117 citations · 222 across the 5 of their papers we have counts for
11 papers
Non-parametric Local Pseudopotentials with Machine Learning: a Tin Pseudopotential Built Using Gaussian Process Regression
Johann Lueder, Sergei Manzhos
We present novel non-parametric representation math for local pseudopotentials (PP) based on Gaussian Process Regression (GPR). Local pseudopotentials are needed for materials simu…
Data-driven kinetic energy density fitting for orbital-free DFT: linear vs Gaussian process regression
Sergei Manzhos, Pavlo Golub
We study the dependence of kinetic energy densities (KED) on density-dependent variables that have been suggested in previous works on kinetic energy functionals (KEF) for orbital-…
Lithium attachment to C60 and nitrogen- and boron-doped C60: a mechanistic study
Yingqian Chen, Chae-Ryong Cho, Sergei Manzhos
Fullerene-based materials including C60 and doped C60 have previously been proposed as anodes for lithium ion batteries. It was also shown earlier that n- and p-doping of small mol…
Revisiting Backbonding: The Influence of Orbitals on Metal-CO Bonds and Ligand Red Shifts
Daniel Koch, Yingqian Chen, Pavlo Golub +1
The concept of backbonding is widely used to explain the complex stabilities and CO stretch frequency red shifts of transition metal carbonyls. We theoretically investigate a n…
Machine learning optimization of the collocation point set for solving the Kohn-Sham equation
Jonas Ku, Aditya Kamath, Tucker Carrington +1
The rectangular collocation approach makes it possible to solve the Schrödinger equation with basis functions that do not have amplitude in all regions in which wavefunctions have…
A Scheme for Ultrasensitive Detection of Molecules by Using Vibrational Spectroscopy in Combination with Signal Processing
Tay Yong Boon, Ian Tay Rongde, Loy Liang Yi +3
We show that combining vibrational spectroscopy with signal processing can result in a scheme for ultrasensitive detection of molecules. We consider the vibrational spectrum as a s…