3 citations · 4 across the 5 of their papers we have counts for
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Investigating Anharmonicities in Polarization-Orientation Raman Spectra of Acene Crystals with Machine Learning
Paolo Lazzaroni, Shubham Sharma, Mariana Rossi
We present a first-principles machine-learning computational framework to investigate anharmonic effects in polarization-orientation (PO) Raman spectra of molecular crystals, focus…
aims-PAX: Parallel Active eXploration for the automated construction of Machine Learning Force Fields
Tobias Henkes, Shubham Sharma, Alexandre Tkatchenko +2
Recent advances in machine learning force fields (MLFF) have significantly extended the reach of atomistic simulations. Continuous progress in this field requires reliable referenc…
Accurate Machine Learning Interatomic Potentials for Polyacene Molecular Crystals: Application to Single Molecule Host-Guest Systems
Burak Gurlek, Shubham Sharma, Paolo Lazzaroni +2
Emerging machine learning interatomic potentials (MLIPs) offer a promising solution for large-scale accurate material simulations, but stringent tests related to the description of…