| About this Abstract |
| Meeting |
2025 TMS Annual Meeting & Exhibition
|
| Symposium
|
Novel Strategies for Rapid Acquisition and Processing of Large Datasets from Advanced Characterization Techniques
|
| Presentation Title |
Characterization within an Automated Lab for Solid State Synthesis - Challenges and Solutions for Data Handling and Interpretation |
| Author(s) |
Anubhav Jain |
| On-Site Speaker (Planned) |
Anubhav Jain |
| Abstract Scope |
While much discussion around automated labs is centered around the ability to plan and perform synthesis tasks, more attention is needed to the characterization end of automation. Because the interpretation of characterization data is a more open-ended task than performing synthesis operations, it presents unique challenges for automation. In this talk, I will first talk about data handling and management for x-ray diffraction and scanning electron microscopy data in the context of the "A-lab", an inorganic powder synthesis facility located at Lawrence Berkeley National Laboratory that incorporates robotic handling. Data handling considerations are extremely important to ensure future reproducibility and re-interpretation of results. In the second portion of the talk, I will speak about our latest efforts to enable both automated and accurate interpretation of characterization results. Finally, I will present broader perspectives on the future of the field. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Characterization, Computational Materials Science & Engineering, Machine Learning |