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Theoretical and Computational Chemistry

Working Paper

A Bayesian Approach to Predict Solubility Parameters

Benjamin Sanchez-Lengeling, Loic Roch, Jose Dario Perea, Stefan Langner, Christoph J. Brabec, Alan Aspuru-Guzik

Version 2 posted 16 July 2018

2,196

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Materials Science

Working Paper

Organic Molecules with Inverted Gaps between First Excited Singlet and Triplet States and Appreciable Fluorescence Rates

Robert Pollice, Pascal Friederich, Cyrille Lavigne, Gabriel dos Passos Gomes, Alan Aspuru-Guzik

Version 1 posted 29 October 2020

2,270

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2

Citations

Organometallic Chemistry

Working Paper

Machine Learning Reactivity in the Chemical Space Surrounding Vaska's Complex

Pascal Friederich, Gabriel dos Passos Gomes, Riccardo De Bin, Alan Aspuru-Guzik, David Balcells

Version 1 posted 27 November 2019

1,690

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Theoretical and Computational Chemistry

Working Paper

A Diversified Machine Learning Strategy for Predicting and Understanding Molecular Melting Points

ganesh sivaraman, Nicholas Jackson, Benjamin Sanchez-Lengeling, Alvaro Vazquez-Mayagoitia, Alan Aspuru-Guzik, Venkatram Vishwanath, Juan de Pablo

Version 1 posted 30 September 2019

1,935

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1

Citations

Theoretical and Computational Chemistry

Working Paper

The Influence of Sorbitol Doping on Aggregation and Electronic Properties of PEDOT:PSS: A Theoretical Study

Pascal Friederich, Salvador León, Jose Dario Perea, Loic Roch, Alan Aspuru-Guzik

Version 1 posted 18 March 2020

775

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1

Citations

Theoretical and Computational Chemistry

Working Paper

A Molecular Computing Approach to Solving Optimization Problems via Programmable Microdroplet Arrays

Si Yue Guo, Pascal Friederich, Yudong Cao, Tony Wu, Christopher Forman, Douglas Mendoza, Matthias Degroote, Andrew Cavell, Veronica Krasecki, Riley Hickman, Abhishek Sharma, Leroy Cronin, Nathan Gianneschi, Randall Goldsmith, Alan Aspuru-Guzik

Version 1 posted 12 November 2019

1,422

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Theoretical and Computational Chemistry

Working Paper

Machine Learning the Quantum-Chemical Properties of Metal–Organic Frameworks for Accelerated Materials Discovery with a New Electronic Structure Database

Andrew Rosen, Shaelyn Iyer, Debmalya Ray, Zhenpeng Yao, Alan Aspuru-Guzik, Laura Gagliardi, Justin Notestein, Randall Q. Snurr

Version 1 posted 29 October 2020

2,526

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5

Citations

Nanoscience

Working Paper

Frank-van der Merwe Growth in Bilayer Graphene

Haozhe Wang, Zhenpeng Yao, Gang Seob Jung, Qichen Song, Marek Hempel, Tomas Palacios, Gang Chen, Markus J. Buehler, Alan Aspuru-Guzik, Jing Kong

Version 2 posted 11 August 2021

1,518

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Theoretical and Computational Chemistry

Working Paper

Navigating through the Maze of Homogeneous Catalyst Design with Machine Learning

Gabriel dos Passos Gomes, Robert Pollice, Alan Aspuru-Guzik

Version 1 posted 12 August 2020

2,567

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Theoretical and Computational Chemistry

Working Paper

Inverse Design of Nanoporous Crystalline Reticular Materials with Deep Generative Models

Zhenpeng Yao, Benjamin Sanchez-Lengeling, N. Scott Bobbitt, Benjamin J. Bucior, Sai Govind Hari Kumar, Sean P. Collins, Thomas Burns, Tom K. Woo, Omar Farha, Randall Q. Snurr, Alan Aspuru-Guzik

Version 2 posted 25 August 2020

6,222

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Refine Search

66 results in Alan Aspuru-Guzik in Authors: Alan Aspuru-Guzik

A Bayesian Approach to Predict Solubility Parameters

Organic Molecules with Inverted Gaps between First Excited Singlet and Triplet States and Appreciable Fluorescence Rates

Machine Learning Reactivity in the Chemical Space Surrounding Vaska's Complex

A Diversified Machine Learning Strategy for Predicting and Understanding Molecular Melting Points

The Influence of Sorbitol Doping on Aggregation and Electronic Properties of PEDOT:PSS: A Theoretical Study

A Molecular Computing Approach to Solving Optimization Problems via Programmable Microdroplet Arrays

Machine Learning the Quantum-Chemical Properties of Metal–Organic Frameworks for Accelerated Materials Discovery with a New Electronic Structure Database

Frank-van der Merwe Growth in Bilayer Graphene

Navigating through the Maze of Homogeneous Catalyst Design with Machine Learning

Inverse Design of Nanoporous Crystalline Reticular Materials with Deep Generative Models

66 results in Authors: Alan Aspuru-Guzik