Results 101 to 110 of about 89,011,091 (196)

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

Advanced 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, Ri He, Junxian Liu, Liangzhi Kou   +3 more
wiley   +1 more source

Pseudo-Additive Tsallis Entropy and Non-Factorizing Joint Statistics in Product Sheffer Stroke Basic Algebras. [PDF]

Entropy (Basel)
Senturk I, Bilge M, Oner T.
europepmc   +1 more source

Wearable‐Derived Diurnal Alignment Between Physical Activity and Device Temperature Predicts Future Disease and Mortality Risk

Advanced Science, EarlyView.
Wearable‐derived diurnal alignment between physical activity and device temperature, decomposed into 24 h coupling strength (M24), phase deviation (D24), and 12 h harmonic magnitude (M12), is examined in approximately 90,000 UK Biobank participants.
Han Chen, Jiahe Wei, Jonathan Cedernaes, Christian Benedict, Athanasios Tsanas, Zhi Cao, Xiao Tan   +6 more
wiley   +1 more source

Integrating First-Principles Modeling with Explainable Machine Learning for Non-Isothermal Chromatography. [PDF]

ACS Omega
Bilal M, Haq S, Asif M, Alhartomi AM.
europepmc   +1 more source

Machine‐Learning Framework for Designing Stable Interfaces in All‐Solid‐State Lithium‐Ion Batteries

Advanced Science, EarlyView.
A data‐driven strategy is developed to discover coating materials for all‐solid‐state lithium batteries. Using calculations of interfacial reactivity, unsupervised pattern recognition, and machine‐learning prediction, the study identifies low‐reactivity compositional patterns and screens new lithium‐based oxide and polyanion candidates, extending ...
Sehyeok Park, Myeongcho Jang, Hun‐Gi Jung, Kyung Yoon Chung, Seungho Yu   +4 more
wiley   +1 more source

How do my distributions differ? significance testing for the overlapping index using permutation tests. [PDF]

Psychon Bull Rev
Calignano G, Perugini A, Nucci M, Finos L, Pastore M.   +4 more
europepmc   +1 more source

Halide Perovskite: A Rich Source of Thermal Insulator

Advanced Science, EarlyView.
Halide perovskites exhibit ultralow thermal conductivity driven by intrinsic lattice softness and strong anharmonicity, falling below conventional defect‐engineering limits. Weak metavalent bonding, A‐site rattling, and dynamic octahedral tilting drive phonon scattering to the Ioffe–Regel limit, where wave‐like tunneling replaces particle‐like ...
Haolin Ye, Bangzhi Ge, Yuan Yu, Chongjian Zhou   +3 more
wiley   +1 more source

Basis-driven learnable operator for MLP-mixers. [PDF]

Front Artif Intell
Elsheikh A, Fouda ME, Eltawil AM.
europepmc   +1 more source

Deep Learning Network‐Tailored Microenvironment Matching of 4D Bioprinting Bioactive Scaffolds for Bone Regeneration

Advanced Science, EarlyView.
A DLN dataset was built to analyze MABS composition versus in vitro/in vivo osteogenesis and angiogenesis. An MLP neural network, taking BG morphological parameters as input, extracts bioactive features from these datasets. A rabbit tibial defect model then validates 4D‐printed MABS for adaptability and bone regeneration in critical defects.
Xiongjie Liang, Yuechi Zhang, Weifeng Hu, Shiyan Lv, Fan Jia, Yan Zhang, Feng Wu, Changjiang Yang, Guanqi Zhen, Jinglong Yan, Xu Cui, Wei Zhao, Guanghua Chen   +12 more
wiley   +1 more source

Robust Distribution-Free Tests for the Linear Model. [PDF]

Stat Med
Hilbert T, MacEachern SN, Zhang Y.
europepmc   +1 more source