Results 91 to 100 of about 18,699 (193)

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

Hydro-Torsional Compaction for Scalable Production of Aramid Nanofiber Threads with Densely Assembled Double-Helical Nanostructures. [PDF]

Adv Mater
Jeong W, Shin H, Lee J, Eom W, Wie JJ, Han TH.   +5 more
europepmc   +1 more source

Optimizing 3D Bin Packing of Heterogeneous Objects Using Continuous Transformations in SE(3)

Advanced Intelligent Systems, EarlyView.
This article presents a method for solving the three‐dimensional bin packing problem for heterogeneous objects using continuous rigid‐body transformations in SE(3). A heuristic optimization framework combines signed‐distance functions, neural network approximations, point‐cloud bin modeling, and physics simulation to ensure feasibility and stability ...
Michele Angelini, Marco Carricato
wiley   +1 more source

Charge Directed Selective Co-Assembly of Ionic Complementary Peptide Binary Mixtures. [PDF]

Small
Khedr A, Soliman MAN, Corrigan A, Sahota T, Armitage R, Allcock N, Jegadeesan JT, Amer MH, Alazragi R, Ahmad Z, Wychowaniec JK, Elsawy MA.   +11 more
europepmc   +1 more source

Concentric Rheostat Decoupled 3D Force‐Sensing Module for Smart Table Tennis Training

Advanced Intelligent Systems, EarlyView.
A 3D‐printed sensor array intrinsically decouples normal and shear forces through a unique concentric structural design. By integrating piezoresistive, sliding area‐varying capacitive, and concentric rheostat mechanisms, the 12‐sensor module achieves high‐resolution 3D force mapping without complex algorithms.
Zhe Liu, Kunlin Wu, Bingrui Sim, Wenjie Lai, Xingyu Chen, Jiajun Liu, Yifan Wang, Soo Jay Phee   +7 more
wiley   +1 more source

Tropical Refined Curve Counting with Descendants. [PDF]

Commun Math Phys
Kennedy-Hunt P, Shafi Q, Urundolil Kumaran A.   +2 more
europepmc   +1 more source

High‐Performance Solid‐State Lithium Batteries via Dipole‐Matching: Enabling Compact Polymer Microstructure and Stable Interfaces

Carbon Energy, EarlyView.
A dipole–matching strategy is proposed to engineer PVDF‐HFP solid polymer electrolytes by incorporating 3,5–bis(trifluoromethyl)benzoic acid. Dipole interactions regulate polymer nucleation and phase alignment, forming compact microstructures, while controlled FSI– decomposition induces a LiF–rich interphase, enabling fast Li+ transport, uniform ...
Ya Song, Haotian Qu, Bosi Huang, Jie Tang, Yanfei Zhu, Wenqiang Fang, Zijun Li, Zhoujie Lao, Zhuozhao Wu, Xian Wu, Jinlong Yang, Guangmin Zhou   +11 more
wiley   +1 more source

Prediction of carbon nanostructure mechanical properties and the role of defects using machine learning. [PDF]

Proc Natl Acad Sci U S A
Winetrout JJ, Li Z, Zhao Q, Gaber L, Unnikrishnan V, Varshney V, Xu Y, Wang Y, Heinz H.   +8 more
europepmc   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Improved Statistics for F-theory Standard Models. [PDF]

Commun Math Phys
Bies M, Cvetič M, Donagi R, Ong M.
europepmc   +1 more source