get a full understanding of how it affected the operations regarding the respective crisis teams and which factors were considered most important for setting up the teams. Two basic criteria which had to be over-come was the uncertainty and lack of time. It was seen that even though the fundamental structure did not change, crisis teams were added in the form of a crisis management team and task forces. The task forces played a major role in getting an understanding of the problem and the effect it has on the business. The crisis management team, which includes high level managers from all affected functional areas, had to re-evaluate the high level strategy and decide what needs to be done, and who will be doing it. In order to do so, they needed to understand what the priorities are regarding components and products and then decide on the priorities regarding affected business. The new strategy was then handed down to the task forces for implementation. A major focus of this paper was also on decision making and how everything contributed to making decisions that had the right effect in resolving the financial crisis for the organizations.
Supply shortages faced in products and resources from semiconductors to natural gas in recent years have had impact massive on global economy, but such challenges are not new for supply chain professionals. Many major events in the past have disrupted supply chains: 9/11 attack in New York, Tsunami in Japan to name a few, but COVID19 have had the biggest and widespread impact in the modern times. Even though supply chain resilience being a term coined in early 2000’s, its usage and importance has increased since then. With the curiosity of assessing the current state of sup-ply chain resilience literature and finding a resilience measurement method which is a one-fit for all supply chains in the manufacturing industry of Vorarlberg, the following research project was undertaken. Research is carried out with mixed methods, using a systematic literature review followed by expert interviews. In the conclusion of the research the author argues that there is a significant difference in the understanding of the term resilience within industry, there is a lack on the need for a meas-ure for resilience. The ways in which the structure of an organization impacts the level of resilience, foreseen benefits of digitalization and technologies for resilience are also dis-cussed. A comparative analysis on the SCR measurement methods discovered in literature, resulted in recommending Resilience index for on-time delivery proposed by Carvalho et al for the mentioned industry.
Having autonomy in the workplace can have a positive impact on employees’ performance, which in turn can benefit the organization’s competitive advantages. While previous researches have primarily focused on the psychological effects of job autonomy on employee performance and has been limited to certain domains, the relationship between job autonomy and organizational design is an important area of study for organizations seeking to improve their competitiveness. This thesis proposes a conceptual model for designing an organization structure that promotes employee performance in manufacturing companies by removing obstacles towards obtaining job autonomy. The focus is on ambitious employees who seek growth and development opportunities within their organization. The model is based on a review of existing literature on job autonomy and organizational design. Exploratory qualitative research was conducted with selected ambitious employees from different industries by means of one-on-one semi-structured interviews. Overall, the proposed model has practical implications for manufacturing companies looking to motivate their employees, as well as for researchers seeking to advance their understanding of organizational design in our times.
The advent of autonomous and self-driving cranes represents a significant advancement in industrial automation. One critical prerequisites for achieving this long-term goal is the accurate and reliable detection of tools guided by ropes in real-world environments. Since the tool is suspended by ropes, the tool pose cannot be controlled directly. This master’s thesis addresses the challenges of pose estimation for rope-guided tools using point cloud measurements. The proposed algorithm utilizes constraints imposed by the crane kinematics and information extracted during the segmentation process to efficiently infer the pose of the hook, therefore enabling the use of the pose for decision making in real-time critical applications. RANSAC (Random Sample and Consensus) is deployed in the segmentation process to extract geometric primitives from the point cloud which represent the ropes and distinctive parts of the tool. Since the point cloud is often to sparse for feature matching a bounding box is used to estimate the initial position of the tool. Two different methods are presented to improve the initial pose. A computationally expensive method with a high level of confidence, integrating the ICP (Iterative Closest Point) algorithm is used as a benchmark. A linear Kalman filter is used in the second method which is real-time capable. The benchmark is then used to evaluate the real-time capable approach. The core contributions of this research lie in the innovative utilization of bounding boxes for pose estimation. The findings and methodologies presented herein constitute an advancement towards the realization of autonomous and self-driving cranes.
The Fast Average Current Mode control methodology is a novel method for the implementation of a current compensator in a switched-mode power supply. It does not require compensation against sub-harmonic instability and is inductor independent. In this work, the digital implementation of this topology is compared against an analog implementation using simulation. Additionally, a hardware prototype is created to validate the digital simulation's results. In a Simulink environment, parameters of the digital implementation, such as the digital-to-analog converter resolutions and the delay counter frequency are varied to research their impact on system performance. The simulations show that a digital current compensator has similar performance as an analog implementation when designed tailored to the application. When evaluating the whole control loop the digital system is inferior due to added delays caused by digital to analog conversion. By operating the Buck converter hardware implementation as a current source, the functionality of the current mode control implementation in a FPGA was proven. Voltage control cannot be validated due to hardware issues. Due to the successful simulation of the source code with a mixed signal model of the converter, it can be assumed that it is functional. Apart from performance, a digital implementation shows many benefits compared to an analog solution, such as configurability of control parameters and easy compensation of component variations and aging.
Recent years have been commanded by a cascade of unpredictable incidents, that have redefined new standards in our private, but also in our professional life. Events like the financial crisis, the COVID-19 pandemic, the energy crisis in Europe, resource scarcity and so forth have caused instability, forcing companies towards flexibility, constantly adapting their operative structures according to the needs of the moment. The effective adaptation to this environment is the key for reacting the dynamism of the market, and for guaranteeing future success. However, the introduction of these crucial changes on a stable company organisation is challenging. Furthermore, due to digitalisation, boundaries between countries have been removed, and the daily cooperation with co-workers and customers all around the globe became the new standard. The establishment of a good corporate culture where diverse people can work in harmony and, is a difficulty that comes ahead.
This master thesis developed from a professional perspective. The topics of change management and corporate culture where combined, and the relationship between these two concepts was studied. This master thesis aims utilising corporate culture as an instrument in managements favour, to implement strategical changes easily and successfully in a more efficient way. The relation between corporate culture and the resistance to change, focusing on the initiation of the change process, was the main area of study. Research questions and hypothesis, formulated with a solid theoretical background, are to be answered based firstly on literature, and secondly on the results of empirical quantitative re-search. To conclude, a set of recommendations for corporates were suggested with the intention of guiding companies how to use corporate culture as an instrument for change management.
This thesis focuses on implementing and testing communication over a private 5G standalone network in an industrial environment, with a specific emphasis on communication between two articulated robots. The main objective is to examine machine-to-machine communication behavior in various test scenarios. Initially, the 5G core and radio access network components are described, along with their associated interfaces, to establish foundational knowledge. Subsequently, a use case involving two articulated robots is implemented, and essential metrics are defined for testing, including round-trip time, packet and inter-packet delay, and packet error rate. The tests investigate the impact of 5G quality of service, packet size, and transmission interval on communication between the robots, focusing on the effects of network traffic. The results highlight the significance of prioritizing network resources based on the assigned quality of service identifier (5QI), demonstrate the influence of packet sizes on communication performance, and underscore the importance of transmission intervals for automation purposes. Additionally, the study examines how network disturbances influence the movements of a robot controlled via 5G, establishing a direct relationship between network metrics and the resulting deviations in the robot’s trajectory. The work concludes that while machine-to-machine communication can be successfully implemented with 5G SA, tradeoffs must be carefully considered, especially concerning packet error rate, and emphasizes the importance of understanding the required resources before implementation to ensure feasibility. Future research directions include investigating network slicing, secure remote control of robots, and exploring the use of higher frequency bands. The study highlights the significance of aligning theoretical standards with practical implementation options in the evolving landscape of 5G Networks.
Lack of transparency and traceability of products and their raw materials means that most products can only be thrown away or not properly recycled due to a lack of relevant data. This conflicts with the circular economy principles, which are demanded by several initiatives, including the European Union. The aim of this master thesis is to analyze this conflict and to propose a technical solution based on Distributed Ledger Technology that enables transparency and traceability of products and their materials. Therefore, the thesis addresses two central research questions: 1. How can traceability and transparency be enabled by integrating a DLT solution? 2. How would a prototype with the integration of smart contracts and DLT look like? To answer these questions, a blockchain solution is implemented using Hyperledger Fabric. The solution uses the immutability and decentralized nature of DLT to record and track the movement of products and their materials throughout their life cycle in the Circular Economy. Furthermore, with private data collections, confidentiality, and privacy are granted while ensuring transparency. The thesis contributes to the Circular Economy field by exploring the principles, models, and challenges of the Circular Economy and the circularity goals of a Digital Product Passport to develop a suitable technical solution. The chosen blockchain framework, Hyperledger Fabric, is presented, and its key components and features are highlighted. The thesis also delves into the design decisions and considerations behind the Digital Product Passport platform, explaining the architecture and transaction flow together with the prototype implementation and demonstration to showcase the functionality of the solution. Results and analysis provide insights into the challenges of the Circular Economy, sustainable resource management, and the Digital Product Passport, resulting in recommendations for future improvements and enhancements. Overall, this thesis offers a practical solution utilizing DLT to enable transparency and traceability in the Circular Economy, contributing to the realization of sustainable and efficient resource management practices to ultimately contribute to the set Circular Economy initiatives.
A rapid change to remote work during the beginning of the Covid-19 pandemic allowed many organizations to roll out new collaboration platforms to rapidly digitalize their workflows and processes in order to continue operation. This sudden shift to remote work revealed to employees the potential benefits of working remotely in the form of additional flexibility and also showed the challenges and barriers organizations could face by introducing such a strategy. This thesis aims to uncover the key considerations that the organizations of the industrial sector in Vorarlberg need to consider establishing a remote work strategy. According to the results from the research, the Covid-19 pandemic was as a paradigm change for the interviewed decision makers about how they thought about remote work and how they transformed their respective organizations too continue to operate. After the initial phase of Covid-19 restrictions organizations started to experiment with a remote work strategy of their own, based on their past experiences. For now, most of the interviewed organizations use already different remote work concepts and evaluate which one suits best their needs. The main considerations as to why an organization introduced a remote work strategy are to be an attractive employer and to stay ahead in the search for new talent. Further by introducing a remote work strategy, organizations need to change their rules of collaboration, adapt their core values to fit a remote workplace and to introduce collaboration platforms which are designed to support a remote workforce.
This thesis evaluates the feasibility of conducting visual inspection tests on power industry constructions using object detection techniques. The introduction provides an overview of this field’s state-of-the-art technologies and approaches. For the implementation, a case study is then conducted, which is done in collaboration with the partner company OMICRON Electronics GmbH, focusing on power transformers as an example. The objective is to develop an inspection test using photographs to identify power transformers and their subcomponents and detect existing rust spots and oil leaks within these components. Three object detection models are trained: one for power transformers and sub-components, one for rust detection, and one for oil leak detection. The training process utilizes the implementation of the YOLOv5 algorithm on a Linux-based workstation with an NVIDIA Quadro RTX 4000 GPU. The power transformer model is trained on a dataset provided by the partner company, while open-source datasets are used for rust and oil leak detection. The study highlights the need for a more powerful GPU to enhance training experiments and utilizes an Azure DevOps Pipeline to optimize the workflow. The performance of the power transformer detection model is satisfactory but influenced by image angles and an imbalance of certain sub-components in the dataset. Multi-angle video footage is a proposed solution for the inspection test to address this limitation and increase the size of the dataset, focusing on reducing the imbalance. The models trained on open-source datasets demonstrate the potential for rust and oil leak detection but lack accuracy due to their generic nature. Therefore, the datasets must be adjusted with case-specific data to achieve the desired accuracy for reliable visual inspection tests. The results of the case study have been well-received by the partner company’s management, indicating future development opportunities. This case study will likely be a foundation for implementing visual inspection tests as a product.
Programmable Logic Controller (PLC) modules are used in industrial settings to control and monitor various manufacturing processes. Detecting these modules can be helpful during installation and maintenance. However, the limited availability of real annotated images to train an object detector poses a challenge. This thesis aims to research object detection of these modules on real images by using synthetic data during training. The synthetic images are generated from CAD models and improved with Generative Adversarial Networks (GANs). The CAD models are rendered in different scenes, and perfectly annotated images are automatically saved. A technique called domain randomization is applied during rendering. It renders the modules in different poses with constantly changing backgrounds. As the CAD models do not visually resemble the real modules, it is necessary to improve the synthetic images. This project researches StarGAN and CycleGAN for the task of image-to-image translation. A GAN is trained with real and synthetic images and can then translate between these domains. YOLOv8 and Faster R-CNN are tested for object detection. The best mean Average Precision (mAP) is achieved when training with a synthetic dataset where 50% of the images were improved with StarGAN. When trained with YOLOv8 and evaluated on a real dataset, it achieves a mAP of 84.4%. Overall, the accuracy depends on the quality of the CAD models. Using a GAN improves the detection rate for all modules, but especially for unrealistic CAD models.
Scrum has been a prominent project management framework for managing software development projects. The scrum team embodies values such as commitment, focus, respect, courage, and openness to develop trust, which serves as the foundation of the scrum framework. However, in recent years, scrum teams are shifting towards a work-from-home environment which is relatively new to most of them and known to present various challenges. Looking at the benefits of adhering to scrum values, this study aims to investigate the challenges scrum teams experience in adhering to scrum values while operating virtually, as well as to explore practical strategies to overcome the identified challenges, particularly during the storming stage of team development. This research employed a qualitative methodology using semi-structured interviews with scrum team members who have experience working in a virtual environment. Through qualitative content analysis of semi-structured interviews, this research identifies significant challenges within five main categories: communication, collaboration, interpersonal dynamics, the virtual work environment, and personal workspace issues. However, beyond the challenges, the study reveals practical strategies as well for successful team dynamics and higher efficiency. The strategies derived from team members' experiences are categorized into six categories: enhanced meeting management, leveraging in-person engagements, optimizing tools & technology, effective communication strategies, team-building, and nurturing a positive work culture.
Purpose: In this thesis the viable system model (VSM) is used as a framework to develop a model for the management of a business alliance that contains the necessary and sufficient conditions for maintaining synergy of its constituent organisations and for adapting to a changing environment so that it can remain a long-term viable alliance. In addition, a model is developed that makes explicit the inherent link between the VSM and the core elements of knowledge management theory. Based then on the alliance management model and the link established between the VSM and knowledge management, an application framework is developed to guide practitioners in defining necessary alliance management functions and relationships, the knowledge required by that management to fulfill those functions, and the processes that need to be in place to manage that knowledge. Design/strategy: The research has been divided into four phases: theoretical construction, refinement with practitioners, real-world application, and evaluation of test case and toolset. The researcher has worked closely with practitioners actively involved in the formation of a new international alliance to develop a VSM model and application framework for the alliance management. Formally, the research strategy has been defined as an action research and the research philosophy as one of pragmatism. Findings/limitations: The developed application framework, has been successfully used to identify absent and incomplete roles, actions, and interactions within the management of the specific alliance test case. This has helped to demonstrate how the application framework and VSM model can be used to diagnose and, most importantly, to articulate and visualise management deficiencies to facilitate clear and unambiguous discussions. The timing of this cross-sectional research did not allow the application framework to be utilised from the outset of the alliance formation as an organisational planning tool and also not to its full extent to support the development of knowledge processes for the alliance management. However, the step-by-step approach used in developing the toolset and then explaining its application will allow the reader to judge its credability and generalisability for other practical applications. Practical implications: The developed toolset consists of a VSM for an alliance management, job descriptions for that management (responsibilities, interfaces, and core competencies), a visual model illustrating the link between the VSM and knowledge management, and an application framework to guide the filling of the alliance management job descriptions in phases of recruitment, onboarding, and development (of interfaces and activities processes). Overall, one could say that the conditions prescribed by the VSM are rather obvious and yet, as seen by the specific alliance test case, many of these conditions have been completely overlooked by a management that was more than capable, willing, and empowered to enact those conditions. This gives a good indication that the toolset which has been compiled in a visual and tabular systematic fashion may well be useful to practitioners for the organisational planning of an alliance management. The visual representation of a management role in the VSM as a set of knowledge episodes put forward by this research is significant. It forces the express recognition that knowledge management is an integral part of every interaction that takes place and every action performed that, according to the VSM, are necessary and altogether are sufficient for viability. It means that knowledge management cannot be considered as some abstract topic or unnecessary overhead or afterthought – it is entirely necessary, practical and forms a natural course of events during design of action/interaction processes. In other words, if an organisation is viable then, by definition, it does knowledge management whether or not it is formally recognised as such. The VSM, by defining necessary and sufficient actions and interactions for its roles, therefore provides a focus for relevant knowledge and serves as a tool for structured knowledge management. Originality/value: This research addresses a general academic call for hands-on insights of VSM applications by sharing real-world insights, artifacts and reflections generated by a practical and relevant organisational management application. It also addresses the potential, recognised by academics, for VSM as a framework for knowledge management by developing an intuitive model linking those theories and then using that model as part of a framework to guide its application. The introduction to aspects of knowledge management theory relevant to the model developed as well as the meticulousness and comprehensive explanation of the VSM provides a solid theoretical foundation for practitioners. The developed toolset is based on existing theories from multiple fields of research that have been logically linked and extended in an original and novel manner with a strong focus on practical application. This researcher’s hope is that this will stimulate interest for future research and practical application from academics and practitioners alike.
The implementation of direct-to-consumer (D2C) business models has become more important for companies trying to develop a competitive edge and improve consumer engagement in today's rapidly expanding e-commerce market. This master's thesis investigates the important success elements and problems of deploying D2C models in the e-commerce business. The research question focuses on identifying the factors that contribute to the successful transition to D2C models and the obstacles businesses encounter along the way. Through qualitative research using the Eisenhardt method and in-depth case studies with industry experts, this study provides valuable insights into key success factors for direct-to-consumer (D2C) business models in e-commerce.The findings highlight that businesses that effectively implement D2C models utilize key success factors such as a clear value proposition, customer engagement and relationship build- ing, seamless online experiences, targeted marketing and digital advertising, brand identity and storytelling, and flexibility and adaptability. However, they also face challenges related to operational adjustments, marketing and branding investments, competition, and market saturation. Based on these research outcomes, this thesis provides recommendations for businesses seeking to switch to or implement D2C models in e-commerce. These recommendations emphasize embracing a customer-centric mindset, developing digital capabilities, foster- ing strong leadership commitment, leveraging data and analytics, establishing direct customer relationships, optimizing operational processes, building brand trust and credibility, and allocating resources wisely. This master's thesis provides a comprehensive analysis of the key success factors and challenges associated with the transition to or implementation of D2C business models in the e-commerce industry. It provides advice to help companies successfully transition to D2C models.
This thesis aims to determine how banks can prepare for fulfilling and implementing the IFRS S1 requirements, which have been published by the International Sustainability Standard Board. It also examines the extent to which banks in Liechtenstein and Switzerland have already implemented the existing regulatory requirements in the area of sustainability transparency and integrated them into their financial reporting. The focus is to determine whether, and to what extent, these requirements enable banks to disclose relevant information on sustainability aspects in their financial reports. In order to answer the research question appropriately, a qualitative research method according to Mayring was used, which included conducting expert interviews. In this context, it is important to analyze the possibilities of IFRS S1 concerning the identification, assessment, and disclosure of sustainability risks and opportunities. The thesis also analyzes the impact of the regulatory requirements on banks, including the challenges of implementing IFRS S1 and the potential benefits and opportunities for banks of complying with the sustainability transparency requirements. The results are intended to develop a better understanding of how the regulatory requirements for sustainability transparency can be effectively used by banks to improve the quality and comparability of sustainability-related financial information under IFRS S1.
Activation of heat pump flexibilities is a viable solution to support balancing the grid via Demand Side Management measures and fulfill the need for flexibility options. Aggregators as interface between prosumers, distribution system operators and balance responsible parties face the challenge due to data privacy and technical restrictions to transform prosumer information into aggregated available flexibility to enable trading thereof. Thereby, literature lacks a generic, applicable and widely accepted flexibility estimation method for heat pumps,which incorporates reduced sensor and system information, system- and demand-dependent behaviour. In this paper, we adapt and extend a method from literature, by incorporating domain knowledge to overcome reduced sensor and system information. We apply data of five real-world heat pump systems, distinguish operation modes, estimate power and energy flexibility of each single heat pump system, proof transferability of the method, and aggregate the flexibilities available to showcase a small HP pool as a proof of concept.
Open tracing tools
(2023)
Background: Coping with the rapid growing complexity in contemporary software architecture, tracing has become an increasingly critical practice and been adopted widely by software engineers. By adopting tracing tools, practitioners are able to monitor, debug, and optimize distributed software architectures easily. However, with excessive number of valid candidates, researchers and practitioners have a hard time finding and selecting the suitable tracing tools by systematically considering their features and advantages. Objective: To such a purpose, this paper aims to provide an overview of popular Open tracing tools via comparison. Methods: Herein, we first identified 30 tools in an objective, systematic, and reproducible manner adopting the Systematic Multivocal Literature Review protocol. Then, we characterized each tool looking at the 1) measured features, 2) popularity both in peer-reviewed literature and online media, and 3) benefits and issues. We used topic modeling and sentiment analysis to extract and summarize the benefits and issues. Specially, we adopted ChatGPT to support the topic interpretation. Results: As a result, this paper presents a systematic comparison amongst the selected tracing tools in terms of their features, popularity, benefits and issues. Conclusion: The result mainly shows that each tracing tool provides a unique combination of features with also different pros and cons. The contribution of this paper is to provide the practitioners better understanding of the tracing tools facilitating their adoption.
Flexibility estimation is the first step necessary to incorporate building energy systems into demand side management programs. We extend a known method for temporal flexibility estimation from literature to a real-world residential heat pump system, solely based on historical cloud data. The method proposed relies on robust simplifications and estimates employing process knowledge, energy balances and manufacturer's information. Resulting forced and delayed temporal flexibility, covering both domestic hot water and space heating demands as constraints, allows to derive a flexibility range for the heat pump system. The resulting temporal flexibility lay within the range of 24 minutes and 6 hours for forced and delayed flexibility, respectively. This range provides new insights into the system's behaviour and is the basis for estimating power and energy flexibility - the first step necessary to incorporate building energy systems into demand side management programs.
Hot water heat pumps are well suited for demand side management, as the heat pump market faced a rapid growth in the past years with the trend to decentralized domestic hot water use. Sales were accelerated through wants and needs of energy conservation, energy efficiency, and less restrictive rules regarding Legionella. While in literature the model predictive control potential for heat pumps is commonly shown in simulations, the share of experimental studies is relatively low. To this day, experimental studies considering solely domestic hot water use are not available. In this paper, the realistic achievable model predictive control potential of a hot water heat pump is compared to the standard hysteresis control, to provide an experimental proof. We show for the first time, how state-of-the-art approaches (model predictive control, system identification, live state estimation, and demand prediction) can be transferred from electric hot water heaters to hot water heat pumps, combined, and implemented into a real-world hot water heat pump setup. The optimization approach, embedded in a realistic experimental setting, leads to a decrease in electric energy demand and cost per unit electricity by approximately 12% and 14%, respectively. Further, an increase in efficiency by approximately 13% has been achieved.
Immersive educational spaces
(2023)
"If only we had had such opportunities to grasp history like this when I was young" – words by an almost 80-year-old woman holding an iPad on which both, the buildings in the background and a tower in the form of a virtual 3D object, appear within reach. To "grasp" history - what an apt use of this action-oriented word for an augmented reality application built on considerations of thinking and acting in history. This telling image emerged during the first test run of the app i.appear which will be the focus of this article's considerations on the use of immersive learning environments. The application i.appear has been used in the city of Dornbirn (Austria) for a year now to teach historical content through location-based augmented reality and other interactive and multimedia technologies. After a brief description of the potential of such applications, the epistemological structure of the hosting app i.appear and its functionality will be outlined. This article will focus on the “Baroque Master Builders” tour of the hosting app that was created and tested as part of the current research.
This paper presents design, simulation, and optimization of the three-dimensional 1×4 optical multimode interference splitter using IP-Dip polymer as a core and polydimethylsiloxane (PDMS) Sylgard 184 as a cladding. The splitter was simulated by using beam propagation method in BeamPROP simulation engine of RSoft photonic tool and optimized for an operating wavelength of 1.55 µm. According to the minimum insertion loss, the dimensions of the MMI coupler and the length of the whole MMI splitter structure were optimized applying a waveguide with a core size of 4×4 µm2. The objective of the study is to create a design for fabrication by three-dimensional direct laser writing optical lithography.
We present design of planar 16-channel, 100-GHz multi-mode polymer-based AWG. This AWG was designed for central wavelength of 1550 nm applying AWG-Parameters tool. The AWG structure was created and simulated in the commercial photonic tool PHASAR from Optiwave. Achieved transmission characteristics were evaluated by AWG-Analyzer tool. For the design, multi-mode waveguides having a cross-section of (4x4) µm2 were used. The simulated results show strong worsening of the transmission characteristics in comparison when using single-mode waveguides. Nevertheless, the transmitting channels are clearly separated. The reason for using thicker multi-mode waveguides in the design is possibility to fabricate the AWG structure on polymer basis using direct laser writing lithography.
Coupling is one of the most frequently mentioned metric in software systems. However, to measure logical coupling between microservices, runtime information is needed or the availability of service-log files to analyze the calls between services is required. This work presents our emerging results, in which we propose a metric to statically calculate logical coupling between microservices based on commits to versioning systems. We performed an initial validation of the proposed metric with a dataset containing 145 open-source microservices projects. The results illustrate how logical coupling affects every system and increases overtime. However, we did not find a correlation between the number of commits or the number of developers and the introduction of logical coupling. In future, we investigate why, how, and when logical coupling is introduced in a system.
The paper deals with designing and numerical modelling a 2 x 2 optical switch for photonic integrated circuits based on 2 x 2 MMI elements and phase modulators. The 2 x 2 optical switch was modelled in the RsoftCAD with the simulation tool BeamPROP. The 2 x 2 optical switch is a common element for creating more complex 1 x N or N x N optical switches in all-optical signal processing.
In this paper, the design of three-dimensional configuration of Y-branch splitter is compared with Multimode Interference splitter. Both splitters use the IP-Dip polymer as a standard material for 3D laser lithography. The optical properties of the splitters for both approaches are discussed and compared.
In this work, we investigated the influence of different etch depths of the rib waveguides on the performance of SiN-based AWGs. For this purpose, an 8-channel 100 GHz AWG was designed for a center wavelength of 850 nm. The design parameters entered were calculated using the AWG-Parameters tool. The simulations were performed with a commercial photonic tool PHASAR from Optiwave. The simulated performance was evaluated using the AWG-Analyzer tool. For the AWG design, we used three identical rib waveguides with different etch depths to simulate possible etch imperfection. The simulations show the wavelength shift and degradation of the AWG performance.
Optoelectronic system based on photonic integrated circuits to miniaturize spectral domain OCT
(2023)
We present a miniaturized optical coherence tomography (OCT) setup based on photonic integrated circuits (PIC) for the 850 nm range. We designed a 512-channel arrayed waveguide grating (AWG) on a PIC for spectral domain OCT (SD-OCT) that is co-integrated with PIN-photodiodes and analog-to-digital-converters on one single chip. This image sensor is combined with all the necessary electronics to act as a camera. It is integrated into a fiber-based OCT system, achieving a sensitivity of >80dB and various samples are imaged. This optoelectronic system will allow building small and cost-effective OCT systems to monitor retinal diseases.
Semiconducting metal oxides are widely used for solar cells, poto-catalysis, bio-active materials and gas sensors. Besides the material properties of the used semiconductor,the specific surface topology of the sensor determines the device performance. We investigate the preparation and transfer suitable metals onto LIPPS structures on glass for gas sensing applications.
Deep etched structures in GaAs with high aspect ratio have promising applications in optoelectronics and MEMS devices. The key factors in their fabrication process are the choosing of proper mask material and etching conditions which results in high selectivity and an anisotropic etch profile with smooth sidewalls. In this work, we studied several types of mask materials (Al, Ni, Cr, SiO2) for deep reactive ion etching of GaAs using inductively coupled plasma system. Thus, several sets of experiments were performed with varying gas mixture, pressure and ICP/RF power. As a result, we find optimized conditions and minimal thickness of mask material for achieving deep etched (>140 m) GaAs structures.
Various carbon (nano-) forms, so-called allotropes, have become one of the most supporting activities in fundamental and applied research trends. Therefore, a universal deposition process capable of “adjusting” system parameters in one “deposition chamber” is highly demanding. Here, we present a low-pressure large area deposition system combining radiofrequency (RF) and microwave (MW) plasma in one chamber in different configurations, which offers a wide deposition window for the growth of sp2 carbon (carbon nanotubes, amorphous carbon), a mixture of sp2 and sp3 (diamond-like films) and pure sp3 carbon represented by diamond films. We will show that not only the type of plasma source (RF vs. MW) but also the gas mixture and plasma chemistry are crucial parameters for the controllable and reproducible growth of these allotropes at temperatures from 250 to 800 °C.
The properties of SiC and diamond make them attractive materials for MEMS and sensor devices. We innovated specific laser ablation techniques to fabricate membranes and cantilevers made of SiC or nano-(micro-) crystalline diamond films grown on Si/SiO2 substrates by microwave chemical vapour deposition (MWCVD). We started research to generate surface moulds to grow corrugated diamond films for membranes and cantilevers. A software tool was developed to support the design of micromechanical cantilevers. We can measure deformation and resonant frequency of diamond cantilevers and identify the global mechanical properties. A benchmark against finite element simulations enables an inverse identification of the specific system parameters and simplifies the characterization procedure.