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A New Algorithm for “In-Betweening” images applied to Covid, Aging and Continental Drift

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Collaborating with a colleague in Shanghai, we recently published an article that explains the mathematical concept of ‘in-betweening,’in images – calculating intermediate stages of changes in appearance from one image to the next.

Our equilibrium-driven deformation algorithm (EDDA) was used to demonstrate three difficult tasks of ‘in-betweening’ images: Facial aging, coronavirus spread in the lungs, and continental drift.

Part I. Understanding Pneumonia Invasion and Retreat in COVID-19

The pandemic has influenced the entire world and taken away nearly 3 million lives to date. If a person were unlucky enough to contract the virus and COVID-19, one way to diagnose them is to carry out CT scans of their lungs to visualize the damage caused by pneumonia.

However, it is impossible to monitor the patient all the time using CT scans. Thus, the invading process is usually invisible for doctors and researchers.

To solve this difficulty, we developed a mathematical algorithm which relies on only two CT scans to simulate the pneumonia invasion process caused by COVID-19.

We compared a series of CT scans of a Chinese patient taken at different times. This patient had severe pneumonia caused by COVID-19 but recovered after a successful treatment. Our simulation clearly revealed the pneumonia invasion process in the patient’s lungs and the fading away process after the treatment.

Our simulation results also identify several significant areas in which the patient’s lungs are more vulnerable to the virus and other areas in which the lungs have better response to the treatment. Those areas were perfectly consistent with the medical analysis based on this patient’s actual, real-time CT scan images. The consistency of our results indicates the value of the method.

The COVID-19 pneumonia invading (upper panel) and fading away (lower panel) process from the data-driven simulations. Red circles indicate four significant areas in which the patient’s lungs were more vulnerable to the pneumonia and blue circles indicate two significant areas in which the patient’s lungs had better response to the treatment. (Image credit: Gao et al., 2021)
We also applied this algorithm to simulate human facial changes over time, in which the aging processes for different parts of a woman’s face were automatically created by the algorithm with high resolution. (Image credit: Gao et al., 2021. Video)

Part II. Solving the Puzzle of Continental Drift

It has always been mysterious how the continents we know evolved and formed from the ancient single supercontinent, Pangaea. But then German polar researcher Alfred Wegener proposed the continental drift hypothesis in the early 20th century. Although many geologists argued about his hypothesis initially, more sound evidence such as continental structures, fossils and the magnetic polarity of rocks has supported Wegener’s proposition.

Our data-driven algorithm has been applied to simulate the possible evolution process of continents from Pangaea period.

The underlying forces driving continental drift were determined by the equilibrium status of the continents on the current planet. In order to describe the edges that divide the land to create oceans, we proposed a delicate thresholding scheme.

The formation and deformation for different continents is clearly revealed in our simulation. For example, the ‘drift’ of the Antarctic continent from Africa can be seen happening. This exciting simulation presents a quick and obvious way for geologists to establish more possible lines of inquiry about how continents can drift from one status to another, just based on the initial and equilibrium continental status. Combined with other technological advances, this data-driven method may provide a path to solve Wegener’s puzzle of continental drift.

The theory of continental drift reconciled similar fossil plants and animals now found on widely separated continents. The southern part after Pangaea breaks (Gondwana) is shown here evidence of Wegener’s theory. (Image credit: United States Geological Survey)
The continental drift process of the data-driven simulations. Black arrow indicates the formation of the Antarctic. (Image credit: Gao et al., 2021)

The study was supported by the Department of Mathematics and Physics, Duke University.

CITATION: “Inbetweening auto-animation via Fokker-Planck dynamics and thresholding,” Yuan Gao, Guangzhen Jin & Jian-Guo Liu. Inverse Problems and Imaging, February, 2021, DOI: 10.3934/ipi.2021016. Online:

Yuan Gao

Yuan Gao is the William W. Elliot Assistant Research Professor in the department of mathematics, Trinity College of Arts & Sciences.

Jian-Guo Liu is a Professor in the departments of mathematics and physics, Trinity College of Arts & Sciences.

Jian-Guo Liu

Hard-Won Answer Was Worth the Wait

Most of Physics Professor Haiyan Gao’s students see their doctoral dissertations posted on her lab’s web site very soon after they have been awarded their Ph.Ds.

But Yang Zhang, Ph.D. 2018, had to wait two years, because his thesis work had a very good chance of being accepted by a major journal. And this week, it has been published in the journal Science.

What Zhang did was to create the world’s most precise value for a subatomic nuclear particle called a neutral pion. It’s a quark and an antiquark comprising a meson. The neutral pion (also known as p0) is the lightest of the mesons, but a player in the strong attractive force that holds the atom’s nucleus together.

Haiyan Gao (left) with newly-minted physics Ph.D. Yang Zhang in 2018. (Photo courtesy of Min Huang, Ph.D. ’16)

And that, in turn, makes it a part of the puzzle Gao and her students have been trying to solve for many years. The prevailing theory about the strong force is called quantum chromodynamics (QCD), and it’s been probed for years by high-energy physics. But Gao, Zhang and their collaborators are trying to study QCD under more normal energy states, a notoriously difficult problem.

Yang Zhang spent six years analyzing and writing up the data from a Primakoff  (PrimEx-II) experiment in Hall B at Thomas Jefferson National Accelerator Facility (Jefferson Lab) in Newport News, VA. His work was done on equipment supported by both the National Science Foundation and the Department of Energy.  

This is the quark structure of the positive pion – an up quark and an anti-down quark. The strong force is from gluons, represented as the wavy lines (Arpad Horvath via Wikimedia Commons)

In a Primakoff experiment, a photon beam is directed on a nuclear target, producing neutral pions. In both the PrimEx-I and PrimEx-II experiments at Jefferson Lab, the two photons from the decay of a neutral pionwere subsequently detected in an electromagnetic calorimeter. From that, Zhang extracted the pion’s ‘radiative decay width.’ That decay width is a handy thing to have, because it is directly related to the pion’s life expectancy, and QCD has a direct prediction for it.

Zhang’s hard-won answer: The neutral pion has a radiative decay width of 7.8 electron-volts, give or take. That makes it an important piece of the dauntingly huge puzzle about QCD. Gao and her colleagues will continue to ask the fundamental questions about nature, at the finest but perhaps most profound scale imaginable.

The PrimEx-I and PrimEx-II collaborations were led by Prof. Ashot Gasparian from North Carolina A&T State University. Gao and Zhang joined the collaboration in 2011.

“Precision Measurement of the Neutral Pion Lifetime,” appears in Science May 1. Dr. Yang Zhang is now a quantitative researcher at JPMorgan Chase & Co.

Researchers created a tiny circuit through a single water molecule, and here’s what they found

Graphic by Limin Xiang, Arizona State University

Many university labs may have gone quiet amid coronavirus shutdowns, but faculty continue to analyze data, publish papers and write grants. In this guest post from Duke chemistry professor David Beratan and colleagues, the researchers describe a new study showing how water’s ability to shepherd electrons can change with subtle shifts in a water molecule’s 3-D structure:

Water, the humble combination of hydrogen and oxygen, is essential for life. Despite its central place in nature, relatively little is known about the role that single water molecules play in biology.

Researchers at Duke University, in collaboration with Arizona State University, Pennsylvania State University and University of California-Davis have studied how electrons flow though water molecules, a process crucial for the energy-generating machinery of living systems. The team discovered that the way that water molecules cluster on solid surfaces enables the molecules to be either strong or weak mediators of electron transfer, depending on their orientation. The team’s experiments show that water is able to adopt a higher- or a lower-conducting form, much like the electrical switch on your wall. They were able to shift between the two structures using large electric fields.

In a previous paper published fifteen years ago in the journal Science, Duke chemistry professor David Beratan predicted that water’s mediation properties in living systems would depend on how the water molecules are oriented.

Water assemblies and chains occur throughout biological systems. “If you know the conducting properties of the two forms for a single water molecule, then you can predict the conducting properties of a water chain,” said Limin Xiang, a postdoctoral scholar at University of California, Berkeley, and the first author of the paper.

“Just like the piling up of Lego bricks, you could also pile up a water chain with the two forms of water as the building blocks,” Xiang said.

In addition to discovering the two forms of water, the authors also found that water can change its structure at high voltages. Indeed, when the voltage is large, water switches from a high- to a low-conductive form. In fact, it is may be possible that this switching could gate the flow of electron charge in living systems.

This study marks an important first step in establishing water synthetic structures that could assist in making electrical contact between biomolecules and electrodes. In addition, the research may help reveal nature’s strategies for maintaining appropriate electron transport through water molecules and could shed light on diseases linked to oxidative damage processes.

The researchers dedicate this study to the memory of Prof. Nongjian (NJ) Tao.

CITATION: “Conductance and Configuration of Molecular Gold-Water-Gold Junctions Under Electric Fields,” Limin Xiang, Peng Zhang, Chaoren Liu, Xin He, Haipeng B. Li, Yueqi Li, Zixiao Wang, Joshua Hihath, Seong H. Kim, David N. Beratan and Nongjian Tao. Matter, April 20, 2020. DOI: 10.1016/j.matt.2020.03.023

Guest post by David Beratan and Limin Xiang

Origami-inspired robots that could fit in a cell?

Imagine robots that can move, sense and respond to stimuli, but that are smaller than a hair’s width. This is the project that Cornell professor and biophysicist Itai Cohen, who gave a talk on Wednesday, January 29 as a part of Duke’s Physics Colloquium, has been working on with and his team. His project is inspired by the microscopic robots in Paul McEuen’s book Spiral. Building robots at such a small scale involves a lot more innovation than simply shrinking all of the parts of a normal robot. At low Reynolds number, fluids are viscous instead of inertial, Van der Waals forces come into play, as well as other factors that affect how the robot can move and function. 

Cohen’s team designs robots that fold similar to origami creatures. Image from

To resolve this issue, Cohen and his team decided to build and pattern their micro robots in 2D. Then, inspired by origami, a computer would print the 2D pattern of a robot that can fold itself into a 3D structure. Because paper origami is scale invariant, mechanisms built at one scale will work at another, so the idea is to build robot patterns than can be printed and then walk off of the page or out of a petri dish. However, as Cohen said in his talk last Wednesday, “an origami artist is only as good as their origami paper.” And to build robots at a microscopic scale, one would need some pretty thin paper. Cohen’s team uses graphene, a single sheet of which is only one atom thick. Atomic layer deposition films also behave very similarly to paper, and can be cut up, stretch locally and adopt a 3D shape. Some key steps to making sure the robot self-folds include making elements that bend, and putting additional stiff pads that localize bends in the pattern of the robot. This is what allows them to produce what they call “graphene bimorphs.” 

Cilia on the surface of a cell. Image from MedicalXpress.

Cohen and his team are looking to use microscopic robots in making artificial cilia, which are small leg-like protrusions in cells. Cilia can be sensory or used for locomotion. In the brain, there are cavities where neurotransmitters are redirected based on cilial beatings, so if one can control the individual beating of cilia, they can control where neurotransmitters are directed. This could potentially have biomedical implications for detecting and resolving neurological disorders. 

Right now, Cohen and his lab have microscopic robots made of graphene, which have photovoltaics attached to their legs. When a light shines on the photovoltaic receptor, it activates the robot’s arm movement, and it can wave hello. The advantage of using photovoltaics is that to control the robot, scientists can shine light instead of supplying voltage through a probe—the robot doesn’t need any tethers. During his presentation, Cohen showed the audience a video of his “Brobot,” a robot that flexes its arms when a light shines on it. His team has also successfully made microscopic robots with front and back legs that can walk off a petri dish. Their dimensions are 70 microns long, 40 microns wide and two microns thick. 

Cohen wants to think critically about what problems are important to use technology to solve; he wants make projects that can predict the behavior of people in crowds, predict the direction people will go in response to political issues, and help resolve water crises. Cohen’s research has the potential to find solutions for a wide variety of current issues. Using science fiction and origami as the inspiration for his projects reminds us that the ideas we dream of can become tangible realities. 

By Victoria Priester

Scientists Made a ‘T-Ray’ Laser That Runs on Laughing Gas

‘T-Ray’ laser finally arrives in practical, tunable form. Duke physicist Henry Everitt worked on it over two decades. Courtesy of Chad Scales, US Army Futures Command

It was a Frankenstein moment for Duke alumnus and adjunct physics professor Henry Everitt.

After years of working out the basic principles behind his new laser, last Halloween he was finally ready to put it to the test. He turned some knobs and toggled some switches, and presto, the first bright beam came shooting out.

“It was like, ‘It’s alive!’” Everitt said.

This was no laser for presenting Powerpoint slides or entertaining cats. Everitt and colleagues have invented a new type of laser that emits beams of light in the ‘terahertz gap,’ the no-man’s-land of the electromagnetic spectrum between microwaves and infrared light.

Terahertz radiation, or ‘T-rays,’ can see through clothing and packaging, but without the health hazards of harmful radiation, so they could be used in security scanners to spot concealed weapons without subjecting people to the dangers of X-rays.

It’s also possible to identify substances by the characteristic frequencies they absorb when T-rays hit them, which makes terahertz waves ideal for detecting toxins in the air or gases between the stars. And because such frequencies are higher than those of radio waves and microwaves, they can carry more bandwidth, so terahertz signals could transmit data many times faster than today’s cellular or Wi-Fi networks.

“Imagine a wireless hotspot where you could download a movie to your phone in a fraction of a second,” Everitt said.

Yet despite the potential payoffs, T-rays aren’t widely used because there isn’t a portable, cheap or easy way to make them.

Now Everitt and colleagues at Harvard University and MIT have invented a small, tunable T-ray laser that might help scientists tap into the terahertz band’s potential.

While most terahertz molecular lasers take up an area the size of a ping pong table, the new device could fit in a shoebox. And while previous sources emit light at just one or a few select frequencies, their laser could be tuned to emit over the entire terahertz spectrum, from 0.1 to 10 THz.

The laser’s tunability gives it another practical advantage, researchers say: the ability to adjust how far the T-ray beam travels. Terahertz signals don’t go very far because water vapor in the air absorbs them. But because some terahertz frequencies are more strongly absorbed by the atmosphere than others, the tuning capability of the new laser makes it possible to control how far the waves travel simply by changing the frequency. This might be ideal for applications like keeping car radar sensors from interfering with each other, or restricting wireless signals to short distances so potential eavesdroppers can’t intercept them and listen in.

Everitt and a team co-led by Federico Capasso of Harvard and Steven Johnson of MIT describe their approach this week in the journal Science. The device works by harnessing discrete shifts in the energy levels of spinning gas molecules when they’re hit by another laser emitting infrared light.

Their T-ray laser consists of a pencil-sized copper tube filled with gas, and a 1-millimeter pinhole at one end. A zap from the infrared laser excites the gas molecules within, and when the molecules in this higher energy state outnumber the ones in a lower one, they emit T-rays.

The team dubbed their gizmo the “laughing gas laser” because it uses nitrous oxide, though almost any gas could work, they say.

Duke professor Henry Everitt and MIT graduate student Fan Wang and colleagues have invented a new laser that emits beams of light in the ‘terahertz gap,’ the no-man’s-land of the electromagnetic spectrum.

Everitt started working on terahertz laser designs 35 years ago as a Duke undergraduate in the mid-1980s, when a physics professor named Frank De Lucia offered him a summer job.

De Lucia was interested in improving special lasers called “OPFIR lasers,” which were the most powerful sources of T-rays at the time. They were too bulky for widespread use, and they relied on an equally unwieldy infrared laser called a CO2 laser to excite the gas inside.

Everitt was tasked with trying to generate T-rays with smaller gas laser designs. A summer gig soon grew into an undergraduate honors thesis, and eventually a Ph.D. from Duke, during which he and De Lucia managed to shrink the footprint of their OPFIR lasers from the size of an axe handle to the size of a toothpick.

But the CO2 lasers they were partnered with were still quite cumbersome and dangerous, and each time researchers wanted to produce a different frequency they needed to use a different gas. When more compact and tunable sources of T-rays came to be, OPFIR lasers were largely abandoned.

Everitt would shelf the idea for another decade before a better alternative to the CO2 laser came along, a compact infrared laser invented by Harvard’s Capasso that could be tuned to any frequency over a swath of the infrared spectrum.

By replacing the CO2 laser with Capasso’s laser, Everitt realized they wouldn’t need to change the laser gas anymore to change the frequency. He thought the OPFIR laser approach could make a comeback. So he partnered with Johnson’s team at MIT to work out the theory, then with Capasso’s group to give it a shot.

The team has moved to patent their design, but there is still a long way before it finds its way onto store shelves or into consumers’ hands. Nonetheless, the researchers — who couldn’t resist a laser joke — say the outlook for the technique is “very bright.”

This research was supported by the U.S. Army Research Office (W911NF-19-2-0168, W911NF-13-D-0001) and by the National Science Foundation (ECCS-1614631) and its Materials Research Science and Engineering Center Program (DMR-1419807).

CITATION: “Widely Tunable Compact Terahertz Gas Lasers,” Paul Chevalier, Arman Armizhan, Fan Wang, Marco Piccardo, Steven G. Johnson, Federico Capasso, Henry Everitt. Science, Nov. 15, 2019. DOI: 10.1126/science.aay8683.

How Small is a Proton? Smaller Than Anyone Thought

The proton, that little positively-charged nugget inside an atom, is fractions of a quadrillionth of a meter smaller than anyone thought, according to new research appearing Nov. 7 in Nature.

Haiyan Gao of Duke Physics

In work they hope solves the contentious “proton radius puzzle” that has been roiling some corners of physics in the last decade, a team of scientists including Duke physicist Haiyan Gao have addressed the question of the proton’s radius in a new way and discovered that it is 0.831 femtometers across, which is about 4 percent smaller than the best previous measurement using electrons from accelerators. (Read the paper!)

A single femtometer is 0.000000000000039370 inches imperial, if that helps, or think of it as a millionth part of a billionth part of a meter. And the new radius is just 80 percent of that.

But this is a big — and very small — deal for physicists, because any precise calculation of energy levels in an atom will be affected by this measure of the proton’s size, said Gao, who is the Henry Newson professor of physics in Trinity College of Arts & Sciences.

Bohr model of Hydrogen. One proton, one electron, as simple as they come.

What the physicists actually measured is the radius of the proton’s charge distribution, but that’s never a smooth, spherical point, Gao explained. The proton is made of still smaller bits, called quarks, that have their own charges and those aren’t evenly distributed. Nor does anything sit still. So it’s kind of a moving target.

One way to measure a proton’s charge radius is to scatter an electron beam from the nucleus of an atom of hydrogen, which is made of just one proton and one electron. But the electron must only perturb the proton very gently to enable researchers to infer the size of the charge involved in the interaction. Another approach measures the difference between two atomic hydrogen energy levels. Past results from these two methods have generally agreed.

Artist’s conception of a very happy muon by Particle Zoo

But in 2010, an experiment at the Paul Scherrer Institute replaced the electron in a hydrogen atom with a muon, a much heavier and shorter-lived member of the electron’s particle family. The muon is still negatively charged like an electron, but it’s about 200 times heavier, so it can orbit much closer to the proton. Measuring the difference between muonic hydrogen energy levels, these physicists obtained a proton charge radius that is highly precise, but much smaller than the previously accepted value. And this started the dispute they’ve dubbed the “proton charge radius puzzle.”

To resolve the puzzle, Gao and her collaborators set out to do a completely new type of electron scattering experiment with a number of innovations. And they looked at electron scattering from both the proton and the electron of the hydrogen atom at the same time. They also managed to get the beam of electrons scattered at near zero degrees, meaning it came almost straight forward, which enabled the electron beam to “feel” the proton’s charge response more precisely.

Voila, a 4-percent-smaller proton. “But actually, it’s much more complicated,” Gao said, in a major understatement.

The work was done at the Department of Energy’s Thomas Jefferson National Accelerator Facility in Newport News, Virginia, using new equipment supported by both the National Science Foundation and the Department of Energy, and some parts that were purpose-built for this experiment. “To solve the argument, we needed a new approach,” Gao said.

Gao said she has been interested in this question for nearly 20 years, ever since she became aware of two different values for the proton’s charge radius, both from electron scattering experiments.  “Each one claimed about 1 percent uncertainty, but they disagreed by several percent,” she said.

And as always in modern physics, had the answer not worked out so neatly, it might have called into question parts of the Standard Model of particle physics. But alas, not this time.

“This is particularly important for a number of reasons,” Gao said. The proton is a fundamental building block of visible matter, and the energy level of hydrogen is a basic unit of measure that all physicists rely on.

The new measure may also help advance new insights into quantum chromodynamics (QCD), the theory of strong interaction in quarks and gluons, Gao said. “We really don’t understand how QCD works.”

“This is a very, very big deal,” she said. “The field is very excited about it. And I should add that this experiment would not have been so successful without the heroic contributions from our highly talented and hardworking graduate students and postdocs from Duke.”

This work was funded in part by the U. S. National Science Foundation (NSF MRI PHY-1229153) and by the U.S. Department of Energy (Contract No. DE-FG02-03ER41231), including contract No. DE-AC05-06OR23177 under which Jefferson Science Associates, LLC operates Thomas Jefferson National Accelerator Facility.

CITATION: “A Small Proton Charge Radius from An Electron-Proton Scattering Experiment,”  W. Xiong, A. Gasparian, H. Gao, et al. Nature, Nov. 7, 2019. DOI: 10.1038/s41586-019-1721-2 (ONLINE)

Nature Shows a U-Turn Path to Better Solar Cells

The technical-sounding category of “light-driven charge-transfer reactions,” becomes more familiar to non-physicists when you just call it photosynthesis or solar electricity.

When a molecule (in a leaf or solar cell) is hit by an energetic photon of light, it first absorbs the little meteor’s energy, generating what chemists call an excited state. This excited state then almost immediately (like trillionths of a second) shuttles an electron away to a charge acceptor to lower its energy. That transference of charge is what drives plant life and photovoltaic current.

A 20 Megawatt solar farm ( Aerial Innovations via wikimedia commons)

The energy of the excited state plays an important role in determining solar energy conversion efficiency. That is, the more of that photon’s energy that can be retained in the charge-separated state, the better. For most solar-electric devices, the excited state rapidly loses energy, resulting in less efficient devices.

But what if there were a way to create even more energetic excited states from that incoming photon?

Using a very efficient photosynthesizing bacterium as their inspiration, a team of Duke chemists that included graduate students Nick Polizzi and Ting Jiang, and faculty members David Beratan and Michael Therien, synthesized a “supermolecule” to help address this question.

“Nick and Ting discovered a really cool trick about electron transfer that we might be able to adapt to improving solar cells,” said Michael Therien, the William R. Kenan, Jr. Professor of Chemistry. “Biology figured this out eons ago,” he said.

“When molecules absorb light, they have more energy,” Therien said. “One of the things that these molecular excited states do is that they move charge. Generally speaking, most solar energy conversion structures that chemists design feature molecules that push electron density in the direction they want charge to move when a photon is absorbed. The solar-fueled microbe, Rhodobacter sphaeroides, however, does the opposite. What Nick and Ting demonstrated is that this could also be a winning strategy for solar cells.”

Ting Jiang
Nick Polizzi

The chemists devised a clever synthetic molecule that shows the advantages of an excited state that pushes electron density in the direction opposite to where charge flows. In effect, this allows more of the energy harvested from a photon to be used in a solar cell. 

“Nick and Ting’s work shows that there are huge advantages to pushing electron density in the exact opposite direction where you want charge to flow,” Therien said in his top-floor office of the French Family Science Center. “The biggest advantage of an excited state that pushes charge the wrong way is it stops a really critical pathway for excited state relaxation.”

“So, in many ways it’s a Rube Goldberg Like conception,” Therien said. “It is a design strategy that’s been maybe staring us in the face for several years, but no one’s connected the dots like Nick and Ting have here.”

In a July 2 commentary for the Proceedings of the National Academy of Sciences, Bowling Green State University chemist and photoscientist Malcom D.E. Forbes calls this work “a great leap forward,” and says it “should be regarded as one of the most beautiful experiments in physical chemistry in the 21st century.”

Here’s a schematic from the paper.
(Image by Nick Polizzi)

CITATION: “Engineering Opposite Electronic Polarization of Singlet and Triplet States Increases the Yield of High-Energy Photoproducts,” Nicholas Polizzi, Ting Jiang, David Beratan, Michael Therien. Proceedings of the National Academy of Sciences, June 10, 2019. DOI: 10.1073/pnas.1901752116 Online:

Understanding the Universe, Large and Small

From the miniscule particles underlying matter, to vast amounts of data from the far reaches of outer space, Chris Walter, a professor of physics at Duke, pursues research into the great mysteries of the universe, from the infinitesimal to the infinite.

Chris Walter is a professor of physics

As an undergraduate at the University of California at Santa Cruz, he thought he would become a theoretical physicist, but while continuing his education at the California Institute of Technology (Caltech), he found himself increasingly drawn to experimental physics, deriving knowledge of the universe by observing its phenomena.

Neutrinos — miniscule particles emitted during radioactive decay — captured his attention, and he began work with the KamiokaNDE (Kamioka Nucleon Decay Experiment, now typically written as Kamiokande) at the Kamioka Observatory in Hida, Japan. Buried deep underground
in an abandoned mine to shield the detectors from cosmic rays and submerged in water, Kamiokande offered Walter an opportunity to study a long-supposed but still unproven hypothesis: that neutrinos were massless.

Recalling one of his most striking memories from his time in the lab, he described observing and finding answers in Cherenkov light – a ‘sonic boom’ of light. Sonic booms are created by breaking the sound barrier in air.  However, the speed of light changes in different media – the speed of light in water is less than the speed of light in a vacuum — and a particle accelerator could accelerate particles beyond the speed of light in water.  Walter described it like a ring of light bursting out of the darkness.

In his time at the Kamioka Observatory, he was a part of groundbreaking neutrino research on the mass of neutrinos. Long thought to have been massless, Kamiokande discovered the property of neutron oscillation – that neutrinos could change from flavor to flavor, indicating that, contrary to popular belief, they had mass. Seventeen years later, in 2015, the leader of his team, Takaaki Kajita, would be co-awarded the Nobel Prize for Physics, citing research from their collaboration.

Chris Walter (left) and his Duke physics collaborator and partner, Kate Scholberg (right), on a lift inside the Super-Kamiokande neutrino detector.

Neutrinos originated from the cosmic rays in outer space, but soon another mystery from the cosmos captured Walter’s attention.

“If you died and were given the chance to know the answer to just one question,” he said, “for me, it would be, ‘What is dark energy?’”

Observations made in the 1990s, as Walter was concluding his time at the Kamioka Observatory, found that the expansion of the universe was accelerating. The nature of the dark energy causing this accelerating expansion remained unknown to scientists, and it offered a new course of study in the field of astrophysics.

Walter has recently joined the Large Synoptic Survey Telescope (LSST) as part of a 10-year, 3D survey of the entire sky, gathering over 20 terabytes of data nightly and detecting thousands of changes in the night sky, observing asteroids, galaxies, supernovae, and other astronomical phenomena. With new machine learning techniques and supercomputing methods to process the vast quantities of data, the LSST offers incredible new opportunities for understanding the universe. 

To Walter, this is the next big step for research into the nature of dark energy and the great questions of science.

A rendering of the Large Synoptic Survey Telescope. (Note the naked humans for scale)

Guest Post by Thomas Yang, NCSSM 2019

Teaching a Machine to Spot a Crystal

A collection of iridescent crystals grown in space

Not all protein crystals exhibit the colorful iridescence of these crystals grown in space. But no matter their looks, all are important to scientists. Credit: NASA Marshall Space Flight Center (NASA-MSFC).

Protein crystals don’t usually display the glitz and glam of gemstones. But no matter their looks, each and every one is precious to scientists.

Patrick Charbonneau, a professor of chemistry and physics at Duke, along with a worldwide group of scientists, teamed up with researchers at Google Brain to use state-of-the-art machine learning algorithms to spot these rare and valuable crystals. Their work could accelerate drug discovery by making it easier for researchers to map the structures of proteins.

“Every time you miss a protein crystal, because they are so rare, you risk missing on an important biomedical discovery,” Charbonneau said.

Knowing the structure of proteins is key to understanding their function and possibly designing drugs that work with their specific shapes. But the traditional approach to determining these structures, called X-ray crystallography, requires that proteins be crystallized.

Crystallizing proteins is hard — really hard. Unlike the simple atoms and molecules that make up common crystals like salt and sugar, these big, bulky molecules, which can contain tens of thousands of atoms each, struggle to arrange themselves into the ordered arrays that form the basis of crystals.

“What allows an object like a protein to self-assemble into something like a crystal is a bit like magic,” Charbonneau said.

Even after decades of practice, scientists have to rely in part on trial and error to obtain protein crystals. After isolating a protein, they mix it with hundreds of different types of liquid solutions, hoping to find the right recipe that coaxes them to crystallize. They then look at droplets of each mixture under a microscope, hoping to spot the smallest speck of a growing crystal.

“You have to manually say, there is a crystal there, there is none there, there is one there, and usually it is none, none, none,” Charbonneau said. “Not only is it expensive to pay people to do this, but also people fail. They get tired and they get sloppy, and it detracts from their other work.”

Three microscope images of protein crystallization solutions

The machine learning software searches for points and edges (left) to identify crystals in images of droplets of solution. It can also identify when non-crystalline solids have formed (middle) and when no solids have formed (right).

Charbonneau thought perhaps deep learning software, which is now capable of recognizing individual faces in photographs even when they are blurry or caught from the side, should also be able to identify the points and edges that make up a crystal in solution.

Scientists from both academia and industry came together to collect half a million images of protein crystallization experiments into a database called MARCO. The data specify which of these protein cocktails led to crystallization, based on human evaluation.

The team then worked with a group led by Vincent Vanhoucke from Google Brain to apply the latest in artificial intelligence to help identify crystals in the images.

After “training” the deep learning software on a subset of the data, they unleashed it on the full database. The A.I. was able to accurately identify crystals about 95 percent of the time. Estimates show that humans spot crystals correctly only 85 percent of the time.

“And it does remarkably better than humans,” Charbonneau said. “We were a little surprised because most A.I. algorithms are made to recognize cats or dogs, not necessarily geometrical features like the edge of a crystal.”

Other teams of researchers have already asked to use the A.I. model and the MARCO dataset to train their own machine learning algorithms to recognize crystals in protein crystallization experiments, Charbonneau said. These advances should allow researchers to focus more time on biomedical discoveries instead of squinting at samples.

Charbonneau plans to use the data to understand how exactly proteins self-assemble into crystals, so that researchers rely less on chance to get this “magic” to happen.

“We are trying to use this data to see if we can get more insight into the physical chemistry of self-assembly of proteins,” Charbonneau said.

CITATION: “Classification of crystallization outcomes using deep convolutional neural networks,” Andrew E. Bruno, et al. PLOS ONE, June 20, 2018. DOI: 10.1371/journal.pone.0198883


Post by Kara Manke

Stretchable, Twistable Wires for Wearable Electronics

A new conductive “felt” carries electricity even when twisted, bent and stretched. Credit: Matthew Catenacci

The exercise-tracking power of a Fitbit may soon jump from your wrist and into your clothing.

Researchers are seeking to embed electronics such as fitness trackers and health monitors into our shirts, hats, and shoes. But no one wants stiff copper wires or silicon transistors deforming their clothing or poking into their skin.

Scientists in Benjamin Wiley’s lab at Duke have created new conductive “felt” that can be easily patterned onto fabrics to create flexible wires. The felt, composed of silver-coated copper nanowires and silicon rubber, carries electricity even when bent, stretched and twisted, over and over again.

“We wanted to create wiring that is stretchable on the body,” said Matthew Catenacci, a graduate student in Wiley’s group.

The conductive felt is made of stacks of interwoven silver-coated copper nanotubes filled with a stretchable silicone rubber (left). When stretched, felt made from more pliable rubber is more resilient to small tears and holes than felts made of stiffer rubber (middle). These tears can be seen in small cavities in the felt (right). Credit: Matthew Catenacci

To create a flexible wire, the team first sucks a solution of copper nanowires and water through a stencil, creating a stack of interwoven nanowires in the desired shape. The material is similar to the interwoven fibers that comprise fabric felt, but on a much smaller scale, said Wiley, an associate professor of chemistry at Duke.

“The way I think about the wires are like tiny sticks of uncooked spaghetti,” Wiley said. “The water passes through, and then you end up with this pile of sticks with a high porosity.”

The interwoven nanowires are heated to 300 F to melt the contacts together, and then silicone rubber is added to fill in the gaps between the wires.

To show the pliability of their new material, Catenacci patterned the nanowire felt into a variety of squiggly, snaking patterns. Stretching and twisting the wires up to 300 times did not degrade the conductivity.

The material maintains its conductivity when twisted and stretched. Credit: Matthew Catenacci

“On a larger scale you could take a whole shirt, put it over a vacuum filter, and with a stencil you could create whatever wire pattern you want,” Catenacci said. “After you add the silicone, so you will just have a patch of fabric that is able to stretch.”

Their felt is not the first conductive material that displays the agility of a gymnast. Flexible wires made of silver microflakes also exhibit this unique set of properties. But the new material has the best performance of any other material so far, and at a much lower cost.

“This material retains its conductivity after stretching better than any other material with this high of an initial conductivity. That is what separates it,” Wiley said.

Stretchable Conductive Composites from Cu-Ag Nanowire Felt,” Matthew J. Catenacci, Christopher Reyes, Mutya A. Cruz and Benjamin J. Wiley. ACS Nano, March 14, 2018. DOI: 10.1021/acsnano.8b00887

Post by Kara Manke

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