The Fall 2021 MatSE 590 for graduate students consists of an exciting and jam-packed schedule. MATSE 590 is a colloquium (1-3 credits) consist of a series of individual lectures by faculty, students, or outside speakers.
Graduate students will receive a weekly email with information via @psu.edu email. Graduate students are required to attend all 590 Seminars. If you have any questions, please email Hayley Barnes at firstname.lastname@example.org.
*Due to the ongoing Covid Pandemic this program is being offered virtually through Zoom. Please reference the weekly email from Hayley Barnes (email@example.com) for Zoom link.
Tuesday, November 9, 2021
“Understanding Material Growth Using Atomic Layer Deposition”
Angel Yanguas-Gil, Principle Materials Scientist at Argonne National Laboratory
Atomic layer deposition has become a key technique for applications such as microelectronics, energy storage, and catalysis. Based on self-limited precursor -surface interactions, one of its enabling capabilities is that it is intrinsically conformal, allowing the growth and infiltration of high aspect ratio and nanostructured materials. In this talk I will focus on how the combination of in -situ techniques, simulation and theory, and co-design approaches can help accelerate the development of new materials and processes and their transition to manufacturing and microelectronic applications.
I will first explore two fundamental questions of ALD and growth at low temperatures: the evolution of microstructure and emergence of crystallinity during the early stages of growth, and the active control of precursor-surface interactions to drive growth toward desired phases or configurations. Insights gained from these studies have directly led to the design of materials with controlled distribution of dopants, to small inhibitor approaches to area selective deposition, and to the use of surface relaxation as a key to stabilize the low temperature growth of novel materials. These studies have also led to the development of general models that can predict the performance of ALD processes under relevant manufacturing conditions, from growth on nanostructured substrates and 300 mm wafers to scale up using chemical engineering approaches such as roll to roll and fluidized bed reactors, based just on just a few key observables.
I will then introduce on how we are currently using co-design approaches that leverage machine learning and emulation to quickly explore the integration of these novel materials into simple architecture. As an example of this approach, I will focus on the case of architectures inspired on the insect brain capable of extending computing to temperatures exceeding 300 C for on-chip processing of digitally modulated RF signals.
Angel Yanguas-Gil is Principal Materials Scientist at Argonne National Laboratory, where his research focuses on exploring the fundamentals of thin film growth using techniques such as atomic layer deposition as well as architectures for neuromorphic computing and edge processing applications. He obtained his PhD in Physics at the University of Sevilla in Spain in 2006, and after being a postdoctoral researcher at Ruhr University in Germany and at the University of Illinois
at Urbana-Champaign, he joined Argonne National Laboratory as an Assistant Materials Scientist in 2009. In 2013 he became Principal Materials Scientist. He also became Fellow of the Northwestern-Argonne Institute for Science and
Engineering at Northwestern University. Dr. Yanguas-Gil was the Program Chair of The Thin Film Division of the American Vacuum Society for 2021 and he just became the Chair of the Division. He is also member of the organizing and program committee of the Electronic Materials Conference, and member of the program committee of the International Conference on Atomic Layer Deposition and the International Conference on Neuromorphic Systems.