Carbon-based materials, including biochar, activated carbon, and graphite, play important roles in energy technologies, carbon management, environmental remediation, agriculture, and water treatment. Our group develops life cycle assessment, techno-economic analysis, systems modeling, and machine learning approaches to evaluate and guide the sustainable production and use of these materials.
Featured Projects
Assessing the Barriers and Opportunities for Establishing a Resilient Green Graphite Supply Chain in the United States
Graphite is an essential component in clean energy technologies, including lithium-ion batteries, and is primarily imported into the United States. Synthetic graphite could be a more sustainable source. A major challenge is the current reliance on synthetic graphite production on fossil fuel-based feedstocks. Recent advancements in using waste biomass or plastic have made “green” synthetic graphite a more appealing option for domestic supply capacity. In this project, we will identify and analyze key industrial, policy, and regulatory opportunities and barriers. We will evaluate the environmental, economic, and societal implications of scaling up the synthesis of green graphite. Our goal is to pave the way for a resilient and sustainable green graphite supply chain within the United States. This project is sponsored by the Alfred P. Sloan Foundation.
CAREER: Biochar Systems for Sustainable Applications in the Food-Energy-Water Nexus
Biochar is a carbon-rich solid byproduct of thermochemical biomass conversions. It has potential applications in food, energy, and water systems. This project aims to advance potential biochar applications by (1) using artificial intelligence (machine learning) approaches to predict process data and life cycle assessment (LCA) of various combinations of biomass feedstocks, conversion pathways, and applications of biochar; (2) building an integrated framework for modeling and analysis of biochar systems in the food-energy-water (FEW) nexus; and (3) demonstrating the framework through real-world case studies in different geographic, temporal, and socioeconomic contexts. This project is supported by the U.S. National Science Foundation.
Research Themes
Biochar and nature-based carbon management
Our group examines biochar as part of integrated nature-based and circular carbon-management systems. We evaluate pathways that connect afforestation and reforestation on marginal lands, urban tree-waste utilization, durable wood products, and biochar production. This theme supports the design of biochar pathways that can provide environmental benefits while considering economic feasibility, ecosystem impacts, material substitution, and tradeoffs across land and resource systems.
Machine learning for biomass-derived carbon materials
Our group explores how machine learning can accelerate the sustainable design and application of biomass-derived carbon materials by predicting material properties, estimating life cycle inventory data, and identifying key feedstock and processing drivers, and accelerating early-stage screening of feedstocks, conversion processes, and end uses.
Selected Related Publications
Zhang, B., Lan, K., Yang, F., Xu, Y., Piotto, D., Ashton, M., and Yao, Y. (2025). Innovative reforestation mosaics on marginal land in the globally important Mata Atlântica biome can create climate and economic co-benefits. One Earth, 8(5), 101306. https://doi.org/10.1016/j.oneear.2025.101306
Zhang, B., Lan, K., Harris, T.B., Ashton, M.S., and Yao, Y. (2023). Climate-smart forestry through innovative wood products and commercial afforestation and reforestation on marginal land. Proceedings of the National Academy of Sciences, 120(23), e2221840120. https://doi.org/10.1073/pnas.2221840120
Lan, K., Zhang, B., and Yao, Y. (2022). Circular utilization of urban tree waste contributes to the mitigation of climate change and eutrophication. One Earth, 5(8), 944–957. https://doi.org/10.1016/j.oneear.2022.07.001
Wang, H.S.H. and Yao, Y. (2023). Machine learning for sustainable development and applications of biomass and biomass-derived carbonaceous materials in water and agricultural systems: A review. Resources, Conservation and Recycling, 190, 106847. https://doi.org/10.1016/j.resconrec.2022.106847
Liao, M., Kelley, S.S., and Yao, Y. (2020). Generating energy and greenhouse gas inventory data of activated carbon production using machine learning and kinetic-based process simulation. ACS Sustainable Chemistry & Engineering, 8(2), 1252–1261. https://doi.org/10.1021/acssuschemeng.9b06522