Reliable computational protocols capable of predicting infrared (IR) spectra of atomically precise monodisperse metal clusters (AMCs), while explicitly accounting for anharmonic effects, are crucial f...
Title: Unveiling Surfactant-Coated Iron Oxide Nanoparticle Specifications for Enhancing Phosphate Removal in Peritoneal Dialysis-Simulating Conditions Authors: Théo Lucante | Philippe ...
The direct conversion of methane to methanol (DCMM) under continuous flow and atmospheric pressure offers notable environmental benefits and industrial promise, but remains a long-standing challenge d...
Title: Accurate Simulations of Water and Aqueous Solutions through Fine-Tuned Dispersion-Corrected Density Functional Theory and Machine-Learning Interatomic Potentials Authors: 6. ...
Evidence of hydrogen production from water splitting using a nonstoichiometric cubic perovskite, SrFeMoOδ (SFMO), as a catalyst under moderate operating condition is presented. It is demonstrated that...
Cryo-EM and X-ray crystallography provide crucial experimental data for obtaining atomic-detail models of biomacromolecules. Refining these models relies on library-based stereochemical data, which, i...
The delivery efficiency of biologics via lipid nanoparticles (LNPs) is critically dependent on the incorporation of ionizable lipids. The subtle structural changes to these lipids led to dramatic vari...
Relative H-1 NMR spectra of neat [C4mim][BF4] and its aqueous mixtures have been computed with the near-quantitative accuracy for the first time, with root-mean square deviation of 0.2 ppm with respec...
We present an approach to accelerate the construction of reaction energy diagrams and mechanistic pathways of novel bimetallic catalytic systems by exploiting information on a known case, and we test...
We present a computational workflow, the conformal sampling of catalytic processes enhanced with extrapolation techniques (CSCP-X), for constructing machine-learning interatomic potentials (MLIPs) to...
