Related papers: Investigating CO Adsorption on Cu(111) and Rh(111)…
In conventional chemisorption model, the d-band center theory (augmented sometimes with the upper edge of d-band for imporved accuarcy) plays a central role in predicting adsorption energies and catalytic activity as a function of d-band…
High-entropy alloys (HEAs) are metallic materials with solid solutions stabilized by high mixing entropy. Some exhibit excellent strength, often accompanied by additional properties such as magnetic, invar, corrosion, or cryogenic response.…
Machine-learned interatomic potentials (MLPs) provide near density functional theory (DFT) accuracy at reduced computational cost, but their reliability depends on representative training data and often deteriorates in transition-state…
A high-dimensional potential energy surface (PES) for CO interaction with the Au(111) surface is developed using a machine-learning algorithm. Including both molecular and surface coordinates, this PES enables the simulation of the recent…
We report an investigation of the suitability of quantum embedding for modeling the effects of the environment on the X-ray photoelectron spectra of hydrogen chloride and the chloride ions adsorbed on ice surfaces, as well as of chloride…
Understanding the semiconductor-electrolyte interface in photoelectrochemical (PEC) systems is crucial for optimizing stability and reactivity. Despite the challenges in establishing reliable surface structure models during PEC cycles, this…
The adsorption of $CO_2$ on the $Fe_3$$O_4$(001)-($\sqrt{2}$ $\times$ $\sqrt{2}$)R45{\deg} surface was studied experimentally using temperature programmed desorption (TPD), electron spectroscopies (UPS and XPS), and scanning tunneling…
The design of corrosion-resistant high entropy alloys (CR-HEAs) is challenging due to the alloys' virtually astrological composition space. To facilitate this, efficient and reliable high-throughput exploratory approaches are needed. Toward…
Computational high-throughput studies, especially in research on high-entropy materials and catalysts, are hampered by high-dimensional composition spaces and myriad structural microstates. They present bottlenecks to the conventional use…
We characterized CO2 adsorption and diffusion on the missing row reconstructed Cu(100)-O surface using a combination of scanning tunneling microscopy (STM) and density functional theory (DFT) calculations with dispersion. We deposited CO2…
Understanding molecular adsorption on surfaces underpins many problems in chemistry and materials science. Accurately and efficiently describing the adsorption has been a challenging task for first-principles methods as the process can…
Relaxed atomic geometries and chemisorption energies have been calculated for the dissociative adsorption of molecular hydrogen on vicinal Si(001) surfaces. We employ density-functional theory, together with a pseudopotential for Si, and…
Understanding strongly correlated systems is essential for advancing quantum chemistry and materials science, yet conventional methods like Density Functional Theory (DFT) often fail to capture their complex electronic behavior. To address…
We present a systematic theoretical investigation of the surface properties, stability and reactivity, of rock-salt type alkaline-earth metal oxides including MgO, CaO, SrO, and BaO. The accuracy of commonly used exchange-correlation…
Coupled cluster theory with a Kohn-Sham reference (KS-CC) can dramatically outperform its Hartree-Fock counterpart for strongly correlated systems, but the origin of these improvements has remained unclear. Here we demonstrate that these…
The adsorption kinetics of CO on PdAu bimetallic clusters, containing 140 $\pm$ 12 atoms and a composition varying between 0% and 55% of Pd atoms, is investigated by a pulsed molecular beam method (MBRS). The clusters are grown on a…
The theoretical investigation of gas adsorption, storage, separation, diffusion and related transport processes in porous materials relies on a detailed knowledge of the potential energy surface of molecules in a stationary environment. In…
Recent developments in many-body potential energy representation via deep learning have brought new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Here we describe DeePMD-kit, a package written in…
In recent years due to improvements in calculation methods and increased computer power, it has become possible to perform first-principles investigations for ``simple'' chemical reactions at surfaces. We have carried out such studies for…
We demonstrate a convolutional neural network trained to reproduce the Kohn-Sham kinetic energy of hydrocarbons from electron density. The output of the network is used as a non-local correction to the conventional local and semi-local…