Physics students and faculty are well-represented in the College of Science 2020 Summer Undergraduate Research Experience (SURE) Awards. These awards provide 11-week employment in the summer for students, though this year, because of closures during the covid-19 pandemic, the research may have to be stretched out over the academic year.

This year’s physics student awardees are:
Hunter Nelson advised by Tuan Pham (Mathematics)
Rohal Kakepoto advised by Janet Tate
Alan Schultz advised by Hoe Woon Kim (Mathematics)
Alexander van Balderen advised by Liz Gire
Jessica Waymire advised by Matt Graham
Ryan Wong advised by Bo Sun

Students from other departments working with Physics faculty are:
Emily Gemmill, (Biochemistry & Biophysics), advised by Weihong Qiu
Ruben Lopez (BioHealth Sciences) advised by Bo Sun

Congratulations all!

Physics professor Weihong Qiu with Haelyn Epp, a BioHealth Sciences SURE awardee in 2019, in Prof Qiu’s biophysics laboratory at OSU (image from the CoS SURE website).

Drivers on OR34 now see Senior Instructor Randy Milstein smiling at them.

OSU Astronomer in Residence, Senior Physics Instructor and man-about-Corvallis Randall Milstein has been featured by Samaritan Hospital in an article and a huge billboard on OR34. See for the full article. You can meet Randy in person in Physics 104 (Descriptive Astronomy), the class he teaches to hundreds of students every term at Oregon State.

Prof. Bo Sun

In December 2019, Associate Prof. Bo Sun received the Richard T. Jones New Investigator Award from the Medical Research Foundation of Oregon for his work on the biophysics of collective behavior in cells.

For more details on the award see the MRF awards site and the longer College of Science IMPACT article about Bo’s work.

And check out his research group at to read about the successes of the large number of graduate and undergraduate students working in his lab.

Congratulations Bo!

When the novel coronavirus pandemic hit, the Physics Department, like the rest of Oregon State University, scrambled to get its course offerings ready for remote learning in a few days.  Professor David Roundy and his teaching team scrambled as hard as anyone – and incorporated some beginning epidemic modeling into the computational physics class so that the students would begin to acquire the skills that will serve them well as members of the technological community of which they are now junior members.

About the class:

PH366 – Computational Physics – is a course in which students learn how to solve mathematical equations in real-world, complex situations where analytical, “pencil-and-paper” solutions are far too difficult.  For example, it’s easy for a student in Introductory Physics to solve a simple differential equation to find a solution in the form of an equation that describes how a ball falls towards the earth under the influence of gravity, a constant force near the earth’s surface.  But add extra forces that describe real conditions like air resistance, wind and the earth’s rotation, and a simple equation to describe position as a function of time is impossible.  The computer solves the problem numerically, chopping it up into very small time slices and finding a position and velocity for each of the times based on what is was at the previous time. In the PH36x Computational Physics series, students learn techniques to find numerical solutions to many differential equations and they can explore very complex, real-world situations. Roundy has chosen the Python programming language for this class, but the lessons are applicable to any language. In real physics research, few problems are already worked out in a textbook and numerical methods to solve them improve all the time, so the best information is often distributed all over the internet. Physics students must learn to navigate the body of existing literature and identify what information they need to solve a problem.

Another view of the solution shows the difference between displaying results on a linear plot and a logarithmic plot. The logarithmic plot (below) highlights the infection and recovery numbers, which are a small fraction of the overall population and we’d be tempted to ignore the fact that there are hundreds of thousands of sick people if we saw only the linear plot (above).

An example that David Roundy chose for the Spring 2020 Computational Physics course was about the spread of an epidemic, like covid-19.  It was all everyone was talking about, and he wanted the students to learn how their new computational skills are at the heart of epidemiological modeling that gives us the information to understand and mitigate the spread of the coronavirus.  This isn’t an accurate model, Roundy stresses, but it has valuable elements – start with a simple model, probably unrealistic, test it, make sure it works as expected.  Add some complexity, test that, and then proceed. In his easy-to-read description at the PH366 course website, Roundy shows students how to model exponential growth – the increase in number of covid-19 cases is proportional to the number of cases: dI/dt = RI. Then you have to add in the real-world fact that the population is finite (with a doubling time of 1 day, the world human population would be infected in a little over a month). Some people recover and have immunity (we hope), so that must be factored into a more realistic model.  More complexity comes in when you consider how long infected people are contagious, and whether there is a period of immunity following recovery.

Actually, the problem is not too hard to set up – it’s the solution that becomes tedious.  That’s the beauty of computers is that they don’t care about tedium.  They swiftly toil through tedious calculations without becoming bored or tired and their error rate is effectively zero!  The humans have to set up the problem correctly, though, otherwise the results are meaningless.  And this is the skill that Roundy teaches his students. The screenshots below show an example of the students’ work in PH366, with the by-now-familiar plot of an exponential rise in infections at the start, with a peak and fall.  We see the basic recovery and death trends, too.

Screenshot of a student’s model of infections, recoveries and deaths due to an infectious disease

Another view of the solution shows the difference between displaying results on a linear plot and a logarithmic plot. The logarithmic plot (below) highlights the infection and recovery numbers, which are a small fraction of the overall population and we’d be tempted to ignore the fact that there are hundreds of thousands of sick people if we saw only the linear plot (above).

Linear and log plots emphasize different details

Julian Wulf, one of the Physics majors currently in PH 366 commented, “My favorite part of the class is how it allowed me to model physical situations that were too complex to picture, or model by hand. I have found it quite rewarding to finish coding something and have it modeled in front of me, a model that is often easy to adjust to new circumstances.” It’s easy to see how Julian would relish the challenge of modeling a much more complicated solution that factored in even more complexity such as social contact and real transmission rates. 

Teaching in the age of coronavirus:

To deliver PH366, David Roundy goes into Weniger Hall by himself every Tuesday and Thursday and turns on some 20 computers with separate Zoom sessions running (see the panorama view below).  The 40 students and the 4 TAs (teaching assistants) log in from their remote locations. The students implement Roundy’s “pair programming” strategy where they decide how to solve the problem and code in pairs, each providing the crucial check on the other to ensure that the steps make sense.  They constantly question their results, and look up techniques to improve their code and to interpret the results. It’s a real-world programmer situation!  Roundy and the teaching assistants hop between the Zoom breakout rooms to discuss with each pair of students how to troubleshoot and debug their code.  It wasn’t easy for the instructors to change their mode of operation from in-person to remote learning. TA Elena Wennstrom comments, “At the beginning, our TA meetings were devoted to brainstorming possible class formats, testing the limits of our Zoom powers, and discussing issues and possible improvements to the class we had the day before. Now we are more able to focus on the content, and trying out the assignments ourselves (like usual). I’m really proud of the system we’ve developed. Classes go surprisingly smoothly, and the time flies.”  Wennstrom adds that she gets more and better questions from the students in the remote mode.  Roundy remarks that he will offer this new mode of teaching to students with seasonal influenza in “normal” times to help curb the spread of that particular virus.

A panoramic view of the computers in the PH366 classroom in Weniger Hall

The students’ response:

The students agree. Julian Wulf says, “I think the transition to remote learning has mostly gone smoothly. There has been a rapid increase in how well things are being communicated remotely, as well as an increasing ability of the teaching assistants and professor to respond to difficulties we encounter while programming. I find myself looking forward to the continued improvement as each class has run more smoothly than the last, with the teaching assistants and Professor Roundy being increasingly able to react to difficulties people encounter by jumping in and out of Zoom breakout rooms to help.”

As “newbie programmer”, Wulf feels that the pair programming method helped him get over an initial fear of programming, and that he has learned to appreciate how quickly he learns to solve new problems. He found the disease and epidemic modeling project interesting, intellectually stimulating and fun.

Wulf says that the coding skills he is developing will be useful in the future, and that they have already entirely changed his perspective.  He now routinely plots equations in Mathematica to visualize a physical situation, and his new skills make the task “pain-free” and fun rather than being as a dreaded chore.

Former Physics major John Waczak, now a graduate student in Physics at the University of Texas at Dallas, offers similar observations about the Computational Physics series. He says that Computational Physics is an incredibly powerful tool for building physics understanding and to tackle problems that are otherwise unsolvable. It also enables him to create detailed visualizations of just about anything, and those visualizations don’t have to be static! Computers makes it possible to manipulate 2-, 3-, and even 4-dimensional data and create animations. “I have been using this skill a lot lately to visualize results in my [graduate] classes,” he says. Waczak further appreciates that PH36x made him an autodidact. “Dr. Roundy encouraged us to become familiar with the documentation and common programming forums like Stack Exchange. Instead of giving us working code to start with, we had to learn how to diagnose bugs and navigate the wide variety of (often incorrect) answers that exist online.” This meant that he became better programmer (and physicist). “I certainly do not know all of the tools and features that exist in the python programming language. What I do understand is how to evaluate the credibility of a resource and how to extract what’s important from the large body of existing information.” 

Prof. Roundy’s PH366 covid-19 assignment is available at
The TAs for the class are Elena Wennstron, Kira McCoy, Alex Kuepper and Steven Neiman.

David Roundy is an Associate Professor of Physics at Oregon State University, and has been teaching and researching at OSU since 2006.  His work in computational physics spans exotic superconductors, metal-organic frameworks, classical and quantum density functional theory, biological motor proteins and many other topics. He invented the Darcs version control software.  He is a member of the Paradigms in Physics team with significant funding from the National Science Foundation for education-related research focusing on thermal physics and computational physics.

Dear Physics community,

The Physics Beavers are studying remotely this quarter.

Oregon State Physics is still operating, although our labs are in standby mode and our teaching is now all remote.   We’re using online channels like Zoom and Slack to maintain our tradition of student interaction in courses.  Students are still working together on problems and the Society of Physics Students  is launching an online game night.  We could not have done this without herculean efforts by faculty and students to create online labs, videos, and sophisticated live classes in 3 weeks.  Grad students are writing new labs and undergraduates are serving as learning assistants in the Virtual Wormhole.  See this video on vectors produced in our Lightboard studio to see what our students see.

On campus, research is on standby. Biophysicists Weihong Qiu and Bo Sun led the Physics effort to collect personal protective equipment (PPE) that Oregon State then donated to Oregon Emergency Management agencies.  But, you can’t grow carbon nanotubes or cancer cell lines at home so on-campus research is now on hold.  In the short run, we can work on writing things up, doing the literature searches we never have time for and analyzing data, but we’re eager to get back to our labs. 

If you are interested in helping students financially in the short term, Oregon State has set up an emergency fund for students in need.  Many students (or their parents) have lost their jobs and are struggling with basics like books, rent,  food and the now vital internet connection. Please consider donating to the Beavers Care fund which is providing emergency funding to OSU students (You can designate the College of Science) or to the Human Services Resource Center (HSRC) which provides food boxes, loaner computers and other emergency supplies for students.  

We’ll be providing updates as things progress. 

Heidi Schellman

Physics research isn’t just for Physics majors. Biophysicist Weihong Qiu hosts students from BioHealth Sciences and Biochemistry in his lab as well.

Haelyn Epp and Weihong Qiu preparing motor protein samples in the lab.

BioHealth student Haelyn Epp used her #SUREScience scholarship to work in a biophysics lab on motor proteins. “My scholarship replaced one of my jobs, [and] allowed me to focus on research in a way I had not been able to,” says Haelyn. Read the full article at:

Prof. Bo Sun has received an NSF CAREER award for his biophysics research. Please look at the longer IMPACT article for details. (And he’s also the 2019 Richard T. Jones New Investigator Award for the Medical Research Foundation of Oregon, more details on that after the ceremony in Portland later this term.)

A belated post from last Fall:

Ethan Minot, associate professor of physics, received the Milton Harris Award in Basic Research for his impressive accomplishments as a scientist. At Oregon State, Minot has built a world-class materials physics laboratory for the study of the structure and properties of carbon nanomaterials and devices for nanoelectronics.

Ethan Minot (center) receiving the award with Prof. Janet Tate (left) and Dean Roy Haggerty (right).

His research at Oregon State has pushed the limit of fundamental properties of nanoelectronic devices, which have a broad range of applications to biosensing and solar energy harvesting. Some of his achievements are: identifying the fundamental noise mechanism that limits the performance of graphene biosensors in liquid environments; becoming the first to electrically generate and detect single point defects; reaching a new level of control over point defect chemistry; and other pioneering advances in the development of high-quality nanodevices and biosensors.

Reposted from

Scanning electron micrograph of a carbon nanotube (white filament) connecting metal electrodes (shaded yellow).

Oksana Ostroverkhova, Professor of Physics at Oregon State University, and a leading expert on organic electronics, is the editor of the  second edition of Elsevier Publishing Company’s “Handbook of Organic Materials for Electronic and Photonic Devices”.  This 911-page handbook provides an overview of the materials, mechanisms, characterization techniques, and structure property relationships of organic electronic and photonic materials and describes the latest advances in the field. Oksana selected the topics, solicited contributions from the authors, and edited the entire book. and the result, at least a year in the making, is a comprehensive overview of a quickly-developing field.

This is the second handbook that Oksana has edited. The first, “Handbook of Organic Materials for Optical and (Opto)Electronic Devices“, appeared in 2013 and was published by Woodhead Publishing.  Oksana also wrote an extensive review of her own on a related topic that was published in Chemical Reviews in 2016: “Organic Optoelectronic Materials: Mechanisms and Applications”
Chemical Reviews 116, 13279 – 13412 (2016). This review is already her most highly cited publication from her time at Oregon State University.


The Ostroverkhova group’s work on bee vision had attracted a lot of attention!

Ostroverkhova et al examined responses of wild bees to traps designed to selectively stimulate either the blue or the green photoreceptor using sunlight-induced fluorescence in the 420-480 nm or 510-540 nm region. Image credit: Rebekka D.

KATU has an interview with Oksana Ostroverkhova at:

Sci-news has an article

and there is a press release to go with their recent paper in Journal of Comparative Physiology A.

CORVALLIS, Ore. – Researchers at Oregon State University have learned that a specific wavelength range of blue fluorescent light set bees abuzz.

The research is important because bees have a nearly $15 billion dollar impact on the U.S. economy – almost 100 commercial crops would vanish without bees to transfer the pollen grains needed for reproduction.

“The blue fluorescence just triggered a crazy response in the bees, told them they must go to it,” said the study’s corresponding author, Oksana Ostroverkhova. “It’s not just their vision, it’s something behavioral that drives them.”

The findings are a powerful tool for assessing and manipulating bee populations – such as, for example, if a farmer needed to attract large numbers of bees for a couple of weeks to get his or her crop pollinated.

“Blue is broad enough wavelength-wise that we needed to figure out if it mattered to the bees if the light emitted by the sunlight-illuminated trap was more toward the purple end or the green end, and yes, it mattered,” Ostroverkhova said. “What’s also important is now we’ve created traps ourselves using stage lighting filters and fluorescent paint – we’re not just reliant on whatever traps come in a box. We’ve learned how to use commercially available materials to create something that’s very deployable.”

Fluorescent light is what’s seen when a fluorescent substance absorbs ultraviolet rays or some other type of lower-wavelength radiation and then immediately emits it as higher-wavelength visible light – think about a poster whose ink glows when hit by the UV rays of a blacklight.

Like humans, bees have “trichromatic” vision: They have three types of photoreceptors in their eyes.

Both people and bees have blue and green receptors, but the third type for people is red while the third kind for bees is ultraviolet – electromagnetic energy of a lower wavelength that’s just outside the range of human vision.

Flowers’ vibrant colors and patterns – some of them detectable only with UV sight – are a way of helping pollinators like bees find nectar, a sugar-rich fluid produced by plants. Bees get energy from nectar and protein from pollen, and in the process of seeking food they transfer pollen from a flower’s male anther to its female stigma.

Building on her earlier research, Ostroverkhova, a physicist in OSU’s College of Science, set out to determine if green fluorescence, like blue, was attractive to bees. She also wanted to learn whether all wavelengths of blue fluorescence were equally attractive, or if the drawing power tended toward the green or violet edge of the blue range.

In field conditions that provided the opportunity to use wild bees of a variety of species – most bee-vision studies have been done in labs and used captive-reared honeybees – Ostroverkhova designed a collection of bee traps – some non-fluorescent, others fluorescent via sunlight – that her entomology collaborators set up in the field.

Under varying conditions with a diverse set of landscape background colors, blue fluorescent traps proved the most popular by a landslide.

Researchers examined responses to traps designed to selectively stimulate either the blue or the green photoreceptor using sunlight-induced fluorescence with wavelengths of 420 to 480 nanometers and 510 to 540 nanometers, respectively.

They found out that selective excitation of the green photoreceptor type was not attractive, in contrast to that of the blue.

“And when we selectively highlighted the blue photoreceptor type, we learned the bees preferred blue fluorescence in the 430- to 480-nanometer range over that in the 400-420 region,” Ostroverkhova said.

Findings were recently published in the Journal of Comparative Physiology A. The Agricultural Research Foundation and OSU supported this research.


Editor’s note: Images are available at and