John Kitchin

2016 AIChE Annual Meeting (ISBN: 978-0-8169-1097-7)

2015 AIChE Annual Meeting Proceedings (ISBN: 978-0-8169-1094-6)

Applications of DFT+X in Catalysis

2013 AIChE Annual Meeting (ISBN: 978-0-8169-1110-3)

Sessions chaired or co-chaired

2013 AIChE Annual Meeting (ISBN: 978-0-8169-1110-3)

Applications of DFT+X in Catalysis II

2013 AIChE Annual Meeting (ISBN: 978-0-8169-1110-3)

Membrane Reactors II

2013 AIChE Annual Meeting (ISBN: 978-0-8169-1110-3)

Poster Session: Catalysis and Reaction Engineering (CRE) Division

2013 AIChE Annual Meeting (ISBN: 978-0-8169-1110-3)

Areas chaired or co-chaired

2016 AIChE Annual Meeting (ISBN: 978-0-8169-1097-7)

2015 AIChE Annual Meeting Proceedings (ISBN: 978-0-8169-1094-6)

(777g) Property Prediction of Crystalline Solids from Composition and Crystal Structure

2013 AIChE Annual Meeting (ISBN: 978-0-8169-1110-3)

Authored

Bruno A. Calfa

(617gk) Neural Network Predictions of Oxygen Interactions on a Dynamic Pd Surface

2016 AIChE Annual Meeting (ISBN: 978-0-8169-1097-7)

(253v) Practical Data Sharing for Molecular Simulation

2016 AIChE Annual Meeting (ISBN: 978-0-8169-1097-7)

(370f) Neural Network and Reaxff Comparison for Au Properties

2016 AIChE Annual Meeting (ISBN: 978-0-8169-1097-7)

2016 AIChE Annual Meeting (ISBN: 978-0-8169-1097-7)

(595b) Expanding Molecular Simulation Use By Data/Code Sharing in Scientific Publishing

(392g) Relationships Between the Surface Electronic and Chemical Properties of Doped 4d and 5d Late Transition Metal Dioxides

2016 AIChE Annual Meeting (ISBN: 978-0-8169-1097-7)

(403a) Tuning Oxide Activity through Modification of the Crystal and Electronic Structure: From Strain to Potential Polymorphs

2015 AIChE Annual Meeting Proceedings (ISBN: 978-0-8169-1094-6)

(719f) Comparative Microfluidic Screening of Amino Acid Salt Solutions for Post-Combustion CO2 Capture

2015 AIChE Annual Meeting Proceedings (ISBN: 978-0-8169-1094-6)

2015 AIChE Annual Meeting Proceedings (ISBN: 978-0-8169-1094-6)

(432e) Core Level Shifts in Cu-Pd Alloys As a Function of Bulk Composition and Structure

(684c) Accelerated Catalyst Screening Using Computational Alchemy

2015 AIChE Annual Meeting Proceedings (ISBN: 978-0-8169-1094-6)

John Keith

O. Anatole von Lilienfeld

Karthikeyan Saravanan

2017 Annual Meeting (ISBN: 978-0-8169-1102-8)

(377d) Modeling of Segregation on Au-Pd (111) Surfaces with Monte Carlo Simulations and Neural Network Atomic Potentials

(345e) Applying DFT+U and the Self-Consistent Linear Response Approach to Establish a Thermodynamic Framework for Comparing Redox Reaction Energies in Perovskites

2017 Annual Meeting (ISBN: 978-0-8169-1102-8)

Matthew Curnan

(49d) Elucidating Adsorption Mechanisms On Oxides By Comparing Adsorption On FCC Metals and Reduced B1 Monoxide Surfaces

2013 AIChE Annual Meeting (ISBN: 978-0-8169-1110-3)

(289e) Towards More Accurate Reaction Enthalpies With DFT+U Linear Response Methods

2013 AIChE Annual Meeting (ISBN: 978-0-8169-1110-3)

(158f) Leveraging DFT with Machine Learning: Applications in Catalysis

2013 AIChE Annual Meeting (ISBN: 978-0-8169-1110-3)

(538a) Single-NN: A Modified Behler-Parinello Neural Network with a Single Neural Network

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

(411j) Uncertainty Measurement Method for Machine Learned Potentials

Mingjie Liu

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

Ni Zhan

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

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

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

(479a) Data-Driven Acceleration of Catalyst Modeling

(96d) Sharing Good Times with Friends in the CRE Division: Past, Present and Future

Yilin Yang

Mingjie Liu

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

(295a) Modeling Ternary Alloy Segregation with Density Functional Theory and Machine Learning

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

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)

(363c) Process Operability Mapping Using Neural Networks

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)

(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)

(688a) High Throughput Discovery of Ternary Cu-Fe-Ru Alloy Catalysts for Photo-Driven Hydrogen Production

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

(165e) An Implicit Mapping Approach for Process Systems Engineering Applications Using Automatic Differentiation and the Implicit Function Theorem

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

(661a) Data Science & Machine Learning Approaches to Catalysis

(521ea) Streamlining Semiautonomous Workflows through Deep Learning for Materials Discovery in the Oxygen Evolution Reaction (OER)

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

Rohan Sanspeur