205 citations · 209 across the 4 of their papers we have counts for
4 papers
Machine learning force fields: Construction, validation, and outlook
Venkatesh Botu, Rohit Batra, James Chapman +1
Force fields developed with machine learning methods in tandem with quantum mechanics are beginning to find merit, given their (i) low cost, (ii) accuracy, and (iii) versatility. R…
A study of adatom ripening on an Al (111) surface with machine learning force fields
Venkatesh Botu, James Chapman, Rampi Ramprasad
Surface phenomena are increasingly becoming important in exploring nanoscale materials growth and characterization. Consequently, the need for atomistic based simulations is increa…
A learning scheme to predict atomic forces and accelerate materials simulations
Venkatesh Botu, Rampi Ramprasad
The behavior of an atom in a molecule, liquid or solid is governed by the force it experiences. If the dependence of this vectorial force on the atomic chemical environment can be…
Ab-Initio Molecular Dynamics Acceleration Scheme with an Adaptive Machine Learning Framework
Venkatesh Botu, Rampi Ramprasad
Quantum mechanics based ab-initio molecular dynamics (MD) simulation schemes offer an accurate and direct means to monitor the time-evolution of materials. Nevertheless, the expens…