Machine Learning for Soft and Hard Materials II | AIChE

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Machine Learning for Soft and Hard Materials II

Chair(s)

Co-chair(s)

Gissinger, J., University of Colorado-Boulder
Lee, E., University of Chicago
Bartel, C., University of California, Berkeley

Presentations

8:00 AM
(455a) Accelerating Ab Initio Calculations of Chemical Bonding and Equilibria at Material Interfaces Using Machine Learning
8:12 AM
(455b) Neural Network Wave Function Solver
8:24 AM
(455c) Accelerated Discovery of High-Performance Organic Electrode Materials for Battery Applications Using an Interpretable Machine Learning Framework
8:36 AM
(455d) Inverse Design of Materials with Globally Optimal Topology and Geometry through Mixed Integer Linear Programming (MILP)
8:48 AM
(455e) Catberta: Catalyst Energy Prediction and Feature Analysis through Language Models
9:00 AM
(169bv) Systematic Development of Machine Learning Interatomic Potentials for MAPbI3 Perovskites
9:12 AM
(455g) Machine-Learning Accelerated Simulation: Toward Design and Synthesis of Nanocarbon Materials
9:24 AM
(455h) Using Large Language Model to Collect and Analyze Metal-Organic Framework Property Dataset
9:36 AM
(455i) Data-Driven Acceleration of Materials Development: Leveraging AI/ML to Scalably Bridge the Gap from Models to Materials
9:48 AM
(455j) Simulation-Free, Two-Dimensional Histograms As Effective Adsorbent Representations for Machine-Learning Based Adsorption Predictions
10:00 AM
(455k) Representation Learning for All-Silica Zeolites: Model Representations, Transfer Learning, and Multi-Task Learning
10:12 AM
(455l) High-Throughput Simulations and Machine Learning for Adsorption Processes

Topics 

Thermodynamics
Computational Molecular Engineering

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Pricing

Individuals

AIChE Pro Members $150.00
AIChE Emeritus Members $105.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
AIChE Explorer Members $225.00
Non-Members $225.00

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