Zachary Ulissi

Citation name

Ulissi, Z.

Affiliation

Carnegie Mellon University

State

PA

Country

USA

Sessions chaired or co-chaired

Applications of Data Science in Catalysis and Reaction Engineering

2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)

Applications of Data Science in Catalysis and Reaction Engineering I

2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)

Applications of Data Science in Catalysis and Reaction Engineering I

2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)

Applications of Data Science in Catalysis and Reaction Engineering I

2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)

Applications of Data Science in Catalysis and Reaction Engineering II

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

Applications of Data Science in Catalysis and Reaction Engineering II

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

Applications of Data Science in Catalysis and Reaction Engineering II

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

Applications of Data Science in Catalysis and Reaction Engineering III

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

Data Science & Machine Learning Approaches to Catalysis II: AI-Accelerated Modeling of Catalysts and Materials

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

Data Science in Catalysis I

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

Data Science in Catalysis II

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

Authored

(240f) Active Learning across Intermetallics Guides Discovery of Electrocatalysts for Carbon Dioxide Reduction and Hydrogen Evolution

Kevin Tran

Zachary Ulissi

2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)

(699d) Methods to Exploit Large Datasets in Catalysis

Kevin Tran

Zachary Ulissi

2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)

(189i) Capturing Non-Ideal Surfactant/Nanoparticle Interfacial Structure with Variable Coverage Molecular Simulations

Junwoong Yoon

Zachary Ulissi

2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)

(544ds) Using Data Science to Reduce Large Reaction Networks in Catalysis

Aini Palizhati

Zachary Ulissi

2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)

(240g) Design of Optimal Metallic Surface Reconstructions for Heterogeneous Catalysis

Christopher L. Hanselman

2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)

(611g) Practical Applications of Machine Learning to Catalyst Design and Discovery

Zachary Ulissi

2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)

(544at) Prediction of Surface Energies for Complex Pt Structures from Coordination Number and Generalized Coordination Number

Wen Zhong

Christopher L. Hanselman

Kevin Tran

Chrysanthos Gounaris

Zachary Ulissi

2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)

(538g) Automated DFT Calculations for the High-Throughput Screening of Oxygen Evolution Reaction Catalysts

Zachary Ulissi

Kevin Tran

Seoin Back

2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)

(247i) Thermodynamic Techniques to Capture Non-Ideal Surfactant Assembly at Hard Nanoscale Interfaces

Zachary Ulissi

Junwoong Yoon

2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)

(246h) Graph Convolutional Machine Learning Methods for the Predictions of Adsorption and Thermochemistry and Surface Stability

2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)

(560bz) Multi-Task Machine Learning to Predict ORR Catalyst Descriptors and Performance across Surface Composition

2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)

(376aq) Phase Thermodynamics and Ab Initio Simulations to Optimize Oxidation Resistance of High Entropy Alloys in Additive Manufacturing

2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)

(45a) Discovery of Light-Driven Hydrogen Evolution Catalysts Using High Throughput Simulation, Experiments and Machine Learning

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

(710c) Predicting Surface Structure Sensitive Reactivity across All Cu(hkl) Surface Orientations: Tartaric Acid Decomposition

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

(488g) Differentiable Optimization for the Prediction of Ground State Structures in Catalysis

Junwoong Yoon

Zachary Ulissi

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

(513ef) An Active Learning Framework for Accelerating Saddle Point Searches Applied to Propylene Epoxidation

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

(346ap) All-Atom Molecular Dynamics Study for O2 Permeation in a Nafion Polyelectrolyte Membrane

Nicholas Tiwari

Sudheesh Kumar Ethirajan

Zachary Ulissi

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

(106e) The Open Catalyst Project Dataset

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

(656g) Towards Design of Active Site Requirements of Selective Hydrogenation of Different Functionalities

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

(513fd) High-Throughput Determination of Active Site Nuclearity Distribution across Binary Intermetallics for Ethylene Hydrogenation

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

(437a) Discovery of Catalysts for the Application of Nitrate Reduction and Water Purification Using Machine Learning Techniques

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(342ae) Accelerating on-the-Fly Active Learning of Catalyst Simulations Using Large Scale Pretrained Models

Joseph Musielewicz

Muhammed Shuaibi

Zachary Ulissi

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(509da) Nuclearity As a Descriptor for Site and Surface Selection

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(323d) Towards the Design of Active Site Requirements for the Selective Hydrogenation of Different Functionalities

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(118c) Transfer Learning Using Large-Scale ML Models for Catalyst/Molecular Datasets

Adeesh Kolluru

Muhammed Shuaibi

Zachary Ulissi

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(8f) Open Catalyst Project: Advancements and Challenges in Building a Flexible Machine Learning Potential

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(509cr) Neural Networks Learn Fundamental Adsorption Energy Scaling Relations

Brook Wander

Zachary Ulissi

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(342q) Optimization of High-Throughput Photocatalyzed Bimetallic Nanoparticles Using Online Active Learning

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(191k) Transfer Learning of Graph Neural Networks As a General Approach to Accelerate Computational Catalysis Modeling

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(477c) Finetuna: Fine-Tuning Accelerated Molecular Simulations

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(684g) Open Challenges in Developing Generalizable Large Scale Machine Learning Models for Catalyst Discovery

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(582h) Site Geometry Driven Selective Hydrogenation on Intermetallic Catalysts

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(88e) Simulating Closed-Loop Catalyst Discovery Processes Using an Experimental Band Gap Surrogate Model

Kirby Broderick

Zachary Ulissi

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(684h) A Computational Workflow for Intermetallic Catalyst Discovery for Selective Hydrogenation Reactions

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(360o) Electron Density Prediction with Graph Neural Networks on Large Catalyst Datasets

Ethan Sunshine

Zachary Ulissi

Muhammed Shuaibi

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(532ec) Incorporation of Covariance of DFT Energy Ensembles into Gnn Models for the Trustworthy Catalyst Design Method

Janghoon Ock

Tian Tian

Zachary Ulissi

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(662d) Machine Learning Electron Density for Chemical Property Predictions in Catalysis

2023 AIChE Annual Meeting (ISBN: 978-0-8169-1120-2)

(662b) Intermetallic Catalyst Discovery for Selective Hydrogenation Reactions

2023 AIChE Annual Meeting (ISBN: 978-0-8169-1120-2)

(521cl) Using Machine Learning to Model the Enantiospecific Decomposition of Tartaric Acid on Copper Surface Orientations

Carlos Fernandez-Caban

2023 AIChE Annual Meeting (ISBN: 978-0-8169-1120-2)

(244c) Cattsunami: Accelerating Transition State Energy Calculations with Pre-Trained Graph Neural Networks

2024 AIChE Annual Meeting (ISBN: 978-0-8169-1122-6)

Associated proceedings

2018 AIChE Annual Meeting

2019 AIChE Annual Meeting

2020 Virtual AIChE Annual Meeting

2021 Annual Meeting

2022 Annual Meeting

2023 AIChE Annual Meeting

2024 AIChE Annual Meeting

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Zachary Ulissi

Ulissi, Z.

Carnegie Mellon University

PA

USA

Sessions chaired or co-chaired

Authored

Associated proceedings