Fraunhofer Institute for Electronic Nano Systems

This study investigates the use of machine learning regression algorithms to analyze signals from Capacitive Micromachined Ultrasound Transducers (CMUTs) for enhanced flow rate estimation. CMUTs fabricated at Fraunhofer ENAS using wafer bonding technology, operating at a resonant frequency of 2 MHz, were integrated into a custom flow measurement setup based on the transit-time principle, utilizing two CMUTs in transmit and receive modes. To address the challenges in transittime analysis such as, fluctuations due to turbulence, signal overlap and low signal-to-noise ratio at low flow rates, we propose a data-driven approach that uses regression to extract flowdependent features directly from CMUT signals. Through careful feature selection and robust validation techniques, the study demonstrates that even simple models can effectively capture and predict flow rate variations, under constraints of limited dataset. These results highlight the potential of regression-based approaches to enhance the sensitivity and adaptability of CMUTbased flow measurement systems, without the need for additional sensor modifications.

Ensuring security and comfort in public transportation is essential, particularly in the post-COVID-19 era. Passengers not only require reliable transit services but also expect sufficient space and healthy air quality for a safe travel experience. However, existing public transport systems lack realtime monitoring solutions for air quality and vehicle occupancy. This paper presents SenMooVe, a sensor platform designed for real-time air quality monitoring and passenger occupancy estimation in public vehicles. The platform consists of a Master unit for data acquisition and transmission, air quality sensors, and Ultra-wideband (UWB) radar sensors for passenger detection. Additionally, it integrates GPS signals for real-time vehicle tracking and interfaces with the Integrated Board Information System (IBIS) to access passenger information, stop locations, and schedule updates. It also monitors bus door status to enhance operational safety and efficiency. An initial experiment conducted in an suburban/rural environment collected 3,623 data samples over approximately 300 hours of operation. A preliminary correlation between air quality and passenger numbers has been established using data from an already integrated time-of-flight (ToF) based passenger counting system at bus doors. To facilitate further research and development, these datasets are made publicly available, providing valuable insights for transport operators, route planners, academic researchers, and public institutions. Future work will focus on developing a user-friendly visualization summary for real-time passenger information, enhancing situational awareness and ensuring a safer, more comfortable travel experience.

Advanced applications such as the Internet of Things, smart driving and Industry 4.0 rely on miniaturized high-performance devices for different tasks such as sensing, actuating or data processing. For improving their performance, new and advanced materials are required to be integrated as a functional material and construction material. A new packaging platform for smart systems was successfully developed based on Parylene, using the polymer as an ultra-thin substrate, dielectric between multiple redistribution layers as well as encapsulation layer for realizing an ultra-thin printed circuit board for highly flexible electronics and sensors. Within this work, Parylene is investigated for its usage as a memristive material in order to create memristors, that can be directly integrated in that ultrathin printed circuit board and add an additional functionality to the material. Doing so, metal-Parylene-metal layer stacks were fabricated as memristive test architectures and their memristive properties were characterized electrically. For analyzing the impact of the different parameters, the Parylene thickness was varied and various annealing conditions were applied for adjusting and optimizing the crystallinity and molecular density. Furthermore, the electrode size was varied and different experiments for the formation of the filaments were carried out for a better understanding. Typical hysteresis loops were successfully achieved for the Parylene memristors with low voltages and currents as well as a good stability and reproducibility, making the Parylene memristor technology attractive for low-power applications

We present a high-cycle fatigue (HCF) test designed for the accelerated stress testing of metallization layers and bi-material interfaces in microelectronic packages under controlled periodic displacement amplitudes and isothermal conditions. The primary objective of this study is to examine the delamination of bi-material interfaces. The samples utilized for testing are manufactured on a magnetic steel substrate, employing the same processes employed in the production of the microelectronic packages to be tested. A range of methodologies have been developed for sample preparation. To excite the sample, we use magnetic actuation. The sample is subjected to oscillation from a cyclic load, allowing for several million oscillation cycles in a short time. The change in crack length can be determined using a stiffness method by capturing changes in the beam's vibration spectrum. Besides this method of crack measurement, crack progression can also be calculated from the measurement of the bending line. This stress method enables the rapid testing of the integrity of microelectronic components under harsh conditions.

This paper is dedicated to the integration of photonic components into Micro-Electro-Mechanical Systems (MEMS) to develop high-performance inertial sensors, particularly for autonomous vehicle applications. Traditional MEMS sensors face limitations in electrical signal conversion. Optomechanical sensing, which couples mechanical motion with optical detection, offers enhanced sensitivity, reduced noise, and improved stability. By embedding optical components directly into the MEMS structure, we aim to address these advantages for improved performance, to be first demonstrated for a sensor/actuator test structure compatible for acceleration measurement. The paper describes in detail the design and fabrication process, incorporating electrostatic actuators, sensors and optical ring resonators into OptoMEMS. Comprehensive simulations use ANSYS Mechanical for mechanical and electrostatic part with a coupling to ANSYS Lumerical to convert mechanical deformations into optical resonance shifts. Preliminary fabrication and measurement results validate the simulation concept, demonstrating the feasibility of this integrated optomechanical approach.

MaterialDigital Initiative The cover image illustrates the concept of advancing digital transformation within the MaterialDigital Initiative through workflows, as discussed in article number 2402149 by Jörg Schaarschmidt and co-workers. The projects within this initiative utilize various concepts and tools, applied to a broad range of material classes. A digital library, the PMD Workflow Store, has been established to disseminate these workflows enabling FAIR principles. The image shows an examplary workflow developed within StahlDigital, discussed in detail in article number 2402148. Graphical Design: Christine Heinrich.

ABSTRACTThis paper deals with a method for strain determination around boreholes in plastic specimens in the context of residual stress analyses. In contrast to the frequently used hole drilling method with strain gauges, the strains are determined using digital image correlation (DIC). In the investigations presented, load stresses occur instead of residual stresses, which is caused by defined loading conditions. Furthermore, an adaption of the hole drilling method is developed, called staggered machining, which includes the successive drilling of a larger and a smaller borehole to obtain deformation data in larger depths compared to the conventional approach. For strain evaluation, a special method is used with parametrisation of an annulus around the borehole. In this region, B‐spline approximation of the DIC displacements is carried out using an optimisation procedure of the smoothing parameter. The tests of the entire method show very plausible and precise results. Furthermore, a comparison with simulation demonstrates good correlation of the strain distributions.

Abstract The edges of layered double hydroxides (LDHs) display an exceptionally more 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 (1 M KOH), NiFe LDHs‐E exhibits excellent OER activity with very low overpotential (235 mV at 10 mA cm−2) and current densities (at η = 320 mV) up to sixfold 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.