FOM Talks:

Ethan Schwartz, Mechanical Engineering Ph.D. Candidate at UW

FOM Talks:

Ethan Schwartz, Mechanical Engineering Ph.D. Candidate at UW

From research to innovation: Enhancing slot-die coating with AI and custom-engineered tools

At the intersection of advanced materials research and innovative engineering, Ethan Schwartz, a Ph.D. candidate in Mechanical Engineering at the University of Washington, is a familiar face at the Washington Clean Energy Testbeds (WCET). The testbeds are part of the Institute of Clean Energy and are located right next to the University Village, in the vicinity of Washington University in Seattle. WCET is a tiny hub of PhD students, researchers, and start-ups gathered under the same roof together with a lab filled with state-of-the-art R&D instruments for the testing and design of energy devices and systems.

Ethan is in his fourth year of PhD research, and with a keen focus on optimizing coating processes for solar and battery applications, his work highlights the potential of integrating automation, AI, and customized hardware into thin-film research.

Ethan’s background – As a PhD student and research assistant at the University of Washington, Ethan specializes in mechanical engineering with a focus on photovoltaics and data science. His passion for renewable energy drives his commitment to solving complex problems and developing innovative solutions for a sustainable future. His expertise lies in optimizing solar technology and scaling up manufacturing processes, aiming to make renewable energy more accessible and efficient.

The birth of a smarter air knife

One of Ethan’s key innovations is a re-engineered air knife system for drying coated films with enhanced precision. Originally, the air knife was hard-mounted, limiting the ability to adjust drying parameters beyond basic air pressure control. Recognizing the need for greater flexibility, Ethan developed a new system mounted on a three-axis motorized platform, allowing for adjustments in angle, temperature, and pressure.

This system not only enhances the control over solvent drying but also integrates potential machine-learning capabilities. “Depending on the type of solvents you have, they might have different volatilities,” Ethan explains. “You might want to dry later in the coating process versus earlier.” By integrating in-situ sensors and cameras, the system aims to optimize drying conditions dynamically, reducing human trial-and-error.

FOM AlphaSC

Machine learning and coating optimization

Ethan’s work extends beyond hardware improvements. He is actively incorporating machine learning into the coating process to address the vast number of variables researchers must consider, such as coating speed, flow rate, temperature, concentration, humidity, and more. “There are potentially trillions of combinations, and one-variable-at-a-time sampling is too slow,” he explains. “Machine learning can optimize conditions far more efficiently.”

The goal is to create an adaptive system where AI analyzes real-time data and adjusts parameters to achieve the best coating quality. This would be particularly useful for new materials, allowing researchers to determine optimal settings faster than ever before.

The role of FOM Technologies’ equipment

Ethan has primarily worked with FOM alphaSC coater, a tool he values for its mechanical adjustability and precision. “It’s a great tool. It’s exciting to be able to print solar panels at scale, and the manual adjustments make it a fantastic R&D platform,” he shares. “I really appreciate the micrometer control of heights, the fine increments of coating speed, and how reproducible the results are.”

When asked if FOM Technologies’ equipment has helped scale up their research, Ethan is confident. “Absolutely. That’s our whole goal. We’ve successfully taken multiple spin-coated recipes, and then slot-die coated them with very little loss in efficiency,” he shares. “It’s made scaling up much easier and more consistent.”

Clean Room

Ethan’s work spans beyond perovskites and WCET

“Most of my time has been focused on perovskite materials, but recently I’ve started coating battery materials as well,” he says. “Batteries are way easier to coat because they are so much thicker, and you can visually see what you are coating. With solar panels, especially those using transparent materials, it’s harder to know if the coating is working without taking it off the line and inspecting it. With battery materials, you can see the changes immediately, which simplifies the process significantly.”

His vision extends beyond individual labs. “We’re developing a shared database of input parameters and machine-learning algorithms to standardize and improve coating outcomes across different research groups. This will enable scientists to reproduce results with greater accuracy and efficiency, no matter where they are.” One of Ethan’s projects is called MOBO-Kit, an open-source toolkit for accelerating the design of experiments via multi-objective Bayesian optimization. The toolkit was developed collaboratively across the University of Washington, UC San Diego, and MIT, and though it was from the start set for slot-die coating experiments, it can be used for other multi-objective optimization problems.

As he continues his research, Ethan remains enthusiastic about the potential of FOM Technologies’ equipment to evolve alongside these advancements. “The modularity of FOM’s tools is a major advantage. If we, for example, need custom drying setups or additional sensors, we can integrate them seamlessly.”

With researchers like Ethan—whose interests expand across material science, software, and hardware—leading the charge, the future of materials coatings looks increasingly automated, efficient, and adaptable, bridging the gap between cutting-edge research and real-world applications.

WCET and FOM Inc. – Pioneering innovation under one roof

The Washington Clean Energy Testbeds (WCET) is a leading hub for cutting-edge research in clean energy technologies. Located under the same roof as FOM Inc., our U.S. subsidiary, WCET is heavily invested in FOM’s state-of-the-art machinery. From the FOM alphaSC and FOM alphaR2R slot-die coaters to the versatile FOM moduloR2R systems with both slot-die coating and flexographic printing capabilities, WCET utilizes these advanced tools to drive innovation in energy storage, solar, and other functional material applications.

In addition to these capabilities, WCET will open a brand-new battery lab in 2025, with the FOM compact moduloR2R coater as its centerpiece, enabling further advancements in battery research and development.

Did you know that you can book our machines at the WCET? Contact us to learn more.

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