Results 161 to 170 of about 93,904 (259)

Linear and Programmable Long‐Term Plasticity in PECVD Amorphous SiC Memristors

open access: yesAdvanced Electronic Materials, EarlyView.
Stoichiometry‐engineered PECVD amorphous SiC memristors exhibit highly linear and programmable long‐term synaptic plasticity with a nonlinearity as low as 0.08. By controlling the local bonding environment, stable multilevel conductance updates are achieved, enabling robust neural‐network classification on MNIST and CIFAR‐10 and highlighting amorphous ...
Qin Liu   +6 more
wiley   +1 more source

Neighbourhood characteristics and mental disorders in three Chinese cities: multilevel models from the World Mental Health Surveys. [PDF]

open access: yesBMJ Open, 2017
Chiavegatto Filho ADP   +10 more
europepmc   +1 more source

Pulse‐Engineered Synaptic Linearity and Non‐Volatile Memory in MoO3/TiO2 Bilayer Memristors for Neuromorphic Image Recognition

open access: yesAdvanced Electronic Materials, EarlyView.
Pulse‐protocol optimization in an Au/MoO3/TiO2/FTO bilayer memristor enables linear analog synaptic conductance modulation along with digital resistive switching for memory. Controlled filament evolution produces stable learning‐forgetting characteristics with low nonlinearity, resulting in significantly enhanced neural network inference accuracy for ...
Girish Chandrashekar   +2 more
wiley   +1 more source

Design Principles of Electrocatalysts for Industrial‐Scale Water Electrolysis

open access: yesAdvanced Energy Materials, EarlyView.
This Review distills electrocatalyst design for industrial‐scale water electrolysis into integrated principles linking active‐site engineering, phase and lattice modulation, interfacial microenvironment regulation and mass‐transport control. By connecting catalyst families with HER/OER mechanisms and practical operating demands, it outlines pathways ...
Hong Tang, Cui Ce, John Wang
wiley   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

open access: yesAdvanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj   +2 more
wiley   +1 more source

Advancing Efficient Error Reduction in DNA Data Storage Systems with Deep Learning‐Based Denoising Models

open access: yesAdvanced Intelligent Discovery, EarlyView.
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo   +5 more
wiley   +1 more source

Policy Implications of Achievement Testing Using Multilevel Models: The Case of Brazilian Elementary Schools. [PDF]

open access: yesFront Psychol, 2016
Menezes IG   +6 more
europepmc   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath   +4 more
wiley   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia   +2 more
wiley   +1 more source

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