Resnick Young Investigators Symposium
The Resnick Young Investigators Symposium celebrates innovators in the science and technology of sustainability. The program highlights young researchers whose work shows great promise in tackling key science and engineering challenges in sustainability.
2023 Program
Opening Comments
Climate-Informed Adaptive Water Supply Planning
Dr. Sarah Fletcher, Assistant Professor of Civil and Environmental Engineering and Center Fellow at the Woods Institute for the Environment at Stanford University
Water planners face the challenge of ensuring reliable, affordable water supplies in a changing and uncertain climate. Adaptive planning approaches, in which planners delay or change action and respond as the climate changes over time, have the potential to enable reliability without unnecessary, expensive infrastructure development. However, adaptive planning also poses a risk: When will we have learned enough to adapt? And what changes should we make? The answers are highly dependent on the local climate. Regions facing slow, long-term change in average precipitation require different responses than those facing increased frequency of short, intense droughts. In regions where decadal oscillations dominate precipitation variability, long-term trends are more difficult to discern and plan for. In this talk, I present progress towards a computational framework for climate-informed adaptive planning using contrasting case studies in sub-Saharan Africa and California.
Creative Machine Learning Approaches for Climate Change Detection
Dr. Zachary Labe, Postdoctoral Research Associate at Princeton University and NOAA GFDL
The popularity of machine learning methods is rapidly expanding in nearly all areas of Earth science. The interest in these tools also coincides with a growing influx of observational and modeled data and the need for high efficiency in solving predication problems. However, there is also some hesitancy in adopting the use of deep learning algorithms due to concerns about their reliability, reproducibility, and interpretability.
In climate science, we often consider signal-to-noise problems to help disentangle anthropogenic climate change from natural variability. These applications typically involve complicated relationships between different feedbacks at play in the ocean, cryosphere, land, and atmosphere. Recent work has shown that neural networks can be a promising tool for solving these types of statistical problems when combined with explainability techniques developed by the fields of computer science and image processing. Interestingly, these methods have revealed that neural networks often spatially leverage regional patterns of climate change to make their predictions. In this talk, I will share examples from climate science that use a few of these visualization methods to peer into the "black box" of neural networks, which help us to better understand their decision-making process while also learning new science. These same machine learning visualization methods can be easily adapted for a wide variety of applications in global environmental change.
30-Minute Break
CRISPR-guided insights into the biology of methanogenic archaea
Dr. Dipti D. Nayak, Assistant Professor in the Division of Genetics, Genomics, Evolution and Development in the Department of Molecular and Cell Biology at University of California, Berkeley
Microorganisms that produce methane gas as a by-product of respiration, commonly known as methanogens, are prevalent in a wide range of anoxic environments on our planet. Microbial methanogenesis accounts for 75 to 80 percent of the methane emissions annually. A fundamental understanding of methanogenesis is crucial to develop effective intervention strategies to curb methane emissions globally. To this end, my research group develops and applies high-throughput genetic approaches, including CRISPR-Cas9 based genome editing, to study enzymes involved in methanogenesis. In this talk, I will focus on the enzyme methyl-coenzyme M reductase (MCR) that catalyzes a chemical reaction that leads to the formation of methane. First, I will describe how certain amino acids in MCR acquire unusual post-translation modifications (PTMs) and then discuss the ramifications of these PTMs on methane production. Next, I will discuss the use of Cryo-electron microscopy to understand the intricate process involved in the assembly of MCR and the proteins involved in this process. Overall, these studies provide new targets for the design of MCR inhibitors that can be applied to landfills and rice paddies or added to livestock feed to reduce methane emissions.
Redox-mediated electrochemical strategies for precision separations: a pathway for decarbonization and circularity
Dr. Xiao Su, Assistant Professor of Chemical and Biomolecular Engineering at University of Illinois at Urbana-Champaign
Innovations in separation technologies are critical to guarantee our supply-chain security, the availability of chemical and materials resources, and clean air and water at a global scale. Electrochemical separations can promote sustainability through the integration of renewable energy, plug-and-play modularity, and elimination of secondary waste. However, the deployment of electrochemical technologies has been limited by the lack of molecular selectivity for many multicomponent separation contexts. Here, we discuss molecular design strategies that overcome these challenges, and enable us to achieve highly selective electrochemical separations for major application areas in energy and sustainability.
First, we discuss recent advances from our group on the design of redox-(co)polymers for imparting selectivity towards critical element recovery, materials recycling, and environmental remediation. Through synthetic control of redox-active organometallic systems, we can superimpose non-covalent interactions onto electrodes that reach beyond double-layer effects, and achieve specificity towards target species. Next, we translate these approaches to innovate separation processes for organic-phase chemical manufacturing, such as demonstrating a new approach for the electrochemical recycling of homogeneous organometallic catalysts, and designing chiral interfaces for electrochemically-driven enantioselective interactions. We show that by "programming" the polymer structure, we can access precise control over binding and release towards target species, and even tap into supramolecular effects that amplify selectivity.
Finally, we discuss the incorporation of these functional materials into electrochemical architectures, that integrate distinct reaction and separation processes into a single step. We utilize this process intensification strategy for the energy-efficient capture and destruction of perfluoroalkyl substances (PFAS), and the waste valorization of nitrogenous pollutants. Our work highlights the tremendous versatility of electrochemical separations, and its potential for decarbonization and sustainability across major areas of chemical and biochemical manufacturing, resource recovery and recycling, environmental management, and water purification.