TY  - JOUR 
AU  - Shanavas Rasheeda, Dilshana
AU  - Martín Santa Daría, Alberto
AU  - Schröder, Benjamin
AU  - Mátyus, Edit
AU  - Behler, Jörg
PY  - 2022
SN  - 1463-9076
UR  - http://hdl.handle.net/10366/170094
AB  - [EN]In recent years, machine learning potentials (MLP) for atomistic simulations have attracted a lot of attention in chemistry and materials science. Many new approaches have been developed with the primary aim to transfer the accuracy of electronic...
LA  - eng
PB  - ROYAL SOC CHEMISTRY
KW  - Machine learning potentials (MLP)
KW  - Anharmonic vibrational frequencies
KW  - Variational vibrational computations
KW  - Formic acid dimer
TI  - High-dimensional neural network potentials for accurate vibrational frequencies: the formic acid dimer benchmark
DO  - 10.1039/D2CP03893E
T2  - Physical Chemistry Chemical Physics
VL  - 24
M2  - 29381
ER  -