AI-driven autonomy to accelerate X-ray experiment-based discovery - CHESS 2030 Workshop - June 21-22

On June 21-22nd, the Cornell High Energy Synchrotron Source will host a highly interdisciplinary online workshop identifying important fundamental questions related to artificial-intelligence-driven autonomy in combination X-ray based characterization techniques. The workshop will bring together leaders in the field from industry, academia, and the national labs to explore and articulate the most critical opportunities and challenges to exploiting artificial intelligence and automation for materials discovery.

 

Register here!

Download the workshop flyer.

laser annealing setup with detector

Autonomous laser annealing / GIWAXS setup at the FMB beamline at CHESS. See here for details.

Autonomous experimentation is a closed-loop iterative process, where a computational system proposes hypotheses and actively chooses the next experiment, which is performed by an automated experimentation platform. In recent years, the opportunities and potential gains from AI-driven experimentation as well as the technology and tools to deploy it have flourished.

Materials science and engineering have emerged as particularly promising areas in which to test ideas and tools for AI-driven science, and have helped articulate the remaining challenges in realizing its potential. At the same time, the information provided by X-ray techniques regarding the interplay of materials composition, materials structure, and functional properties provides unique value for the development of novel materials with functionalities engineered for specific applications.

This workshop will assemble leaders in the field to present on and discuss interrelated aspects of autonomous, AI-driven experimental science, with the goal of articulating the scientific case for and significant challenges to realizing its promise for revolutionizing the search for materials that can transform our world. It will be divided into four sessions,  each of which will feature a series of short invited talks and discussion. The four session topics are:

  • Session 1: June 21, 10:30-12:30 PM EST: AI-Driven Experimental Science
  • Session 2: June 21,  1:30 - 3:45 PM EST: AI-Driven Exploration with Synchrotron Radiation
  • Session 3: June  22, 10:30-12:30 PM EST: Challenges & Opportunities in Autonomous Control
  • Session 4: June 22,  1:30-3:30 PM  EST: Automation in Characterization and Data Analysis

Agenda

 

 

Monday, June 21st (All Times EST)
AI-Driven Experimental Science, Benji Maruyama, Jed Pitera, Arthur Woll, Chairs
Title
10:30 AM EST Welcome: Organizing Committee  
10:35 AM Benji Maruyama, AFRL Autonomous Research Systems for Materials Development
11:05 AM Jed Pitera, IBM Accelerating Materials Discovery for Global Challenges
11:25 AM Keith Brown, Boston U.  Incorporating Prior Knowledge into Autonomous Experimentation: a Case Study using Mechanics
11:45 AM Tammy Ma, LLNL A new regime of laser-driven High Energy Density (HED) Physics: coupling high-rep-rate experiments with AI
12:05 - 12:30 PM Discussion  
12:30-1:30 PM Break  
 
AI-Driven Exploration with Synchrotron Radiation, Peter Beaucage, Chair
  
1:30 PM Kevin Yager, BNL Autonomous X-ray Scattering: Analytics and Control
2:00 PM Ron Jones, NIST The NIST Autonomous Formulation Laboratory: Neutrons, X-rays, and so much more
2:20 PM Apurva Mehta, SLAC Prerequisites for AI-driven Material Discoveries
2:40 PM John Gregoire, Cal Tech Aggregating knowledge for materials data interpretation and property prediction
3:00 PM Krishnanand M Mallayya, Cornell Xray Temperature Clustering (XTEC): an interpretable and unsupervised machine learning tool for Xray diffraction
3:05 PM Nikunjkumar Visaveliya, CCNY Composite Particles for Surface-Enhanced Raman Scattering (SERS) Sensing
3:10 - 3:45 PM Discussion  
3:30 - 4:00 PM Break  
4:00 - 5:30 PM Reserved for Extended Discussion  

 

Tuesday, June 22nd
Challenges & Opportunities in Autonomous Control, Carla Gomes & Bruce VanDover, Chairs
Title
10:30 AM Ichiro Takeuchi, U. Maryland Discovery of high-performance phase change memory materials using closed-loop autonomous materials exploration and optimization (CAMEO)
11:00 AM Peter Zwart, LBNL Gaussian Process Driven Hyperspectral Imaging
11:20 AM Jason Hattrick-Simpers, U. Toronto Autonomous Science: A Path Towards Trust in AI

11:40 AM

 Max Amsler, Cornell Autonomous High-Throughput Exploration of Metastable Materials - On the development of the scientific autonomous reasoning agent, SARA
12:00 - 12:30 PM Discussion  
12:30 - 1:30 PM Break  
 
Automation in Characterization and Data Analysis, Chris Wolverton & Mike Thompson, Chairs
  
1:30 PM Joseph Kline, NIST Automated Characterization for Process Control in the Semiconductor Industry
1:50 PM Jesse Hopkins, APS Automating data collection and analysis in biological solution SAXS
2:10 PM Dan Allan, NSLS-II Enabling Automation and Improvisation with Bluesky
2:30 PM Howie Joress, NIST Nuts and bolts of full-stack autonomous experimentation using a scanning droplet cell
2:50 - 3:30 PM Discussion & Close-out  

Organizing Committee:

AFRL: Benji Maruyama

Cornell: Joel Brock, Bruce van Dover, Carla Gomes, Mike Thompson, Grace Xing

CHESS: Jacob Ruff, Louisa Smieska, Arthur Woll

IBM: Jed Pitera

NIST: Peter Beaucage

Northwestern:  Chris Wolverton

 

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