W2D2S2 - High-throughput Materials Synthesis in Atomic Layer Processing



Online Via Zoom


The Western Washington Data-driven Discovery Seminar Series (W2D2S2) is hosting a series of events in partnership with Pacific Northwest National Laboratory again this Fall on Thursdays from 3:00-4:00pm! Please keep an eye out and email w2d2s2organizers@gmail.com for the zoom invite link!

Keynote Speaker: Professor David Bergsman, University of Washington

Title: High-throughput Materials Synthesis in Atomic Layer Processing

Abstract: Recent years have seen a surge of interest in the development of scalable tools for nanomaterials synthesis. Many emerging technologies, like solar cells, batteries, catalysts, and membranes, rely on atomically-precise materials design to operate effectively. Tools for creating these materials with increased scalability and decreased costs are thus required to enable the widespread adoption of these technologies. One suite of tools, known collectively as atomic layer processing (ALP), is particularly interesting for nanomaterials synthesis, due to its ability to create ultrathin films with sub-nanometer thickness and compositional control. ALP has also been used in the semiconductor industry over several decades, making it easy to deploy in other manufacturing processes. Commercial solar panels and battery electrodes have already started to incorporate ALP-deposited films as passivation layers. However, as demand for nanotechnology increases, there is a continued need to expand the library of materials that can be made with these tools and to accelerate the pace with which these materials are deployed. This presentation will highlight how the Bergsman Research Group at the University of Washington is expanding the applicability of ALP by creating new processes with higher-throughput screening tools. We will describe some of the use cases of ALP in semiconductor processing, catalysis, and membrane separations, along with the challenges associated with making new materials processes with these tools. Then, we will discuss existing methods for more rapid deployment of new processes. Finally, we will discuss our work to speed up materials development using a high-throughput reactor, along with our efforts to implement a connected data pipeline for easier analysis of process parameters.

Bio: David Bergsman (he/him) is an Assistant Professor in the Department of Chemical Engineering at the University of Washington. He received his B.S. in Chemical Engineering from the University of Washington in 2012 and his PhD in Chemical Engineering from Stanford University in 2018 under the mentorship of Prof. Stacey Bent. He later completed postdoctoral work at the Massachusetts Institute of Technology with Prof. Jeff Grossman. Now, at UW, his research is focused on using ultrathin films and coatings to tackle challenges in energy, water, sustainability, and semiconductor processing.

Keynote Speaker: Dr. Steven R. Spurgeon, Pacific Northwest National Laboratory and University of Washington

Title: Welcoming our AI Overlords: Operationalizing Machine Learning for Materials Discovery and Design

Abstract: Artificial intelligence (AI) promises to reshape scientific inquiry and enable breakthrough discoveries in areas such as energy storage, quantum computing, and biomedicine. While it is now possible to produce nanomaterials in almost limitless configurations, engineering of desirable functionality depends on precise control of atomistic structure and defects. Complex synthesis pathways can lead to significant deviations from idealized structures, which occur at length scales that are challenging to probe experimentally and theoretically. Mastery of materials is therefore predicated on the ability to acquire and interpret complex, heterogeneous, and fast-evolving data streams, a task uniquely suited to emerging AI and machine learning methods. Here I will discuss our efforts to develop a new framework for materials discovery in the electron microscope, leveraging low-level system automation, domain-grounded data pre-processing, and emerging sparse data analytics to extract truly statistical insights. I will discuss the current and future potential of this platform to both unlock experimentation at scale and derive richer, more meaningful physical models for important material systems.

Bio: Dr. Steven R. Spurgeon is a research scientist in the Energy and Environment Directorate at Pacific Northwest National Laboratory, with an affiliate appointment as an Associate Professor of Physics at the University of Washington. He serves as thrust lead for PNNL’s Chemical Dynamics Initiative and an editor of the international journal Microscopy and Microanalysis. His work focuses on developing artificial intelligence and machine learning approaches to accelerate the synthesis, characterization, and modeling of nanomaterials for next-generation electronics, quantum computing, and energy storage. He has published over 65 journal articles and book chapters and has received awards from the U.S. Department of Energy, the National Science Foundation, the Materials Research Society, the Microscopy Society of America, and the U.S. Department of Defense. Prior to joining PNNL, he received his Ph.D. in Materials Science from Drexel University and his B.S. in Materials Science from Carnegie Mellon University.

See our W2D2S2 website for more information

Please email w2d2s2organizers@gmail.com for the zoom invite link!


The Fall 2022 W2D2S2 Organizing Committee

Sarah Akers, Ying Bao, Stefan Dernbach, Brian Hutchinson, Tim Kowalczyk, Kimihiro Noguchi, Mohammad Taufique