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Collaborating for clean tech

Theodore Cohen

Collaborating for clean tech

This Q&A was originally published by the UW Molecular Engineering & Sciences Institute (MolES). Ted Cohen is a 4th year molecular engineering (MolE) Ph.D. student co-advised by chemistry professor Daniel Gamelin and materials science & engineering professors Christine Luscombe and Devin MacKenzie. MolES recently caught up with Cohen about his research and his experience in the MolE Ph.D. program. 

January 24, 2020

What brought you to the molecular engineering program at UW?

Originally, I planned to get a job after college that would utilize my undergraduate degree in chemical engineering. I looked into some positions at big oil companies, but quickly realized that their values and beliefs were at odds with my own. This led me to think about clean energy. I saw that much of the innovation in this space was coming out of universities, so I applied to grad school. While applying to the chemical engineering Ph.D. program here at UW, I learned about the MolE program. The MolE program’s focus on clean tech research was a great fit with my interest in clean energy.


How do you define molecular engineering?

In my view, molecular engineers seek to understand fundamental aspects of materials at a molecular level. Using this knowledge, molecular engineers attempt to design, from the bottom-up, new materials that preserve and exploit those unique properties for various real-world applications. Molecular engineering encompasses many different disciplines from chemical engineering and materials science, to basic science disciplines like chemistry and physics. Through the MolE program, I’ve learned to translate insights gained from basic research towards applied, engineering problems.


Tell us about your research.

My research involves perovskite nanocrystals. Clean energy scientists are especially interested in developing solar materials made of perovskite nanocrystals because they are excellent at converting light and are cheap to produce. Unfortunately, perovskite nanocrystals are not yet commercially viable in part because their inherent chemical instability leads them to degrade. I am working to develop a new method to effectively disperse and stabilize perovskite nanocrystals in a solid polymer for use in a variety of real-world applications.

One application we’ve looked at is luminescent solar concentrators (LSCs). LSCs are large, window-like devices made of a transparent piece of plastic or glass with florescent dyes or quantum dots embedded in it. They collect diffuse solar radiation and concentrate it at the edges of the device to generate electricity. To get these devices to work, we need a material that can absorb as much of the solar spectrum as possible and transfer that energy to silicon solar cells attached at the device edges. This increases the power generated by the solar cells.

In addition to LSCs, we are interested in using these materials for light-emitting diodes (LEDs), low energy, color specific lasers, and as photon sources for quantum computing.


You have three advisors! How has this impacted your research?

Having three advisors has really benefited my research because each advisor has unique, but related, expertise. My project initially focused on characterizing perovskite nanocrystals made in the Gamelin lab. Based on this research, we filed a patent for a novel LSC design. To use this material for other applications, we needed to find the right polymer to suspend and stabilize the material in a device. So, I worked with the Luscombe lab to develop a custom polymer that is compatible with perovskite nanocrystals. Now we are turning to the MacKenzie lab to figure out how to best process these materials using the printing resources available at the Washington Clean Energy Testbeds. I don’t think a collaboration like this would have been possible outside of molecular engineering. The great thing about this program is that you aren’t restricted to working with advisors from just one department. You really have the flexibility to follow your interests and facilitate new collaborations.


People in colorful shirts in front of a fountain

The Gamelin lab at the University of Washington.

Your advisors are all part of the Clean Energy Institute (CEI). What role has CEI played in your research experience at UW?

CEI is a big reason I decided to come to UW. As a molecular engineer focused on cleantech, I’ve used CEI resources and the research tools at their Testbeds facility quite frequently. I’ve also been able to tap into the CEI network by attending their seminars and biennial Orcas Conference and participating in their data science training program.


You mentioned you were a CEI DIRECT Data Science Trainee. Why was it important to you to gain data science skills?

From a practical research perspective, being able to manipulate complex data sets has made processing my data much faster and has substantially accelerated my research. I’ve also found that this skillset has helped me visualize my data better and communicate my science more clearly. I think data science skills will be useful when I’m looking for a job one day. Whether or not my role calls for these skills, it’s likely I’ll be working with data scientists, so understanding the things they care about – like decision trees and neural networks – will be beneficial.


You are a graduate professional and student senator. Why did you get involved?

At the start of the Trump administration in early 2017, a colleague reached out asking whether students at UW wanted to sign on to a letter to congress imploring them to ensure leaders of agencies – like the Environmental Protection Agency and Department of Energy – had an appreciation for science. I worked with our student representative at that time, MolE alum Grant Williamson, to get a resolution passed to allow GPSS to sign on to that letter. The experience inspired me to become a student senator myself. It has been a great opportunity to help shape the broader graduate student experience at UW.


What do you want to do next?

At this point, I’m torn between academia and industry. Luckily, I still have some time to figure it out! If I go the academic route, I will look for a postdoctoral fellowship where I can apply some of the machine learning techniques I’ve learned to fundamental chemistry problems. Otherwise, I’m interested in an industry position that directly applies the cross-disciplinary skills I’ve acquired through the MolE program.


To learn more about the MolE Ph.D. program, visit