Results 81 to 90 of about 784,927 (243)

Machine Learning Driven Window Blinds Inspired Porous Carbon‐Based Flake for Ultra‐Broadband Electromagnetic Wave Absorption

Advanced Science, EarlyView.
Inspired by the regulation mechanism of window blinds, this study designs an electromagnetic wave‐absorbing metamaterial. By introducing the magneto‐electric coupling concept and integrating it with an artificial intelligence‐based data‐driven collaborative optimization strategy, the material optimizes impedance matching performance and enhances loss ...
Zhe Wang, Wanchong Li, Lu Feng, Zaiqing Yang, Shicheng Jin, Dongxu Zhao, Xiaoyong Wu, Yan Wang, Yu Mao, Jinsong Zhang   +9 more
wiley   +1 more source

Catechol Derivative‐Based Bioadhesives: Molecular Design for Precision Medical Adhesion

Advanced Science, EarlyView.
This study utilizes tree‐inspired side‐chain engineering to graft five catechol derivatives onto PVA, systematically revealing how side‐chain length and substituents regulate adhesion and cohesion properties. Among them, the PVA‐CA patch demonstrates superior tissue adhesion, biocompatibility, and promotes regeneration, establishing a programmable ...
Xueyu Wang, Zixin Yang, Shan Wang, Weiwei Tan, Zhirui He, Qinyu Duan, Huanan Wang, Tao Chen, Shanshan Hu   +8 more
wiley   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Basal Plane Activation of SnS2 Thin‐Film by Fluorine Doping for Selective Solar‐Driven CO2 Reduction With Enhanced Quantum Efficiency

Advanced Science, EarlyView.
The synergistic effect of fluorine doping and sulfur vacancies boosts the activity of the active sites without active‐site modulation, leading to enhanced CO2 photoreduction efficiency and a selectivity switch from CH4 to CO on tin disulfide continuous thin films. ABSTRACT Photocatalytic conversion of CO2 into value‐added fuels offers a viable approach
Tadios Tesfaye Mamo, Mohammad Qorbani, Adane Gebresilassie Hailemariam, Putikam Raghunath, Che‐Men Chu, Wen‐Hsin Yuan, Amr Sabbah, Yen‐Yu Wang, Shuo‐Yun Chang, Ming‐Chang Lin, Wei‐Yen Woon, Yu‐Jung Lu, Heng‐Liang Wu, Ken‐Tsung Wong, Kuei‐Hsien Chen, Li‐Chyong Chen   +15 more
wiley   +1 more source

Accelerated Screening of Halide Double Perovskites via Hybrid Density Functional Theory and Machine Learning for Thermoelectric Energy Conversion

Advanced Energy and Sustainability Research, EarlyView.
This study integrates hybrid density functional theory, Boltzmann transport theory, and machine learning to accelerate the discovery of lead‐free halide double perovskites for thermoelectric energy conversion. By screening 102 compounds, the authors identify high‐performing candidates such as Rb2GeI6 and Cs2SnBr6, offering a sustainable pathway toward ...
Souraya Goumri‐Said, Ghouti Abdellaoui, Mohammed Benali Kanoun   +2 more
wiley   +1 more source

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

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +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

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source