Chemnitz University of Technology

The die-attach layer is a vulnerable structure that is important to the reliability of an insulated-gate bipolar transistor (IGBT) module. A new failure mechanism named fatigue crack network (FCN) has been identified in the central area of the IGBT modules' solder layer. In this paper, to investigate the formation mechanism of the FCN, a fast power cycling test (PCT) (current on 0.2s and current off 0.4s) was designed and performed on a commercial IGBT module. Subsequently, scanning acoustic microscopy (SAM) and X-ray imaging were used for non-destructive inspection of the defects of the solder layer. The cross-section was based on the non-destructive inspection results. Then electron backscattered diffraction (EBSD) analysis was carried out on both observed vertical and horizontal cracks. As a result, both networked vertical cracks at the center and horizontal cracks at the edge of the solder layer were detected. The recrystallization occurred during the PCT. The voids and cracks emerged at high-angle grain boundaries. A finite element (FE) simulation was performed to understand the driving force of FCN qualitatively. The stress simulation results indicate that under time-dependent multi-axial stress at the center of the solder, the defects nucleated, expanded, and connected vertically to form the FCNs.

Context Chatbots based on large language models are becoming an important tool in modern software development, yet little is known about how programming beginners interact with this new technology to write code and acquire new knowledge. Thus, we are missing key ingredients to develop guidelines on how to adopt chatbots for becoming productive at programming. Objective With our research, we aim at identifying these ingredients. Specifically, we want to understand how programming beginners use conversational chatbots when writing source code. Method To this end, we study programming beginners’ interaction with a chatbot in a CS2 course while they were solving programming assignments. Additionally, we evaluate the correctness of submitted solutions and compare them to solutions of beginners who did not use a conversational chatbot. Results We analyzed 756 prompts of 129 conversations, most of them focusing on code generation. Interestingly, conversations that contain prompts asking for debugging or testing of code are linked with higher success rates, indicating that deeper engagement with code leads to higher quality code. Moreover, prompts without sufficient context often lead to unsatisfying results. Conclusions While not surprising, this underpins the importance that programming beginners need to know how to use chatbots, instead of merely using it as code generators without investing time in code quality. Moreover, companies should employ prompt guidelines, in which code quality prompts might be enforced after a code generation prompt has been stated.

Kurzfassung Die Autoren gehen der Frage nach, ob die zunehmende Bedeutung sogenannter kritischer mineralischer und metallischer Rohstoffe die Beobachtung der entsprechenden Lieferketten durch geheime staatliche Nachrichtendienste erforderlich macht. Systemrelevante Rohstoffe wie etwa Erdöl waren nie nur wirtschaftlich bedeutsam, sondern wurden von Staaten stets auch unter versorgungsstrategischen und sicherheitspolitischen Aspekten mithilfe von Auslandsnachrichtendiensten analysiert. Derzeit stehen kritische Elemente wie Seltene Erden oder Lithium im Fokus des öffentlichen Interesses. In diesem Zusammenhang befasst sich dieser Aufsatz mit zwei zentralen Fragen: (1) Können geheime Nachrichtendienste einen substanziellen Mehrwert bei der Analyse von Rohstoffmärkten für den Staat und gegebenenfalls die Industrie leisten? Und (2) welche Risiken und Potenziale sind mit dem Einsatz geheimer Nachrichtendienste in diesem Bereich verbunden? Die Verfasser verstehen ihren Beitrag als Debattenanstoß und sind sich bewusst, dass die Empirie im Bereich Nachrichtendienstforschung nicht systematisch erhebbar ist. Möglicherweise sind die hier behandelten Fragestellungen im nachrichtendienstlichen Tagesgeschäft schon diskutiert und teils bereits implementiert worden.

The edges of layered double hydroxides (LDHs) display an exceptionally efficient oxygen evolution reaction (OER) activity than the (001) basal plane as demonstrated by both theoretical calculations and experimental studies. However, a controllable synthesis method of LDHs with abundant edges has yet to be described. Herein, we report a strategy enabling the synthesis of nickel‐iron LDHs with abundant edges (NiFe LDHs‐E) based on the use of citrate anions as the structure‐directing agent. The edge density is characterized using spectroscopy techniques and its OER performance is compared with that of nickel‐iron LDHs with abundant basal planes (NiFe LDHs‐B). In alkaline electrolyte (1M KOH), NiFe LDHs‐E exhibits excellent OER activity with very low overpotential (235 mV at 10 mA cm−2) and current densities up to sixfold (at η = 320 mV) higher than those of NiFe LDHs‐B. Density functional theory (DFT) calculations confirm the high OER activities ascribed to the abundant side‐plane edges with optimal strength of binding of OER intermediates. Overall, a comprehensive investigation, employing both experimental and computational methodologies, yields new insights to fabricate superior catalysts meticulously designed with specific crystal planes and unveils the crucial structural attributes, thus unleashing the limitless potential of the catalytic domain.

Many cyber-physical systems face the challenge of appropriately integrating domain-specific human expert knowledge into the cyber part to create a shared sphere of knowledge and intelligent interactions between humans and the semi-autonomous technical system. Cognitive engineering contributes methods and insights into higher-order cognition that help to embed human knowledge in an appropriate way. The original research introduces a novel transdisciplinary framework called Human-CoMo, which demonstrates a systematic modelling process, different human perspectives, and the integration of expert knowledge at multiple hierarchical levels. Fundamental principles inspired by human cognition, such as conceptual chunking and knowledge precision, are characterised. Furthermore, it is shown how knowledge hierarchies can be methodically reflected in appropriate data analysis and modelling levels for small and big data applications including artificial intelligence approaches. Combined knowledge- and data-based modelling approaches offer more flexibility to integrate the strengths of humans and technology in a complementary way. The cognitive foundations and their computational reflections are outlined for the technical example process electroplating from the field of materials and surface engineering. The possibilities and limitations of integrating human knowledge through formalisation and implications for future forms of human-machine interaction are discussed.

We characterize the condition $(\Omega )$ ( Ω ) for smooth kernels of partial differential operators in terms of the existence of shifted fundamental solutions satisfying certain properties. The conditions $(P\Omega )$ ( P Ω ) and $(P\overline{\overline{\Omega }})$ ( P Ω ¯ ¯ ) for distributional kernels are characterized in a similar way. By lifting theorems for Fréchet spaces and (PLS)-spaces, this provides characterizations of the problem of parameter dependence for smooth and distributional solutions of differential equations by shifted fundamental solutions. As an application, we give a new proof of the fact that the space $\{ f \in {\mathscr {E}}(X) \, | \, P(D)f = 0\}$ { f ∈ E ( X ) | P ( D ) f = 0 } satisfies $(\Omega )$ ( Ω ) for any differential operator P ( D ) and any open convex set $X \subseteq {\mathbb {R}}^d$ X ⊆ R d .

Microwave resonators are a technology with the potential to automate the rapid acquisition of vapour-liquid equilibrium data in multicomponent mixtures. However, the re-entrant resonators commonly used for fluid characterization have limited ability to mix or drain adequately due to the bulbs and narrow gaps used within the sample volume to spatially distribute the sensing regions with intense electric fields. This work describes a novel composite cavity combining two toroidal split-ring resonators and a cylindrical resonator, each sealed and partially filled with the polymer PEEK, to spatially separate sensing regions whilst maintaining an unobstructed sample volume. This unique design also allows for the total sample volume to be an order-of-magnitude smaller than conventional microwave cavities, without significantly increasing the resonant frequencies. Mass transfer between phases is facilitated by mechanical agitation, reducing equilibration time. Finite element analysis (FEA) is used to model how the dielectric interfaces within the cavity perturb electric field distributions. This model is used to interpret measurements of two-phase propane to quantify liquid volume fraction and phase dielectric permittivities.

The transition from planar (2D) to three-dimensional (3D) magnetic nanostructures represents a significant advancement in both fundamental research and practical applications, offering vast potential for next-generation technologies like ultrahigh-density storage, memory, logic, and neuromorphic computing. Despite being a relatively new field, the emergence of 3D nanomagnetism presents numerous opportunities for innovation, prompting the creation of a comprehensive roadmap by leading international researchers. This roadmap aims to facilitate collaboration and interdisciplinary dialogue to address challenges in materials science, physics, engineering, and computing. The roadmap comprises eighteen sections, roughly divided into three parts. The first section explores the fundamentals of 3D nanomagnetism, focusing on recent trends in fabrication techniques and imaging methods crucial for understanding complex spin textures, curved surfaces, and small-scale interactions. Techniques such as two-photon lithography and focused electron beam-induced deposition enable the creation of intricate 3D architectures, while advanced imaging methods like electron holography and Lorentz electron Ptychography provide sub-nanometer resolution for studying magnetization dynamics in three dimensions. Various 3D magnetic systems, including coupled multilayer systems, artificial spin ice, magneto-plasmonic systems, topological spin textures, and molecular magnets, are discussed. The second section introduces analytical and numerical methods for investigating 3D nanomagnetic structures and curvilinear systems, highlighting geometrically curved architectures, interconnected nanowire systems, and other complex geometries. Finite element methods are emphasized for capturing complex geometries, along with direct frequency domain solutions for addressing magnonic problems. The final section focuses on 3D magnonic crystals and networks, exploring their fundamental properties and potential applications in magnonic circuits, memory, and spintronics. Computational approaches using 3D nanomagnetic systems and complex topological textures in 3D spintronics are highlighted for their potential to enable faster and more energy-efficient computing.

This study demonstrates the development of multifunctional printable piezoelectric actuators using PVDF‐TrFE and PEDOT:PSS, capable of operating at low voltages and supporting a wide range of applications. By leveraging the high piezoelectric coefficient of PVDF‐TrFE and the conductivity of PEDOT:PSS, the actuators exhibit stable performance with precise inkjet printing deposition and optimized waveform parameters. The fabrication process integrates inkjet printing and standard lithography, enabling monolithic integration for high‐performance actuation and multifunctional sensing. The PVDF‐TrFE‐based actuators achieve low‐voltage operation (as low as 50 V), efficient energy transfer, and mechanical stability. Enhancing the beta phase of PVDF‐TrFE resulted in a deflection of ≈600 µm and vortex generation, crucial for lift in aerial robotic applications. Durability tests confirmed minimal performance degradation after 2,300 actuation cycles. Beyond mechanical deflection, the actuators exhibit sound detection and strain sensing capabilities. Experimental evaluations validated their ability to differentiate sound frequencies, detect muscle strain, and replicate bio‐inspired flight dynamics. A preliminary proof of concept for a double‐wing structure demonstrated lift generation at low voltages and resonant frequencies. The results indicate that these piezoelectric actuators are well‐suited for miniaturized robotic applications, particularly in aerial locomotion and multifunctional sensing, opening new possibilities for innovations in micro‐robotics, wearables, and aerial robotics.

Over the last years, infectious diseases have been traveling across international borders faster than ever before, resulting in major public health crises such as the Covid‐19 pandemic. Given the rapid changes and unknown risks that mark such events, risk communication faces the challenge to raise awareness and concern among the public without creating panic. Drawing on the social amplification of risk framework—a concept that theorizes how and why risks are amplified or attenuated during the (1) transfer of risk information (by, for instance, news media) and (2) audiences’ interpretation and perception of these information—we were interested in the portrayal of risk information and its impact on audiences’ risk perception over the first wave of the Covid‐19 pandemic in Germany. We therefore conducted a quantitative content analysis of a major public and private television (TV) newscast (N = 321) and combined it with survey data (two‐wave panel survey, t1: N = 1378 and t2: N = 1061). Our results indicate that TV news (as a major information source at that time) were characterized by both risk‐attenuating and risk‐amplifying characteristics, although risk‐amplifying attributes were particularly pronounced by the private TV newscast. Notably, those who only used private TV news between both waves showed the highest perceived severity at time 2. However, the interaction effect of time and use of public and/or private TV news was only significant for perceived susceptibility. Overall, more research is needed to examine the effects of different types of media and changes in risk perceptions over time.

Zinc‐ion capacitors (ZICs) have attracted great attention due to a series of advantages. However, the cathode materials are still the bottleneck for high‐performance ZICs to be achieved. Therefore, ZIF‐8‐derived porous carbons are one of the most promising candidates but ZIF‐8 nanoparticles with different sizes exhibited various electrochemical performances in ZICs. Herein, a series of monodispersed ZIF‐8 nanoparticles are first prepared by a temperature‐controlled process to fabricate the corresponding ZIF‐8‐based porous carbon nanoparticles with pre‐designed sizes. The as‐prepared materials have been tested as cathode materials in ZICs. Thus, their size effect allowed us to disclose its correlation with other factors such as ion transport/storage and capacitance. The results reveal that the optimal‐sized porous carbon particles can effectively shorten the ion transport distance and accelerate the ion diffusion rate, resulting in lower electrical resistance, larger ion diffusion coefficients, and faster electron transport. The presented findings can facilitate the design of new advanced cathode materials paving the way for the development of high‐performance cathode materials for ZICs in the future.

Im Jahr 2015 wurden seitens der internationalen Gemeinschaft 17 globale Ziele für nachhaltige Entwicklung definiert, welche die Schaffung einer menschlicheren Zukunft sowie den Erhalt natürlicher Ressourcen zum Ziel haben. Die Umstellung auf grüne Elektromobilität stellt ein entscheidendes Element zur Erreichung einiger der genannten Ziele dar. Ein bloßer Mobilitätswandel ist jedoch nicht ausreichend. Auch der Umgang mit den Batteriesystemen von Elektrofahrzeugen am Ende ihrer Produktlebensdauer sollte geregelt werden, um die Ressourcenschonung zu maximieren.

In our digitalized world and under the economic pressure of competition, every company must react flexibly to opportunities and problems that arise. One way to cope with these challenges is to use web-based Enterprise Resource Planning (ERP) or Customer Relationship Management (CRM) Systems, which provide significant functionality inside their system range. Third-party systems often have to be integrated with ERP or CRM systems but cannot be connected, for instance, because of limited Application Programming Interfaces (API) or data structures. Therefore, such tasks are complex and time-consuming and must be done by software engineers , who are limited resources in today's enterprise context. However, HTML documents can be integrated with web-based systems such as ERP or CRM, and HTML creation is not limited to the software engineering workforce. Our low-code environment, which is based on W3C web components standards and RESTful web services with state-of-the-art authentication approaches, could solve the shortage because we empower business developers to embed dynamic database content declaratively in static HTML pages or web-based systems such as WordPress or SoftEngine ERP-Suite. Our system also allows the declarative integration of forms for creating/modifying and deleting data records (CRUD functionality). The low-code web components access the database via the RESTful service. The API of the RESTful service abstracts the database manufacturer-specific characteristics, such as the storage format of the metadata.

A methodology for evaluating experimental uncertainty is presented. Based on the Guide to the Expression of Uncertainty in Measurement (GUM) in conjunction with a sensitivity analysis, this method readily applies to systems of various degrees of complexity. It consists of three steps: (1) to estimate each uncertainty contribution of the system based on GUM; (2) to determine the sensitivity of the calculated results to variations in each of the input measurands in turn, replacing the partial derivatives of the GUM with a purely numerical approach; and (3) to calculate the overall uncertainty using the error propagation principle. Furthermore, the calculated sensitivity coefficients enable a critical evaluation of the investigated system, allowing the detection of possible targeted improvements. For this reason, the presented method is called “the sensitivity analysis method.” This is applied to three case studies with increasing complexity: a mass calibration procedure, a volume calibration procedure, and a gravimetric densimeter characterized by a multi-parameter nonlinear measuring model. When possible, the results are compared to the GUM uncertainty framework or values available in the literature.