ZU
Zachary Ward Ulissi
cond-mat.mtrl-scics.LGphysics.chem-phphysics.comp-phcs.CEcs.AINeural Networks, ComputerSoftware2D materials2D membranes
On Valency
published · living versionsW_q6v7yqy5·v1 · currentpublished
EVA-Flow: Learning Shared Chemistry for Unified Environment-Aware Molecular Conformation Generation
with Bing Yan, Anuroop Sriram, Kyunghyun Cho, Ricky T. Q. Chen +1
1 version
W_qspcx4nn·v2published
Preprints & journals
69 papers in the corpus · 2006–2026Quantum-accurate atomistic modeling of enzyme catalysis using a machine learned potential2609.09293v2 · Meng Gao, Armin Shayesteh Zadeh, Aniruddha Seal et al.2026 · 0 citationsarXivon Valency
The Open Materials 2024 (OMat24) inorganic materials dataset and models.42230827 · Barros-Luque, Luis, Shuaibi, Muhammed, Fu, Xiang et al.2026 · 21 citationsNature computational science. 2026;6(6):642-652
A recipe for scalable attention-based MLIPs: unlocking long-range accuracy with all-to-all node attention2603.06567v1 · Eric Qu, Brandon M. Wood, Aditi S. Krishnapriyan et al.2026 · 3 citationsarXiv
Open Molecular Crystals 2025 (OMC25) dataset and models.41639080 · Gharakhanyan, Vahe, Barroso-Luque, Luis, Yang, Yi et al.2026 · 20 citationsScientific data. 2026;13(1)
Genetic algorithm-accelerated computational discovery of liquid crystal polymers with enhanced optical properties.41209325 · Zhou, Jianing, Huang, Yuge, Boromand, Arman et al.2025 · 2 citationsRSC advances. 2025;15(50):43161-43173
Insights into CO dimerization at electrified Cu interfaces from large-scale machine learning simulations2509.17862v2 · Sushree Jagriti Sahoo, Mikael Maraschin, Joel B Varley et al.2025 · 10 citationsarXiv
Roadmap for Transforming Heterogeneous Catalysis with Artificial Intelligence10.26434/chemrxiv-2025-chn4j · Hongliang Xin, John Kitchin, Núria López et al.2025 · 29 citationsChemRxiv
The Open DAC 2025 Dataset for Sorbent Discovery in Direct Air Capture2508.03162v2 · Anuroop Sriram, Logan M. Brabson, Xiaohan Yu et al.2025 · 7 citationsarXiv
FastCSP: Accelerated Molecular Crystal Structure Prediction with Universal Model for Atoms2508.02641v2 · Vahe Gharakhanyan, Yi Yang, Luis Barroso-Luque et al.2025 · 3 citationsarXiv
UMA: A Family of Universal Models for Atoms2506.23971v2 · Brandon M. Wood, Misko Dzamba, Xiang Fu et al.2025 · 86 citationsarXiv
The Open Molecules 2025 (OMol25) Dataset, Evaluations, and Models2505.08762v2 · Daniel S. Levine, Muhammed Shuaibi, Evan Walter Clark Spotte-Smith et al.2025 · 80 citationsarXiv
Multi-Physics Inverse Design of Varifocal Optical Devices using Data-Driven Surrogates and Differential Modeling2503.18911v1 · Zeqing Jin, Zhaocheng Liu, Nagi Elabbasi et al.2025 · 0 citationsarXiv
All-atom Diffusion Transformers: Unified generative modelling of molecules and materials2503.03965v2 · Chaitanya K. Joshi, Xiang Fu, Yi-Lun Liao et al.2025 · 9 citationsarXiv
Open Catalyst Experiments 2024 (OCx24): Bridging Experiments and Computational Models2411.11783v1 · Jehad Abed, Jiheon Kim, Muhammed Shuaibi et al.2024 · 19 citationsarXiv
Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models2410.12771v2 · Luis Barroso-Luque, Muhammed Shuaibi, Xiang Fu et al.2024 · 97 citationsarXiv
Pourbaix Machine Learning Framework Identifies Acidic Water Oxidation Catalysts Exhibiting Suppressed Ruthenium Dissolution.38830239 · Abed, Jehad, Heras-Domingo, Javier, Sanspeur, Rohan Yuri et al.2024 · 97 citationsJournal of the American Chemical Society. 2024;146(23):15740-15750
CatTSunami: Accelerating Transition State Energy Calculations with Pre-trained Graph Neural Networks2405.02078v3 · Brook Wander, Muhammed Shuaibi, John R. Kitchin et al.2024 · 47 citationsarXiv
The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture.38799660 · Sriram, Anuroop, Choi, Sihoon, Yu, Xiaohan et al.2024 · 105 citationsACS central science. 2024;10(5):923-941
Adapting OC20-trained EquiformerV2 Models for High-Entropy Materials2403.09811v1 · Christian M. Clausen, Jan Rossmeisl, Zachary W. Ulissi2024 · 43 citationsarXiv
Fine-Tuned Language Models Generate Stable Inorganic Materials as Text2402.04379v2 · Nate Gruver, Anuroop Sriram, Andrea Madotto et al.2024 · 31 citationsarXiv
Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Data Set.38049389 · Garrison, Aaron G, Heras-Domingo, Javier, Kitchin, John R et al.2023 · 27 citationsJournal of chemical information and modeling. 2023;63(24):7642-7654
Generalization of Graph-Based Active Learning Relaxation Strategies Across Materials2311.01987v1 · Xiaoxiao Wang, Joseph Musielewicz, Richard Tran et al.2023 · 10 citationsarXiv
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction2310.16802v2 · Nima Shoghi, Adeesh Kolluru, John R. Kitchin et al.2023 · 23 citationsarXiv
Cluster-MLP: An Active Learning Genetic Algorithm Framework for Accelerated Discovery of Global Minimum Configurations of Pure and Alloyed Nanoclusters.37824704 · Raju, Rajesh K, Sivakumar, Saurabh, Wang, Xiaoxiao et al.2023 · 28 citationsJournal of chemical information and modeling. 2023;63(20):6192-6197
Chemical Properties from Graph Neural Network-Predicted Electron Densities2309.04811v1 · Ethan M. Sunshine, Muhammed Shuaibi, Zachary W. Ulissi et al.2023 · 24 citationsarXiv
Beyond independent error assumptions in large GNN atomistic models.37260012 · Ock, Janghoon, Tian, Tian, Kitchin, John et al.2023 · 11 citationsThe Journal of chemical physics. 2023;158(21)
WhereWulff: A Semiautonomous Workflow for Systematic Catalyst Surface Reactivity under Reaction Conditions.37017312 · Sanspeur, Rohan Yuri, Heras-Domingo, Javier, Kitchin, John R et al.2023 · 14 citationsJournal of chemical information and modeling. 2023;63(8):2427-2437
WhereWulff: A semi-autonomous workflow for systematic catalyst surface reactivity under reaction conditions2302.14103v1 · Rohan Yuri Sanspeur, Javier Heras-Domingo, John R. Kitchin et al.2023 · 0 citationsarXiv
AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials2211.16486v3 · Janice Lan, Aini Palizhati, Muhammed Shuaibi et al.2022 · 123 citationsarXiv
Catlas: an automated framework for catalyst discovery demonstrated for direct syngas conversion2208.12717v1 · Brook Wander, Kirby Broderick, Zachary W. Ulissi2022 · 17 citationsarXiv
Screening of bimetallic electrocatalysts for water purification with machine learning.35987588 · Tran, Richard, Wang, Duo, Kingsbury, Ryan et al.2022 · 18 citationsThe Journal of chemical physics. 2022;157(7):074102
Robust and scalable uncertainty estimation with conformal prediction for machine-learned interatomic potentials2208.08337v2 · Yuge Hu, Joseph Musielewicz, Zachary Ulissi et al.2022 · 40 citationsarXiv
Detailed microkinetics for the oxidation of exhaust gas emissions through automated mechanism generation10.26434/chemrxiv-2022-r5wn0-v2 · Bjarne Kreitz, Patrick Lott, Jongyoon Bae et al.2022 · 30 citationsChemRxiv
Spherical Channels for Modeling Atomic Interactions2206.14331v2 · C. Lawrence Zitnick, Abhishek Das, Adeesh Kolluru et al.2022 · 35 citationsarXiv
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts2206.08917v3 · Richard Tran, Janice Lan, Muhammed Shuaibi et al.2022 · 327 citationsarXiv
Identifying Limitations in Screening High-Throughput Photocatalytic Bimetallic Nanoparticles with Machine-Learned Hydrogen Adsorptions10.26434/chemrxiv-2022-fkj67-v2 · Kirby Broderick, Eric Lopato, Brook Wander et al.2022 · 25 citationsChemRxiv
Open Challenges in Developing Generalizable Large Scale Machine Learning Models for Catalyst Discovery2206.02005v2 · Adeesh Kolluru, Muhammed Shuaibi, Aini Palizhati et al.2022 · 73 citationsarXiv
Transfer learning using attentions across atomic systems with graph neural networks (TAAG).35568535 · Kolluru, Adeesh, Shoghi, Nima, Shuaibi, Muhammed et al.2022 · 35 citationsThe Journal of chemical physics. 2022;156(18):184702
FINETUNA: Fine-tuning Accelerated Molecular Simulations2205.01223v2 · Joseph Musielewicz, Xiaoxiao Wang, Tian Tian et al.2022 · 36 citationsarXiv
GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets2204.02782v3 · Johannes Gasteiger, Muhammed Shuaibi, Anuroop Sriram et al.2022 · 50 citationsarXiv
Rotation Invariant Graph Neural Networks using Spin Convolutions2106.09575v1 · Muhammed Shuaibi, Adeesh Kolluru, Abhishek Das et al.2021 · 44 citationsarXiv
Computational catalyst discovery: Active classification through myopic multiscale sampling.33810693 · Tran, Kevin, Neiswanger, Willie, Broderick, Kirby et al.2021 · 12 citationsThe Journal of chemical physics. 2021;154(12):124118
Elimination of Multidrug-Resistant Bacteria by Transition Metal Dichalcogenides Encapsulated by Synthetic Single-Stranded DNA.33570927 · Debnath, Abhishek, Saha, Sanchari, Li, Duo O et al.2021 · 25 citationsACS applied materials & interfaces. 2021;13(7):8082-8094
Differentiable Optimization for the Prediction of Ground State Structures (DOGSS).33156640 · Yoon, Junwoong, Ulissi, Zachary W2020 · 14 citationsPhysical review letters. 2020;125(17):173001
The Open Catalyst 2020 (OC20) Dataset and Community Challenges2010.09990v5 · Lowik Chanussot, Abhishek Das, Siddharth Goyal et al.2020 · 770 citationsarXiv
An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage2010.09435v1 · C. Lawrence Zitnick, Lowik Chanussot, Abhishek Das et al.2020 · 49 citationsarXiv
In silico discovery of active, stable, CO-tolerant and cost-effective electrocatalysts for hydrogen evolution and oxidation.32856642 · Back, Seoin, Na, Jonggeol, Tran, Kevin et al.2020 · 17 citationsPhysical chemistry chemical physics : PCCP. 2020;22(35):19454-19458
Enabling robust offline active learning for machine learning potentials using simple physics-based priors2008.10773v1 · Muhammed Shuaibi, Saurabh Sivakumar, Rui Qi Chen et al.2020 · 33 citationsarXiv
Discovery of Acid-Stable Oxygen Evolution Catalysts: High-Throughput Computational Screening of Equimolar Bimetallic Oxides.32799519 · Back, Seoin, Tran, Kevin, Ulissi, Zachary W2020 · 70 citationsACS applied materials & interfaces. 2020;12(34):38256-38265
Accelerated discovery of CO2 electrocatalysts using active machine learning.32405017 · Zhong, Miao, Tran, Kevin, Min, Yimeng et al.2020 · 1,540 citationsNature. 2020;581(7807):178-183
Career total: 193 works. 69 are in this corpus.Showing the 50 most recent.
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