Innovative approaches to make the world more energy efficient, proposed by UC Santa Barbara faculty, have received a significant boost from the Institute for Energy Efficiency (IEE). The IEE is an interdisciplinary research institute committed to improving energy efficiency across three key themes: smart societal infrastructure, computing and communications, and the food-energy-water nexus.
Recently, an IEE committee selected four proposals to be the inaugural recipients of research seed funding awards. The scope of projects ranges from protecting the citrus industry, increasing energy storage on the smart grid, and minimizing the carbon footprint of artificial intelligence (AI). Each project aligns with at least one IEE theme and will receive up to $50,000, support made possible by a gift from an anonymous donor
“Supporting projects in the early stages of development is an essential step to the creation and delivery of high-impact solutions for energy efficiency,” said John Bowers, IEE Director and Professor of Electrical and Computer Engineering at UCSB. “Each seed project addresses and attacks a grand challenge by taking an innovative approach or developing new technology. They will result in interdisciplinary research and leverage IEE’s legacy of scientific discovery.”
The seed program is intended to produce preliminary results that the researchers can use to apply for major external funding to further fund and expand their research. The awarded projects create a total of three new interdisciplinary partnerships and bring the innovative research of eight faculty, including four new junior faculty, to the IEE.
New proposals for funding will be accepted starting July 1, 2020.
Descriptions of the four selected projects are included below.
COLLABORATING TO PROTECT THE CITRUS INDUSTRY
A bacterial disease, HLB, which is spread by the Asian citrus psyllid (ACP), has reduced Florida’s citrus production by 50 percent from 2003-2017, according to the National Agricultural Statistics Service. HLB has no known cure and pesticides have only minimal impact on ACP. Recently, the ACP was detected in Southern California, along the ground freight corridors that link Los Angeles with the lower San Joaquin Valley, which is where the majority of the nation’s citrus is now grown.
Currently, there is one promising defense against ACP under development, Citrus Under Protective Screens (CUPS). The permanent protective screen structures block all pests larger than 0.5 microns from trees inside the structure. In small-scale tests, CUPS kept out the problematic pests and produced HLB-free trees.
However, CUPS have not been widely implemented because too many uncertainties exist about the productivity and economic returns of screen-protected citrus. A multi-disciplinary team, led by Professors Chandra Krintz and Rich Wolski from the Computer Science Department, and Steven DenBaars from the Materials and Electrical and Computer Engineering departments, plans to answer those questions. They plan to explore new technologies for measuring and controlling environmental conditions with and without CUPS in order to make them economically viable and sustainable for growers.
Their project, Sensing and Lighting for Citrus Under Protective Screens, involves researchers who specialize in lighting, computer science, entomology, farm operations management, and agriculture pathology. While their work will immediately benefit the citrus industry, the project also has the potential to impact crops grown in other controlled environments like greenhouses, or through alternative methods like vertical farming.
“The security of water, energy, and food are linked. Demand for all three is increasing, which is why the food-energy-water nexus is central to sustainable development and a central theme of the IEE,” said Mark Abel, Associate Director and Executive Advisor of the IEE. “This interdisciplinary project tests a solution and sets out to make it as affordable, efficient and sustainable as possible.”
The $50,000 grant allows the team to quantify the impact that CUPS have on growing conditions and identify potential opportunities for sensing, lighting, actuation, control and automation to minimize the costs imposed on growers. The team’s strategy includes using instruments like weather sensors, multi-spectral cameras, and insect traps, as well as evaluating lighting and robotic options, and incorporating machine learning.
In addition to establishing test CUPS at UCSB, researchers will also have access to the first experimental commercial-sized CUPS deployment, currently under construction at the Lindcove Research Extension Center in Tulare County.
BUILDING A PHOTO-BATTERY TO BOOST THE GRID
People tend to only think about energy storage when their laptop or cellphone batteries are running out of juice. However, energy storage is a key concept for utility companies, who are constantly managing the supply and demand of energy on the electrical grid. The more variability that exists in supply and demand, the more difficult it is to stabilize the grid. Battery energy storage systems (BESSs) provide scalable and modular utilities to mitigate fluctuations in energy supply and demand. They charge by drawing in excess power from the grid that can be stored, and they inject power back into the grid during times of high demand. Remaining problems with such systems include their limited capacity and unavailability in several parts of the world. Therefore, there is a constant need for new energy storage solutions.
Two Assistant Professors from UCSB, Raphaële Clément from the Materials Department and Gabriel Ménard from the Chemistry and Biochemistry Department, are teaming up to design a novel energy storage solution for the smart grid, in the form of a photoactive redox flow battery (P-RFB).
Like all batteries, RFBs store electrical energy as chemical energy and convert that energy back into electricity when needed. A battery has three main components: two terminals made of different chemicals, the anode and the cathode; and the electrolyte, a chemical medium that allows ions to transport chemical energy from one terminal to the other. In order to generate an electric current, ions transport current through the electrolyte while electrons flow between the terminals. RFBs are designed to hold energy in soluble, redox-active molecules that are stored in electrolyte reservoirs. Scaling up batteries to store more power simply requires bigger reservoirs of electrolytes.
“Grid-scale energy storage is becoming one of the main impediments to the broad implementation of renewables,” said Ménard. “For places with abundant sunshine, such as California, this potential new technology offers the ability to couple solar energy harvesting directly with energy storage, eliminating potential energy losses.”
In their project, Synthesis and Advanced Magnetic Resonance Characterization of New Photoactive Materials, Clément and Ménard propose replacing the two-step capture and storage of energy by designing and applying new photoactive electrode materials to RFBs. Photoactive electrodes are electric conductors that, following the absorption of light, trigger energy conversion. The collaboration between the two researchers combines the synthetic inorganic and electrochemical expertise of Ménard with the magnetic resonance (MR) characterization expertise of Clément.
To design and synthesize new photoactive materials and develop new MR techniques, Ménard and Clément plan to use the $50,000 to hire a senior graduate student and pay for the use of the nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) instruments at UCSB’s Materials Research Lab.
Clément and Ménard are two of the four junior faculty who are newly affiliated with the IEE through the seed funding program.
“We are thrilled to be a part of the IEE, its collaborative atmosphere, and team of scientists with different areas of expertise,” said Ménard. “There is unlimited potential to advance science.”
MAKING AI MORE ENERGY EFFICIENT
Training artificial intelligence (AI), an activity that involves processing vast amounts of data, is an energy-intensive process. One recent estimate by a researcher at the University of Massachusetts Amherst suggested that training a single AI creates a carbon dioxide (CO2) footprint of 626,000 pounds, or five times the lifetime emissions of the average American car. That same paper asserted that using a state-of-the-art language model for natural language processing equals the CO2 emissions of one human for 30 years. Both findings provide a jarring quantification of AI’s environmental impact, which becomes more troublesome since nearly every industry uses AI and machining learning (ML) to improve decision making and problem solving.
Reducing the energy footprint and optimizing technology that drives society is one of three core themes recently established by the IEE. Two projects awarded seed funding explore new solutions to challenges created by the widespread use of AI and machine learning and the resources required to train learning models and complete the necessary computations.
Professor Xifeng Yan and Assistant Professor William Wang, both faculty in the Computer Science Department, are teaming up to improve the energy efficiency of AI and machine learning at algorithmic and systems level. Their work could potentially impact industry and academia.
“AI is revolutionizing many industries, but most research projects focus only on its accuracy. We believe energy efficiency should be a critical factor in the development of sustainable AI systems,” said Wang, who has received research and faculty awards from Google, Facebook, IMB, Adobe, and the U.S. government’s Defense Advanced Research Projects Agency (DARPA). “Because AI is transforming our society, we also want to ensure it positively impacts our planet.”
Dmitri Strukov, an Electrical and Computer Engineering Professor, plans to tackle the challenge by advancing computer architecture and hardware. He proposes using hardware, designed similar to the human brain, for solving some of the hardest optimization problems. His project, Energy-Efficient Mixed-Signal Neuro-Optimization Hardware, employs mixed-signal neuromorphic circuits with integrated metal-oxide memristors, which are non-volatile memory devices that his group has been developing for the past ten years. Such circuits enable very dense, fast, and energy-efficient implementation of probabilistic vector-by-matrix multiplier, which is the most common operation in bio-inspired optimization algorithms. The preliminary results from his group show that the proposed hardware implementation is estimated to be 70 times faster and 20,000 times more energy efficient compared to the most efficient conventional approach.
With the seed funding, Strukov plans to redesign existing circuits and build an interdisciplinary team of people who specialize in algorithms, application domain, and system integration.
“I am excited to work with the IEE team and find new opportunities for collaboration, especially in areas I have never explored,” said Strukov. “The seed funding will be crucial for verifying our initial ideas. I hope it leads to a large-scale project to develop this technology that is especially suitable for solving some of the hardest computational problems.”