BU’s 2022 NSF CAREER Award Winners Innovate in Single Molecule Data and Circuit Systems | The edge

This year, two Boston University researchers won prestigious National Science Foundation (NSF) Early Career Awards intended to celebrate future superstars.

Manos Athanassoulis, assistant professor of computer science in the College of Arts and Sciences, and Masha Kamenetska, assistant professor of chemistry and physics at CAS, received the Faculty Early Career Development (CAREER) awards, a respected five-year grant that supports young teachers. Both scientists are at the forefront of making the technology that powers our modern world smaller, faster and more reliable.

Kamenetska is studying how to make transistors – the tiny semiconductors in electrical circuits that work in almost any technology – from a single molecule. And Athanassoulis is working to redesign the big data systems used in nearly every industry, from social media to online shopping to scientific research. The two researchers are also laying the foundation for the next generation of scientists by using the funding to support students and mentorship. The edge caught up with BU’s latest CAREER award winners to learn more about what they’re working on.

Masha Kamenetska

Transistors—crucial components of a circuit which switch electric currents on and off to regulate and amplify electronic signals – are fundamental technology; the computer or smartphone you’re reading this on wouldn’t work without them. They’ve come a long way since their beginnings in bulky radios, computers that took up entire rooms, and bulky telephone exchanges. The chip that powers the new iPhone 14 Pro, for example, to 16 billion of them, a number once considered unlikely. Over time, scientists rushed to drastically reduce transistors to make electronics portable and more powerful. But how much smaller can they be?

“Scientists are hitting a fundamental limit to how big we can get with current technology,” says Kamenetska. “If we scale today’s silicon-based transistors much smaller than they are now, they won’t work.”

It’s because of the physical properties of silicon, she says, which is largely used in the manufacture of transistors and computer chips. Kamenetska, who founded the Kamenetska Research Group at BU in 2017, is investigating the possibility of replacing current transistor technology with a single molecule. With his NSF CAREER Awardshe and her team are studying how a single molecule can work as part of a circuit.

She is particularly interested in studying circuits formed with paramagnetic molecules, which have a property that could help create an internal on/off switch, such as in a transistor. If you think back to high school chemistry class, you’ve probably seen a diagram that shows the electrons around the nucleus of an atom in pairs, their spins compensating for each other. Having paired electrons is the norm for many molecules, but a paramagnetic molecule has an unpaired electron that spins on its own. This creates a “magnetic moment,” Kamenetska says, due to its rotation on its axis, which can potentially be tipped or controlled by external signals.

Scientists are a long way from creating functional single-molecule circuits because it’s unclear how they can be controlled and replicated, Kamenetska says. But she hopes to uncover the basic science needed to open the door to a whole new generation of single-molecule-powered devices.

Manos Athanassoulis

If you’re just a casual Internet user, it can be easy to forget that behind every web page is a complex data system that stores and manages tons of information. Data systems are an essential part of modern computing and technology – and they are also the bread and butter of Athanassoulis’ research at BU Data-Intensive Systems and Computing Lab. Since starting the lab in 2019, one of Athanassoulis’ main projects has been to transform a common type of data system, called a Log Structured Merge (LSM) system, which runs behind the scenes of many types of web applications.

An LSM-based system structures data into a “tree” and helps power programming that supports social media platforms, e-commerce, and other data-intensive applications. Meta, for example, has developed an LSM system called RochesDB which is part of the infrastructure of Meta and Facebook and is used by other big tech companies like Netflix, Airbnb, Yahoo, Pinterest and LinkedIn.

But since most computations are performed on public and private clouds, applications increasingly face interference from each other, says Athanassoulis, leading to some uncertainty as to how the system will react. With NSF CAREER Award supportAthanassoulis and his team are creating a new generation of LSM-based data systems that can deliver near-optimal performance.

Making the system more reliable and less dependent on human intervention will require an interdisciplinary effort from experts in computing and data systems, algorithmic data mining, machine learning, and hardware understanding.

“This NSF CAREER grant will have a transformative effect on how we build and tune data systems,” says Athanassoulis, who became fascinated with computing after writing his first curriculum in fifth grade. “We want to build technological tools to manage and make sense of data and therefore the world around us.”

The grant also supports a number of graduate students, the development of new computer science classes and teaching materials, and targeted internship programs. Athanassoulis says he wants to foster a new generation of data systems experts, both at the doctoral and undergraduate levels. The end goal, along with building new systems, is to give students the opportunity to learn technical and societal skills that can help them solve important real-world problems. “That’s what I consider to be the most important measure of success,” says Athanassoulis.