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Recent advances in the Self-Referencing Embedding Strings (SELFIES) library
Alston Lo, Robert Pollice, AkshatKumar Nigam +3
String-based molecular representations play a crucial role in cheminformatics applications, and with the growing success of deep learning in chemistry, have been readily adopted in…
Inverse molecular design and parameter optimization with Hückel theory using automatic differentiation
R. A. Vargas-Hernández, K. Jorner, R. Pollice +1
Semi-empirical quantum chemistry has recently seen a renaissance with applications in high-throughput virtual screening and machine learning. The simplest semi-empirical model stil…
From absorption spectra to charge transfer in PEDOT nanoaggregates with machine learning
Loïc M. Roch, Semion K. Saikin, Florian Häse +4
Fast and inexpensive characterization of materials properties is a key element to discover novel functional materials. In this work, we suggest an approach employing three classes…
Mechanistic Regimes of Vibronic Transport in a Heterodimer and the Design Principle of Incoherent Vibronic Transport in Phycobiliproteins
Doran I. G. Bennett, Pavel Maly, Christoph Kreisbeck +2
Following the observation of coherent oscillations in non-linear spectra of photosynthetic pigment protein complexes, particularly phycobilliprotein such as PC645, coherent vibroni…
Temperature-dependent conformations of exciton-coupled Cy3 dimers in double-stranded DNA
Loni Kringle, Nicolas P. D. Sawaya, Julia Widom +4
Understanding the properties of electronically interacting molecular chromophores, which involve internally coupled electronic-vibrational motions, is important to the spectroscopy…
Reproducing Quantum Probability Distributions at the Speed of Classical Dynamics: A New Approach for Developing Force-Field Functors
Vikram Sundar, David Gelbwaser-Klimovsky, Alan Aspuru-Guzik
Modeling nuclear quantum effects is required for accurate molecular dynamics (MD) simulations of molecules. The community has paid special attention to water and other biomolecules…