Publications
Found 114 results
, “Approaching enzymatic catalysis with zeolites or how to select one reaction mechanism competing with others”, Nature Communications, vol. 14, p. 2878, 2023.
, “Atom-by-atom design of metal oxide catalysts for the oxygen evolution reaction with machine learning”, arXiv:2305.19930, 2023.
, “Automated patent extraction powers generative modeling in focused chemical spaces”, Digital Discovery, 2023.
, “Autonomous, multiproperty-driven molecular discovery: from predictions to measurements and back”, Science, vol. 382(6677), p. eadi1407, 2023.
, “Chemically Transferable Generative Backmapping of Coarse-Grained Proteins”, arXiv:2303.01569, 2023.
, “Chemistry-Informed Machine Learning for Polymer Electrolyte Discovery”, ACS Central Science, 2023.
, “Data-Driven, Physics-Informed Descriptors of Cation Ordering in Multicomponent Oxides”, arXiv:2305.01806, 2023.
, “Differentiable Simulations for Enhanced Sampling of Rare Events”, arXiv:2301.03480, 2023.
, “Effect of framework composition and NH3 on the diffusion of Cu+ in Cu-CHA catalysts predicted by machine-learning accelerated molecular dynamics”, arXiv:2305.12896, 2023.
, “Entropy and Energy Profiles of Chemical Reactions”, arXiv:2304.10676, 2023.
, “Expanding the Extrapolation Limits of Neural Network Force Fields using Physics-Based Data Augmentation”, in Workshop on "Machine Learning for Materials" at ICLR, 2023.
, “Generating, Managing, and Mining Big Data in Zeolite Simulations”, in AI‐Guided Design and Property Prediction for Zeolites and Nanoporous Materials, John Wiley & Sons, Ltd, 2023, pp. 81-111.
, “Graph theory-based structural analysis on density anomaly of silica glass”, Computational Materials Science, vol. 225, p. 112190, 2023.
, “Lamellar ionenes with highly dissociative, anionic channels provide lower barriers for cation transport”, J. Am. Chem. Soc., 2023.
, “Learning a reactive potential for silica-water through uncertainty attribution”, arXiv:2307.01705, 2023.
, “Learning Pair Potentials using Differentiable Simulations”, The Journal of Chemical Physics, vol. 158, p. 044113, 2023.
, “Machine-learning-accelerated simulations enable heuristic-free surface reconstruction”, arXiv:2305.07251, 2023.
, “Mapping the space of photoswitchable ligands and photodruggable proteins with computational modeling”, J. Chem. Inf. Model., 2023.
, “A Model Ensemble Approach Enables Data-Driven Property Prediction for Chemically Deconstructable Thermosets in the Low Data Regime”, ChemRxiv, 2023.
, “Molecular machine learning with conformer ensembles”, Machine Learning: Science and Technology, 2023.
, “Regularized indirect learning improves phage display ligand discovery”, ChemRxiv, 2023.
, “Representations of Materials for Machine Learning”, Annual Review of Materials Research, vol. 53, 2023.
, “Simulations with machine learning potentials identify the ion conduction mechanism mediating non-Arrhenius behavior in LGPS”, Journal of Physics Energy, 2023.
, “Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles”, arXiv:2305.01754, 2023.
, “Thermal Half-Lives of Azobenzene Derivatives: Virtual Screening Based on Intersystem Crossing Using a Machine Learning Potential”, ACS Central Science, 2023.
, “Unsupervised machine learning leads to an abiotic picomolar peptide ligand”, ChemRxiv, 2023.
, “Bottlebrush polymers with flexible enantiomeric side chains display differential biological properties”, Nature Chemistry, vol. 14, pp. 85-93, 2022.
, “Chemistry-informed Macromolecule Graph Representation for Similarity Computation, Unsupervised and Supervised Learning”, Machine Learning: Science and Technology, 2022.
, “Examining graph neural networks for crystal structures: limitation on capturing periodicity”, arXiv:2208.05039, 2022.
, “Excited state non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential”, Nature Communications, vol. 13, p. 3440, 2022.
, “Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations”, arXiv:2210.07237, 2022.
, “From Free-Energy Profiles to Activation Free Energies”, The Journal of Chemical Physics, vol. 157, p. 084113, 2022.
, “Generative Coarse-Graining of Molecular Conformations”, arXiv:2201.12176, 2022.
, “GEOM: Energy-annotated molecular conformations for property prediction and molecular generation”, Scientific Data, vol. 9, p. 185, 2022.
, “Human- and machine-centred designs of molecules and materials for sustainability and decarbonization”, Nature Reviews Materials, 2022.
, “Learning Matter: Materials Design with Machine Learning and Atomistic Simulations”, Accounts of Materials Research, 2022.
, “Machine Learning and High Throughput Synthesis Acceleration of the Discovery of Alkaline Electrolyte Oxygen Evolution Reaction Electrocatalysts”, in ECS Meeting Abstracts, 2022.
, “Multi-fidelity prediction of molecular optical peaks with deep learning”, Chemical Science, vol. 13(4), pp. 1152 - 1162, 2022.
, “Neural Scaling of Deep Chemical Models”, ChemRxiv, 2022.
, “Repurposing Templates for Zeolite Synthesis from Simulations and Data Mining”, Chemistry of Materials, 2022.
, “Sampling Lattices in Semi-Grand Canonical Ensemble with Autoregressive Machine Learning”, npj Computational Materials, vol. 8, p. 61, 2022.
, “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, vol. 126(4), pp. 2264–2275, 2022.
, “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.
, “Accelerating the screening of amorphous polymer electrolytes by learning to reduce random and systematic errors in molecular dynamics simulations”, arXiv:2101.05339, 2021.
, “Benchmarking binding energy calculations for organic structure-directing agents in pure-silica zeolites”, The Journal of Chemical Physics, vol. 154, p. 174109, 2021.
, “Crystal graph convolutional neural networks for per-site property prediction”, in Fourth Workshop on Machine Learning and the Physical Sciences at NeurIPS, 2021.
, “Data-Driven Design of Biselective Templates for Intergrowth Zeolites”, The Journal of Physical Chemistry Letters, vol. 12, pp. 10689-10694, 2021.
, “Deep Learning Enables Discovery of a Short Nuclear Targeting Peptide for Efficient Delivery of Antisense Oligomers”, JACS Au, vol. 1(11), pp. 2009–2020, 2021.
, “Deep learning to design nuclear-targeting abiotic miniproteins”, Nature Chemistry, 2021.
, “Differentiable sampling of molecular geometries with uncertainty-based adversarial attacks”, Nature Communications, vol. 12, p. 5104, 2021.
, “Discovering relationships between OSDAs and zeolites through data mining and generative neural networks”, ACS Central Science, vol. 7, pp. 858–867, 2021.
, “An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming”, in International Conference on Machine Learning, 2021.
, “Machine Learning Guides Peptide Nucleic Acid Flow Synthesis and Sequence Design”, Advanced Science, p. 2201988, 2021.
, “A priori control of zeolite phase competition and intergrowth with high-throughput simulations”, Science, p. eabh3350, 2021.
, “Supramolecular Recognition in Crystalline Nanocavities Through Monte Carlo and Voronoi Network Algorithms”, The Journal of Physical Chemistry C, vol. 125 (5), pp. 3009-3017, 2021.
, “Synthetic Glycomacromolecules of Defined Valency, Absolute Configuration, and Topology Distinguish between Human Lectins”, JACS Au, vol. 1(10), pp. 1621–1630, 2021.
, “Active Learning Accelerates Ab Initio Molecular Dynamics on Pericyclic Reactive Energy Surfaces”, Chem, vol. 7(3), pp. 738-51, 2020.
, “Active Learning and Neural Network Potentials Accelerate Molecular Screening of Ether-based Solvate Ionic Liquids”, Chemical Communications, 2020.
, “Deep learning for prediction and optimization of fast-flow peptide synthesis”, ACS Central Science, vol. 6, pp. 2277–2286, 2020.
, “Differentiable Molecular Simulations for Control and Learning”, arXiv:2003.00868, 2020.
, “Generative Models for Automatic Chemical Design”, in Machine Learning Meets Quantum Physics, Cham: Springer International Publishing, 2020, pp. 445 - 467.
, “Machine learning and big-data in computational chemistry”, Handbook of Materials Modeling: Methods: Theory and Modeling, pp. 1939–1962, 2020.
, “Quantitative Mapping of Molecular Substituents to Macroscopic Properties Enables Predictive Design of Oligoethyleneglycol-Based Lithium Electrolytes”, ACS Central Science, 2020.
, “Reusability report: Designing organic photoelectronic molecules with descriptor conditional recurrent neural networks”, Nature Machine Intelligence, vol. 2, pp. 749–752, 2020.
, “Temperature-transferable coarse-graining of ionic liquids with dual graph convolutional neural networks”, The Journal of Chemical Physics, vol. 153, p. 164501, 2020.
, “Coarse-graining auto-encoders for molecular dynamics”, npj Computational Materials, vol. 5, no. 1, p. 125, 2019.
, “Computational discovery of organic LED materials”, Comput. Mater. Disc, pp. 423–446, 2019.
, “Data-driven modeling and learning in science and engineering”, Comptes Rendus Mécanique, vol. 347, pp. 845–855, 2019.
, “Graph similarity drives zeolite diffusionless transformations and intergrowth”, Nature Materials, vol. 18, pp. 1177 - 1179, 2019.
, “Mapping the frontiers of quinone stability in aqueous media: implications for organic aqueous redox flow batteries”, J. Mater. Chem. A, vol. 7, pp. 12833-12841, 2019.
, “The Materials Research Platform: Defining the Requirements from User Stories”, Matter, vol. 1, no. 6, pp. 1433 - 1438, 2019.
, “Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules”, ACS Central Science, vol. 4, no. 2, pp. 268 - 276, 2018.
, “Reaction: The Near Future of Artificial Intelligence in Materials Discovery”, Chem, vol. 4, no. 6, pp. 1189 - 1190, 2018.
, “An Alternative Host Material for Long-Lifespan Blue Organic Light-Emitting Diodes Using Thermally Activated Delayed Fluorescence”, Advanced Science, vol. 4, 2017.
, “Anthraquinone Derivatives in Aqueous Flow Batteries”, Advanced Energy Materials, vol. 7, 2017.
, “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, vol. 19, 2017.
, “Comparative study of singlet oxygen production by photosensitiser dyes encapsulated in silicone: Towards rational design of anti-microbial surfaces”, Physical Chemistry Chemical Physics, vol. 18, 2016.
, “Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach”, Nature Materials, vol. 15, 2016.
, “Photocell optimization using dark state protection”, Physical Review Letters, vol. 117, 2016.
, “A redox-flow battery with an alloxazine-based organic electrolyte”, Nature Energy, vol. 1, 2016.
, “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, vol. 9941.
, “Combinatorial design of OLED-emitting materials”, in Digest of Technical Papers - SID International Symposium, 2015, vol. 46.
, “Convolutional networks on graphs for learning molecular fingerprints”, in Advances in Neural Information Processing Systems, 2015, vol. 2015-Janua.
, “Synthesis and investigation of donor-porphyrin-acceptor triads with long-lived photo-induced charge-separate states”, Chemical Science, vol. 6, 2015.
, “Alkylating potential of styrene oxide: Reactions and factors involved in the alkylation process”, Chemical Research in Toxicology, vol. 27, 2014.
, “Interference by nitrous acid decomposition in the kinetic study of nitrosation reactions”, International Journal of Chemical Kinetics, vol. 46, 2014.
, “Vibration-assisted resonance in photosynthetic excitation-energy transfer”, Physical Review A - Atomic, Molecular, and Optical Physics, vol. 90, 2014.
, “Mechanisms of lactone hydrolysis in acidic conditions”, Journal of Organic Chemistry, vol. 78, 2013.
, “Mechanisms of lactone hydrolysis in neutral and alkaline conditions”, Journal of Organic Chemistry, vol. 78, 2013.
, “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, vol. 241-242, 2012.
, “Connecting the chemical and biological reactivity of epoxides”, Chemical Research in Toxicology, vol. 25, 2012.
, “DNA damage by genotoxic hydroxyhalofuranones: An in silico approach to MX”, Environmental Science and Technology, vol. 46, 2012.
, “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, vol. 25, 2012.
, “Genotoxic halofuranones in water: Isomerization and acidity of mucohalic acids”, Journal of Physical Organic Chemistry, vol. 25, 2012.
, “Potential of the NBP method for the study of alkylation mechanisms: NBP as a DNA-model”, Chemical Research in Toxicology, vol. 25, 2012.
, “Taurine-nitrite interaction as a precursor of alkylation mechanisms”, Food Chemistry, vol. 134, 2012.
, “DNA-damaging disinfection byproducts: Alkylation mechanism of mutagenic mucohalic acids”, Environmental Science and Technology, vol. 45, 2011.
, “Reactivity of mucohalic acids in water”, Water Research, vol. 45, 2011.