Loïc M. Roch
Loïc M. Roch
Chief Technology Officer & co-founder, Atinary Technologies
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Accelerating the discovery of materials for clean energy in the era of smart automation
DP Tabor, LM Roch, SK Saikin, C Kreisbeck, D Sheberla, JH Montoya, ...
Nat. Rev. Mater. 3, 5-20, 2018
Self-driving laboratory for accelerated discovery of thin-film materials
BP MacLeod, FGL Parlane, TD Morrissey, F Häse, LM Roch, ...
Science Advances 6 (20), eaaz8867, 2020
Phoenics: A Bayesian optimizer for chemistry
F Häse, LM Roch, C Kreisbeck, A Aspuru-Guzik
ACS central science 4 (9), 1134-1145, 2018
Next-generation experimentation with self-driving laboratories
F Häse, LM Roch, A Aspuru-Guzik
Trends in Chemistry 1 (3), 282-291, 2019
Beyond Ternary OPV: High‐Throughput Experimentation and Self‐Driving Laboratories Optimize Multicomponent Systems
S Langner, F Häse, J Darío Perea, T Stubhan, J Hauch, LM Roch, ...
Advanced Materials, 1907801, 2020
ChemOS: orchestrating autonomous experimentation
LM Roch, F Häse, C Kreisbeck, T Tamayo-Mendoza, LPE Yunker, ...
Science Robotics 3 (19), eaat5559, 2018
Data-science driven autonomous process optimization
M Christensen, LPE Yunker, F Adedeji, F Häse, LM Roch, T Gensch, ...
Communications Chemistry 4 (1), 112, 2021
ChemOS: An orchestration software to democratize autonomous discovery
LM Roch, F Häse, C Kreisbeck, T Tamayo-Mendoza, LPE Yunker, ...
PLoS ONE 15 (4), e0229862, 2020
ChemOS: An Orchestration Software to Democratize Autonomous Discovery
LM Roch, F Häse, A Aspuru-Guzik
Artificial Intelligence in Drug Discovery 75, 351, 2020
Chimera: enabling hierarchy based multi-objective optimization for self-driving laboratories
F Häse, LM Roch, A Aspuru-Guzik
Chemical science 9 (39), 7642-7655, 2018
Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge
F Häse, M Aldeghi, RJ Hickman, LM Roch, A Aspuru-Guzik
Applied Physics Reviews 8 (3), 2021
Materials Acceleration Platform: Accelerating Advanced Energy Materials Discovery by Integrating High-Throughput Methods with Artificial Intelligence.
A Aspuru-Guzik, K Persson, A Alexander-Katz, C Amador, D Solis-Ibarra, ... …, 2018
A Bayesian approach to predict solubility parameters
B Sanchez‐Lengeling, LM Roch, JD Perea, S Langner, CJ Brabec, ...
Advanced Theory and Simulations 2 (1), 1800069, 2019
Olympus: a benchmarking framework for noisy optimization and experiment planning
F Häse, M Aldeghi, RJ Hickman, LM Roch, M Christensen, E Liles, ...
Machine Learning: Science and Technology 2 (3), 035021, 2021
π-Depletion as criterion to predict π-stacking ability
J Gonthier, S Steinmann, L Roch, A Ruggi, N Luisier, K Severin, ...
Chemical Communications (London) 48 (74), 9239 - 9241, 2012
Designing and understanding light-harvesting devices with machine learning
F Häse, LM Roch, P Friederich, A Aspuru-Guzik
Nature Communications 11 (1), 4587, 2020
Interface molecular engineering for laminated monolithic perovskite/silicon tandem solar cells with 80.4% fill factor
CO Ramírez Quiroz, GD Spyropoulos, M Salvador, LM Roch, M Berlinghof, ...
Advanced Functional Materials 29 (40), 1901476, 2019
Pentaindenocorannulene: Properties, Assemblies and C60 Complex
S Lampart, LM Roch, AK Dutta, Y Wang, R Warshamanage, AD Finke, ...
Angewandte Chemie International Edition 128 (47), 14868 - 14872, 2016
Kinetics of the Regeneration by Iodide of Dye Sensitizers Adsorbed on Mesoporous Titania
J Teuscher, A Marchioro, J Andrès, LM Roch, M Xu, SM Zakeeruddin, ...
Journal of Physical Chemistry C 118 (30), 17108 - 17115, 2014
Toward Accurate Adsorption Energetics on Clay Surfaces
A Zen, LM Roch, SJ Cox, X Hu, S Sorella, D Alfè, A Michaelides
Journal of Physical Chemistry C 120 (46), 26402 - 26413, 2016
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