Publications
Found 17 results
Filters: Author is Daniel Schwalbe-Koda [Clear All Filters]
“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.
, “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.
, “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.
, “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.
, “Benchmarking binding energy calculations for organic structure-directing agents in pure-silica zeolites”, The Journal of Chemical Physics, vol. 154, p. 174109, 2021.
, “Data-Driven Design of Biselective Templates for Intergrowth Zeolites”, The Journal of Physical Chemistry Letters, vol. 12, pp. 10689-10694, 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.
, “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.
, “Active Learning Accelerates Ab Initio Molecular Dynamics on Pericyclic Reactive Energy Surfaces”, Chem, vol. 7(3), pp. 738-51, 2020.
, “Generative Models for Automatic Chemical Design”, in Machine Learning Meets Quantum Physics, Cham: Springer International Publishing, 2020, pp. 445 - 467.
, “Temperature-transferable coarse-graining of ionic liquids with dual graph convolutional neural networks”, The Journal of Chemical Physics, vol. 153, p. 164501, 2020.
, “Graph similarity drives zeolite diffusionless transformations and intergrowth”, Nature Materials, vol. 18, pp. 1177 - 1179, 2019.
,