Alán Aspuru-Guzik
University of Toronto
664 Papers
4.7K Citations
Alán Aspuru-Guzik is an academic researcher from University of Toronto. The author has contributed to research in topics: Quantum computer & Quantum. The author has an hindex of 97, co-authored 628 publications. Previous affiliations of Alán Aspuru-Guzik include D-Wave Systems & National Autonomous University of Mexico.
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Papers
Inverse design of nanoporous crystalline reticular materials with deep generative models
Zhenpeng Yao,Zhenpeng Yao,Benjamin Sanchez-Lengeling,N. Scott Bobbitt,Benjamin J. Bucior,Sai Govind Hari Kumar,Sean P. Collins,Thomas Burns,Tom K. Woo,Omar K. Farha,Randall Q. Snurr,Alán Aspuru-Guzik +11 more
TL;DR: In this article, an automated nanoporous materials discovery platform powered by a supramolecular variational autoencoder was proposed for the generative design of reticular materials, which can efficiently explore this space.
Beyond Ternary OPV: High-Throughput Experimentation and Self-Driving Laboratories Optimize Multicomponent Systems.
Stefan Langner,Florian Häse,José Darío Perea,Tobias Stubhan,Jens Hauch,Loïc M. Roch,Thomas Heumueller,Alán Aspuru-Guzik,Christoph J. Brabec,Christoph J. Brabec +9 more
TL;DR: The development of high-throughput and autonomous experimentation methods for the effective optimization of multicomponent polymer blends for OPVs and a method for automated film formation enabling the fabrication of up to 6048 films per day is introduced.
240
Anthraquinone Derivatives in Aqueous Flow Batteries
Michael R. Gerhardt,Liuchuan Tong,Rafael Gómez-Bombarelli,Qing Chen,Michael P. Marshak,Cooper J. Galvin,Alán Aspuru-Guzik,Roy G. Gordon,Michael J. Aziz +8 more
TL;DR: In this article, the authors investigate four anthraquinone derivatives as negative electrolyte candidates for an aqueous quinone-bromide redox flow battery: AQS-2-sulfonic acid (AQS), 1,8-dihydroxyanthrathraquinones-2,7-disulfonics acid (DHAQDS), alizarin red S (ARS), and 1,4-dioxymethyl sulfonic acid, and DHAQDMS.
239
Optimizing distributions over molecular space. An Objective-Reinforced Generative Adversarial Network for Inverse-design Chemistry (ORGANIC)
TL;DR: ORGANIC as mentioned in this paper is a framework based on Objective-Reinforced Generative Adversarial Networks (ORGAN), capable of producing a distribution over molecular space that matches with a certain set of desirable metrics.
234
Chemical Basis of Trotter-Suzuki Errors in Quantum Chemistry Simulation
TL;DR: It is argued that chemical properties, such as the maximum nuclear charge in a molecule and the filling fraction of orbitals, can be decisive for determining the cost of a quantum simulation.