WHAT THEY LEARNED: Avi Bregman ’14

Chemistry major Avi Bregman’s thesis, “Charge Transport Properties of Doped Nanographene Bowties,” picked up where his former classmate, Jennifer Whealdon, left off with her own thesis research a year before.

Chemistry major Avi Bregman picked up where his former classmate, Jennifer Whealdon ’13, left off in her research last year. His thesis, “Charge Transport Properties of Doped Nanographene Bowties,” expanded a project Whealdon previously worked on for her own thesis.

Bregman, who will start a Ph.D. program in materials science and engineering at the University of Michigan in the fall, chose Assistant Professor of Chemistry Joshua Schrier as his thesis advisor because he wanted some exposure to computational chemistry. “I did not have a background in computer science, coding, [or] programming before I started working with Josh,” says Bregman. “But I started in the summer before senior year and he and the other students in the lab helped me get the hang of it. After the initial learning phase, I still struggled a little because a lot of the information and techniques were new to me, but whenever I needed his help, Josh would sit down with me.”

 

What did you learn working on your thesis?

As far as techniques go, I learned a good bit of coding in a few different languages as well as a good amount of chemistry. I think my biggest takeaway is that research is really tough sometimes. In, fact, it is that way most of the time. I really enjoy challenging myself, and I learned that I really enjoy the challenge of research. There were so many times when I really wanted to not do my work, not because I was lazy, but because I felt like I would never succeed. But if you spend enough hours thinking and plugging away, eventually something works, and that is an amazing feeling.

What are the implications for your thesis work?

The main point of my thesis was trying to develop a good tool for analyzing a specific property related to charge transport in organic electronic devices. This is important for people who try to minimize the cost of researching new molecules or systems by performing computational studies before actually trying to create or fabricate the device in question. I am going to make all of my code public so that in the future researchers can use my tool in their own studies to hopefully further their research.

 

“What They Learned” is a blog series exploring the thesis work of members of the Class of 2014.