Results 151 to 160 of about 2,265,648 (271)
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Efficient and Accurate Detection of Topologically Associating Domains from Contact Maps.
, 2017 Continuous improvements to high-throughput conformation capture (Hi-C) are revealing richerinformation about the spatial organization of the chromatin and its role in cellular functions.Several studies have confirmed the existence of structural features of the genome 3D organiza-tion that are stable across cell types and conserved across species ...
Abbas Roayaei Ardakany, Stefano Lonardi
openaire +4 more sources
Advanced Science, EarlyView.Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li +6 more
wiley +1 more source
Advanced Science, EarlyView.First‐principles calculations reveal that monolayer In2O${\rm In}_2{\rm O}$ hosts type‐II Dirac fermions near the Fermi level, which split into Weyl points under spin‐orbit coupling. The material exhibits negative and giant magnetoresistance, a pronounced spin Hall effect, and phonon‐mediated superconductivity at 1.5 K, establishing it as a unique ...
Qing‐Bo Liu +6 more
wiley +1 more source
Advanced Science, EarlyView.By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
Advanced Science, EarlyView.An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li +8 more
wiley +1 more source
Two‐Dimensional Triferroics: From Fundamental Couplings to Multifunctional Applications
Advanced Science, EarlyView.This graphic summarizes the three main types of currently reported 2D triferroic couplings. From the structural perspective, existing systems can be broadly classified into two categories, which exhibit distinct symmetry features and coupling behaviors. Beyond the lattice difference, a third type involves the interplay among ferroelectricity, magnetism,
Yang Li, Jialin Gong, Zhiqing Li
wiley +1 more source
Evolutionary and Functional Conservation of Topologically Associating Domain Boundaries in Rice Genomes. [PDF]
Int J Mol SciGeyman O, Kurbidaeva A.
europepmc +1 more source
Harnessing Phase Separation for the Development of High‐Performance Hydrogels
Advanced Science, EarlyView.ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao +3 more
wiley +1 more source
Integrating heterogeneity into topologically associating domain boundary prediction in large genomic context in human. [PDF]
NAR Genom BioinformSun Y +3 more
europepmc +1 more source