The Advanced Photon Source
a U.S. Department of Energy Office of Science User Facility

APS Scientific Computation Seminar Series

Sessions will normally be held on the 3rd Monday of the month at 1:00 p.m. and last approximately one hour.

This seminar series focuses on scientific computation for APS experiments. The series focuses on advanced software and computing infrastructure for analysis, reduction, reconstruction, and simulation. It provides an opportunity to learn about state-of-the-art computational techniques and tools and how they are being applied to science at the APS. It will start with talks from Argonne staff who are working on projects in collaboration or in support of APS science.

Next Seminar:
Title: Panoramic Synthesis
Presenter:  John Mitchell, Senior Scientist and Interim Director, Materials Science Division, Argonne National Laboratory
Date: February 12, 2019
Time: 1:00 p.m.
Location: 401/A1100

A notable ‘synthesis gap’ exists between what we can now predict with exceptional speed and fidelity (i.e., MGI approaches) and our ability to create these targets in the laboratory. Although high-throughput synthesis is well-established as a technique for optimization, and is now bringing AI/ML to bear in autonomous systems, the underlying synthetic approaches—solid state reaction, flux growth, vapor deposition, etc.– are largely unchanged for decades. A re-imagining of how we discover materials and synthesize them is needed to bridge the synthesis gap; panoramic synthesis bolstered by AI/ML presents one such new pathway to synthesis by design. In this computationally-guided approach to synthesis science, in situ and operando approaches will be leveraged to reveal the fundamental mechanisms of how materials and molecules assemble from atoms or complex building blocks. Multimodal approaches that capture structural and/or electronic signatures will be integrated through ML to create models of the synthesis mechanism itself. Ultimately, responsive, on-the-fly approaches to steering reaction pathways may be achievable in a feedback loop.

Previous Seminars:

20192018 | 2017 | 2016 | 2015