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Spearheading next wave of human flourishing

Sandhya Susarla earns prestigious honors for contributions to the quantum computing field

by | Jun 24, 2025 | Faculty, Features

Pictured left to right: Sandhya Susarla, assistant professor in the School for Engineering of Matter, Transport and Energy, part of the Ira A. Fulton Schools of Engineering at Arizona State University, is shown with her students, Sriram Sankar, Patrick Hays and Mahir Manna, in a microscopy lab at ASU. She recently received the 2025 Society Awards from the Microscopy Society of America, the highest early career honor in the field of microscopy. Photographer: Erika Gronek/ASU

A century ago, life expectancy in the U.S. was 47 years. Today, it’s 78.

This dramatic leap didn’t happen by chance. It was largely due to technological advances in medicine, agriculture and communication. But none of it would have been possible without a deeper understanding of the most foundational building blocks of the world: atoms and molecules. These form the foundation of nearly every product and technology we rely on today.

While our understanding of materials’ behavior has led to significant improvements in different aspects of life, in the age of artificial intelligence, or AI, new challenges like hacking are emerging, threatening online systems that are increasingly becoming the backbone of most economic and social activities.

At Arizona State University, Sandhya Susarla, an assistant professor in the School for Engineering of Matter, Transport and Energy, part of Ira A. Fulton Schools of Engineering, is paving the way for making modern systems unhackable using quantum computers.

Susarla is one of only nine recipients of the 2025 Society Awards from the Microscopy Society of America. Particularly, she received the Albert Crewe Award, the highest early career honor in the microscopy field. Her research has the potential to unlock unprecedented progress in quantum computing, which would lead to the next leap in human prosperity.

But if quantum computers are that powerful, why haven’t they been widely adopted?

Breaking down quantum computers

While there are similarities, quantum computers operate differently from classical computers such as your phone or laptop.

For example, when you start a Monday morning email with, “Hello, I hope you had a great weekend,” the computer uses bits, which are the fundamental units of digital information, to store and process the sentence in its Random Access Memory, or RAM. Each bit can exist in only two physical states, represented by 0 and 1, and the computer groups bits into bytes, unlocking the ability to store massive amounts of data.

In the American Standard Code for Information Interchange, or ASCII, each character is represented by a unique eight-bit binary code. So, the sentence, “Hello, I hope you had a great weekend,” is stored in the computer’s RAM as just a string of binary code.

While classical computers are powerful, the fact that they process data in bits limits their computing ability.

Enter quantum computers. Unlike classical computers, quantum computers store and process information in qubits, which have a unique feature that makes them powerful: superposition. Unlike bits, qubits can exist in two physical states, represented by 0 and 1, simultaneously. The ability to explore multiple possibilities at once allows quantum computers to process large volumes of data in a fraction of the time it would take even the most powerful classical computers. But, there’s a problem.

Quantum computers require highly controlled environments, such as very low temperatures, to maintain the qubits’ fragile quantum states. Hence, building and maintaining them is extremely costly.

Seeing the unseen

Susarla has dedicated her professional life to advancing research in this field. However, her mission requires an accurate understanding of subatomic-level interactions.

Susarla is like a sociologist investigating social dynamics in a close-knit neighborhood — but instead of people, she studies the interactions between a material’s sub-atomic particles, and how they affect the overall material’s behavior.

Let’s use silicon, the most common semiconductor material, as an example. Imagine silicon as a neighborhood: its atoms are the houses, and the electron behaviors are like the interactions between the neighbors. Just as a sociologist needs to observe both macro- and micro-level dynamics to understand relationships in a neighborhood, Susarla and other material scientists need to have both perspectives to better understand why a material like silicon behaves the way it does. But Susarla says that traditionally, materials scientists don’t take this approach.

“There are tools to measure materials’ behavior at a large scale, and computational materials scientists have methodologies to measure and predict electronic states. But, there is no way to do both things simultaneously,” she says.

She adds that because studying subatomic interactions is expensive, computational materials scientists simulate a small sample, typically about six atoms.

“They also assume that atoms are perfectly arranged,” Susarla says, “but it never happens that way. Materials are imperfect.”

Her approach, one that could lead to more stable quantum computers, is distinct in two ways.

Using, as she puts it, “two of the very best microscopes,” Susarla can study thousands of atoms under various temperature and pressure conditions.
“I’m blessed that ASU has a lot of world-class tools, and I also access the resources at many Department of Energy national labs,” she says.

Specifically, Susarla uses the FEI Titan ETEM and Nion UltraSTEM 100 microscopes, which allow her to study a material’s electronic behavior using a technique known as Electron Energy Loss Spectroscopy. For her, using these two microscopes is like a sociologist walking the streets of the sample neighborhood, talking to people and observing how they interact with each other.

The second part of the puzzle is accurately analyzing the data generated from the microscopes. Susarla deploys data processing algorithms powered by AI to extract information about how materials behave at the smallest scale possible.

Combining the bird’s eye view and the zoomed-in view of a material leads to insights that are useful in designing more stable material systems for quantum computers’ hardware. This would not only make financial and other systems safer but also help accelerate breakthroughs in fields like medicine, clean energy and secure communication — all of which contribute to people living longer, healthier lives. Susarla is thrilled to be recognized for the contributions she has made not only to quantum computing but also to the microscopy field.

“It has definitely brought me into the limelight,” she says. “It’s a huge responsibility because I need to continue delivering high-quality work that I’ve been awarded for. But I’m ready to do that.”

Susarla adds that her receiving the award inspires the students in her group to continue making great strides in their research.

“They feel great about contributing to the community,” she says.

Ten years of progress in one

When Susarla embarked on the journey of understanding materials’ behavior as a doctoral student, she couldn’t have imagined that the field would evolve so quickly.

She says that, at the time, electron microscopy was all about taking photos of atoms and figuring out patterns purely from the photographs. With advances in technology and technique, materials scientists can now see atomic movements, and Susarla is even more excited about how AI will impact the field.

“Today, we can measure displacements at as tiny as 10 picometers scale, which is absolutely bizarre,” she says.

To put it in perspective, a picometer is equal to one trillionth of a meter.

“All the mundane tasks, like operating the microscope and tuning the microscope, will all be automated in the future thanks to AI,” she says. “I’m excited about this because now the students can spend their time actually thinking about what they’re measuring, rather than doing laborious tasks.”

Susarla also says that AI is streamlining the data processing step, which helps the team get to useful conclusions at a speed never possible before.

“It used to take a student around 24 hours logging data collected from the microscope, and now we’re at the verge of being able to automate that step, freeing the students to analyze the data and draw conclusions,” she says.

It might not be tomorrow or the following week, but, in the future, Susarla’s research could lead to technologies that redefine how we treat disease, protect our health and secure the systems we rely on. These advances could ultimately extend the human lifespan just as scientific breakthroughs did a century ago.

About The Author

Roger Ndayisaba

Roger Ndayisaba is a communications specialist embedded in the School for Engineering of Matter, Transport and Energy. Roger earned a bachelor's degree of arts in communications from Southern New Hampshire University. Before joining the Fulton Schools, Roger was on the African Institute for Mathematical Sciences (AIMS) communications team, implementing marketing strategies to raise its brand awareness.

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