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Kevin Dressler

Publications and source records attributed to Kevin Dressler.

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An Automated Magnetron Sputtering Chamber for Ferroelectric Thin Film Deposition

Optimization of next-generation materials synthesis and manufacturing processes can be accelerated by effective use of digital datasets. However, a majority of existing custom research infrastructure, including that for thin film deposition, is primarily manually operated and not compatible with this new research paradigm. Here, a template is provided for upgrading existing manual deposition chambers to enable automated and autonomous experimentation. As an example, the upgrade of an existing magnetron sputtering chamber dedicated to synthesis of wurtzite ferroelectrics is presented. Focus is placed on automation of instrumentation; system and deposition control; and synchronized and automated data collection strategies. An example use case of the system for semi-autonomous determination of process-property relationships is presented, specifically minimization of coercive field in wurtzite Al$_{1-x-y}$Sc$_x$B$_y$N thin films.

cond-mat.mtrl-sci

Lifetime Sample Tracking (LiST): A Data Platform for Materials Science

The 2D Crystal Consortium Materials Innovation Platform (2DCC-MIP) is an NSF supported national user facility focused on advancing the synthesis of 2D materials, monolayers, surfaces, and interfaces. The need for the facility to organize and share data with users led to the development of an internal data management and analysis engine, the Lifetime Sample Tracking platform (LiST). This infrastructure allows the automated capture, curation, analysis and dissemination of data ranging from experimental materials synthesis parameters and characterization, to theoretical first-principles and ReaxFF molecular dynamics modeling1. The system currently hosts synthesis and property data (accessible via a REST API) on approximately twenty thousand samples produced by the 2DCC grown using a variety of techniques from bulk crystal growth to metal-organic chemical vapor deposition (MOCVD) and molecular beam epitaxy (MBE), among others. Data used in publications can easily be grouped by the system into data packages that are given digital object identifiers (DOIs) for inclusion with each publication. The LiST platform is now being used by groups outside of the 2DCC as a solution for data curation in materials science. Data management tools such as LiST support the materials development process by allowing a closed loop iteration between synthesis, characterization, theory, and targeted materials design. This also enables machine learning (ML) research, artificial intelligence (AI) analysis, and the potential for autonomous synthesis in the future.

cond-mat.mtrl-sci