MARCH 10-12, 2026 | RALEIGH, NC
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  AI, Modeling, and Simulation  
for Advanced Materials Design  



The use of AI and ML have revolutionized the way new materials are being developed and it has shown to be the most effective when combined with physics based simulation models. Especially to boost the accuracy level of the simulation of materials and related material properties AI/ML techniques play a key role. In this symposium the latest developments in this field will be presented and discussed with a focus on relevant cases from industry.


Topics & Application Areas
  • AI, Modeling & Simulation for Materials Design
  • Materials Informatics
  • Machine Learning
  • Autonomous Research Approaches
  • Quantitative Structure Property Relationship (QSAR) Methods
  • Data Science
  • Intersection of Simulation and Experimentation
  • Method Development
  • Battery Application
  • Sustainability Application
  • Other
 

Symposium Co-Chairs


Jan-Willem Handgraaf

Jan-Willem Handgraaf

Senior Technical Product Manager

Siemens Digital Industries Software

Michael Webb

Michael Webb

Assistant Professor

Princeton University



Key Speakers


Taku Watanabe

Bridging Accuracy and Scale: AI-Accelerated Atomistic Simulation with Matlantis™

Taku Watanabe

Principal researcher,

Matlantis

Janhavi Nistane

AI-driven polymers & formulations innovations at the industrial scale

Janhavi Nistane

Scientist,

Matmerize, Inc


Matt Tamasi

Accelerating Polymer Discovery: Integrating High-Throughput Automation and Machine Learning for Tailored Macro

Matt Tamasi

CTO,

Plexymer, Inc.



 
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2026 Symposium Sessions

Wednesday March 11

1:30AI, Modeling, and Simulation for Advanced Materials Design
4:00AI for Materials Discovery - Posters

2026 Symposium Program

Wednesday March 11

1:30AI, Modeling, and Simulation for Advanced Materials DesignMarriott State E
Session chair: Michael Webb, Princeton University, & Jan-Willem Handgraaf, Siemens
Accelerating Polymer Discovery: Integrating High-Throughput Automation and Machine Learning for Tailored Macromolecular Design
M. Tamasi, A.J. Gormley, Plexymer, Inc., US
AI-driven polymers & formulations innovations at the industrial scale
J. Nistane, R. Ramprasad, Matmerize, Inc, US
*STUDENT BEST ABSTRACT WINNER* SemiOrg: An Open-Data, Open-Source FAIR Data Infrastructure for AI-Driven Discovery of Semiconducting Organic Materials
T. Trapier, North Carolina State University, US
The Use of AI Tools for Phosphorus Sustainability
S.K. Pinky, P. Hogsed, A. Kancharla, N.A. Zaid, A. Gulyuk, D.S. Pendyala, R. Lakshmi-Ratan, R. Chirkova, E. McLamore, Y.G. Yingling, North Carolina State University, US
Bridging Accuracy and Scale: AI-Accelerated Atomistic Simulation with Matlantis™
T. Watanabe, Matlantis Corp., JP
SimuScan and Large-Area AFM: Toward Autonomous Nanoscale Discovery through Synthetic Data and Machine Learning
R. Millan‐Solsona, M. Checa, L. Collins, Oak Ridge National Laboratory, US
Finite Element Analysis and Experimental Evaluation of Biobased Flexible Packaging Films
A. Rathaur, L. Pal, North Carolina State University, US
Forecasting Emissions from Carbon Capture Plants Leveraging Advanced Artificial Intelligence Models
K. Nithyanandam, S. Bhavsar, C. Kulkarni, Impact Innovations LLC, US
4:00AI for Materials Discovery - PostersExpo Hall AB
Efficient in-sensor and multimodal signal processing using Hyperdimensional computing algorithms implemented on an FPGA
V. Ehsan, N. Srinivasa, R. Kim, and Y. Khurana, Arch Systems, LLC, US
AI-Driven Knowledge Graphs for Sustainable Materials Discovery and a Circular Phosphorus Economy
N. Abu Zaid, Q. Yang, S. Changlani, D.S. Pendyala, B.P. Allen, A.V. Gulyuk, R. Chirkova, Y.G. Yingling, North Carolina State university, US
Waste Valorization and AI-driven Optimization for Industrial Application.
K. Shah, S. Mandal, Texas State University, US
Temperature-Dependent Diffusion Mechanisms in Metal–Organic Frameworks Revealed by Machine-Learning Interatomic Potentials
S.K. Ethirajan, A. Kulkarni, University of California, Davis, US
SDDC-YOLO: A Diagnostic Framework for Defect Detection in Industrial Materials
M. Gao, E. Shim, M. Zhu, North Carolina State University, US
Designing Biomolecule and Surface Agnostic Interaction Descriptors Using MD
M. Fedai, A.Y. Pandya, A.L. Kwansa, Y.G. Yingling, North Carolina State University, US
Catalyzing Chemistry: Ultra High-Throughput Physical Experimentation for Advanced Materials Discovery & Optimization
Z. Batts, Dot Energy LLC, US



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