JUNE 17-19, 2024
WASHINGTON, DC

AI TechConnect
 

AI for Advanced Materials Design

Submit Abstract - due December 15 »

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Symposium Co-Chairs

Shruti VenkatramShruti Venkatram
Materials Data Scientist
3M

Jan-Willem HandgraafJan-Willem Handgraaf
Senior Technical Product Manager
Siemens Digital Industries Software


2023 Key Speakers

Nick JacksonGenerative Models for Synthetically Accessible Polymers
Nick Jackson
Assistant Professor, University of Illinois Urbana-Champaign

 
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2023 Symposium Sessions

Tuesday June 20

10:30Molecular Modeling
1:30AI for Materials
4:00AI for Materials - Posters

2023 Symposium Program

Tuesday June 20

10:30Molecular ModelingChesapeake A
Session chair: Jan-Willem Handgraaf, Siemens Digital Industries Software, NE
10:30Molecular Dynamics Simulation of the Dynamic Hydration Layer in a Polyzwitterionic Polymer
J.A. Clark, V.M. Prabhu, J.F. Douglas, National Institute of Standards and Technology, US
10:50First-principles study of the tritium diffusion and formation in γ-LiAlO2 pellets
Y. Duan, T. Jia, H. Paudel, Y.-L. Lee, D. Senor, A.M. Casella, National Energy Technology Laboratory, US
11:10How molecular simulations can help to energetic transition?
D. Pantano, Total Energies, US
11:35Molecular Dynamic Simulation Study on the Effects of Moisture Content on the Water Activity and Glass Transition Temperature of Food Carbohydrates
L. Abudour, General Mills, US
1:30AI for MaterialsChesapeake A
Session chair: Jan-Willem Handgraaf, Siemens Digital Industries Software, NE
1:30Generative Models for Synthetically Accessible Polymers
N.E. Jackson, University of Illinois Urbana-Champaign, US
1:55Accelerating Materials Discovery and Design using AI and Machine Learning
P.S. Dutta, A. Koneru, D. Sanpui, A. Chandra, H. Chan, S. Manna, S. Banik, T.D. Loeffler, S.K.R.S. Sankaranarayanan, University of Illinois at Chicago, US
2:15Robocoater: Automated, Multi-Modal Optical Characterization Platform for Performing Closed-loop Bayesian Optimization of Thin-Film Hybrid Perovskite for PV Application
N. Woodward, B. Guo, M. Chauhan, M. Abolhasani, K. Rayes, A. Amassian, North Carolina State University, US
2:35Machine Learning-Driven Automated Scanning Probe Microscopy
Y. Liu, K.P. Kelley, R.K. Vasudevan, M. Ziatdinov, S.V. Kalinin, Oak Ridge National Laboratory, US
2:55Machine learning accelerated computational design of materials and processes
T.P.M. Goumans, M. Hellström, P.S.N. Onofrio, N. Aguirre, R. Rüger, Software for Chemistry & Materials, NL
4:00AI for Materials - PostersExpo Hall AB
Metal Hydride Composition-Derived Parameters as Machine Learning Features for Alloy Design and H2 Storage
S. Nations, T. Nandi, A. Ramazani, S. Wang, Y. Duan, National Energy Technology Laboratory, US
Single-Electron Reservoir Computing Circuit with Online Learning
S. Watanabe, T. Oya, Yokohama National University, JP
AI-driven Part Printability Recommendation System for Additive Manufacturing
J.A. Steets, D. Mooney, B. O’Briant, Illumination Works, LLC., US
Relatable Explanations For AI Applications
J. Tan, National University of Singapore, SG
Faux-Data Injection Optimization for Accelerating Data-Driven Discovery of Materials
A. Ziaullah, S. Chawla, F. El Mellouhi, Hamad Bin Khalifa University, QA
Accelerating Materials discovery: Best practices for Research Data Management Strategies
J. Medina, A. Wahab Ziaullah, E-T. Bentria, H. Park, I.E. Castelli, A. Shaon, H. Bensmail, F. El-Mellouhi, Hamad Bin Khalifa University, QA
Physics-informed machine learning prediction of Curie temperature of rare-earth magnetic materials
P. Singh, T. Del Rose, A. Palasyuk, Y. Mudryk, Ames National Laboratory, US
AI-Based Linearization Schemes for 5G/6G Fiber/Wireless Systems
L.A. Melo Pereira, L..L. Mendes, C.J. Albanez Bastos Filho, A. Cerqueira Sodré Junior, National Institute of Telecommunications (Inatel), BR
Design and Implementation of a Modified Shortest Path Algorithm for Package Delivery
B. Abegaz, Loyola University Chicago, US
Developing a Multi-Sensing Platform for a Six Degrees of Freedom Industrial Robot
B. Abegaz, Loyola University Chicago, US
Topics & Application Areas
  • AI, Modeling & Simulation for Materials Design
  • Materials Informatics
  • Machine Learning
  • Autonomous Research Approaches
  • Quantitative Structure Property Relationship (QSAR) Methods
  • Data Science
  • Other
 

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