Path integral simulations of condensed-phase vibrational spectroscopy
SC Althorpe - Annual Review of Physical Chemistry, 2024 - annualreviews.org
Recent theoretical and algorithmic developments have improved the accuracy with which
path integral dynamics methods can include nuclear quantum effects in simulations of …
path integral dynamics methods can include nuclear quantum effects in simulations of …
MACE-OFF23: Transferable machine learning force fields for organic molecules
Classical empirical force fields have dominated biomolecular simulation for over 50 years.
Although widely used in drug discovery, crystal structure prediction, and biomolecular …
Although widely used in drug discovery, crystal structure prediction, and biomolecular …
[HTML][HTML] Experimental and simulation-based characterization of surfactant adsorption layers at fluid interfaces
Adsorption of surfactants to fluid interfaces occurs in numerous technological and daily-life
contexts. The coverage at the interface and other properties of the formed adsorption layers …
contexts. The coverage at the interface and other properties of the formed adsorption layers …
Quasi-one-dimensional hydrogen bonding in nanoconfined ice
Abstract The Bernal-Fowler ice rules stipulate that each water molecule in an ice crystal
should form four hydrogen bonds. However, in extreme or constrained conditions, the …
should form four hydrogen bonds. However, in extreme or constrained conditions, the …
Data-efficient fine-tuning of foundational models for first-principles quality sublimation enthalpies
Calculating sublimation enthalpies of molecular crystal polymorphs is relevant to a wide
range of technological applications. However, predicting these quantities at first-principles …
range of technological applications. However, predicting these quantities at first-principles …
[HTML][HTML] Density isobar of water and melting temperature of ice: Assessing common density functionals
We investigate the density isobar of water and the melting temperature of ice using six
different density functionals. Machine-learning potentials are employed to ensure …
different density functionals. Machine-learning potentials are employed to ensure …
Efficient Composite Infrared Spectroscopy: Combining the Double-Harmonic Approximation with Machine Learning Potentials
Vibrational spectroscopy is a cornerstone technique for molecular characterization and
offers an ideal target for the computational investigation of molecular materials. Building on …
offers an ideal target for the computational investigation of molecular materials. Building on …
Tensorial properties via the neuroevolution potential framework: Fast simulation of infrared and Raman spectra
Infrared and Raman spectroscopy are widely used for the characterization of gases, liquids,
and solids, as the spectra contain a wealth of information concerning, in particular, the …
and solids, as the spectra contain a wealth of information concerning, in particular, the …
Efficient Parametrization of Transferable Atomic Cluster Expansion for Water
We present a highly accurate and transferable parametrization of water using the atomic
cluster expansion (ACE). To efficiently sample liquid water, we propose a novel approach …
cluster expansion (ACE). To efficiently sample liquid water, we propose a novel approach …
Fast quasi-centroid molecular dynamics for water and ice
We describe how the fast quasi-centroid molecular dynamics (f-QCMD) method can be
applied to condensed-phase systems by approximating the quasi-centroid potential of mean …
applied to condensed-phase systems by approximating the quasi-centroid potential of mean …