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2025	Molecular design of organic photovoltaic donors and non-fullerene acceptors: a combined machine learning and genetic algorithm approach Journal of Materials Chemistry C Rui Cao, Cai-Rong Zhang, Xiao-Meng Liu, Ji-Jun Gong, Mei-Ling Zhang, Zi-Jiang Liu, You-Zhi Wu, Hong-Shan Chen
2025	Knowledge-Informed Molecular Design for Zeolite Synthesis Using General-Purpose Pretrained Large Language Models Toward Human-Machine Collaboration Chemistry of Materials Shusuke Ito, Koki Muraoka, Akira Nakayama
2025	Bayesian illumination: Inference and quality-diversity accelerate generative molecular models SciPost Chemistry Jonas Verhellen
2024	Discovery of molybdenum based nitrogen fixation catalysts with genetic algorithms Chemical Science Magnus Strandgaard, Julius Seumer, Jan H. Jensen
2024	Proceedings of the Genetic and Evolutionary Computation Conference Companion Maiia Pinchuk, Grigorii Kirgizov, Lyubov Yamshchikova, Nikolay Nikitin, Irina Deeva, Karine Shakhkyan, Ivan Borisov, Kirill Zharkov, Anna Kalyuzhnaya
2024	2024 IEEE Congress on Evolutionary Computation (CEC) Tomoya Hömberg, Sanaz Mostaghim, Satoru Hiwa, Tomoyuki Hiroyasu
2024	Gaussian Process Regression-Based Near-Infrared d-Luciferin Analogue Design Using Mutation-Controlled Graph-Based Genetic Algorithm Journal of Chemical Information and Modeling Sung Wook Moon, Seung Kyu Min
2024	Machine Learning for Orbital Energies of Organic Molecules Upwards of 100 Atoms physica status solidi (b) Christopher Gaul, Santiago Cuesta-Lopez
2024	Comprehensive Computational Chemistry Marco Foscato, Jonas B. Ekeli, Marcello Costamagna, David Grellscheid, Vidar R. Jensen
2023	Generative Models as an Emerging Paradigm in the Chemical Sciences Journal of the American Chemical Society Dylan M. Anstine, Olexandr Isayev
2023	Determining best practices for using genetic algorithms in molecular discovery The Journal of Chemical Physics Brianna L. Greenstein, Danielle C. Elsey, Geoffrey R. Hutchison
2023	Genetic algorithm-based re-optimization of the Schrock catalyst for dinitrogen fixation PeerJ Physical Chemistry Magnus Strandgaard, Julius Seumer, Bardi Benediktsson, Arghya Bhowmik, Tejs Vegge, Jan H. Jensen
2023	AI‐Guided Design and Property Prediction for Zeolites and Nanoporous Materials Steven Bennett, Kim E. Jelfs
2023	Guided diffusion for inverse molecular design Nature Computational Science Tomer Weiss, Eduardo Mayo Yanes, Sabyasachi Chakraborty, Luca Cosmo, Alex M. Bronstein, Renana Gershoni-Poranne
2022	Pareto Optimization of Oligomer Polarizability and Dipole Moment Using a Genetic Algorithm The Journal of Physical Chemistry A Danielle C. Hiener, Geoffrey R. Hutchison
2022	Using deep neural networks to explore chemical space Expert Opinion on Drug Discovery Martin Vogt
2022	Graph-based molecular Pareto optimisation Chemical Science Jonas Verhellen
2022	Approaches for enhancing the analysis of chemical space for drug discovery Expert Opinion on Drug Discovery Fernanda I. Saldívar-González, José L. Medina-Franco
2022	A benchmark study of machine learning methods for molecular electronic transition: Tree‐based ensemble learning versus graph neural network Bulletin of the Korean Chemical Society Beomchang Kang, Chaok Seok, Juyong Lee
2022	Organic photoredox catalysts for CO2 reduction: Driving discovery with genetic algorithms The Journal of Chemical Physics Kareesa J. Kron, Andres Rodriguez-Katakura, Pranesh Regu, Maria N. Reed, Rachelle Elhessen, Shaama Mallikarjun Sharada
2022	Curiosity in exploring chemical spaces: intrinsic rewards for molecular reinforcement learning Machine Learning: Science and Technology Luca A Thiede, Mario Krenn, AkshatKumar Nigam, Alán Aspuru-Guzik
2022	Generating stable molecules using imitation and reinforcement learning Machine Learning: Science and Technology Søren Ager Meldgaard, Jonas Köhler, Henrik Lund Mortensen, Mads-Peter V Christiansen, Frank Noé, Bjørk Hammer
2022	Towards a chemistry-informed paradigm for designing molecules Current Opinion in Chemical Engineering Srinivas Rangarajan
2022	Neural-network-backed evolutionary search for SrTiO3(110) surface reconstructions Digital Discovery Ralf Wanzenböck, Marco Arrigoni, Sebastian Bichelmaier, Florian Buchner, Jesús Carrete, Georg K. H. Madsen
2021	MOLGENGO: Finding Novel Molecules with Desired Electronic Properties by Capitalizing on Their Global Optimization ACS Omega Beomchang Kang, Chaok Seok, Juyong Lee
2021	Perspective and challenges in electrochemical approaches for reactive CO2 separations iScience Burcu Gurkan, Xiao Su, Aidan Klemm, Yonghwan Kim, Shaama Mallikarjun Sharada, Andres Rodriguez-Katakura, Kareesa J. Kron
2021	Deep molecular dreaming: inverse machine learning for de-novo molecular design and interpretability with surjective representations Machine Learning: Science and Technology Cynthia Shen, Mario Krenn, Sagi Eppel, Alán Aspuru-Guzik
2021	Defining and Exploring Chemical Spaces Trends in Chemistry Connor W. Coley
2021	Beyond generative models: superfast traversal, optimization, novelty, exploration and discovery (STONED) algorithm for molecules using SELFIES Chemical Science AkshatKumar Nigam, Robert Pollice, Mario Krenn, Gabriel dos Passos Gomes, Alán Aspuru-Guzik
2021	MolFinder: an evolutionary algorithm for the global optimization of molecular properties and the extensive exploration of chemical space using SMILES Journal of Cheminformatics Yongbeom Kwon, Juyong Lee
2020	Illuminating elite patches of chemical space Chemical Science Jonas Verhellen, Jeriek Van den Abeele