Perfecting Defects Could Impact Semiconductors

Uncategorized computer modeling, Dr. Haixuan Xu, point defects, semiconductors

Haixuan Xu In baking, cooks often start with a simple recipe of flour, baking powder, butter, sugar, and eggs. This basic list of ingredients will come together to make a base for a variety of different goods. From here, the addition of milk will turn that base into cake batter, while baking soda will make cookie dough. The use of different ingredients in the same base can lead to vastly different outcomes.

The same can be said of materials science and the study of low-dimensional materials. Haixuan Xu, assistant professor of materials science and engineering, and his JDRD team propose to expand the understanding of the effect of point defects and impurities on low-dimensional materials such as graphene.

“We are trying to see how we can control the creation of defects in low-dimensional materials,” said Xu. “A defect could be a hole or what you call a vacancy in the material system. Then we want to put something else in there. That’s called a dopant.”

Dopants, or impurities, are inserted into a substance to change its electrical or optical properties. This is often done with semiconductor materials currently of interest in the advancement of electronics and computing.

The ultimate aim of Xu’s work is to advance the science of quantum computing by contributing to the foundation of knowledge needed in order to move forward.

“The joint LDRD [Laboratory Directed Research and Development] and JDRD work is trying to see if we can precisely control the atomic and material environment used to prepare and maintain coherent superposition of quantum states, which is the heart of the challenge for quantum computing. But there are many steps in between,” said Xu.

Xu’s project will study these defects in an attempt to ascertain how the use of particular dopants can affect the base material, particularly with relation to the electronic structure of the system. In order to do this, his team must first determine how to create defects in a controlled manner, a task that is currently under way.

Xu’s ORNL partner, Stephen Jesse, will tackle the same problem from an experimental angle using the national lab’s scanning electron beam microscope and helium ion microscope. Xu’s team will be hammering away at the theoretical understanding through computer modeling, with the intention of bringing their results together to provide a more complete picture.

“There is nice synergy between the Oak Ridge and UT teams. We’re actually studying the same scientific problem from two different and complementary perspectives,” said Xu. “Hopefully we can get a better understanding of what’s really going on in the system.”

Algorithms May Enhance Computational Efficiency

2017 Spotlights cooperative solvers, Dr. Oleg Shylo, high-performance computing

Imagine a busy airport. Planes from a dozen airlines take off and land hundreds of thousands of times a day, heading to and from hundreds of cities. Passengers scurry from plane to plane catching connecting flights to arrive at their final destination. To ensure that the whole system works reliably and efficiently, complex and large-scale decisions have to be made.

In mathematical language, the decision-making process can be formulated as what computer scientists call an optimization problem—one that looks for the best possible solution out of many alternatives. In the airport setting, this approach will ensure that thousands of planes can take off and land in an orderly fashion and relatively on schedule.

Optimization models that fully capture the essence of industrial-scale problems require computational capacities afforded only by high-performance computing systems. Oleg Shylo, assistant professor of industrial and systems engineering, is hoping to utilize these systems in his JDRD work by designing new algorithms to work in parallel.

“The approach that we’re taking is so-called cooperative solvers, where a group of optimization algorithms work together and, as the word cooperative implies, they communicate with each other to solve problems,” said Shylo.

The use of cooperative solvers comes with its own unique set of constraints, as the communication between these algorithms can quickly overwhelm the system’s bandwidth. Optimization problems frequently have a large number of variables and need to be solved very quickly, something that can’t happen if algorithms are using all the computing power to share updates.

“As in human communication, if you have 10,000 people talking to each other at the same time it’s going to be chaotic and you won’t have time to do any useful work,” said Shylo. “The same applies to algorithms. You need to design communication structures and topologies to alleviate those kinds of issues.”

Shylo will use theoretical models to discover the best communication structures. Through his LDRD partnership with Jack Wells, director of science for the Oak Ridge Leadership Computing Facility at ORNL, Shylo will have the opportunity to test his algorithms on one of the high-performance computing systems, such as Titan, at the national lab. He hopes these tests will confirm his theoretical work and clear the path toward solving real-world optimization problems.

Designing Better Aluminum Alloys

2017 Spotlights, Science Alliance News aluminum alloy, Dr. Seungha Shin, interfacial transport, microstructure design, theta phase

On November 2, 1944, Howard Hughes’s infamous plane the Spruce Goose made its inaugural and final flight, traveling a single mile. Contrary to its name, the Spruce Goose was constructed primarily of laminated birch in an attempt to work within the government’s wartime materials restrictions. Weighing approximately 300,000 pounds, the plane was estimated to travel less than a quarter of a mile per gallon of fuel. In contrast, a modern Boeing 747 travels approximately five miles on a gallon.

Aside from the modern technology operating within the 747, the most obvious difference between the two aircraft lies in their construction materials. The 747 is made of a high-tech aluminum alloy. The study and improvement of aluminum alloys continue to make up an important area of research within the field of materials science.

Lighter, more heat-resistant alloys can improve the performance and fuel efficiency of transportation vehicles like cars and planes. This is precisely the subject Seungha Shin, assistant professor of mechanical, aerospace, and biomedical engineering, proposes to address with his JDRD project. Shin’s team, in conjunction with his partner Amit Shyam, a research scientist at ORNL, is investigating mass and thermal transport near microstructural interfaces in the search for better-designed aluminum alloys.

“Aluminum is kind of a soft metal, so in order to have better mechanical properties we add copper. In mechanical properties, most failures occur near the interface, so when designing a microstructure, the interface is very important,” said Shin.

Shin hopes his project will lead to a more thorough understanding of how to design alloys to create microstructures that provide specific effects, such as greater durability under high temperature conditions.

“Normally, light metals are not that good at high temperatures, so to use that kind of lightweight metal we need to develop some new materials,” said Shin.

Microstructures have an important role to play in the development of these new materials. The unique microstructure of a material determines its physical properties, such as toughness, corrosion resistance, and thermal transport behavior. These properties then determine the applications and industries for which that material is suited. Essentially, microstructures dictate the uses of materials.

“If we have an aluminum-copper alloy, it creates a certain phase of microstructure called the theta phase. It begins all mixed together, then forms the theta prime phase followed by the theta phase,” said Shin. “The theta phase is not good, but the theta prime phase can create a stronger aluminum alloy. We want to prevent the diffusion, or transition, from the theta prime to theta phase.”

Shin’s team will focus on computational simulations of interfacial transport at the atomic level with the goal of developing a theoretical framework for controlling these properties. His ORNL partners will model on both fundamental and system scales. Shin’s work will provide the missing piece for effective alloy design, with wide-ranging applications in air and ground transportation.

Catalyst Design Could Impact Pharmaceutical Development

2017 Spotlights, Science Alliance News Dr. Sharani Roy, heterogeneous catalysis, surface chemistry

The pharmaceutical industry is a multibillion-dollar business that touches the lives of nearly everyone on earth in one way or another. In the United States alone, about four billion individual prescriptions are filled at pharmacies across the country each year. The California Biomedical Research Association estimates that 12 years of development goes into the creation of a single drug. Sharani Roy, assistant professor of chemistry, could impact that development process with her JDRD project.

Surface chemistry—specifically heterogeneous catalysis, the acceleration of a chemical reaction on the surface of a solid—has played a major role in pharmaceutical research for a number of years. Members of Roy’s JDRD team have focused their efforts on controlling the outcome of the reaction generated by heterogeneous catalysis, or catalytic selectivity.

“Two reactants come together. They react, and maybe there are two or three different possible products: A, B, and C. But how do you design a catalyst so that it makes A but not B and C? A lot of times you don’t want all the products. You’re looking for a particular one,” said Roy.

Roy’s team will study the process of catalytic selectivity by examining these surface reactions, which she hopes will lead to a better understanding of how to create and control that selectivity. The ability to direct this reaction could play a major role in advancing and expediting pharmaceutical research and drug creation. In the second phase of her project, Roy will study selectivity in a more realistic environment.

“In industry, when people are making a molecule in bulk, you don’t have these pristine surfaces that you make in the laboratory,” she said. “They are using what they have. They have high-pressure conditions and temperature conditions. Those are the real catalysts that are used every day. There’s a gap between that and these very model, ideal systems that we study in the laboratories.”

Roy’s ORNL partner, research scientist Benjamin Doughty, will provide her team with chemical images captured via the vibrational sum–frequency generation microscope he developed. The two hope their collaborative efforts result in a more complete understanding of interfacial molecular processes.

New Device Could Lead to Better Cancer Outcomes

2017 Spotlights, Science Alliance News cancer, Dr. Eric Lukosi, nuclear nonproliferation, radiation therapy, radiotherapy, Will Gerding

Graduate student Will Gerding. According to the National Cancer Institute, approximately 39.6 percent of men and women will be diagnosed with cancer over the course of their lifetime. In the United States cancer is responsible for roughly 171 out of every 100,000 deaths. The number of patients living beyond a cancer diagnosis is on the rise, however, thanks to ever-improving treatments.

Radiation therapy, or radiotherapy, has become increasingly popular, with an estimated 60 percent of cancer patients in the US receiving it at some point. The JDRD team headed by Eric Lukosi, assistant professor of nuclear engineering, proposes to improve those treatments through the creation of a microfluidic device. This device will integrate with the treatment apparatus and measure dosage and purity in addition to removing steps from the measuring process.

“There have been experiments performed using actinium-225 and bismuth-213 that show they are extremely effective at radiotherapy,” said Will Gerding, the graduate student supported by Lukosi’s JDRD project. “One of the downsides of that is to make sure you have the right ratio you need to do gamma spectroscopy in a separate device. That makes the process a bit longer and causes the bismuth, from radioactive decay, to become less effective.”

When actinium decays it eventually becomes bismuth—specifically, the isotope of bismuth needed for radiation treatments. One of the ongoing challenges with these treatments is ensuring that the bismuth is making its way into patients but the actinium is not. Currently, gamma spectroscopy is used to assess the purity of the treatment.

In order to conduct the gamma spectroscopy, the solution must be taken from the dispenser to a different location and processed through multiple steps before being put into a vacuum for the final spectroscopic analysis. The process requires a great deal of time, during which the bismuth may decay past its effective stage before it can be examined.

“If you could just push it through my microfluidic sampler, that would remove a lot of steps there—so it would be a time- and cost-saving measure for radiochemists analyzing samples,” said Lukosi.

Lukosi’s JDRD work has a number of potential applications, including environmental sampling and nuclear nonproliferation.

“There is actually a whole host of applications for this technology. I originally thought of the idea for nonproliferation for pyroprocessing, which is electrifying spent nuclear fuels,” said Lukosi. “So when someone says he removed two tons of plutonium out of this fuel, how do we know that it was really two tons? Is he taking grams at a time over years to sell to terrorists?”

Lukosi’s device would be able to provide accurate and detailed measurements of the contents of the fluids that pass through it. That precision would make it a useful tool for researchers in a number of fields, including medical treatment.

Working with his ORNL partner, Senior Research Scientist David DePaoli, will provide Lukosi an opportunity to test the device on the actinium/bismuth generating system they are building. With positive outcomes, this UT-ORNL partnership could potentially increase the number of patients outliving their cancer diagnoses in future generations.

Modeling for Improved Nuclear Waste Storage

2017 Spotlights, Research Spotlights, Science Alliance News Dr. Maik Lang, ICE-MAN, JDRD, nuclear waste storage, Spallation Neutron Source

The Spallation Neutron Source (SNS) at ORNL is a unique research facility capable of producing the most intense neutron beams currently available anywhere in the world. With this beam technology, SNS offers unprecedented research and data collection opportunities through neutron scattering. Unfortunately, that data does not emerge in a readily useful format. Maik Lang, assistant professor of nuclear engineering and Pietro F. Pasqua Fellow, is working to change that.

Lang’s JDRD project focuses on understanding the effects of extreme conditions on glass. His team has already gathered initial neutron scattering data that will be used by his ORNL partners to set up a new integrated environment for translating raw data into a usable format.

“This platform will help to process your raw data collected at the spallation source and better understand that data and tie it together to other measurements you did at different beam lines, or even at different facilities,” said Lang.

This platform, the Integrated Computational Environment–Modeling and Analysis for Neutrons, or ICE-MAN, will work as a translator, taking the information logged by the SNS and converting it into the format needed for modeling and analysis.

“It’s kind of like a black box. The data enters in one format and then the black box changes it into the right format for your software or models,” said Lang. By integrating his “black box” with the measuring device, Lang hopes to streamline the process from data collection to useful information for researchers studying a variety of materials.

This technology will allow Lang to use his data to model the effects of radiation on glass, a popular storage substance for nuclear waste. Researchers need to know exactly how and when glass and other storage materials begin to break down from exposure to plasma in order to determine possible uses and future complications.

According to Lang, the disordered nature of glass makes it especially difficult to study, as the effects of radiation are very subtle.

“When you have glass, it’s a noncrystalline material so you have no order. When you measure you get a lot of peaks but don’t know what it means,” said Lang. “You have data but you can’t interpret it. For this you need modeling, and for the modeling we need this platform.”

Lang’s team will assist a team at ORNL led by Anibal Ramirez-Cuesto in setting up ICE-MAN using the JDRD project data and in creating a manual for the system. Lang believes this collaboration will not only create opportunities for future efforts and funding but also open the door for discovery in materials science as a whole.