Results 151 to 160 of about 3,444 (219)

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

Ion‐Gating Reservoir Computing for Preprocessing‐Free Speech Recognition from Throat Vibrations

Advanced Electronic Materials, EarlyView.
This work presents a throat‐mounted mechanoelectric sensor integrated with an ion‐gel/graphene reservoir device for on‐device speech recognition. The system converts raw biomechanical vibrations into rich nonlinear current dynamics, enabling efficient classification through a simple linear readout. The approach highlights a compact and tunable physical‐
Daiki Nishioka, Akito Tateyama, Hina Kitano, Takashi Nakanishi, Kazuya Terabe, Takashi Tsuchiya   +5 more
wiley   +1 more source

Bridging Performance and Fate: A Framework for Sustainable, Composite‐Based Flexible Electronic Systems

Advanced Electronic Materials, EarlyView.
Composite‐based flexible electronics integrate biodegradable polymers, conductive networks, and multilayer device architectures to balance electrical performance, mechanical durability, and controlled degradation. Interfacial engineering and encapsulation regulate transport stability and operational lifetime, while programmed disassembly enables ...
Sayam, Sangho Cho
wiley   +1 more source

Environmental Effects on RRAM Cells Based on 2D Halide Perovskite Materials

Advanced Electronic Materials, EarlyView.
RRAM offers high speed, scalability, and low power, positioning it as a next‐generation non‐volatile memory. Two‐dimensional halide perovskites show promise due to tunable optoelectronic properties and flexible processing but suffer from environmental sensitivity. This review examines degradation from humidity, temperature, light, and strain, discusses
Mojtaba Joodaki, Babitha Arun, Hartmut Hillmer, Chih‐Chieh Hsu   +3 more
wiley   +1 more source

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

Advanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali, David Lehninger, Florencio Sánchez, Ignasi Fina   +3 more
wiley   +1 more source

Two‐Dimensional Materials for Flexible Neuromorphic Devices: Materials, Engineering Strategies, Architectures, and Emerging Applications

Advanced Electronic Materials, EarlyView.
This review explains how atomically thin materials can combine information storage, processing, and mechanical flexibility in neuromorphic devices. It connects material properties and engineering strategies with device architecture, synaptic behavior, and performance under bending.
Junzhe Tang, Letian Dai
wiley   +1 more source

Atomic‐Scale Mechanisms of Anisotropic Thermal Decomposition in GeSn Alloys With Stepwise Pinning

Advanced Electronic Materials, EarlyView.
Combining in situ TEM with DFT calculations, this work elucidates atomic‐scale anisotropic thermal decomposition in GeSn films, identifying laminar receding in defect‐free regions and stepwise pinning at stacking faults. Driven by crystallographic anisotropy and defect‐mediated energetic penalties, these findings establish a physical framework for ...
YiXin Wang, Qi Liu, XiYan Chang, Chi Xu, Tao Wang, XinZheng Li, ChunLai Xue   +6 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Redesigning Interlayers for Anode‐Free Batteries: Harnessing Continuity and Metal Inventory

Advanced Energy Materials, EarlyView.
Interlayers for anode‐free batteries must provide continuous interfacial coverage while remaining thin enough to preserve the finite cathode‐derived active‐metal inventory. This Perspective couples thin‐film closure with stoichiometric active‐metal consumption to reveal practical design windows across chemistry, substrate roughness, cathode loading ...
Rosalía Cid, Lorenzo Fallarino
wiley   +1 more source