Results 161 to 170 of about 1,759,166 (246)

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

Competing Charge Separation Pathways Govern Charge Generation in Organic Photovoltaic Blends: Insights From Transient Electron Spin Resonance

open access: yesAdvanced Energy Materials, EarlyView.
Transient electron spin resonance distinguishes interfacial charge‐transfer states from separated charges, revealing competing charge separation pathways in organic photovoltaic blends. The relative contributions of fast charge separation and a pathway mediated by spin‐polarized charge‐transfer states vary across different blends, with high‐efficiency ...
Jack M. S. Palmer, Claudia E. Tait
wiley   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

open access: yesAdvanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows   +7 more
wiley   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Talk to Your Data: An Agentic Artificial Intelligence‐Driven Decision‐Support Framework for Prosumer Energy Optimization and Recommendations

open access: yesAdvanced Intelligent Systems, EarlyView.
An agentic AI‐driven decision‐support framework for prosumers is proposed, integrating PV generation, load profiling, and multihorizon optimization within a four‐agent architecture. The approach significantly reduces grid dependence, enhances self‐sufficiency and prevents system oversizing.
Adela BÂRA, Simona‐Vasilica OPREA
wiley   +1 more source

Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture

open access: yesAdvanced Intelligent Systems, EarlyView.
The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen   +3 more
wiley   +1 more source

Robust Representation Learning for Clean Feature Discovery in Incomplete Multi‐View Clustering

open access: yesAdvanced Intelligent Systems, EarlyView.
Robust feature discovery in incomplete multi‐view clustering is achieved by coupling RPCA‐based clean representation recovery with neural‐network‐assisted graph learning. The resulting RIMVC framework constructs cleaner and more discriminative graph‐structured representations from incomplete and noisy multi‐view data, improving clustering robustness ...
Ping Hu   +4 more
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

open access: yesAdvanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne   +5 more
wiley   +1 more source

Scaffold‐Free Living Cellular Structure With Omnidirectional Architectures

open access: yesAdvanced NanoBiomed Research, EarlyView.
Hydrogel lumen confinement enables the direct formation of mechanically stable, scaffold‐free cellular filaments under entirely aqueous, phototoxicity‐free conditions. These processable living building blocks support omnidirectional assembly into complex three‐dimensional architectures, providing a simple and versatile platform for scaffold‐free ...
Jing Ma   +7 more
wiley   +1 more source

In Vivo Nb4C3Tx MXene‐Assisted Photothermal Therapy of Melanoma in Mice

open access: yesAdvanced NanoBiomed Research, EarlyView.
Nb4C3Tx MXene converts pulsed 1064 nm irradiation into localized heat, producing concentration‐ and time‐dependent melanoma cell killing in vitro and suppressing tumor growth in mice. Histology reveals extensive tumor damage, macrophage‐associated material clearance, and no detectable persistent deposits in examined visceral organs, supporting Nb4C3Tx ...
Anton Roshchupkin   +22 more
wiley   +1 more source

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