Results 151 to 160 of about 67,619 (257)

Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

Advanced Functional Materials, EarlyView.
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang, Qian Wang, Seong‐Hoon Jang, Hao Li   +3 more
wiley   +1 more source

Interpretable machine learning model based on multimodal MRI radiomics for Alzheimer's disease diagnosis. [PDF]

Front Aging Neurosci
Keranmu N, Aizezi D, Pan X, Yang L, Liu Y, Liu J.   +5 more
europepmc   +1 more source

Advances in Solution‐Processed Textile Triboelectric Nanogenerators: Ink Formation, Processing Strategies, Applications, and Challenges

Advanced Functional Materials, EarlyView.
Advanced ink systems for solution‐processed textile triboelectric nanogenerators are systematically summarized, spanning conductive, tribo‐negative, and tribo‐positive layers. By connecting ink chemistry, deposition methods, and device function, the present review reveals the key governing principles of solution development and highlights practical ...
Xinlong Sun, Stephen Beeby
wiley   +1 more source

Interpretable machine-learning for depression classification based on a three-component EEG marker. [PDF]

Front Comput Neurosci
Zhang H, Kan J, Tong W, Wu B, Zhao Y, Ma Y.   +5 more
europepmc   +1 more source

Autonomous Multi‐Objective Nanoscale Characterization of Combinatorial (Al, Sc, B)N Films Reveals Composition‐Dependent Ferroelectric Regimes

Advanced Functional Materials, EarlyView.
Autonomous scanning probe microscopy and multi‐objective Bayesian optimization navigate a ternary (Al,Sc,B)N combinatorial library. Registered photoluminescence, electron‐probe compositional mapping, and X‐ray diffraction connect local electromechanical function to defect‐sensitive emission, composition, and crystal structure.
Yu Liu, Aditya Raghavan, Utkarsh Pratiush, Ian Mercer, Pochun Hsieh, Albert Suceava, Chih‐Yu Lee, Edgar Dimitrov, Mauricio Terrones, Ichiro Takeuchi, Venkatraman Gopalan, Jon‐Paul Maria, Sergei V. Kalinin   +12 more
wiley   +1 more source

Interpretable machine learning for endometriosis classification: a rule-based approach. [PDF]

BMC Med Inform Decis Mak
Anbari Moghadam S, Akhondzadeh Noughabi E, Jahanian Sadatmahalleh S.   +2 more
europepmc   +1 more source

Designing Vanadium‐Based Oxide Electrocatalysts for Water Splitting: Experimental and Mechanistic Insights with Machine Learning

Advanced Functional Materials, EarlyView.
This review establishes structure‐property‐mechanism relationships across six modification strategies for V‐based oxide water‐splitting electrocatalysts: lattice engineering, heteroatom doping, interface engineering, carbon‐based hybridization, morphology engineering, and surface reconstruction and pre‐catalyst design, where dissolution is reframed as ...
Youness El Issmaeli, Amina Lahrichi, Hoje Chun, Rafael Gómez‐Bombarelli, Bruno G. Pollet   +4 more
wiley   +1 more source

Architecture‐Driven Functional Coupling in Vertically Aligned Nanocomposites

Advanced Functional Materials, EarlyView.
Vertically aligned nanocomposites define a growth‐engineered architecture in which vertical interfaces, strain fields, defect pathways, and phase connectivity are created simultaneously. This review shows how these architectural features couple ferroic, optical, ionic, electrochemical, and device responses, establishing design rules and open challenges
Md Shatil Islam‐Shanto, Javier Zamudio‐García, Abraham Sánchez‐Caballero, David Marrero‐López, Vincenzo Esposito   +4 more
wiley   +1 more source

Optimizing NiMo Electrocatalyst Coatings for Hydrogen Evolution in Alkaline Electrolysis With The Machine Learning‐Guided Autonomous Platform CatBot

Advanced Functional Materials, EarlyView.
This work presents a closed‐loop optimization workflow integrating CatBot, an automated synthesis and testing system, to discover NiMo hydrogen‐evolution catalysts. CatBot synthesised and evaluated 228 unique samples, identifying the best performing catalysts for transfer to nickel‐foam electrodes. The best candidate is highly active, reaching 1 Acm−2${
Paolo Vincenzo Freiesleben de Blasio, Jonas Elsborg, Elif Coşkun, Andreas Burger, Pradipkumar Manubhai Leuaa, Thu Pham Anh Phan, Jin Hyun Chang, Christodoulos Chatzichristodoulou   +7 more
wiley   +1 more source

Correction: Interpretable machine learning-based real-time sepsis diagnosis. [PDF]

Sci Rep
Mahmud F, Quamruzzaman M, Sanka AI, Cheung RCC, Chowdhury MH.   +4 more
europepmc   +1 more source