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Nikiruy, Kristina; Perez, Eduardo; Baroni, Andrea; Reddy, Keerthi Dorai Swamy; Pechmann, Stefan; Wenger, Christian; Ziegler, Martin
Blooming and pruning: learning from mistakes with memristive synapses. - In: Scientific reports, ISSN 2045-2322, Bd. 14 (2024), 7802, S. 1-11

Blooming and pruning is one of the most important developmental mechanisms of the biological brain in the first years of life, enabling it to adapt its network structure to the demands of the environment. The mechanism is thought to be fundamental for the development of cognitive skills. Inspired by this, Chialvo and Bak proposed in 1999 a learning scheme that learns from mistakes by eliminating from the initial surplus of synaptic connections those that lead to an undesirable outcome. Here, this idea is implemented in a neuromorphic circuit scheme using CMOS integrated HfO2-based memristive devices. The implemented two-layer neural network learns in a self-organized manner without positive reinforcement and exploits the inherent variability of the memristive devices. This approach provides hardware, local, and energy-efficient learning. A combined experimental and simulation-based parameter study is presented to find the relevant system and device parameters leading to a compact and robust memristive neuromorphic circuit that can handle association tasks.



https://doi.org/10.1038/s41598-024-57660-4
Hannappel, Thomas; Shekarabi, Sahar; Jaegermann, Wolfram; Runge, Erich; Hofmann, Jan Philipp; Krol, Roel van de; May, Matthias M.; Paszuk, Agnieszka; Hess, Franziska; Bergmann, Arno; Bund, Andreas; Cierpka, Christian; Dreßler, Christian; Dionigi, Fabio; Friedrich, Dennis; Favaro, Marco; Krischok, Stefan; Kurniawan, Mario; Lüdge, Kathy; Lei, Yong; Roldán Cuenya, Beatriz; Schaaf, Peter; Schmidt-Grund, Rüdiger; Schmidt, W. Gero; Strasser, Peter; Unger, Eva; Montoya, Manuel Vasquez; Wang, Dong; Zhang, Hongbin
Integration of multi-junction absorbers and catalysts for efficient solar-driven artificial leaf structures : a physical and materials science perspective. - In: Solar RRL, ISSN 2367-198X, Bd. 0 (2024), 0, S. 1-88

Artificial leaves could be the breakthrough technology to overcome the limitations of storage and mobility through the synthesis of chemical fuels from sunlight, which will be an essential component of a sustainable future energy system. However, the realization of efficient solar-driven artificial leaf structures requires integrated specialized materials such as semiconductor absorbers, catalysts, interfacial passivation, and contact layers. To date, no competitive system has emerged due to a lack of scientific understanding, knowledge-based design rules, and scalable engineering strategies. Here, we will discuss competitive artificial leaf devices for water splitting, focusing on multi-absorber structures to achieve solar-to-hydrogen conversion efficiencies exceeding 15%. A key challenge is integrating photovoltaic and electrochemical functionalities in a single device. Additionally, optimal electrocatalysts for intermittent operation at photocurrent densities of 10-20 mA cm^-2 must be immobilized on the absorbers with specifically designed interfacial passivation and contact layers, so-called buried junctions. This minimizes voltage and current losses and prevents corrosive side reactions. Key challenges include understanding elementary steps, identifying suitable materials, and developing synthesis and processing techniques for all integrated components. This is crucial for efficient, robust, and scalable devices. Here, we discuss and report on corresponding research efforts to produce green hydrogen with unassisted solar-driven (photo-)electrochemical devices. This article is protected by copyright. All rights reserved.



https://doi.org/10.1002/solr.202301047
Freisinger, Elena; McCarthy, Ian P.
What fails and when? : a process view of innovation failure. - In: Technovation, Bd. 133 (2024), 102995, S. 1-14

Research on innovation failure has proliferated lately but with little theoretical attention given to the diversity of the concept. Using process theorizing, we present a model and propositions to understand how a firm's anticipation and value toward failure depends on the type of failure (task versus outcome) and the phase (divergent versus convergent) and point (early versus later) ‘within’ the process that the failure occurs. Using the anticipation-value stances, we then present a typology of four modes of innovation failure that can arise ‘from’ task and outcomes failure in the innovation process. The four modes (and associated learning response) are unsolicited failures (prevent-alert-eliminate); hazardous failures (predict-modify-mitigate); fortuitous failures (probe-expose-extrapolate); and excursive failures (facilitate-analyze-harness). To help explain the ideas in our process model and typology, we use the well-known IDEO shopping cart innovation project as an illustrative example. Together, these contributions provide contingency oriented insights on how failure varies and journeys within and from the innovation process, which helps researchers and managers to better understand the related causes, effects and learning responses.



https://doi.org/10.1016/j.technovation.2024.102995
Zheng, Niannian; Luan, Xiaoli; Shardt, Yuri A. W.; Liu, Fei
Dynamic-controlled Bayesian network for process pattern modeling and optimization. - In: Industrial & engineering chemistry research, ISSN 1520-5045, Bd. 0 (2024), 0, S. 1-11

Capturing the current statistical features of a process and its dynamic evolution is important for controlling and monitoring its overall operational status. In terms of capturing the process dynamics, existing probabilistic latent-variable methods mostly consider autoregressive relationships, and thus, the causality from the control inputs to the pattern, or key hidden variable, remains unmodeled or implicit. To bridge this gap, a model structured by a newly designed dynamic-controlled Bayesian network (DCBN) is proposed in this paper for pattern modeling, especially pattern control and optimization. Significantly, the innovation and advantage of the DCBN lie in explicitly quantifying the impulse response of the pattern under control inputs. As well, the expectation-maximization algorithm is specially designed for learning the DCBN model. Finally, a new framework for pattern-based process control and optimization is presented in which online pattern filtering and control can be implemented. A case study on the combustion process from an industrial boiler illustrates the advantages of the proposed method in that it can capture the controlled dynamics of the process and achieve optimization by tracking the pattern set point or trajectory.



https://doi.org/10.1021/acs.iecr.3c04391
Pikushina, Alena; Centeno, Luis Fernando; Stehr, Uwe; Jacobs, Heiko O.; Hein, Matthias
Electrical lengths and phase constants of stretchable coplanar transmission lines at GHz frequencies. - In: Flexible and printed electronics, ISSN 2058-8585, Bd. 9 (2024), 1, 015005, S. 1-12

Elastic, bendable and stretchable electronics establish a new and promising area of multi-physics engineering for a variety of applications, e.g. on wearables or in complex-shaped machine parts. While the area of metamorphic electronics has been investigated comprehensively, the behavior at radio frequencies (RFs), especially in the GHz range, is much less well studied. The mechanical deformation of the soft substrates, for instance, due to stretching, changes the geometrical dimensions and the electrical properties of RF transmission lines. This effect could be desirable in some cases, e.g. for smart devices with shape-dependent transmission or radiation characteristics, or undesirable in other cases, e.g. in feed and distribution networks due to the variable electrical lengths and thus phase variations. This contribution describes the results of a systematic study of the broadband RF properties of coplanar transmission lines on Ecoflex® substrates, based on numerical simulations and experimental data. Two types of stretchable transmission line structures were studied: Meander- and circular ring-segmented lines. Modeling and simulation were performed combining a 2D circuit simulation software with electromagnetic full-wave simulations. The experimental part of the work included the fabrication of metamorphic substrates metallized with thin copper layers and systematic measurements of the electrical lengths and phase constants of coplanar waveguides in the frequency range from 1 to 5 GHz based on vector network analysis for different stretching levels. With the given substrate technology, we succeeded in demonstrating stretchability up to a level of 21%, while the theoretical limit is expected at 57%. The meander- and circular-shaped line structures revealed markedly different sensitivities to the stretching level, which was lower for circular structures compared to the meander structures by approximately a factor of three.



https://doi.org/10.1088/2058-8585/ad1efd
Petrich, Martin; Kletzin, Ulf
Practical fatigue strength diagrams for compression springs based on the FKM-guideline “Analytic Strength Assessment for Springs“. - In: International journal of fatigue, Bd. 183 (2024), 108273, S. 1-8

Metal springs are used extensively in technical products. The mathematical relationships and Goodman diagrams contained in the DIN EN 13906-1 standard form the essential basis for the design and calculation of cylindrical helical compression springs. They are used not only nationally, but internationally in the spring industry and by spring users. However, the diagrams are more than 50 years old and no longer reflect the current status of modern spring materials and spring manufacturing technologies. This results in great uncertainty for users of the standard, which currently has to be compensated by costly fatigue tests. In order to overcome the problems, the research project IGF 19693 aimed to renew the Goodman diagrams of the DIN EN 13906-1 standard in accordance with the state of spring technology. Therefore, the FKM guideline “Analytic Strength Assessment for Springs and Spring Elements“ was used to calculate permissible fatigue strength values for standard springs. Additionally, an extensive experimental program was carried out with fatigue tests on cold-formed helical compression springs to validate the calculations. The main results of the project are presented in this manuscript, which strengthens SMEs in designing competitive springs, which they can offer in a shorter time and at a lower cost due to lower development costs.



https://doi.org/10.1016/j.ijfatigue.2024.108273
Schwarz, Andreas; Unselt, Janina Jacqueline
Rage against the machine? : framing societal threat and efficacy in YouTube videos about artificial intelligence. - In: Risk analysis, ISSN 1539-6924, Bd. 0 (2024), 0, S. 1-19

Artificial intelligence (AI) has become a part of the mainstream public discourse beyond expert communities about its risks, benefits, and need for regulation. In particular, since 2014, the news media have intensified their coverage of this emerging technology and its potential impact on most domains of society. Although many studies have analyzed traditional media coverage of AI, analyses of social media, especially video-sharing platforms, are rare. In addition, research from a risk communication perspective remains scarce, despite the widely recognized potential threats to society from many AI applications. This study aims to detect recurring patterns of societal threat/efficacy in YouTube videos, analyze their main sources, and compare detected frames in terms of reach and response. Using a theoretical framework combining framing and risk communication, the study analyzed the societal threat/efficacy attributed to AI in easily accessible YouTube videos published in a year when public attention to AI temporarily peaked (2018). Four dominant AI frames were identified: the balanced frame, the high-efficacy frame, the high-threat frame, and the no-threat frame. The balanced and no-threat frames were the most prevalent, with predominantly positive and neutral AI narratives that neither adequately address the risks nor the necessary societal response from a normative risk communication perspective. The results revealed the specific risks and benefits of AI that are most frequently addressed. Video views and user engagement with AI videos were analyzed. Recommendations for effective AI risk communication and implications for risk governance were derived from the results.



https://doi.org/10.1111/risa.14299
Ved, Kalpan; Lenk, Claudia; Ivanov, Tzvetan; Hövel, Philipp; Ziegler, Martin
Bio-inspired, adaptive acoustic sensor : Sensing properties in dependence of feedback parameters. - In: AIP conference proceedings, ISSN 1551-7616, Bd. 3062 (2024), 1, 040011, S. 040011-1-040011-10

Pre-processing of the sound signal during sensing is an integral functionality of the cochlea, the part of human hearing responsible for sound sensing. This pre-pocessing, which is integrated into the sensing stage directly, enables the remarkable properties of human hearing. Similarly, integrating some of these pre-processing functionalities in technological speech processing systems strongly improves their recognition performance.We developed a bio-inspired, adaptive acoustic sensor with pre-processing capabilities like nonlinear amplification and frequency filtering functionality. The sensor is composed of a single clamped silicon beam with integrated deflection sensing and thermo-mechanical actuation, subjected to a real-time feedback. While the resonance frequency and bandwidth are determined by the geometry of the sensor beam, its transfer characteristics can be switched dynamically from linear to nonlinear regime by changing the feedback parameters. In the linear regime, the feedback controls the sensitivity and bandwidth of the sensors. Here, we elaborate on the influence of the sign of feedback strength and offset on the sensor behaviour. Changing the sign of the feedback parameters switches between amplification and damping behaviour, enabling the change of sensitivity by 44 dB. Thereby, complex oscillation modes are observed for feedback parameters with similar polarity.



https://doi.org/10.1063/5.0189488
Sharifi Ghazijahani, Mohammad; Cierpka, Christian
Spatio-temporal dynamics of superstructures and vortices in turbulent Rayleigh-Bénard convection. - In: Physics of fluids, ISSN 1089-7666, Bd. 36 (2024), 3, 035120, S. 035120-1-035120-19

Understanding turbulent thermal convection is essential for modeling many natural phenomena. This study investigates the spatiotemporal dynamics of the vortical structures in the mid-plane of turbulent Rayleigh-Bénard convection in SF6 via experiments. For this, a Rayleigh-Bénard cell of aspect ratio 10 is placed inside a pressure vessel and pressurized up to 1, 1.5, and 2.5 bar in order to reach Rayleigh numbers of Ra = 9.4 × 10^5, 2.0 × 10^6, and 5.5 × 10^6, respectively. For all three cases, the Prandtl number is Pr = 0.79 and Δ T ≈ 7 K. Then, stereoscopic particle image velocimetry is conducted to measure the three velocity components in the horizontal-mid-plane for 5.78 × 10^3 free fall times. For the given aspect ratio, the flow is no longer dominated by the side walls of the cell and turbulent superstructures that show a two-dimensional repetitive organization form. These superstructures show diverse shapes with faster dissipation rates as Ra increases. Out-of-plane vortices are the main feature of the flow. As Ra increases, the number of these vortices also increases, and their size shrinks. However, their total number is almost constant for each Ra through the measurement period. Furthermore, their occurrence is random and does not depend on whether the flow is upward-heated, downward-cooled, or horizontally directed. Vortex tracking was applied to measure lifetime, displacement, and traveled distance of these structures. The relation between lifetime and traveled distance is rather linear. Interestingly, in the vortex centers, the out-of-plane momentum transport is larger in comparison to the bulk flow. Therefore, these vortices will play a major role in the heat transport in such flows.



https://doi.org/10.1063/5.0191403
Wunsch, Lennard; Görner Tenorio, Christian; Anding, Katharina; Golomoz, Andrei; Notni, Gunther
Data fusion of RGB and depth data with image enhancement. - In: Journal of imaging, ISSN 2313-433X, Bd. 10 (2024), 3, 73, S. 1-17

Since 3D sensors became popular, imaged depth data are easier to obtain in the consumer sector. In applications such as defect localization on industrial objects or mass/volume estimation, precise depth data is important and, thus, benefits from the usage of multiple information sources. However, a combination of RGB images and depth images can not only improve our understanding of objects, capacitating one to gain more information about objects but also enhance data quality. Combining different camera systems using data fusion can enable higher quality data since disadvantages can be compensated. Data fusion itself consists of data preparation and data registration. A challenge in data fusion is the different resolutions of sensors. Therefore, up- and downsampling algorithms are needed. This paper compares multiple up- and downsampling methods, such as different direct interpolation methods, joint bilateral upsampling (JBU), and Markov random fields (MRFs), in terms of their potential to create RGB-D images and improve the quality of depth information. In contrast to the literature in which imaging systems are adjusted to acquire the data of the same section simultaneously, the laboratory setup in this study was based on conveyor-based optical sorting processes, and therefore, the data were acquired at different time periods and different spatial locations. Data assignment and data cropping were necessary. In order to evaluate the results, root mean square error (RMSE), signal-to-noise ratio (SNR), correlation (CORR), universal quality index (UQI), and the contour offset are monitored. With JBU outperforming the other upsampling methods, achieving a meanRMSE = 25.22, mean SNR = 32.80, mean CORR = 0.99, and mean UQI = 0.97.



https://doi.org/10.3390/jimaging10030073