Results 31 to 40 of about 609 (157)

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Fast Terahertz 3D Super-Resolution Surface Reconstruction by Variational Model from Limited Low-Resolution Sampling [PDF]

, 2022
Integrating with the signal processing, inverse Radon transform, and the variational model, the framework at least saving 83% data acquisition time for fast, smooth three-dimensional (3D) reconstruction from the limited dataset is elucidated in the field
Zhang, Yiyao, Yang, Shang-Hua, Chen, Ke, Yang, Shang Hua   +3 more
core   +1 more source

Extraction of Iris Characteristics Using a Combination Transform for Biometric Any individual Identification

Iraqi Journal of Information & Communication Technology
 The iris of the eye is used as an identifying and affirmative biometric in many vital applications such as banking and airports.And iris identification is one of the most reliable and accurate biometric identification systems available due to its ...
Noora H. Sherif, Anmar A. Wahab, Mohammed H. Ali   +2 more
doaj   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Advanced detection and tracking in medium PRF radar [PDF]

, 2009
4th EMRS DTC Technical Conference – Edinburgh 2007This paper describes an improved method of target tracking particularly applicable to littoral environments where a wide range of clutter characteristics are present.
Lewis, Michael B., Hughes, Evan J.
core  

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

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

Surface Charges Guided Quasi‐TEM‐mode Microwave Propagation along Dielectric Nanowire

Advanced Physics Research, EarlyView.
According to Maxwell's equations, a single‐conductor transmission line cannot allow TEM‐mode electromagnetic wave propagation, however, this is based upon the assumption that dielectric material is isolated from the environment. In practice, surface electrostatic charges widely existed in nano‐materials with large surface‐to‐volume ratio.
BoYan Xu, Kaibo Zhang, Haojie Gao, Zhiyuan Gao, Kai Wang, Lihuan Zhao, Qi Yang, Bifeng Cui   +7 more
wiley   +1 more source

Copula‐based joint modelling of emergency department visits with time‐varying dependence

Canadian Journal of Statistics, EarlyView.
Abstract Jointly modelling multiple correlated count time series is essential in health services research, where outcomes like emergency visits for mental health and substance use often evolve together. Ignoring these dependencies can obscure meaningful trends and limit the effectiveness of policy evaluation.
Guanjie Lyu, Cindy Feng, Lihui Liu
wiley   +1 more source