Engineering Student Shares Insights from a Semester at Los Alamos National Laboratory

Zhiqin Huang

Zhiqin Huang, a doctoral student in Electrical and Computer Engineering at Duke’s Pratt School of Engineering, received a grant to spend time at the Center for Integrated Nanotechnologies at Los Alamos National Laboratory in New Mexico. By leveraging the lab’s cutting-edge facilities and other resources, she aimed to gain skills and knowledge to inform her dissertation on novel nanostructures to develop extremely low-energy and ultrafast plasmonic switches.

Huang was among 19 graduate students from five schools at Duke who received Graduate Student Training Enhancement Grants in 2016 for training beyond their core disciplines. Her faculty mentor was David R. Smith. She shared this update.

Thanks to the GSTEG, I had a chance to visit Los Alamos National Lab (LANL) for a half year. Located in New Mexico, it is probably the most famous federal government laboratory and well known for decades due to the development of the first atomic bomb and research in multiple disciplines.

During this visit, I obtained a comprehensive training including hands-on laser training, electricity safety training, cryogen safety, radiological training, chemical safety, hazardous waste and environment management as well as lab management trainings.

Since I needed to go to Sandia National Lab (SNL) to do experiments, I got various related training there on different high-tech fabrication tools such as JEOL EBL (E-beam lithography) and ALD (Atomic layer deposition). I also learned how to make graphene, which is a very interesting 2D material. All these trainings were very helpful to my research in LANL and at Duke.

The main purpose of the visit was to learn optics-related experiment techniques. I had a chance to work with scientists in the laboratory for ultrafast materials and optical sciences (LUMOS). In particular, I got involved in the optical ultrafast pump-probe experiments to investigate new materials such as Weyl’s metals and Dirac materials. I also learned the Terahertz (THz) pump and optical probe system.

Based on the rich resources in the national lab, I even built a new pump-probe system independently and did a group of experiments using newly fabricated samples and obtained primary results.

In addition, I attended the training for a newly developed optical system known as scattering-type scanning near-field optical microscopy (s-SNOM), which includes AFM, nano-FTIR, nano-imaging and ultrafast pump-probe with the spatial resolution of 10nm and temporal resolution of 10fs. This incredible experience will be essential when we build our own system at Duke in the near future.

Furthermore, I attended several LANL internal forums related to nanooptics as well as invaluable seminars given by researchers in the lab and invited scholars. Through discussions with some talented experts in the field of my research, I gained a much better understanding on both theory and experiments.

This internal funding mechanism from the Office of the Vice Provost for Interdisciplinary Studies encourages graduate students to step away from their core research and training to acquire additional skills, knowledge or co-curricular experiences that will give them new perspectives on their research agendas. Graduate Student Training Enhancement Grants are intended to deepen preparation for academic positions and other career trajectories.

Read about other 2016-2017 recipients’ experiences:

Engineering Doctoral Student Teaches Undergraduates about the Power of Data Science

Chris Tralie wasn’t even working with big data when he came to Duke as a graduate student. But a movement gaining steam here in 2013 helped him realize he had the technical skillset to reveal structures and patterns where others saw chaos—or nothing.

“There were people working on Big Data problems in various departments when I first got to campus,” said Tralie, a doctoral candidate in electrical & computer engineering (ECE) and a National Science Foundation Graduate Research Fellow. “Then the Information Initiative at Duke launched. It was brilliant because it brought everyone together and let them learn from each other’s work. There was real and sudden excitement in the air.”

Tralie found his niche while learning about topology with John Harer, a professor of mathematics with a secondary appointment in ECE. The class boiled down to understanding the “shape” of data. Tralie thought, “Why can’t we do this with music?”

Tralie designed a program that analyzes many different musical parameters of a song and mathematically reduces each time point into 3D space. The resulting shape can help determine which genre of music a song belongs to and can even recognize covers of songs by other bands.

“Nobody thought you could do that, because of the differences in vocals and instruments,” said Tralie.

Tralie took his own academic journey and used it to turn other Duke students on to big data—creating a “Data Expedition” using his method for visualizing songs as a fun and approachable way to teach undergraduates how to design data-crunching algorithms.

Data Expeditions and Data+ both benefit our undergraduates by making technical subjects more relevant and exciting, but they’re also professional development opportunities for our graduate students.

Data Expeditions are projects proposed and taught by graduate students within the context of an existing undergraduate course. “Data Expeditions and Data+ both benefit our undergraduates by making technical subjects more relevant and exciting, but they’re also professional development opportunities for our graduate students,” said Robert Calderbank, director of iiD, which sponsors both programs. “Industry and academia both need people who can lead projects and manage multidisciplinary teams, so these experiences can provide a competitive advantage for Duke graduates.”

“The Data Expeditions were really useful for me growing as a mentor,” said Tralie. “I got to work with really talented students who were still learning the basics and yet had amazing new ideas that I could learn from too. Those skills will translate to my future career, where I hope to be a faculty member advising graduate students of my own someday in engineering or applied math.”

He also developed a new course for graduate students about using data analytics on video recognition challenges, like tracking heartbeats from video clips. Tralie’s own promising work in that arena can potentially add another element to an app developed to recognize signs of autism by another of his advisors, Guillermo Sapiro, the Edmund T. Pratt, Jr. School Professor of Electrical and Computer Engineering.

After defending his dissertation this spring, Tralie plans to stay in academia, at least in part because he loves the teaching experiences he has had while at Duke.

“Mentoring and teaching forces me to explain my work in simple terms, which raises my own understanding of it,” said Tralie. “Plus the students all end up going out and doing their own interesting things, which they can later teach me about in return. They’re like my eyes and ears out there in the fast developing world of Big Data.”

 

By Ken Kingery; originally posted on the Pratt School of Engineering website

Photo: Chris Tralie with advisors John Harer (Math) and Guillermo Sapiro (ECE)