Results 211 to 220 of about 5,883,213 (294)

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

open access: yesAdvanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram   +4 more
wiley   +1 more source

Multiferroic‐Centric Materials and Systems Engineering for Battery Applications: An Insight Into Mechanisms, Strategies, and Characterizations

open access: yesAdvanced Science, EarlyView.
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su   +13 more
wiley   +1 more source

Unveiling a Hidden Conversion Pathway in CoSe2 Anodes via Rationally Designed CNT‐Interwoven Hollow Carbon Microclusters for High‐Performance Potassium‐Ion Batteries

open access: yesAdvanced Science, EarlyView.
A rational architectural design of hierarchical, CNT‐interwoven hollow carbon microclusters unlocks and stabilizes a unique monoclinic Co3Se4‐mediated conversion–insertion pathway for potassium storage. This structural confinement effectively guides the reaction kinetics and accommodates severe mechanical strain.
Ho Rim Kim   +8 more
wiley   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

open access: yesAdvanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai   +3 more
wiley   +1 more source

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

open access: yesAdvanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi   +7 more
wiley   +1 more source

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