Pushing Quantum Chemistry by Advancing Photoswitchable Catalysis

Risultati finali

Creation and submission of a Data Management Plan

Pubblicazioni

Modular Synthesis of Benzocyclobutenes via Pd(II)-Catalyzed Oxidative [2+2] Annulation of Arylboronic Acids with Alkenes

Autori: Takuji Fujii, Simone Gallarati, Clemence Corminboeuf, Qian Wang, Jieping Zhu
Pubblicato in: Journal of American Chemical Society, 2022, ISSN 0002-7863
Editore: American Chemical Society
DOI: 10.1021/jacs.2c03565

Reaction-based machine learning representations for predicting the enantioselectivity of organocatalysts

Autori: Simone Gallarati, Raimon Fabregat, Rubén Laplaza, Sinjini Bhattacharjee, Matthew D. Wodrich, Clemence Corminboeuf
Pubblicato in: Chemical Science, 2021, ISSN 2041-6520
Editore: Royal Society of Chemistry
DOI: 10.1039/d1sc00482d

Learning on-top: Regressing the on-top pair density for real-space visualization of electron correlation

Autori: Alberto Fabrizio, Ksenia R. Briling, David D. Girardier, Clemence Corminboeuf
Pubblicato in: The Journal of Chemical Physics, Numero 153/20, 2020, Pagina/e 204111, ISSN 0021-9606
Editore: American Institute of Physics
DOI: 10.1063/5.0033326

How Robust Is the Reversible Steric Shielding Strategy for Photoswitchable Organocatalysts?

Autori: Simone Gallarati; Raimon Fabregat; Veronika Juraskova; Theo Jaffrelot Inizan; Clemence Corminboeuf
Pubblicato in: Journal of Organic Chemistry, Numero 00223263, 2022, Pagina/e 8849–8857, ISSN 0022-3263
Editore: American Chemical Society
DOI: 10.1021/acs.joc.1c02991

Benchmarking machine-readable vectors of chemical reactions on computed activation barriers

Autori: Puck van Gerwen, Ksenia R. Briling, Yannick Calvino Alonso, Malte Franke, Clemence Corminboeuf
Pubblicato in: Digital Discovery, 2024, ISSN 2635-098X
Editore: Royal Society of Chemistry
DOI: 10.1039/d3dd00175j

Learning the Exciton Properties of Azo-dyes

Autori: Sergi Vela, Alberto Fabrizio, Ksenia R. Briling, Clemence Corminboeuf
Pubblicato in: Journal of Physical Chemistry Letters, Numero 12, 2021, Pagina/e 5957-5962, ISSN 1948-7185
Editore: American Chemical Society
DOI: 10.1021/acs.jpclett.1c01425

Assessing the persistence of chalcogen bonds in solution with neural network potentials

Autori: Veronika Juraskova, Frederic Celerse, Ruben Laplaza, Clemence Corminboeuf
Pubblicato in: Journal of Chemical Physics, Numero 156, 2022, Pagina/e 154112, ISSN 0021-9606
Editore: American Institute of Physics
DOI: 10.1063/5.0085153

Mapping Catalyst-Solvent Interplay in Competing Carboamination/Cyclopropanation Reactions

Autori: Matthew D. Wodrich, Miyeon Chang, Simone Gallarati, Łukasz Woźniak, Nicolai Cramer, Clemence Corminboeuf
Pubblicato in: Chemistry - A European Journal, 2022, Pagina/e e202200399, ISSN 0947-6539
Editore: John Wiley & Sons Ltd.
DOI: 10.1002/chem.202200399

Harvesting the fragment-based nature of bifunctional organocatalysts to enhance their activity

Autori: Simone Gallarati; Ruben Laplaza; Clemence Corminboeuf
Pubblicato in: Organic Chemistry Frontiers, Numero 20524110, 2022, Pagina/e 4041-4051, ISSN 2052-4110
Editore: Royal Society of Chemistry
DOI: 10.1039/d2qo00550f

Genetic Algorithms for the Discovery of Homogeneous Catalysts

Autori: Simone Gallarati, Puck van Gerwen, Alexandre A. Schoepfer, Ruben Laplaza, Clemence Corminboeuf
Pubblicato in: Chimia, Numero 77, 2023, Pagina/e 39-47, ISSN 2673-2424
Editore: Swiss Chemical Society
DOI: 10.2533/chimia.2023.39

A genetic optimization strategy with generality in asymmetric organocatalysis as a primary target

Autori: Simone Gallarati, Puck van Gerwen, Ruben Laplaza, Lucien Brey, Alexander Makaveev, Clemence Corminboeuf
Pubblicato in: Chemical Science, Numero 15, 2024, Pagina/e 3640-3660, ISSN 2041-6539
Editore: Royal Society of Chemistry
DOI: 10.1039/d3sc06208b

Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides

Autori: Raimon Fabregat, Alberto Fabrizio, Edgar A. Engel, Benjamin Meyer, Veronika Juraskova, Michele Ceriotti, Clemence Corminboeuf
Pubblicato in: Journal of Chemical Theory and Computation, 2022, ISSN 1549-9618
Editore: American Chemical Society
DOI: 10.1021/acs.jctc.1c00813

OSCAR: An Extensive Repository of Chemically and Functionally Diverse Organocatalysts

Autori: Simone Gallarati, Puck van Gerwen, Ruben Laplaza, Sergi Vela, Alberto Fabrizio, Clemence Corminboeuf
Pubblicato in: Chemical Science, Numero 20416520, 2022, ISSN 2041-6520
Editore: Royal Society of Chemistry
DOI: 10.1039/d2sc04251g

SPAHM(a,b): Encoding the Density Information from Guess Hamiltonian in Quantum Machine Learning Representations

Autori: Ksenia R. Briling, Yannick Calvino Alonso, Alberto Fabrizio, Clemence Corminboeuf
Pubblicato in: Journal of Chemical Theory and Computation, Numero 20, 2024, Pagina/e 1108-1117, ISSN 1549-9618
Editore: American Chemical Society
DOI: 10.1021/acs.jctc.3c01040

Learning (from) the Electron Density: Transferability, Conformational and Chemical Diversity

Autori: Alberto Fabrizio, Ksenia Briling, Andrea Grisafi, Clémence Corminboeuf
Pubblicato in: CHIMIA International Journal for Chemistry, Numero 74/4, 2020, Pagina/e 232-236, ISSN 0009-4293
Editore: Schweizerische Chemische Gedellschaft
DOI: 10.2533/chimia.2020.232

Impact of quantum-chemical metrics on the machine learning prediction of electron density

Autori: Ksenia R. Briling, Alberto Fabrizio, Clemence Corminboeuf
Pubblicato in: The Journal of Chemical Physcics, Numero 155, 2021, Pagina/e 024107, ISSN 0021-9606
Editore: American Institute of Physics
DOI: 10.1063/5.0055393

Hamiltonian-reservoir Replica Exchange and Machine Learning Potentials for Computational Organic Chemistry

Autori: Raimon Fabregat, Alberto Fabrizio, Benjamin Meyer, Daniel Hollas, Clémence Corminboeuf
Pubblicato in: Journal of Chemical Theory and Computation, 2020, ISSN 1549-9618
Editore: American Chemical Society
DOI: 10.1021/acs.jctc.0c00100

Tuning the Thermal Stability and Photoisomerization of Azoheteroarenes through Macrocycle Strain**

Autori: Sergi Vela, Alan Scheidegger, Raimon Fabregat, Clémence Corminboeuf
Pubblicato in: Chemistry – A European Journal, Numero 27/1, 2021, Pagina/e 419-426, ISSN 0947-6539
Editore: John Wiley & Sons Ltd.
DOI: 10.1002/chem.202003926

Metric learning for kernel ridge regression: assessment of molecular similarity

Autori: Raimon Fabregat; Puck van Gerwen; Matthieu Haeberle; Friedrich Eisenbrand; Clémence Corminboeuf
Pubblicato in: Machine Learning: Science and Technology, Numero 26322153, 2022, Pagina/e 035015, ISSN 2632-2153
Editore: IOP publishing
DOI: 10.1088/2632-2153/ac8e4f

Quantum Chemistry Meets Machine Learning

Autori: Alberto Fabrizio, Benjamin Meyer, Raimon Fabregat, Clemence Corminboeuf
Pubblicato in: CHIMIA International Journal for Chemistry, Numero 73/12, 2019, Pagina/e 983-989, ISSN 0009-4293
Editore: Schweizerische Chemische Gedellschaft
DOI: 10.2533/chimia.2019.983

From Organic Fragments to Photoswitchable Catalysts: The OFF–ON Structural Repository for Transferable Kernel-Based Potentials

Autori: Frédéric Célerse, Matthew D. Wodrich, Sergi Vela, Simone Gallarati, Raimon Fabregat, Veronika Juraskova, Clémence Corminboeuf
Pubblicato in: Journal of Chemical Information and Modeling, Numero 64, 2024, Pagina/e 1201-1212, ISSN 1549-9596
Editore: American Chemical Society
DOI: 10.1021/acs.jcim.3c01953

Identifying the Trade-off between Intramolecular Singlet Fission Requirements in Donor–Acceptor Copolymers

Autori: J. Terence Blaskovits, Maria Fumanal, Sergi Vela, Raimon Fabregat, Clémence Corminboeuf
Pubblicato in: Chemistry of Materials, Numero 33/7, 2021, Pagina/e 2567-2575, ISSN 0897-4756
Editore: American Chemical Society
DOI: 10.1021/acs.chemmater.1c00057

Is a Single Conformer Sufficient to Describe the Reorganization Energy of Amorphous Organic Transport Materials

Autori: Jacob Terence Blaskovits; Kun-Han Lin; Raimon Fabregat; Iwona Swiderska; Helene Wu; Clémence Corminboeuf
Pubblicato in: Journal of Physical Chemistry C, Numero 1, 2021, Pagina/e 7355–17362, ISSN 1932-7455
Editore: American Chemical Society
DOI: 10.1021/acs.jpcc.1c04067

SPAHM: the spectrum of approximated Hamiltonian matrices representations

Autori: Alberto Fabrizio, Ksenia R. Briling, Clemence Corminboeuf
Pubblicato in: Digital Discovery, 2022, ISSN 2635-098X
Editore: Royal Society of Chemistry
DOI: 10.1039/d1dd00050k

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