Name: High-throughput and Data-driven Approaches Guiding Smart Operando Experiments (Workshop 3)
Start: 2018-05-22T13:00:00-04:00
End: 2018-05-22T18:30:00-04:00
Location: Berkner Hall, Bldg. 488, Conf. Rm. B

High-throughput and Data-driven Approaches Guiding Smart Operando Experiments (Workshop 3)

Tuesday, 22 May 2018 - 13:00

Monday, 21 May 2018
Tuesday, 22 May 2018

13:00 Opening Remarks
Opening Remarks
13:00 - 13:10
13:10 Product and Process Analysis by High-throughput X-ray Absorption Spectroscopy: From Concept to Reality - Sven L. M. Schroeder, University of Leeds
Product and Process Analysis by High-throughput X-ray Absorption Spectroscopy: From Concept to Reality
- Sven L. M. Schroeder, University of Leeds
13:10 - 13:50
13:50 An Iterative Machine Learning – High-throughput Experimental Approach to Discovering Novel Amorphous Alloys - Jason Hattrick-Simpers, National Institute of Standards and Technology
An Iterative Machine Learning – High-throughput Experimental Approach to Discovering Novel Amorphous Alloys
- Jason Hattrick-Simpers, National Institute of Standards and Technology
13:50 - 14:10
14:10 Machine Learning for Automated X-ray Scattering Experiments - Kevin Yager, Center for Functional Nanomaterials
Machine Learning for Automated X-ray Scattering Experiments
- Kevin Yager, Center for Functional Nanomaterials
14:10 - 14:30
14:30 Extracting Nanoscale Details from X-ray Absorption Data by Supervised Machine Learning - Janis Timoshenko, Stony Brook University
Extracting Nanoscale Details from X-ray Absorption Data by Supervised Machine Learning
- Janis Timoshenko, Stony Brook University
14:30 - 14:50
14:50 Coffee Break (Included) and Group Photo
Coffee Break (Included) and Group Photo
14:50 - 15:10
15:10 Combining Atomistic Modeling and Machine Learning for Co-refinement of x-ray and Electron Characterization Data - Maria Chan, Argonne National Laboratory
Combining Atomistic Modeling and Machine Learning for Co-refinement of x-ray and Electron Characterization Data
- Maria Chan, Argonne National Laboratory
15:10 - 15:50
15:50 X-ray Spectroscopy Theory, Data Base Mining, and Bayesian Analysis - John Rehr, University of Washington
X-ray Spectroscopy Theory, Data Base Mining, and Bayesian Analysis
- John Rehr, University of Washington
15:50 - 16:10
16:10 Prospects for Elucidating Reaction Mechanisms via Adaptive Transient Kinetics Experiments - Andrew Medford, Georgia Tech
Prospects for Elucidating Reaction Mechanisms via Adaptive Transient Kinetics Experiments
- Andrew Medford, Georgia Tech
16:10 - 16:30
16:30 Coffee Break
Coffee Break
16:30 - 16:40
16:40 The Materials Project: Conception to Confirmation in a Virtual Lab - Shyam Dwaraknath, Lawrence Berkeley National Laboratory
The Materials Project: Conception to Confirmation in a Virtual Lab
- Shyam Dwaraknath, Lawrence Berkeley National Laboratory
16:40 - 17:10
17:10 Data Management and Data-Enabled Research at NIST - Robert Hanisch, National Institute of Standards and Technology
Data Management and Data-Enabled Research at NIST
- Robert Hanisch, National Institute of Standards and Technology
17:10 - 17:40
17:40 Provenance-enabled Sample Measurements and Tracking for Multi-modal Analysis and Predictive Synthesis - Line Pouchard, Computational Science Initiative
Provenance-enabled Sample Measurements and Tracking for Multi-modal Analysis and Predictive Synthesis
- Line Pouchard, Computational Science Initiative
17:40 - 18:00
18:00 Summary and Discussion
Summary and Discussion
18:00 - 18:30