Results 151 to 160 of about 3,436,516 (244)

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

open access: yesAdvanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho   +6 more
wiley   +1 more source

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

open access: yesAdvanced 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   +3 more
wiley   +1 more source

Tuning Local Modulus at Liquid Metal‐Polymer Interfaces Regulates Electrocaloric Effect in Ferroelectric Nanocomposites

open access: yesAdvanced Electronic Materials, EarlyView.
Liquid metal nanoparticles create mechanically compliant polymer interfaces that facilitate reversible dipolar reorientation under electric fields, whereas rigid interfaces impose stronger local constraints. This soft–rigid interface comparison reveals local interfacial modulus as a key parameter for tuning electrocaloric entropy change in ...
Tian Yao   +15 more
wiley   +1 more source

Oxygen‐Scavenging‐Driven Interlayer Engineering for Balancing Linearity and Retention in IGZO Synaptic Memristors

open access: yesAdvanced Electronic Materials, EarlyView.
Oxygen‐scavenging‐induced self‐formed interlayers regulate Schottky‐barrier modulation in IGZO memristors, producing a fundamental trade‐off between synaptic update linearity and retention. A preserved AlOx interlayer moderates voltage distribution and enables gradual, nearly linear conductance updates, whereas a soft‐broken SiO2 interlayer provides a ...
Jae Woo Lee   +11 more
wiley   +1 more source

Engineering Polar Nanoregions in COFs via Controlled Symmetry Breaking Toward Piezocatalysis

open access: yesAngewandte Chemie, EarlyView.
Polar nanoregions (PNRs) are engineered within covalent organic frameworks via asymmetric grafting of highly polar polyfluoroalkyl chains, which enables controlled symmetry breaking. These randomly oriented artificial PNRs dynamically respond to mechanical stimuli and impart relaxation behavior to the COFs (TFB‐TAPT‐FA).
Ge Yan   +13 more
wiley   +2 more sources

Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology

open access: yesAdvanced Intelligent Discovery, EarlyView.
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh   +3 more
wiley   +1 more source

Light‐Driven Control of Polar Order in Ferroelectric Nematic Liquid Crystals

open access: yesAngewandte Chemie, EarlyView.
Light‐responsive ferroelectric nematics are achieved by molecularly matching azobenzene photo‐switches to the polar packing motif of DIO. This design yields intrinsically photo‐responsive ferroelectric nematic mesogens and optically addressable DIO blends, in which light reversibly modulates spontaneous polarization and switches between high‐ and low ...
Anjali Devi Das   +5 more
wiley   +2 more sources

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

open access: yesAdvanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi   +3 more
wiley   +1 more source

Mirror versus Inversion Symmetry Breaking in Mesogenic Dimers: NTB versus NF Phase

open access: yesAngewandte Chemie, EarlyView.
Two non‐conventional nematic phases, twist‐bend NTB and ferroelectric NF, are observed within the same homologous series of dimers built of two strongly dipolar mesogenic units linked by a flexible spacer. The type of the phase formed depends on the molecular geometry, defined by parity of internal linkage.
Małgorzata Bakiera   +6 more
wiley   +2 more sources

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

open access: yesAdvanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi   +2 more
wiley   +1 more source

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