Want to learn more about TREX? On this page, you can find our archive of informative publication materials: reports, deliverables, presentations and articles from experts within the TREX community speaking about various TREX related topics. All the public materials published by TREX partners are available on the TREX Zenodo Community: https://zenodo.org/communities/trex/

Spin-Pure Stochastic-CASSCF via GUGA-FCIQMC Applied to Iron–Sulfur Clusters

Werner Dobrautz, Oskar Weser, Nikolay A. Bogdanov, Ali Alavi, Giovanni Li Manni

Chemical Theory Comput. 17, 5684–5703 (2021); DOI https://doi.org/10.1021/acs.jctc.1c00589 ARXIV https://arxiv.org/abs/2106.07775


Range-separated multiconfigurational density functional theory methods

Katarzyna Pernal, Michał Hapka

WIREs Compututational Molecular Science (2021); DOI https://doi.org/10.1002/wcms.1566


Probing anharmonic phonons by quantum correlators: A path integral approach

Tommaso Morresi, Lorenzo Paulatto, Rodolphe Vuilleumier, Michele Casula

Journal of Chemical Physics 154, 224108 (2021); DOI https://doi.org/10.1063/5.0050450


Tailoring CIPSI Expansions for QMC Calculations of Electronic Excitations: The Case Study of Thiophene

Monika Dash, Saverio Moroni, Claudia Filippi, Anthony Scemama

Chemical Theory Comput. 17, 3426–3434 (2021); DOI https://doi.org/10.1021/acs.jctc.1c00212


Localization versus inhomogeneous superfluidity: Submonolayer 4He on fluorographene, hexagonal boron nitride, and graphene

Saverio Moroni, Francesco Ancilotto, Pier Luigi Silvestrelli, Luciano Reatto

PHYSICAL REVIEW B 103, 174514 (2021); DOI https://doi.org/10.1103/PhysRevB.103.174514


Spin-adapted selected configuration interaction in a determinant basis

Vijay Gopal Chilkuri, Thomas Applencourt, Kevin Gasperich, Pierre-François Loos, Anthony Scemama

Chemical Physics (2021); ARXIV https://arxiv.org/abs/1812.06902


Energy-free machine learning predictions of ab initio structures

Dominik Lemm, Guido Falk von Rudorff, O. Anatole von Lilienfeld

Chemical Physics (2021); ARXIV https://arxiv.org/abs/2102.02806


Elucidating atmospheric brown carbon -- Supplanting chemical intuition with exhaustive enumeration and machine learning

Enrico Tapavicza, Guido Falk von Rudorff, David O. De Haan, Mario Contin, Christian George, Matthieu Riva, O. Anatole von Lilienfeld

Environmental Science & Technology 55, 8447–8457 (2021); DOI https://doi.org/10.1021/acs.est.1c00885 ARXIV https://arxiv.org/abs/2101.07301


Machine Learning of Free Energies in Chemical Compound Space Using Ensemble Representations: Reaching Experimental Uncertainty for Solvation

Jan Weinreich, Nicholas J. Browning, O. Anatole von Lilienfeld

Journal Of Chemical Physics 154, 134113 (2021); DOI https://doi.org/10.1063/5.0041548 ARXIV https://arxiv.org/abs/2012.09722


Ab initio machine learning in chemical compound space

Bing Huang, O. Anatole von Lilienfeld