Barrett Hicks

Senior Material Scientist at Applied Materials

Based in San Francisco, United States

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Seniority

Staff

Department

Science

Location

San Francisco

Industry

Semiconductor Manufacturing

Company size

30K

Contact information

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Email

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b•••••••@appliedmaterials.com

Phone

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Background

About Barrett Hicks

I build new capabilities by a thirst for growth and development. My joy is asking the right questions and learning new ways to think. In recent years, as a senior material scientist and hardware engineer in the semiconductor industry, I embraced the challenges. The rapid pace of serving multiple project teams in parallel encouraged me to develop new abilities. As a result, concept and feasibility projects under my ownership quickly developed into tangibles that directly helped the pivotal timelines of strategic products. The problems placed in front of me are best described as hardware challenges for new processes pathways needed to enable the next semiconductor technology nodes. Extremely small printed features may not have known ways to either deposit or etch away materials to the necessary specifications. Other times, it is too costly to re-designing all of the complex internal hardware of fabrication systems. From the high-level architecture down to alloy compositions of individual components there are dependencies that may not even be known when new processing chemicals or combinations of existing chemicals are introduced. Iteratively upgrading and validating hardware is costly, time-consuming and often limited in effectiveness by the choices of off-shelf alloys. A better way, in principle, is to preserve existing design architectures and customize properties at the surface for each application by coating materials. In practice, coating solutions are limited by the methods of deposition and the ability to serve all impacted hardware, including 3-dimensionally-complex and sensitive substrates. New coating technology needed to be invented and developed. Each composition type can have more than one method that has unique process characteristics and limited predictive modeling from existing reference data. Methods such as CAD designing, finite element simulation, image processing with machine learning etc. needed to persuade other teams to join the effort. So I learned how to make proposals for collaborations. The developed methods of hardware, physical models, chemical sensors and metrology work together in a seamless top-down approach to quickly achieve well-controlled results and customizable for serving any type of hardware system. Minimal experiments are required to scale up test processes. Key products needing rapid adaption to new processes and market shares are able to shift with upgrades to entire hardware systems without redesign. Several patents are pending. I not only enjoy the work but look to inspire others to enjoy their work.

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