Results 171 to 180 of about 12,670 (246)

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Disentangling Brillouin's Negentropy Law of Information and Landauer's Law on Data Erasure. [PDF]

Entropy (Basel)
Lairez D.
europepmc   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

A principled basis for nonequilibrium network flows. [PDF]

Nat Commun
Yang YJ, Dill KA.
europepmc   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

Mitigating Stress‐Induced Nonphotoactive Phase Transition Through Sodium Sulfonate Engineering for Stable and Efficient Perovskite Solar Cells

Angewandte Chemie, EarlyView.
To address the phase stability issue of α‐FAPbI3, we employed a cation doping strategy using 1‐decanesulfonate (C10H21NaO3S). This doping releases lattice strain and suppresses the formation of the δ‐phase, enabling breakthrough performance in perovskite solar cells with a power conversion efficiency of 26.67% and excellent thermal and photostability ...
Zhihuan Tang, Mingzi Sun, Jinghao Ge, Ying Wang, Yunfan Wang, Yiran Tao, Lu Zhang, Xinhui Lu, Sai‐Wing Tsang, Weizhong Tian, Rui Wang, Hao‐Chung Kuo, Bolong Huang, Shengzhong (Frank) Liu, Jiaxue You, Alex K. Y. Jen   +15 more
wiley   +2 more sources

Minimum-Entropy Optimal Control of Electromechanical Linkages for Energy Harvesting. [PDF]

Entropy (Basel)
Fathizadeh M, Richter H.
europepmc   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Chelation Drives Surface Substitution in Hybrid‐MXenes

Angewandte Chemie, EarlyView.
We demonstrate ethylenediamine‐derived bidentate binding on Ti3C2 by controlled deprotonation of ─NH2 groups during reaction with Ti3C2Br2. XRD, XPS, ssNMR, STEM, DFT, and INS confirm the bidentate coordination and the superior stability of chelating modes, while AIMD reveals proton transfer and new surface imine–Ti bonding mode.
Vikash Khokhar, Young‐Hwan Kim, Abu Rashed Md. Shawon, Fatemeh Karimi, Danial Zangeneh, Yongqiang Cheng, Chang Liu, Murillo Longo Martins, Alexander S. Filatov, Robert F. Klie, Aaron J. Rossini, John S. Anderson, Dmitri V. Talapin, De‐en Jiang   +13 more
wiley   +2 more sources

Thermodynamic Operations and Entropy Considerations for a Ring-of-Charge Oscillator System. [PDF]

Entropy (Basel)
Cole DC.
europepmc   +1 more source