Results 111 to 120 of about 4,496 (248)

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

Template‐Encoded Assembly and Adaptive Function in Selenium‐Based Molybdenum Chalcoxide Rings

Angewandte Chemie, EarlyView.
External templates write structural information into Se‐containing molybdenum rings, while selenium's softness confers adaptive host–guest behaviour and catalytic responsiveness, an integrated framework for programmable inorganic function. ABSTRACT Controlling both structure and function in inorganic self‐assembly remains a major challenge.
Giulia Pellegrino, Alexander Elliott, Yu‐Fei Song, Nuno A. G. Bandeira, Haralampos N. Miras   +4 more
wiley   +2 more sources

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

NONMETAL TO METAL TRANSITION IN LIQUID CHALCOGENIDES

, 1981
From static magnetic susceptibilities it is found that a nonmetal to metal transition occurs in some doped liquid chalcogenides. With increasing doping level the transition is shifted to lower temperatures. The density ds of paramagnetic centers at the transition is constant in both of the systems investigated.
openaire   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Physics‐Grounded Probabilistic Bits for Hardware‐Efficient Intelligent Inference and Optimization

Advanced Intelligent Systems, EarlyView.
Si–SiNx interface traps are harnessed as a complementary metal–oxide–semiconductor‐compatible source of controllable randomness for probabilistic bits. Pulse‐width‐programmed stochastic capture converts nanoscale defect dynamics into Boltzmann‐consistent binary outputs, while a physics‐based Simulation Program with Integrated Circuit Emphasis model ...
Dokyoung Lee, Jun‐Young Park, Joon‐Kyu Han, Sungho Kim   +3 more
wiley   +1 more source

AI‐Powered Smart Displays and AR Glasses: Perspectives and Challenges

Advanced Intelligent Systems, EarlyView.
This perspective examines how AI is reshaping smart displays and AR glasses. The latest in image‐quality enhancement, sensor‐integrated display optimization, and physiological sensing in display systems, followed by AI‐assisted AR technologies including waveguide optimization, image compensation, foveated rendering, and multimodal sensing, is discussed.
Luke Benoit, Yizhou Qian, Yi‐Chien Chen, Ziyang Shen, Po‐Sheng Chiu, Youngeon Lee, Cheng‐Han Ke, Chih‐Lung Lin, Shin‐Tson Wu   +8 more
wiley   +1 more source

Rolling Up Transition Metal Chalcogenides/Oxide Heterostructures Enables Polarity-Tunable and High-Switchable Memristors. [PDF]

Adv Mater
Wang X, Chen X, Qiao R, Xu J, Liu J, Yu K, Zhao Y, Liu X, Zhang E, Rong R, Gao L, Guo Y, Liu Y, Guo W.   +13 more
europepmc   +1 more source

Structure-Property-Application Correlations of Early Transition Metal Chalcogenides: A Dichalcogenide-Centered Perspective. [PDF]

Small
Jaidka S, Gupta A, Shelly D, Kaur Y, Garg A, Lee SY, Park SJ.   +6 more
europepmc   +1 more source

Prediction of Two-Dimensional Janus Transition-Metal Chalcogenides: Robust Ferromagnetic Semiconductor with High Curie Temperature. [PDF]

Molecules
Wang Z, Qureshi AH, Duan Y, Liu Y, Wang Y, Zhu J, Lu J, Guo T, Liu Y, Zhang X.   +9 more
europepmc   +1 more source