Dan Molzahn, assistant professor in the school of electrical and computer engineering and SEI initiative lead for the Energy Club received the outstanding teacher award from the College of Engineering (COE) as a part of its third annual Faculty awards. COE honored eight faculty members for their excellence in research, service, teaching, inventorship, and commercialization.

In addition to his research on energy systems, Molzahn has a goal of educating the next generation of electric power engineers. For instance, he leads a 30-student Vertically Integrated Projects (VIP) team that develops video game simulations of power grids operating during extreme events. A first iteration of the game currently is installed at the Georgia Tech Dataseum in the Price Gilbert Library and plans are underway to incorporate a version into next year’s Seth Bonder high school summer camps.

The Energy Policy Innovation Center (EPICenter), along with the Beneficial Electrification League and Wells Fargo, hosted the Georgia Electrification Leadership Summit on the Georgia Tech campus. More than 140 people from the energy industry participated in the highly engaged event that included discussions on innovations and challenges in electrification in the transportation, residential, and industrial sectors. Additionally, the event addressed the economic development that the recent federal funding in the energy area is expected to bring to the state of Georgia.

The event began with a virtual welcome address by Georgia U.S. Sen. Jon Ossoff, followed by an introduction by Joe Hagerman, the director of EPIcenter, that operates within the Strategic Energy Institute at Georgia Tech. EPICenter was created to provide an unbiased and interdisciplinary framework for stimulating innovation in energy policy and technology for the Southeast region. Keith Dennis, founder and CEO of the Beneficial Electrification League, engaged the audience with his presentation on the benefits of electrification, followed by key energy industry leaders from the state of Georgia discussing their viewpoints on electrification opportunities in their industry. The morning keynote by Bentina Terry, senior vice president of Customer Strategy and Solutions at Georgia Power, brought focus on the everyday customer. Terry said they can be swayed with energy solutions only if the solutions providers advocate the benefits through the lens of the consumer.    

The stakeholder dialogue on electric transportation included Georgia Public Service Commissioner Tim Echols, who emphasized that the state of Georgia needs to focus on expanding the state’s transportation infrastructure to meet the rising EVs on Georgia roads and the urgent need for electrification in transportation. Richard Simmons, director of Research and Studies at the Strategic Energy Institute, also brought home the fact that transportation sector has caught on to the benefits of electrification more than any other sector in the country. GDOT team member in the discussion revealed the timeline of the National Electric Vehicle Infrastructure (NEVI) program that has $135 million in funds apportioned to the state of Georgia.

On electrification in residential homes, panelists including Anita Moreno, Michelle Moore and Andrea Pinabell shared different perspectives and examples of the huge impact electrification has in residential homes, especially in low and moderate income and rural communities of Georgia.

The team from the Georgia Environmental Finance Authority, an entity that funds environmental infrastructure projects in the state, discussed the historical funding coming through the Infrastructure Investment and Jobs Act (Bipartisan Infrastructure Law) and Inflation Reduction Act. With more than $300 million coming through the Georgia State Energy Office and most of the funding residential focused, the team discussed the challenges and consumer expectations and how they ensure projects that get funded save money and lead to client satisfaction.

Stakeholder dialogue on electrification of commercial technology included Chandra Farley, the chief sustainability officer of the City of Atlanta, who discussed decarbonization of public buildings, training the workforce, and electrification of the public fleet, while advancing the city’s goal to achieve 100% clean energy by 2035. Panelists also discussed heat pumps as a cost-effective method of supplying low-temperature heat for industrial processes and the advantages of industrial heat pumps over combustion technologies for electrification and energy efficiency.

“At EPICenter, we leverage Georgia Tech’s expertise and innovation to help inform energy policy and technology for the Southeast,” said Hagerman. “The GA Electrification Leadership Summit is another example of how we have brought together diverse stakeholders to foster collaboration and dialogue on Georgia’s energy future. EPICenter will continue to support electrification, energy access, and deep community engagement. Georgia Tech and EPICenter can play an outsized role in helping the Southeast achieve a vibrant, clean, and competitive energy future for all Georgians.”

Over 9% of global passenger vehicle sales last year were electric vehicles (EVs) according to Bloomberg New Energy Finance. EV sales are surging due to a combination of policy support, improvements in battery technology, more charging infrastructure, and new compelling vehicles from automakers.

To address the rapid growth in the EV industry, the George W. Woodruff School of Mechanical Engineering has partnered with Siemens to offer a new course, Electric Vehicles & the Grid. The course launched in the spring semester and is providing a transformative learning experience to Georgia Tech students while preparing them to charge into the future. 

With a focus on innovation and sustainability, Electric Vehicles & the Grid teaches engineering principles of electric transportation and the energy infrastructure. The class also covers the emerging technologies of batteries, renewables, and connectivity that will allow further optimization of the products with the grid. 

Although EV courses are taught across the nation, the class's additional focus on the grid is a component that is missing from courses taught at other institutions.  

Read Full Story on the George W. Woodruff School of Mechanical Engineering Website

We have a problem with our current solar cells. They were built with very little thought towards end-of-life. Current solar panels tend to last twenty to thirty years. As those solar panels start to age, we are left with the challenge to think about how to recycle them. When the National Science Foundation (NSF) put out an interdisciplinary challenge for clean energy, Dr. Correa-Baena, Dr. Naomi Deneke, and Dr. Ilke Celik partnered to write a proposal to tackle recycling of perovskite solar cells.

Read Full Story on the MSE website.

- Written by Benjamin Wright -

As Georgia Tech establishes itself as a national leader in AI research and education, some researchers on campus are putting AI to work to help meet sustainability goals in a range of areas including climate change adaptation and mitigation, urban farming, food distribution, and life cycle assessments while also focusing on ways to make sure AI is used ethically and equitably.

Josiah Hester, interim associate director for Community-Engaged Research in the Brook Byers Institute for Sustainable Systems (BBISS) and associate professor in the School of Interactive Computing, sees these projects as wins from both a research standpoint and for the local, national, and global communities they could affect.

“These faculty exemplify Georgia Tech's commitment to serving and partnering with communities in our research,” he says. “Sustainability is one of the most pressing issues of our time. AI gives us new tools to build more resilient communities, but the complexities and nuances in applying this emerging suite of technologies can only be solved by community members and researchers working closely together to bridge the gap. This approach to AI for sustainability strengthens the bonds between our university and our communities and makes lasting impacts due to community buy-in.”

Flood Monitoring and Carbon Storage

Peng Chen, assistant professor in the School of Computational Science and Engineering in the College of Computing, focuses on computational mathematics, data science, scientific machine learning, and parallel computing. Chen is combining these areas of expertise to develop algorithms to assist in practical applications such as flood monitoring and carbon dioxide capture and storage.

He is currently working on a National Science Foundation (NSF) project with colleagues in Georgia Tech’s School of City and Regional Planning and from the University of South Florida to develop flood models in the St. Petersburg, Florida area. As a low-lying state with more than 8,400 miles of coastline, Florida is one of the states most at risk from sea level rise and flooding caused by extreme weather events sparked by climate change.

Chen’s novel approach to flood monitoring takes existing high-resolution hydrological and hydrographical mapping and uses machine learning to incorporate real-time updates from social media users and existing traffic cameras to run rapid, low-cost simulations using deep neural networks. Current flood monitoring software is resource and time-intensive. Chen’s goal is to produce live modeling that can be used to warn residents and allocate emergency response resources as conditions change. That information would be available to the general public through a portal his team is working on.

“This project focuses on one particular community in Florida,” Chen says, “but we hope this methodology will be transferable to other locations and situations affected by climate change.”

In addition to the flood-monitoring project in Florida, Chen and his colleagues are developing new methods to improve the reliability and cost-effectiveness of storing carbon dioxide in underground rock formations. The process is plagued with uncertainty about the porosity of the bedrock, the optimal distribution of monitoring wells, and the rate at which carbon dioxide can be injected without over-pressurizing the bedrock, leading to collapse. The new simulations are fast, inexpensive, and minimize the risk of failure, which also decreases the cost of construction.

“Traditional high-fidelity simulation using supercomputers takes hours and lots of resources,” says Chen. “Now we can run these simulations in under one minute using AI models without sacrificing accuracy. Even when you factor in AI training costs, this is a huge savings in time and financial resources.”

Flood monitoring and carbon capture are passion projects for Chen, who sees an opportunity to use artificial intelligence to increase the pace and decrease the cost of problem-solving.

“I’m very excited about the possibility of solving grand challenges in the sustainability area with AI and machine learning models,” he says. “Engineering problems are full of uncertainty, but by using this technology, we can characterize the uncertainty in new ways and propagate it throughout our predictions to optimize designs and maximize performance.”

Urban Farming and Optimization

Yongsheng Chen works at the intersection of food, energy, and water. As the Bonnie W. and Charles W. Moorman Professor in the School of Civil and Environmental Engineering and director of the Nutrients, Energy, and Water Center for Agriculture Technology, Chen is focused on making urban agriculture technologically feasible, financially viable, and, most importantly, sustainable. To do that he’s leveraging AI to speed up the design process and optimize farming and harvesting operations.

Chen’s closed-loop hydroponic system uses anaerobically treated wastewater for fertilization and irrigation by extracting and repurposing nutrients as fertilizer before filtering the water through polymeric membranes with nano-scale pores. Advancing filtration and purification processes depends on finding the right membrane materials to selectively separate contaminants, including antibiotics and per- and polyfluoroalkyl substances (PFAS). Chen and his team are using AI and machine learning to guide membrane material selection and fabrication to make contaminant separation as efficient as possible. Similarly, AI and machine learning are assisting in developing carbon capture materials such as ionic liquids that can retain carbon dioxide generated during wastewater treatment and redirect it to hydroponics systems, boosting food productivity.

“A fundamental angle of our research is that we do not see municipal wastewater as waste,” explains Chen. “It is a resource we can treat and recover components from to supply irrigation, fertilizer, and biogas, all while reducing the amount of energy used in conventional wastewater treatment methods.”

In addition to aiding in materials development, which reduces design time and production costs, Chen is using machine learning to optimize the growing cycle of produce, maximizing nutritional value. His USDA-funded vertical farm uses autonomous robots to measure critical cultivation parameters and take pictures without destroying plants. This data helps determine optimum environmental conditions, fertilizer supply, and harvest timing, resulting in a faster-growing, optimally nutritious plant with less fertilizer waste and lower emissions.

Chen’s work has received considerable federal funding. As the Urban Resilience and Sustainability Thrust Leader within the NSF-funded AI Institute for Advances in Optimization (AI4OPT), he has received additional funding to foster international collaboration in digital agriculture with colleagues across the United States and in Japan, Australia, and India.

Optimizing Food Distribution

At the other end of the agricultural spectrum is postdoc Rosemarie Santa González in the H. Milton Stewart School of Industrial and Systems Engineering, who is conducting her research under the supervision of Professor Chelsea White and Professor Pascal Van Hentenryck, the director of Georgia Tech’s AI Hub as well as the director of AI4OPT.

Santa González is working with the Wisconsin Food Hub Cooperative to help traditional farmers get their products into the hands of consumers as efficiently as possible to reduce hunger and food waste. Preventing food waste is a priority for both the EPA and USDA. Current estimates are that 30 to 40% of the food produced in the United States ends up in landfills, which is a waste of resources on both the production end in the form of land, water, and chemical use, as well as a waste of resources when it comes to disposing of it, not to mention the impact of the greenhouses gases when wasted food decays.

To tackle this problem, Santa González and the Wisconsin Food Hub are helping small-scale farmers access refrigeration facilities and distribution chains. As part of her research, she is helping to develop AI tools that can optimize the logistics of the small-scale farmer supply chain while also making local consumers in underserved areas aware of what’s available so food doesn’t end up in landfills.

“This solution has to be accessible,” she says. “Not just in the sense that the food is accessible, but that the tools we are providing to them are accessible. The end users have to understand the tools and be able to use them. It has to be sustainable as a resource.”

Making AI accessible to people in the community is a core goal of the NSF’s AI Institute for Intelligent Cyberinfrastructure with Computational Learning in the Environment (ICICLE), one of the partners involved with the project.

“A large segment of the population we are working with, which includes historically marginalized communities, has a negative reaction to AI. They think of machines taking over, or data being stolen. Our goal is to democratize AI in these decision-support tools as we work toward the UN Sustainable Development Goal of Zero Hunger. There is so much power in these tools to solve complex problems that have very real results. More people will be fed and less food will spoil before it gets to people’s homes.”

Santa González hopes the tools they are building can be packaged and customized for food co-ops everywhere.

AI and Equity

Like Santa González, Joe Bozeman III is also focused on the ethical and sustainable deployment of AI and machine learning, especially among marginalized communities. The assistant professor in the School of Civil and Environmental Engineering is an industrial ecologist committed to fostering equitable climate change adaptation and mitigation strategies. His Social Equity and Environmental Engineering Lab works to make sure researchers understand the consequences of decisions before they move from academic concepts to policy decisions, particularly those that rely on data sets involving people and communities.

“With the administration of big data, there is a human tendency to assume that more data means everything is being captured, but that's not necessarily true,” he cautions. “More data could mean we're just capturing more of the data that already exists, while new research shows that we’re not including information from marginalized communities that have historically not been brought into the decision-making process. That includes underrepresented minorities, rural populations, people with disabilities, and neurodivergent people who may not interface with data collection tools.”

Bozeman is concerned that overlooking marginalized communities in data sets will result in decisions that at best ignore them and at worst cause them direct harm.

“Our lab doesn't wait for the negative harms to occur before we start talking about them,” explains Bozeman, who holds a courtesy appointment in the School of Public Policy. “Our lab forecasts what those harms will be so decision-makers and engineers can develop technologies that consider these things.”

He focuses on urbanization, the food-energy-water nexus, and the circular economy. He has found that much of the research in those areas is conducted in a vacuum without consideration for human engagement and the impact it could have when implemented.

Bozeman is lobbying for built-in tools and safeguards to mitigate the potential for harm from researchers using AI without appropriate consideration. He already sees a disconnect between the academic world and the public. Bridging that trust gap will require ethical uses of AI.

“We have to start rigorously including their voices in our decision-making to begin gaining trust with the public again. And with that trust, we can all start moving toward sustainable development. If we don't do that, I don't care how good our engineering solutions are, we're going to miss the boat entirely on bringing along the majority of the population.”

BBISS Support

Moving forward, Hester is excited about the impact the Brooks Byers Institute for Sustainable Systems can have on AI and sustainability research through a variety of support mechanisms.

“BBISS continues to invest in faculty development and training in community-driven research strategies, including the Energy Equity, Environmental Justice, and Community Engagement Faculty Fellows Program (with the Center for Sustainable Communities Research and Education), while empowering multidisciplinary teams to work together to solve grand engineering challenges with AI by supporting the AI+Climate Faculty Interest Group, as well as partnering with and providing administrative support for community-driven research projects.”

The Energy, Policy, and Innovation Center (EPICenter) hosted the 2024 cohort of Energy Unplugged, a Science, Technology, Engineering, Art, and Math (STEAM) summer program for high school students. The weeklong camp was held at Georgia Tech’s Atlanta and Savannah campuses this summer and has earned a reputation as one of the most sought-after high-school-level summer camps hosted by Georgia Tech. 

Rich Simmons, director of Research and Studies at the Strategic Energy Institute, has been the driving force behind the camp since its inception in 2019. Simmons, a faculty instructor in the George W. Woodruff School of Mechanical Engineering at Georgia Tech, brings his award-winning teaching expertise to high school students, ensuring that each session of Energy Unplugged is both educational and engaging. The program covered a range of timely topics, from basic energy principles such as conservation laws, electric circuits, and battery storage to more complex subjects like environmental impacts, data analytics, and decision-making. In addition, students were immersed in hands-on activities, interactive demonstrations, and power plant site visits.

During the first two days, students formed teams to construct catapults and mousetrap cars, discussed the underlying physics involving energy conversion, and then launched projectiles and vehicles to test their predictions. In one of the camp’s most popular activities, students raced remote-controlled cars around an obstacle course to learn about the importance of balancing multiple objectives, such as energy use, elapsed time, safety, and cargo capacity. The week culminated in a small-group mini-project, where campers applied the skills they had acquired to solve a real-world challenge — to optimize a cooking process using solar energy. Given specific parameters on energy generation, storage, and meal demand, the students determined the best approach to convert solar energy for cooking and storage to meet a daily lunch and dinner schedule for a food truck business. The program concluded with the campers presenting their preferred designs to an audience of parents, faculty, and staff, adding public speaking and technical presentation skills to their summer experiences.

Every year, students highlight the energy field trips to power plants, data centers, robotics labs, and makerspaces as some of their favorite aspects of the camp. A student poll during the final presentations used words like fun, informative, interesting, magical, epic, exciting, educational, and fantastical to describe the camping experience. The camp introduced the students to STEM-related careers and the many undergraduate programs that could provide a pathway for them. 

Energy Unplugged provides a portal for Georgia Tech graduate student interns such as Jake Churchill and staff members such as Jordann Shields to engage students with energy concepts, activities, career paths, and information about attending Georgia Tech. 

Energy Unplugged is administered by Georgia Tech Summer P.E.A.K.S. (Program for Enrichment and Accelerated Knowledge in STEAM) at CEISMC (the Center for Education Integrating Science, Mathematics, and Computing), the primary connection point between Tech faculty and students and the K-12 STEAM education community. Annually, CEISMC programs are accessible to more than 39,000 students; 1,700 teachers; and 200 schools in over 75 school districts throughout Georgia.

As part of the Strategic Energy Institute, EPICenter taps into regional and national expertise within academia, businesses, non-governmental organizations, and research facilities to provide an unbiased and interdisciplinary framework for driving innovation in energy policy and technology in the Southeast.

Nylon, Teflon, Kevlar. These are just a few familiar polymers — large-molecule chemical compounds — that have changed the world. From Teflon-coated frying pans to 3D printing, polymers are vital to creating the systems that make the world function better. 

Finding the next groundbreaking polymer is always a challenge, but now Georgia Tech researchers are using artificial intelligence (AI) to shape and transform the future of the field. Rampi Ramprasad’s group develops and adapts AI algorithms to accelerate materials discovery. 

This summer, two papers published in the Nature family of journals highlight the significant advancements and success stories emerging from years of AI-driven polymer informatics research. The first, featured in Nature Reviews Materials, showcases recent breakthroughs in polymer design across critical and contemporary application domains: energy storage, filtration technologies, and recyclable plastics. The second, published in Nature Communications, focuses on the use of AI algorithms to discover a subclass of polymers for electrostatic energy storage, with the designed materials undergoing successful laboratory synthesis and testing. 

“In the early days of AI in materials science, propelled by the White House’s Materials Genome Initiative over a decade ago, research in this field was largely curiosity-driven,” said Ramprasad, a professor in the School of Materials Science and Engineering. “Only in recent years have we begun to see tangible, real-world success stories in AI-driven accelerated polymer discovery. These successes are now inspiring significant transformations in the industrial materials R&D landscape. That’s what makes this review so significant and timely.”

AI Opportunities

Ramprasad’s team has developed groundbreaking algorithms that can instantly predict polymer properties and formulations before they are physically created. The process begins by defining application-specific target property or performance criteria. Machine learning (ML) models train on existing material-property data to predict these desired outcomes. Additionally, the team can generate new polymers, whose properties are forecasted with ML models. The top candidates that meet the target property criteria are then selected for real-world validation through laboratory synthesis and testing. The results from these new experiments are integrated with the original data, further refining the predictive models in a continuous, iterative process. 

While AI can accelerate the discovery of new polymers, it also presents unique challenges. The accuracy of AI predictions depends on the availability of rich, diverse, extensive initial data sets, making quality data paramount. Additionally, designing algorithms capable of generating chemically realistic and synthesizable polymers is a complex task. 

The real challenge begins after the algorithms make their predictions: proving that the designed materials can be made in the lab and function as expected and then demonstrating their scalability beyond the lab for real-world use. Ramprasad’s group designs these materials, while their fabrication, processing, and testing are carried out by collaborators at various institutions, including Georgia Tech. Professor Ryan Lively from the School of Chemical and Biomolecular Engineering frequently collaborates with Ramprasad’s group and is a co-author of the paper published in Nature Reviews Materials.

"In our day-to-day research, we extensively use the machine learning models Rampi’s team has developed,” Lively said. “These tools accelerate our work and allow us to rapidly explore new ideas. This embodies the promise of ML and AI because we can make model-guided decisions before we commit time and resources to explore the concepts in the laboratory."

Using AI, Ramprasad’s team and their collaborators have made significant advancements in diverse fields, including energy storage, filtration technologies, additive manufacturing, and recyclable materials.

Polymer Progress

One notable success, described in the Nature Communications paper, involves the design of new polymers for capacitors, which store electrostatic energy. These devices are vital components in electric and hybrid vehicles, among other applications. Ramprasad’s group worked with researchers from the University of Connecticut.

Current capacitor polymers offer either high energy density or thermal stability, but not both. By leveraging AI tools, the researchers determined that insulating materials made from polynorbornene and polyimide polymers can simultaneously achieve high energy density and high thermal stability. The polymers can be further enhanced to function in demanding environments, such as aerospace applications, while maintaining environmental sustainability. 

“The new class of polymers with high energy density and high thermal stability is one of the most concrete examples of how AI can guide materials discovery,” said Ramprasad. “It is also the result of years of multidisciplinary collaborative work with Greg Sotzing and Yang Cao at the University of Connecticut and sustained sponsorship by the Office of Naval Research.”

Industry Potential

The potential for real-world translation of AI-assisted materials development is underscored by industry participation in the Nature Reviews Materials article. Co-authors of this paper also include scientists from Toyota Research Institute and General Electric. To further accelerate the adoption of AI-driven materials development in industry, Ramprasad co-founded Matmerize Inc., a software startup company recently spun out of Georgia Tech. Their cloud-based polymer informatics software is already being used by companies across various sectors, including energy, electronics, consumer products, chemical processing, and sustainable materials. 

“Matmerize has transformed our research into a robust, versatile, and industry-ready solution, enabling users to design materials virtually with enhanced efficiency and reduced cost,” Ramprasad said. “What began as a curiosity has gained significant momentum, and we are entering an exciting new era of materials by design.”