Results 111 to 120 of about 111,108 (251)
Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone +11 more
wiley +1 more source
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner +14 more
wiley +1 more source
ABSTRACT Electronic waste has emerged as a major environmental challenge, driven by the massive consumption and a limited lifetime of modern electronic devices, stimulating the development of sustainable electronics. Here, an all‐biomaterial gelatin‐choline‐citric acid ([Ch][CA]) ionogel is developed as an active binder to realize self‐sintered ...
Lin Guo +10 more
wiley +1 more source
Electrospun Wood‐Derived Biopolymers as Electrodes in Electrochemical Energy Storage Technologies
Electrospinning transforms wood‐derived cellulose and lignin into architecturally defined, binder‐free carbon electrodes with tuneable porosity and functionality. This review shows how fibre design enables decoupled charge and mass transport, enhancing performance across battery systems, while identifying key challenges in spinnability, scalability ...
Michael W. Thielke +3 more
wiley +1 more source
Ionic Precursors Transformed Into Vinyl Acetate Synthesis Catalyst via Reaction‐Driven Restructuring
This work demonstrates that a simple physical mixture of Pd and Au ionic precursors, KOAc promoter, and SiO2 support can transform into a highly active vinyl acetate synthesis catalyst through reaction‐driven restructuring. The results highlight reaction‐induced restructuring as an innovative and sustainable catalyst design strategy.
Byeong Jun Cha +11 more
wiley +1 more source
Combinatorial vapor deposition enables independent tuning of Cs/Pb and Br/Cl in wide‐bandgap perovskites. Automated multimodal mapping of 500+ compositions reveals a high‐energy optical transition that correlates with enhanced photoluminescence, defining a practical Cs/Pb window.
Alexander Wieczorek +6 more
wiley +1 more source
A systematic review is conducted to assess the influence of electrode architecture across micro‐ to mesoscopic length scales on electron‐transfer pathways in electrocatalysis. We discuss the structure‐activity relationships in electrocatalytic applications, including resource recovery and environmental remediation, and provide cost‐effective, efficient
Manshu Zhao +6 more
wiley +1 more source
Low‐frequency noise spectroscopy defines the resolvable conductance states of synaptic FeFETs by coupling read‐current fluctuation with usable dynamic range. The resulting noise‐limited bit precision establishes a universal, device‐agnostic reliability metric beyond the memory window, enabling quantitative benchmarking and rational design of high ...
Jaehong Park +12 more
wiley +1 more source
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan +4 more
wiley +1 more source

