Results 51 to 60 of about 299 (217)
Super‐Resolution and High‐Data‐Density Acoustic Meta‐Hologram via Amplitude and Phase Coupling
Advanced Science, EarlyView.A super‐resolution acoustic meta‐hologram utilizes amplitude‐phase coupling under energy conservation constraints to overcome the traditional diffraction limit. This conceptually advanced approach achieves high‐fidelity acoustic field reconstruction and dense information transmission, unlocking new potentials for high‐resolution acoustic imaging and ...
Xiao Guo +15 more
wiley +1 more source
Advanced Energy Materials, EarlyView.A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan +12 more
wiley +1 more source
Generalized teleparallel de Sitter geometries. [PDF]
Eur Phys J C Part Fields, 2023 Coley AA +3 more
europepmc +1 more source
, 2011 Spherical, Euclidean, and hyperbolic simplices can be characterized by the dihedral angles on their codimension-two faces. These characterizations analyze the Gram matrix, a matrix with entries given by cosines of dihedral angles.
Champion, Daniel James
core
AIChE Journal, EarlyView.Abstract Transformer‐based molecular models pretrained on SMILES strings demonstrate strong performance in property prediction. However, these model often lack explicit integration of molecular surface charge distributions that govern intermolecular interactions such as hydrogen bonding and polarity.
Tae Hyun Kim +2 more
wiley +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
Advanced Intelligent Discovery, EarlyView.This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley +1 more source
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 +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia +2 more
wiley +1 more source
Angewandte Chemie, EarlyView.Epimer discrimination remains challenging due to subtle NMR differences. Here, we propose a methodology based on 13C‐RCSA and RDC anisotropic parameters, enabling the assignment of two flexible tetraprenyltoluquinol epimers (1a and 1b) with remote stereoclusters.
Juan Carlos C. Fuentes‐Monteverde +6 more
wiley +2 more sources