Heather Kulik
Authored
(152j) Machine-Learning Enabled Screening of MOFs for Ion Selective Membranes
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(360ac) Using Text-Mining and Community Knowledge to Quantify and Engineer Stability in MOFs
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(477b) Finding Needles in a Haystack: Sifting through 16M Catalysts for Optimal Methane-to-Methanol Catalyst Design Under Weak Thermodynamic Scaling
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(191i) Accelerating the Design of Single-Site Materials for Catalysis Using Computational Data, Experimental Data, and Machine Learning
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(43e) Investigating the Genesis of Catalytic Promotion for Silica-Supported Molybdenum Oxide during Propylene Metathesis
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(562a) Irreversible Synthesis of an Ultrastrong Two-Dimensional Polymeric Material
2022 Annual Meeting (ISBN: 978-0-8169-1118-9)
(544k) Estimating and Correcting DFT Error of Metal-Organic Frameworks through Molecular Derivatives
2023 AIChE Annual Meeting (ISBN: 978-0-8169-1120-2)
(662a) Machine Learning for Homogeneous Open-Shell Transition Metal Catalyst Discovery
2023 AIChE Annual Meeting (ISBN: 978-0-8169-1120-2)
(561a) Discovering Single Site and Single Atom Catalysts with High-Throughput Computational Screening
2023 AIChE Annual Meeting (ISBN: 978-0-8169-1120-2)
(647d) Time Series Analysis of Membrane Aging in Organic Environments
2023 AIChE Annual Meeting (ISBN: 978-0-8169-1120-2)
(609k) Data-Driven Screening of Metal-Organic Frameworks for Selective C2 Separations
2023 AIChE Annual Meeting (ISBN: 978-0-8169-1120-2)
(676e) Ru or Fe? Understanding Trends in C–H Activation Catalysis with High-Throughput Screening
2023 AIChE Annual Meeting (ISBN: 978-0-8169-1120-2)
(451b) Designing Molecular Coordination Environments for Selective Ion Binding Using Machine Learning
2023 AIChE Annual Meeting (ISBN: 978-0-8169-1120-2)
(88a) Accelerating discovery with computational chemistry in challenging materials spaces
2023 AIChE Annual Meeting (ISBN: 978-0-8169-1120-2)
(169b) Data Set and Data-Driven Models for Predicting Metal-Organic Framework Stability in Water and Harsh Environments
2024 AIChE Annual Meeting (ISBN: 978-0-8169-1122-6)
(690d) A Literature-Derived Data Set and Machine Learning-Enabled Prediction of Metal-Organic Framework Water Stability
2024 AIChE Annual Meeting (ISBN: 978-0-8169-1122-6)
(673b) Computational Discovery of Metal-Organic Frameworks with High Water Uptake Capacity for Next-Generation Membranes
2024 AIChE Annual Meeting (ISBN: 978-0-8169-1122-6)
(169d) Exploring the Role of Functional Groups and Nanoconfinement on the Structural and Dynamical Properties of Water and Ions inside Metal-Organic Frameworks
2024 AIChE Annual Meeting (ISBN: 978-0-8169-1122-6)
(271a) Leveraging Experimental Data in Machine Learning Models to Accelerate the Discovery of New Materials and Catalysts
2024 AIChE Annual Meeting (ISBN: 978-0-8169-1122-6)
(557f) Modeling Polymer Aging in Solvent Environments with Symbolic Regression
2024 AIChE Annual Meeting (ISBN: 978-0-8169-1122-6)
(556c) Data-Driven Screening of Metal-Organic Frameworks for Selective C2 Separations
2024 AIChE Annual Meeting (ISBN: 978-0-8169-1122-6)
(435b) Using Machine Learning to Overcome Limitations in Electronic Structure Methodology for Chemical Discovery
2024 AIChE Annual Meeting (ISBN: 978-0-8169-1122-6)
Associated proceedings
2022 Annual Meeting
2023 AIChE Annual Meeting
2024 AIChE Annual Meeting