2021

Schwalbe-Koda D, Gómez-Bombarelli R. Supramolecular Recognition in Crystalline Nanocavities Through Monte Carlo and Voronoi Network Algorithms. The Journal of Physical Chemistry C [Internet]. 2021;125 (5):3009-3017. https://pubs.acs.org/doi/10.1021/acs.jpcc.0c10108
Schwalbe-Koda D, Gómez-Bombarelli R. Benchmarking binding energy calculations for organic structure-directing agents in pure-silica zeolites. The Journal of Chemical Physics [Internet]. 2021;154:174109. https://doi.org/10.1063/5.0044927
Schwalbe-Koda D, Tan ARui, Gomez-Bombarelli R. Differentiable sampling of molecular geometries with uncertainty-based adversarial attacks. arXiv [Internet]. 2021;:2101.11588. https://arxiv.org/abs/2101.11588
Mohapatra S, An J, Gómez-Bombarelli R. Chemistry-informed Macromolecule Graph Representation for Similarity Computation and Supervised Learning. arXiv: 2103.02565 [Internet]. 2021;:1–25. http://arxiv.org/abs/2103.02565

2020

Schwalbe-Koda D, Gómez-Bombarelli R. Generative Models for Automatic Chemical Design. In: Schütt KT, Chmiela S, O. von Lilienfeld A, Tkatchenko A, Tsuda K, Müller K-R. Machine Learning Meets Quantum Physics [Internet]. Cham: Springer International Publishing; 2020. pp. 445 - 467. https://doi.org/10.1007/978-3-030-40245-7_21
Axelrod S, Gómez-Bombarelli R. GEOM: Energy-annotated molecular conformations for property prediction and molecular generation. arXiv preprint arXiv:2006.05531 [Internet]. 2020;. https://arxiv.org/pdf/2006.05531.pdf
Qiao B, Mohapatra S, Lopez J, Leverick G, Tatara R, Shibuya Y, et al.. Quantitative Mapping of Molecular Substituents to Macroscopic Properties Enables Predictive Design of Oligoethyleneglycol-Based Lithium Electrolytes. ACS Central Science [Internet]. 2020;. https://doi.org/10.1021/acscentsci.0c00475
Axelrod S, Gómez-Bombarelli R. Molecular machine learning with conformer ensembles. arXiv preprint arXiv:2012.08452 [Internet]. 2020;. https://arxiv.org/pdf/2012.08452.pdf
Mohapatra S, Hartrampf N, Poskus M, Loas A. Deep Learning for Prediction and Optimization of Fast-Flow Peptide Synthesis. [Internet]. 2020;. https://chemrxiv.org/articles/preprint/Deep_Learning_for_Prediction_and_Optimization_of_Fast-Flow_Peptide_Synthesis/12649343
Ang SJun, Wang W, Schwalbe-Koda D, Axelrod S, Gómez-Bombarelli R. Active Learning Accelerates Ab Initio Molecular Dynamics on Pericyclic Reactive Energy Surfaces. [Internet]. 2020;. https://chemrxiv.org/articles/Active_Learning_Accelerates_Ab_Initio_Molecular_Dynamics_on_Pericyclic_Reactive_Energy_Surfaces/11910948
Wang W, Yang T, Harris WHunt, Gómez-Bombarelli R. Active Learning and Neural Network Potentials Accelerate Molecular Screening of Ether-based Solvate Ionic Liquids. Chemical Communications [Internet]. 2020;. http://pubs.rsc.org/en/Content/ArticleLanding/2020/CC/D0CC03512B
Wang W, Axelrod S, Gómez-Bombarelli R. Differentiable Molecular Simulations for Control and Learning. [Internet]. 2020;. http://arxiv.org/abs/2003.00868
Schissel CK, Mohapatra S, Wolfe JM, Fadzen CM, Bellovoda K, Wu C-L, et al.. Interpretable Deep Learning for De Novo Design of Cell-Penetrating Abiotic Polymers. bioRxiv [Internet]. 2020;. https://www.biorxiv.org/content/10.1101/2020.04.10.036566v1
Mohapatra S, Yang T, Gomez-Bombarelli R. Reusability report: Designing organic photoelectronic molecules with descriptor conditional recurrent neural networks. Nature Machine Intelligence [Internet]. 2020;2:749–752. https://www.nature.com/articles/s42256-020-00268-w
Ruza J, Wang W, Schwalbe-Koda D, Axelrod S, Harris WHunt, Gómez-Bombarelli R. Temperature-transferable coarse-graining of ionic liquids with dual graph convolutional neural networks [Internet]. 2020. https://arxiv.org/abs/2007.14144

2019

Aykol M, Hummelshøj JS, Anapolsky A, Aoyagi K, Bazant MZ, Bligaard T, et al.. The Materials Research Platform: Defining the Requirements from User Stories. Matter. 2019;1(6):1433 - 1438.
Wang W, Gómez-Bombarelli R. Coarse-graining auto-encoders for molecular dynamics. NPJ Computational Materials. 2019;5(1):125.
Schwalbe-Koda D, Jensen Z, Olivetti E, Gómez-Bombarelli R. Graph similarity drives zeolite diffusionless transformations and intergrowth. Nature Materials. 2019;18:1177 - 1179.
Tabor DP, Gómez-Bombarelli R, Tong L, Gordon RG, Aziz MJ, Aspuru-Guzik A. Mapping the frontiers of quinone stability in aqueous media: implications for organic aqueous redox flow batteries. J. Mater. Chem. A. 2019;7:12833-12841.

2018

Gómez-Bombarelli R, Wei JN, Duvenaud D, Hernández-Lobato JMiguel, Sánchez-Lengeling B, Sheberla D, et al.. Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules. ACS Central Science. 2018;4(2):268 - 276.

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