computational-chemistry

Importance Sampling within Configuration Space Integration for Adsorbate Thermophysical Properties: A Case Study for CH3/Ni(111)

A new strategy is presented for computing anharmonic partition functions for the motion of adsorbates relative to a catalytic surface. Importance sampling is compared with conventional Monte Carlo. The importance sampling is significantly more …

Configuration Space Integration for Adsorbate Partition Functions: The Effect of Anharmonicity on the Thermophysical Properties of CO–Pt(111) and CH3OH–Cu(111)

A method for computing anharmonic thermophysical properties for adsorbates on metal surfaces has been extended to include libration, or frustrated rotation. Classical phase space integration is used with Monte Carlo sampling of the configuration …

Pynta-An Automated Workflow for Calculation of Surface and Gas–Surface Kinetics

Many important industrial processes rely on heterogeneous catalytic systems. However, given all possible catalysts and conditions of interest, it is impractical to optimize most systems experimentally. Automatically generated microkinetic models can …

Sella, an Open-Source Automation-Friendly Molecular Saddle Point Optimizer

We present a new algorithm for the optimization of molecular structures to saddle points on the potential energy surface using a redundant internal coordinate system. This algorithm automates the procedure of defining the internal coordinate system, …

Minima-preserving neural network (MPNN) for potential energy surface approximation

Talk

Adsorbate Partition Functions via Phase Space Integration: Quantifying the Effect of Translational Anharmonicity on Thermodynamic Properties

A new method for computing anharmonic thermophysical properties for adsorbates on metal surfaces is presented. Classical Monte Carlo phase space integration is performed to calculate the partition function for the motion of a hydrogen atom on …

Geometry Optimization Speedup through a Geodesic Approach to Internal Coordinates

We present a new geodesic-based method for geometry optimization in a basis set of redundant internal coordinates. Our method updates the molecular geometry by following the geodesic generated by a displacement vector on the internal coordinate …

Active Machine Learning with Uncertainties and Gradients

Talk

Accelerated Saddle Point Refinement through Full Exploitation of Partial Hessian Diagonalization

Identification and refinement of first order saddle point (FOSP) structures on the potential energy surface (PES) of chemical systems is a computational bottleneck in the characterization of reaction pathways. Leading FOSP refinement strategies for …

Sparse Low Rank Approximation of Potential Energy Surfaces with Applications in Estimation of Anharmonic Zero Point Energies and Frequencies

We propose a method that exploits sparse representation of potential energy surfaces (PES) on a polynomial basis set selected by compressed sensing. The method is useful for studies involving large numbers of PES evaluations, such as the search for …