Sergi Trias-Llimós
[DDHealth Protocol: Justification, design and implementation of a cross-sectional survey of sociodemographic health, health literacy and digital divide in 2,000 adults aged fifty to seventy-nine residing in Spain in 2022]
Revista espanola de salud publica
important yet challenging aspect atomistic materials modeling reconciling experimental computational results conventional approaches involve generating numerous configurations molecular dynamics monte carlo structure optimization selecting one closest match experiment however inefficient process guaranteed succeed introduce general method combine atomistic machine learning ml experimental observables produces atomistic structures compatible experiment design use approach combination grandcanonical monte carlo within modified hamiltonian formalism generate configurations agree experimental data chemically sound low energy apply approach understand atomistic structure oxygenated amorphous carbon acox intriguing carbonbased material answer question much oxygen added carbon fully decomposes co co2 utilizing mlbased xray photoelectron spectroscopy xps model trained gw density functional theory dft data conjunction ml interatomic potential identify acox structures compliant experimental xps predictions also energetically favorable respect dft employing network analysis accurately deconvolve xps spectrum motif contributions revealing inaccuracies inherent experimental xps interpretation granting us atomistic insight structure acox method generalizes multiple experimental observables allows elucidation atomistic structure materials directly experimental data thereby enabling experimentdriven materials modeling degree realism previously reach