2.1k citations · 3.7k across the 10 of their papers we have counts for
10 papers
Accelerated Organic Crystal Structure Prediction with Genetic Algorithms and Machine Learning
Amit Kadan, Kevin Ryczko, Andrew Wildman +3
We present a high-throughput, end-to-end pipeline for organic crystal structure prediction (CSP) -- the problem of identifying the stable crystal structures that will form from a g…
The Generalized Boltzmann Distribution is the Only Distribution in Which the Gibbs-Shannon Entropy Equals the Thermodynamic Entropy
Xiang Gao, Emilio Gallicchio, Adrian E. Roitberg
We show that the generalized Boltzmann distribution is the only distribution for which the Gibbs-Shannon entropy equals the thermodynamic entropy. This result means that the thermo…
Multidimensional Replica Exchange simulations for Efficient constant pH and Redox Potential Molecular Dynamics
Vinícius Wilian D. Cruzeiro, Adrian E. Roitberg
Efficient computational methods that are capable of supporting experimental measures obtained at constant values of pH and redox potential are important tools as they serve to, amo…
Transferable Molecular Charge Assignment Using Deep Neural Networks
Ben Nebgen, Nick Lubbers, Justin S. Smith +6
We use HIP-NN, a neural network architecture that excels at predicting molecular energies, to predict atomic charges. The charge predictions are accurate over a wide range of molec…
Redox potential replica exchange molecular dynamics at constant pH in AMBER: Implementation and validation
Vinicius Wilian D. Cruzeiro, Marcos S. Amaral, Adrian E. Roitberg
Redox processes are important in chemistry, with applications in biomedicine, chemical analysis, among others. As many redox experiments are also performed at a fixed value of pH,…
Less is more: sampling chemical space with active learning
Justin S. Smith, Ben Nebgen, Nicholas Lubbers +2
The development of accurate and transferable machine learning (ML) potentials for predicting molecular energetics is a challenging task. The process of data generation to train suc…