Results 141 to 150 of about 517,528 (292)

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Advanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

Fourier transform-based single domain generalization for crowd counting. [PDF]

Sci Rep
Song L, Li T, Cai Z, Guo J, He J, Xie J, Zhang Y.   +6 more
europepmc   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Anti-Inflammatory Activity of <i>Mandragora autumnalis</i> Ethanolic Extract: In Vitro and Cellular Mechanistic Insights. [PDF]

Pharmaceuticals (Basel)
Albahri G, Hellany H, Badran A, Abdel-Rahem R, Al-Remawi M, Alame M, Hijazi A, Bechelany M, Baydoun E.   +8 more
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Redefining multi-target weather forecasting with a novel deep learning model: Hierarchical temporal convolutional long short-term memory with attention (HTC-LSTM-Attn) in Bangladesh. [PDF]

PLoS One
Kabir MA, Chakma C.
europepmc   +1 more source

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

Advanced Intelligent Discovery, EarlyView.
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc, Pritam Banerjee, Felipe Jacques Lima Duarte, Joerg R. Jinschek, Premkumar Murugesan, Babak Rezaei, Stephan Sylvest Keller, Roland A. Fischer, Mian Zahid Hussain   +8 more
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Multipath Credibility Selection for Robust UWB Angle-of-Arrival Estimation in Narrow Underground Corridors. [PDF]

Sensors (Basel)
Li J, Yu B, Cui S, Yang M, Zhao J, Su R, Tian R.   +6 more
europepmc   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Advanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source