Heather Kulik

Presentation History

2023 MRS Fall Meeting

Exciton Dynamics and Anisotropy in 2D Silver Phenylchalcogenolates

Nov 30, 2023, 4:00 PM

2023 MRS Fall Meeting

Leveraging Electrochromic Polymers for Organic Electrochemical Synaptic Devices by Unraveling Polymer-Ion Interactions

Nov 29, 2023, 8:00 PM

2023 MRS Fall Meeting

Leveraging Community Knowledge in Machine Learning Models to Accelerate the Discovery of New MOF Catalysts and Materials

Nov 29, 2023, 4:30 PM

2023 MRS Fall Meeting

Estimating and Correcting DFT Error of Metal-Organic Frameworks Through Molecular Derivatives

Nov 27, 2023, 3:45 PM

2023 MRS Fall Meeting

Overcoming the Limits of Approximate Electronic Structure Models in Machine Learning Accelerated Materials Discovery

Nov 27, 2023, 3:00 PM

2022 MRS Fall Meeting

Excitonic Properties in 2D Silver Phenlychalcogenolates

Nov 29, 2022, 9:15 AM

2021 MRS Fall Meeting

Transforming Automated Quantum Chemistry Calculation Workflows with Machine Learning—Towards Faster and More Accurate Materials Discovery

Nov 30, 2021, 2:00 PM

2021 MRS Spring Meeting

Late News: Elucidating Ionization Anomalies Observed in Nanoporous Polyamide Membranes

Apr 23, 2021, 3:15 PM

2019 MRS Fall Meeting

A Non-Empirical Method for Eliminating Delocalization and Static Correlation Errors within Density Functional Theory for Studying Correlated Materials

Dec 3, 2019, 8:00 PM

2019 MRS Fall Meeting

Using Data Driven Models to Gain Insight on Spin- and Oxidation-State Dependent Behavior of Reaction Energetics for Light Alkane Oxidation

Dec 3, 2019, 8:00 PM

2019 MRS Fall Meeting

Leveraging Large-Scale Electronic Structure for Multi-Scale Models of Confined Solutions

Dec 3, 2019, 2:15 PM

2019 MRS Fall Meeting

Accelerating Discovery in Inorganic Chemistry with Machine Learning

Dec 3, 2019, 2:00 PM

2019 MRS Fall Meeting

High-Throughput Design of Organic Friction Reducers in Engine Oils

Dec 3, 2019, 9:00 AM

2019 MRS Fall Meeting

Accelerating Materials Discovery with Autonomous Job Control Systems Aided by Machine Learning

Dec 2, 2019, 8:00 PM