2022

Wang W, Wu Z, Gómez-Bombarelli R. Learning Pair Potentials using Differentiable Simulations. arXiv:2209.07679. 2022;.
Peng J, Schwalbe-Koda D, Akkiraju K, Xie T, Giordano L, Yu Y, et al.. Human- and machine-centred designs of molecules and materials for sustainability and decarbonization. Nature Reviews Materials. 2022;.
Gong S, Xie T, Shao-Horn Y, Gómez-Bombarelli R, Grossman JC. Examining graph neural networks for crystal structures: limitation on capturing periodicity. arXiv:2208.05039. 2022;.
Frey N, Soklaski R, Axelrod S, Samsi S, Gómez-Bombarelli R, Coley C, et al.. Neural Scaling of Deep Chemical Models. ChemRxiv. 2022;.
Axelrod S, Shakhnovich E, Gómez-Bombarelli R. Excited state non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential. Nature Communications. 2022;13:3440.
Schwalbe-Koda D, Santiago-Reyes OA, Corma A, Román-Leshkov Y, Moliner M, Gómez-Bombarelli R. Repurposing Templates for Zeolite Synthesis from Simulations and Data Mining. Chemistry of Materials. 2022;.
Dietschreit JCB, Diestler DJ, Hulm A, Ochsenfeld C, Gómez-Bombarelli R. From Free-Energy Profiles to Activation Free Energies. The Journal of Chemical Physics. 2022;157:084113.
Bello-Jurado E, Schwalbe-Koda D, Nero M, Paris C, Uusimäki T, Román-Leshkov Y, et al.. Tunable CHA/AEI Zeolite Intergrowths with A Priori Biselective Organic Structure-Directing Agents: Controlling Enrichment and Implications for Selective Catalytic Reduction of NOx. Angewandte Chemie International Edition. 2022;.
Axelrod S, Schwalbe-Koda D, Mohapatra S, Damewood J, Greenman KP, Gómez-Bombarelli R. Learning Matter: Materials Design with Machine Learning and Atomistic Simulations. Accounts of Materials Research. 2022;.
Wang W, Xu M, Cai C, Miller BKurt, Smidt T, Wang Y, et al.. Generative Coarse-Graining of Molecular Conformations. arXiv:2201.12176 [Internet]. 2022;. https://arxiv.org/abs/2201.12176
Urata S, Nakamura N, Tada T, Tan ARui, Gómez-Bombarelli R, Hosono H. Suppression of Rayleigh Scattering in Silica Glass by Codoping Boron and Fluorine: Molecular Dynamics Simulations with Force-Matching and Neural Network Potentials. The Journal of Physical Chemistry C. 2022;126(4):2264–2275.
Nguyen HV-T, Jiang Y, Mohapatra S, Wang W, Barnes JC, Oldenhuis NJ, et al.. Bottlebrush polymers with flexible enantiomeric side chains display differential biological properties. Nature Chemistry. 2022;14:85-93.
Damewood J, Schwalbe-Koda D, Gómez-Bombarelli R. Sampling Lattices in Semi-Grand Canonical Ensemble with Autoregressive Machine Learning. npj Computational Materials. 2022;8:61.
Greenman KP, Green WH, Gómez-Bombarelli R. Multi-fidelity prediction of molecular optical peaks with deep learning. Chemical Science. 2022;13(4):1152 - 1162.
Mohapatra S, An J, Gómez-Bombarelli R. Chemistry-informed Macromolecule Graph Representation for Similarity Computation, Unsupervised and Supervised Learning. Machine Learning: Science and Technology. 2022;.
Axelrod S, Gómez-Bombarelli R. GEOM: Energy-annotated molecular conformations for property prediction and molecular generation. Scientific Data. 2022;9:185.

2021

Tan ARui, Urata S, Yamada M, Gómez-Bombarelli R. Graph theory-based structural analysis on density anomaly of silica glass. arXiv:2111.07452 [Internet]. 2021;. https://arxiv.org/abs/2111.07452
López-Vidal EM, Schissel CK, Mohapatra S, Bellovoda K, Wu C-L, Wood JA, et al.. Deep Learning Enables Discovery of a Short Nuclear Targeting Peptide for Efficient Delivery of Antisense Oligomers. JACS Au. 2021;1(11):2009–2020.
Hartweg M, Jiang Y, Yilmaz G, Jarvis CM, Nguyen HV-T, Primo GA, et al.. Synthetic Glycomacromolecules of Defined Valency, Absolute Configuration, and Topology Distinguish between Human Lectins. JACS Au. 2021;1(10):1621–1630.
Li C, Zhang G, Mohapatra S, Callahan A, Loas A, Gómez-Bombarelli R, et al.. Machine Learning Guides Peptide Nucleic Acid Flow Synthesis and Sequence Design. ChemRxiv. 2021;.
Jensen Z, Kwon S, Schwalbe-Koda D, Paris C, Gómez-Bombarelli R, Román-Leshkov Y, et al.. Discovering relationships between OSDAs and zeolites through data mining and generative neural networks. ACS Central Science. 2021;7:858–867.
Xie T, France-Lanord A, Wang Y, Lopez J, Stolberg MAustin, Hill M, et al.. Accelerating the screening of amorphous polymer electrolytes by learning to reduce random and systematic errors in molecular dynamics simulations. arXiv:2101.05339 [Internet]. 2021;. https://arxiv.org/abs/2101.05339
Xu M, Wang W, Luo S, Shi C, Bengio Y, Gómez-Bombarelli R, et al.. An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. In International Conference on Machine Learning [Internet]. 2021. https://arxiv.org/abs/2105.07246
Schwalbe-Koda D, Corma A, Román-Leshkov Y, Moliner M, Gómez-Bombarelli R. Data-Driven Design of Biselective Templates for Intergrowth Zeolites. The Journal of Physical Chemistry Letters. 2021;12:10689-10694.
Schwalbe-Koda D, Kwon S, Paris C, Bello-Jurado E, Jensen Z, Olivetti E, et al.. A priori control of zeolite phase competition and intergrowth with high-throughput simulations. Science. 2021;:eabh3350.
Schissel CK, Mohapatra S, Wolfe JM, Fadzen CM, Bellovoda K, Wu C-L, et al.. Deep learning to design nuclear-targeting abiotic miniproteins. Nature Chemistry. 2021;.
Schwalbe-Koda D, Gómez-Bombarelli R. Benchmarking binding energy calculations for organic structure-directing agents in pure-silica zeolites. The Journal of Chemical Physics. 2021;154:174109.
Schwalbe-Koda D, Tan ARui, Gomez-Bombarelli R. Differentiable sampling of molecular geometries with uncertainty-based adversarial attacks. Nature Communications. 2021;12:5104.
Schwalbe-Koda D, Gómez-Bombarelli R. Supramolecular Recognition in Crystalline Nanocavities Through Monte Carlo and Voronoi Network Algorithms. The Journal of Physical Chemistry C. 2021;125 (5):3009-3017.

2020

Gómez-Bombarelli R, Aspuru-Guzik A. Machine learning and big-data in computational chemistry. Handbook of Materials Modeling: Methods: Theory and Modeling. 2020;:1939–1962.
Axelrod S, Gómez-Bombarelli R. Molecular machine learning with conformer ensembles. arXiv:2012.08452 [Internet]. 2020;. https://arxiv.org/abs/2012.08452
Mohapatra S, Yang T, Gomez-Bombarelli R. Reusability report: Designing organic photoelectronic molecules with descriptor conditional recurrent neural networks. Nature Machine Intelligence. 2020;2:749–752.
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. The Journal of Chemical Physics. 2020;153:164501.
Mohapatra S, Hartrampf N, Poskus M, Loas A. Deep Learning for Prediction and Optimization of Fast-Flow Peptide Synthesis. ChemRxiv. 2020;.
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. 2020;.
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. 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. Cham: Springer International Publishing; 2020. pp. 445 - 467.
Ang SJun, Wang W, Schwalbe-Koda D, Axelrod S, Gómez-Bombarelli R. Active Learning Accelerates Ab Initio Molecular Dynamics on Pericyclic Reactive Energy Surfaces. Chem. 2020;7(3):738-51.
Wang W, Axelrod S, Gómez-Bombarelli R. Differentiable Molecular Simulations for Control and Learning. arXiv:2003.00868 [Internet]. 2020;. https://arxiv.org/abs/2003.00868

2019

Montáns FJ, Chinesta F, Gómez-Bombarelli R, J Kutz N. Data-driven modeling and learning in science and engineering. Comptes Rendus Mécanique. 2019;347:845–855.
Montáns FJ, Chinesta F, Gómez-Bombarelli R, J Kutz N. Complex algorithms for data-driven model learning in science and engineering. 2019.
Gómez-Bombarelli R, Aspuru-Guzik A. Computational discovery of organic LED materials. Comput. Mater. Disc. 2019;:423–446.
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.
Gómez-Bombarelli R. Reaction: The Near Future of Artificial Intelligence in Materials Discovery. Chem. Elsevier; 2018;4(6):1189 - 1190.

2017

Tong L, Chen Q, Wong AA, Gómez-Bombarelli R, Aspuru-Guzik A, Gordon RG, et al.. UV-Vis spectrophotometry of quinone flow battery electrolyte for: In situ monitoring and improved electrochemical modeling of potential and quinhydrone formation. Physical Chemistry Chemical Physics. 2017;19.
Gerhardt MR, Tong L, Gómez-Bombarelli R, Chen Q, Marshak MP, Galvin CJ, et al.. Anthraquinone Derivatives in Aqueous Flow Batteries. Advanced Energy Materials. 2017;7.
Ihn S-G, Lee N, Jeon SO, Sim M, Kang H, Jung Y, et al.. An Alternative Host Material for Long-Lifespan Blue Organic Light-Emitting Diodes Using Thermally Activated Delayed Fluorescence. Advanced Science. 2017;4.

2016

Fruchtman A, Gómez-Bombarelli R, Lovett BW, Gauger EM. Photocell optimization using dark state protection. Physical Review Letters. 2016;117.
Noimark S, Salvadori E, Gómez-Bombarelli R, MacRobert AJ, Parkin IP, Kay CWM. Comparative study of singlet oxygen production by photosensitiser dyes encapsulated in silicone: Towards rational design of anti-microbial surfaces. Physical Chemistry Chemical Physics. 2016;18.
Gómez-Bombarelli R, Aguilera-Iparraguirre J, Hirzel TD, Duvenaud D, Maclaurin D, Blood-Forsythe MA, et al.. Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach. Nature Materials. 2016;15.
Gómez-Bombarelli R, Aguilera-Iparraguirre J, Hirzel TD, Ha D-G, Einzinger M, Wu T, et al.. Turbocharged molecular discovery of OLED emitters: From high-throughput quantum simulation to highly efficient TADF devices. In Proceedings of SPIE - The International Society for Optical Engineering. 2016.
Lin K, Gómez-Bombarelli R, Beh ES, Tong L, Chen Q, Valle A, et al.. A redox-flow battery with an alloxazine-based organic electrolyte. Nature Energy. 2016;1.

2015

Aspuru-Guzik A, Adams R, Baldo M, Aguilera-Iparraguirre J, Gómez-Bombarelli R. Combinatorial design of OLED-emitting materials. In Digest of Technical Papers - SID International Symposium. 2015.
Pyzer-Knapp EO, Suh C, Gómez-Bombarelli R, Aguilera-Iparraguirre J, Aspuru-Guzik A. What Is High-Throughput Virtual Screening? A Perspective from Organic Materials Discovery. Annual Review of Materials Research. 2015.
Kelber JB, Panjwani NA, Wu D, Gómez-Bombarelli R, Lovett BW, Morton JJL, et al.. Synthesis and investigation of donor-porphyrin-acceptor triads with long-lived photo-induced charge-separate states. Chemical Science. 2015;6.
Duvenaud D, Maclaurin D, Aguilera-Iparraguirre J, Gómez-Bombarelli R, Hirzel T, Aspuru-Guzik A, et al.. Convolutional networks on graphs for learning molecular fingerprints. In Advances in Neural Information Processing Systems. 2015.

2014

Irish EK, Gómez-Bombarelli R, Lovett BW. Vibration-assisted resonance in photosynthetic excitation-energy transfer. Physical Review A - Atomic, Molecular, and Optical Physics. 2014;90.
González-Pérez M, Gómez-Bombarelli R, Pérez-Prior MT, Arenas-Valgañõn J, García-Santos MP, Calle E, et al.. Alkylating potential of styrene oxide: Reactions and factors involved in the alkylation process. Chemical Research in Toxicology. 2014;27.
Arenas-Valgañõn J, Gómez-Bombarelli R, González-Pérez M, González-Jiménez M, Calle E, Casado J. Interference by nitrous acid decomposition in the kinetic study of nitrosation reactions. International Journal of Chemical Kinetics. 2014;46.

2013

Gómez-Bombarelli R, Calle E, Casado J. Mechanisms of lactone hydrolysis in acidic conditions. Journal of Organic Chemistry. 2013;78.
Gómez-Bombarelli R, Calle E, Casado J. Mechanisms of lactone hydrolysis in neutral and alkaline conditions. Journal of Organic Chemistry. 2013;78.

2012

Gómez-Bombarelli R, González-Pérez M, Pérez-Prior MT, Calle E, Casado J. Genotoxic halofuranones in water: Isomerization and acidity of mucohalic acids. Journal of Physical Organic Chemistry. 2012;25.
Pérez-Prior MT, Gómez-Bombarelli R, González-Sánchez MI, Valero E. Biocatalytic oxidation of phenolic compounds by bovine methemoglobin in the presence of H\textlessinf\textgreater2\textless/inf\textgreaterO\textlessinf\textgreater2\textless/inf\textgreater: Quantitative structure-activity relationships}. Journal of Hazardous Materials. 2012;241-242.
Gómez-Bombarelli R, Calle E, Casado J. DNA damage by genotoxic hydroxyhalofuranones: An in silico approach to MX. Environmental Science and Technology. 2012;46.
González-Pérez M, Gómez-Bombarelli R, Arenas-Valgañõn J, Pérez-Prior MT, García-Santos MP, Calle E, et al.. Connecting the chemical and biological reactivity of epoxides. Chemical Research in Toxicology. 2012;25.
Gómez-Bombarelli R, González-Pérez M, Calle E, Casado J. Erratum: Potential of the NBP method for the study of alkylation mechanisms: NBP as a DNA-model (Chemical Research in Toxicology (2012) 25:6 (1176-1191) DOI: 10.1021/tx300065v). Chemical Research in Toxicology. 2012;25.
Goýmez-Bombarelli R, González-Pérez M, Calle E, Casado J. Potential of the NBP method for the study of alkylation mechanisms: NBP as a DNA-model. Chemical Research in Toxicology. 2012;25.
Arenas-Valgañõn J, Gómez-Bombarelli R, González-Pérez M, González-Jiménez M, Calle E, Casado J. Taurine-nitrite interaction as a precursor of alkylation mechanisms. Food Chemistry. 2012;134.

2011

Gómez-Bombarelli R, González-Pérez M, Arenas-Valgañõn J, Céspedes-Camacho IF, Calle E, Casado J. DNA-damaging disinfection byproducts: Alkylation mechanism of mutagenic mucohalic acids. Environmental Science and Technology. 2011;45.
Gómez-Bombarelli R, González-Pérez M, Calle E, Casado J. Reactivity of mucohalic acids in water. Water Research. 2011;45.
González-Pérez M, Gómez-Bombarelli R, Pérez-Prior MT, Manso JA, Céspedes-Camacho IF, Calle E, et al.. Reactivity of p-nitrostyrene oxide as an alkylating agent. A kinetic approach to biomimetic conditions. Organic and Biomolecular Chemistry. 2011;9.

2010

M. Pérez-Prior T, Gómez-Bombarelli R, González-Pérez M, Manso JA, M. García-Santos P, Calle E, et al.. Reactivity of the mutagen l,4-dinitro-2-methylpyrrole as an alkylating agent. Journal of Organic Chemistry. 2010;75.
Céspedes-Camacho IF, Manso JA, M. Pérez-Prior T, Gómez-Bombarelli R, González-Pérez M, Calle E, et al.. Reactivity of acrylamide as an alkylating agent: A kinetic approach. Journal of Physical Organic Chemistry. 2010;23.
Gómez-Bombarelli R, Palma BB, Martins C, Kranendonk M, Rodrigues AS, Calle E, et al.. Alkylating potential of oxetanes. Chemical Research in Toxicology. 2010;23.

2009

Gómez-Bombarelli R, González-Pérez M, Pérez-Prior MT, Calle E, Casado J. Computational study of the acid dissociation of esters and lactones. A case study of diketene. Journal of Organic Chemistry. 2009;74.
Gómez-Bombarelli R, González-Pérez M, Pérez-Prior MT, Calle E, Casado J. Computational calculation of equilibrium constants: Addition to carbonyl compounds. Journal of Physical Chemistry A. 2009;113.
Gómez-Bombarelli R, González-Pérez M, Pérez-Prior MT, Manso JA, Calle E, Casado J. Kinetic study of the neutral and base hydrolysis of diketene. Journal of Physical Organic Chemistry. 2009;22.
Pérez-Prior MT, Manso JA, Gómez-Bombarelli R, González-Pérez M, Céspedes IF, García-Santos MP, et al.. Solvent effects in the decomposition reaction of some products formed by the reaction of sorbic acid with sodium nitrite: 1, 4-dinitro-2-methylpyrrole and ethylnitrolic acid. Journal of Physical Organic Chemistry. 2009;22.
Pérez-Prior MT, Gómez-Bombarelli R, González-Pérez M, Manso JA, García-Santos MP, Calle E, et al.. Sorbate-nitrite interactions: Acetonitrile oxide as an alkylating agent. Chemical Research in Toxicology. 2009;22.
Manso JA, Pérez-Prior MT, Gómez-Bombarelli R, González-Pérez M, Céspedes F, García-Santos MP, et al.. Alkylating potential of N-phenyl-N-nitrosourea. Journal of Physical Organic Chemistry. 2009;22.

2008

Gómez-Bombarelli R, González-Pérez M, M. Pérez-Prior T, Manso JA, Calle E, Casado J. Chemical reactivity and biological activity of diketene. Chemical Research in Toxicology. 2008;21.
Pérez-Prior MT, Manso JA, Gómez-Bombarelli R, González-Pérez M, García-Santos MP, Calle E, et al.. Reactivity of some products formed by the reaction of sorbic acid with sodium nitrite: Decomposition of 1,4-dinitro-2-methylpyrrole and ethylnitrolic acid. Journal of Agricultural and Food Chemistry. 2008;56.

2007

Larciprete MC, Dini D, Ostuni R, Sibilia C, Bertolotti M, Alvarez-Mico X, et al.. Optical switching of a photochromic bis-phenylazo compound in PMMA films. Journal of Materials Science. 2007;42.

2006

Micó XA, Bombarelli RG, Subramanian LR, Ziegler T. Ring-opening reactions of benzotriazoles with Wittig reagents. Tetrahedron Letters. 2006;47.