Results 201 to 210 of about 6,228,394 (297)

Experimental Demonstration of Temporally Aware Fault‐Tolerant Sensor Fusion Using Memristive Associative Learning

open access: yesAdvanced Electronic Materials, EarlyView.
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj   +4 more
wiley   +1 more source

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

open access: yesAdvanced 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

Metric validation for detection of delayed and directed coupling. [PDF]

open access: yesJ Neural Eng
Dembny K   +4 more
europepmc   +1 more source

Sulfide‐Based Electrolytes for All‐Solid‐State Sodium Batteries

open access: yesAdvanced Energy Materials, EarlyView.
This review covers the structural features and synthesis strategies of sulfide‐based solid electrolytes, as well as critical challenges related to conductivity, interfacial and moisture stability, and scaling‐up for practical application in Sodium‐based All Solid‐State Batteries.
Han Yang   +6 more
wiley   +1 more source

Emerging Materials and Future Strategies for Solid Oxide Electrochemical Cells

open access: yesAdvanced Energy Materials, EarlyView.
Solid oxide electrochemical cells operate under strongly coupled electrochemical and thermodynamic conditions, where performance is constrained by interactions among crystal structure, defect chemistry, and interfacial evolution. This review, based on a structure‐defect‐property‐durability framework, reveals the roles of lattice symmetry and defect ...
Qiuchun Lu   +4 more
wiley   +1 more source

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

open access: yesAdvanced 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   +19 more
wiley   +1 more source

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