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From the 15 of 444 papers with an AI index.

most citedSPT-3G D1: CMB temperature and polarization power spectra and cosmology from 2019 and 2020 observations of the SPT-3G Main field

55 citations

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cond-mat.mtrl-sci2026

A coupled fully kinetic hydrogen transport and ductile phase-field fracture framework for modeling hydrogen embrittlement

Abdelrahman Hussein, Yann Charles, Jukka Kömi +1

The paper presents a computational framework that couples a kinetic model of hydrogen transport with a geometric phase‑field method for ductile fracture, enabling simulation of hyd…

cond-mat.mtrl-sci2026

Bottlenecks in Hamiltonian-Adaptive Resolution Simulation Method for Modeling Interfaces

Hari Haran Sudhakar, Alessandra Serva, Rocio Semino

The Hamiltonian-Adaptive Resolution Simulation (H-AdResS) method allows to combine atomistic and particle-based coarse-grained models in a single simulation box, which makes it ver…

cond-mat.mtrl-sci2026

Optimizing spin-based terahertz emission from magnetic heterostructures

Francesco Foggetti, Francesco Cosco, Peter M. Oppeneer +4

Terahertz radiation pulses can be generated efficiently through femtosecond laser excitation of a ferromagnetic/nonmagnetic heterostructure, wherein an ultrafast laser-induced spin…

cond-mat.mtrl-sci2026

Partially reactive force field for the UiO-66 metal-organic framework

Akanksha Nawani, Rocio Semino

UiO-66 is the most widely studied metal-organic framework (MOF), on account of its structural tunability given by its capacity of sustaining high amounts of point defects in its st…

cond-mat.mtrl-sci2026

Machine Learning and Molecular Simulations Reveal Mechanisms of ZIFs Polymorph Selection

Emilio Méndez, Rocio Semino

Zn(imidazolate) metal-organic frameworks (MOFs) exhibit a remarkable degree of polymorphism. Because of their promising industrial applications, many research groups have inves…

cond-mat.mtrl-sci2026

Geometry-Based Neural-Network Prediction of Electron Localization Function Topology in Dense Hydrogen

Xiaoyu Wang, Miriam Marqués, Sergio Gómez +3

We develop a machine-learning framework to predict the electron localization function (ELF) of pure, dense hydrogen directly from atomic geometry, bypassing explicit electronic-str…