This month, three UCSB projects received awards from the Institute for Energy Efficiency (IEE). The IEE’s Research Seed and Software Impact Seed Programs provide critical introductory funding to launch new research projects that promote energy efficiency in areas ranging from computing and communications to infrastructure. 

"IEE seed funding empowers our researchers to advance innovative ideas that are still in the early stages of development but hold tremendous potential to improve energy efficiency,” said Steven DenBaars, director of the IEE and a professor of materials and electrical and computer engineering. “These projects often serve as launchpads for securing additional external funding, extending their impact from the laboratory to commercial products and broader societal benefits.”

The IEE Research Seed program began in 2019 to fund promising energy-efficiency research each year, while supporting new faculty members and novel collaborations across disciplines and departments. In 2022, the IEE added the annual Investment Group of Santa Barbara (IGSB) Software Impact Grant to bolster software projects that lead to significant advances or risk reduction, and are likely to result in commercial products that can have a positive effect on society.

Since the two IEE seed programs began, UCSB faculty members have received a total of $1.4 million in funding, said Mark Abel, executive director of IEE. The money comes entirely from private donations. “The IEE seed programs recognize innovative projects that have the potential to make a real impact on energy efficiency,” he said. “These awards have enrolled more than twenty new faculty members in IEE who have gone on to successfully apply for external grants or start new commercial ventures building on their seed projects.”

 “This year’s seed projects explore critical gaps in the current energy-efficiency landscape through new collaborations and cutting-edge technology,” said emeritus professor of electrical and computer engineering John Bowers, who served as inaugural IEE director until his retirement last spring.  “These researchers are continuing the tradition of excellence in scientific discovery that IEE is known for, and we are looking forward to seeing the directions and the impact of their work on the wider community.”

Sustainable Magnets for Electric Motors

Quiet, ubiquitous electric motors power everything from smartphones and electric toothbrushes to e-bikes and public transport. While these motors have sustainability advantages over their gas-powered equivalents, their components can come from materials that have detrimental effects, said Bolin Liao, an associate professor and vice-chair of the Department of Mechanical Engineering. “One pressing challenge now is related to rare earth elements, which are super important for a lot of applications, including the magnets at the heart of electric motors,” he said. “But the mining process for rare earth is environmentally very harmful,” as it is energy-intensive and creates water pollution, radioactive waste, and health issues for miners. The demand for these magnets — in particular, neodymium-based magnets — is expected to double by 2035.

Liao will join his colleague Stephen Wilson, a professor in the Materials Department to seek out a sustainable magnetic material. “Bolin will use his expertise in machine-learning techniques and computation to try to predict interesting chemistries that will give you magnets with functional advantages,” said Wilson, who is also director of the NSF Quantum Foundry at UCSB. Wilson and his lab will then make these materials and conduct in-depth characterization of their magnetic properties.

The dream, Wilson said, is to develop materials that will not only reduce the need for rare earth materials, but that are also stronger than those used in the current technology. “If you can make a magnet stronger, then you can have less of it,” Wilson said. “The magnet — and the electric motor — can be lighter and more efficient.”  

The pair plan to use their seed-grant research to pursue larger awards, which will allow them to scale up their work. “I'm very grateful for this seed grant, which will give us new resources to explore this new area,” Liao said. “This is a very rapidly evolving field. I'm hopeful that this can lead to a lot of new discoveries beyond the scope of this project.” 

Cryogenic Optical Modulators for Electro-optic Transduction (COMET)

The second IEE Seed Grant tackles important work related to energy efficiency in quantum computing conducted by professor Galan Moody and project scientist Paolo Pintus, both based in the Department of Electrical and Computer Engineering. 

In recent years, quantum computing has excited both scientists and the public for its promise to revolutionize research and to perform complex computational work faster and more efficiently than energy-hungry classical computing. But future quantum computers will need ways to transfer data at extremely low temperatures, close to zero Kelvin. And current superconducting quantum computers in development have relied on coaxial cables for data input and output, which are both bulky and introduce heat into the cryogenic computer.  

“The energy cost of moving information is one of the biggest challenges in scaling quantum computers,” said Moody. “By reimagining how we connect cryogenic quantum processors to room-temperature electronics, we hope to reduce power consumption and enable architectures that are more efficient and more scalable.”

To address this, Moody and Pintus want to investigate the potential for replacing these cables with optical fibers, which can transmit data via light, or optical, signals. Optical fibers can transmit signals at the speed of light over long distances, Pintus said, “and optical fibers are tiny, so you can pack tons of them in the same space and transmit more data.”

A quantum computer using optical fibers will need an optical modulator. An optical modulator converts electrical signals from a quantum computer to light and can provide a link between the cryogenic quantum computing temperature and the room-temperature devices that read the data the quantum computer produces. 

With the seed grant, the team will conduct modeling and design work for cryogenic optical modulators, with a goal of developing a modulator that needs very little power while successfully transmitting the amount of data that a quantum computer can produce. They have also begun collaborating with Google Quantum AI and Raytheon BBN Technologies, and hope that, if they find a feasible model, they can use this grant as a springboard to additional support for hardware fabrication. 

“I’m excited that this seed grant gives us the opportunity to explore new device concepts that sit at the intersection of quantum physics, materials science, and integrated photonics,” Moody said. “It’s a chance to take bold steps toward optical interconnects that could help accelerate scalable quantum computers.”

Life After GPUs: Multiplier-Free LLM Inference for Energy-Efficient AI

Large language models are everywhere, addressing questions about complex scientific research — and about what to cook for dinner. Regardless of the query, each response involves billions of multiplication operations, said electrical and computer engineering professor Kerem Çamsarı, this year’s IGSB Software Impact Grant recipient, and many AI models “think” too hard to answer the simplest of questions, adding up to enormous drains of power. “It’s a very important field,” Çamsarı said, “especially because it has already penetrated daily life. You know, my grandmother uses ChatGPT now. So we have to do something about the energy consumption involved.”

To reduce the energy involved, Çamsarı and his colleagues in the Department of Electrical and Computer Engineering, postdoctoral scholar Corentin Delacour and NSF Fellow Kyle Lee, intend to swap the multiplication that AI models currently use to respond to queries for a more efficient approach based on addition, rooted in Çamsarı’s expertise in probabilistic computing. As part of their award, they are refining an algorithm that allows an AI model to adjust how much data it samples to solve a problem based on the nature of the problem it is trying to solve.

Çamsarı is one of several of this year’s recipients who have been a part of previous IEE Seed Grants, and have successfully used these grants to launch larger projects. “IEE has been very helpful in the past for me,” he said. “I think my very first grant was from the Institute and that turned into much bigger things. I'd like to repeat that success with this project.”