Energy UROPs

Understanding structure-property relationships in mechanical stability of ultrastable metal-organic frameworks via machine learning

Industrial separation processes are energy-intensive, and current membrane technologies face trade-offs between cost, efficiency, and durability, making it challenging to identify materials that achieve high selectivity, permeability, and mechanical stability among countless potential candidates. This project uses machine learning to accelerate the discovery of mechanically stable metal-organic frameworks (MOFs) by predicting properties such as bulk and shear moduli. By uncovering critical structure-property relationships, these predictions guide the selection and design of MOFs that are better suited to address the outlined challenges. Developing durable and efficient MOFs for industrial membranes can reduce energy consumption, lower greenhouse gas emissions, and provide sustainable solutions to global water and energy challenges.

Global warming, driven by the accumulation of greenhouse gases such as CO₂ in the atmosphere, presents a critical challenge to our planet. This project addresses this issue by leveraging the catalytic power of carbonic anhydrase, an enzyme that catalyzes the conversion of CO₂ to bicarbonate, which is mineralized into carbonates, effectively sequestering CO₂. Furthermore, these carbonates have practical applications in construction materials, cement production, and soil amendment, offering additional economic value and offsetting the costs of CO₂ capture. By enhancing the efficiency of CO₂ conversion and providing useful by-products, this project holds significant potential for advancing carbon capture technologies and mitigating the impacts of climate change.

Global warming, driven by the accumulation of greenhouse gases such as CO₂ in the atmosphere, presents a critical challenge to our planet. This project addresses this issue by leveraging the catalytic power of carbonic anhydrase, an enzyme that catalyzes the conversion of CO₂ to bicarbonate, which is mineralized into carbonates, effectively sequestering CO₂. Furthermore, these carbonates have practical applications in construction materials, cement production, and soil amendment, offering additional economic value and offsetting the costs of CO₂ capture. By enhancing the efficiency of CO₂ conversion and providing useful by-products, this project holds significant potential for advancing carbon capture technologies and mitigating the impacts of climate change.

The lack of efficacy and cost efficiency of current capture technologies cannot sustain our planetary limit due to increasing rates of carbon emissions due to mass industrialization. Carbonic anhydrase is an enzyme that can speed up mineralization, however it must be immobilized to be re-used. But when immobilized, the carbon cannot reach the active binding sites due to steric hindrance. We have developed a new immobilization technique that extends the spacer arm allowing for easier binding between the enzyme and carbon substrate, thus decreasing the cost-efficient aspect of carbon capture.

The lack of efficacy and cost efficiency of current capture technologies cannot sustain our planetary limit due to increasing rates of carbon emissions due to mass industrialization. Carbonic anhydrase is an enzyme that can speed up mineralization, however it must be immobilized to be re-used. But when immobilized, the carbon cannot reach the active binding sites due to steric hindrance. We have developed a new immobilization technique that extends the spacer arm allowing for easier binding between the enzyme and carbon substrate, thus decreasing the cost-efficient aspect of carbon capture.

Medicinal drug delivery research is crucial for improving patient treatment and expanding the range of treatable conditions. Once a drug is put into the body, it is difficult to control the release with any great complexity. To address this complexity, we can take advantage of polymers to create a drug delivery device that can be remotely controlled, safely powered and dissolvable. My research focuses on the battery of the delivery device, developing a novel polymer-based energy storage system. By characterizing metrics like capacity, discharge rate, and resistance of different polymers, this battery system would be optimized for peak performance, which would allow for more sophisticated ailments to be treated easier than ever.

There is a need for carbon dioxide (CO₂) capture processes that are energy efficient and low cost to adequately mitigate the excessive release of CO₂ into the atmosphere. Novel electrochemical CO₂ capture systems may meet this need, but, to the best of our knowledge, there are limited techno-economic comparisons between commercially deployed thermochemical systems and potentially lower-cost electrochemical systems. Using a process modeling platform, I develop and optimize a state-of-the-art thermochemical CO₂ capture system that allows for direct cost and performance evaluations against electrochemical alternatives. This modeling aids in quantifying key cost contributors for each system while also guiding future research directions and policy in the carbon capture field.

The current state of the industry of synthesizing methanol is posing a threat to the environment, mainly due to the susceptibility of methanol to overoxidation to carbon dioxide, a greenhouse gas. In nature, however, metalloenzymes like methane monooxygenases (MMOs) have demonstrated capability to convert methane to methanol under mild conditions, such as ambient temperature. Our project is the development of a Molecular Organic Framework that could synthesize industrially valuable methanol, while reducing greenhouse gas emissions associated with current methods of methanol synthesis. This project has a potential to lower the carbon footprint in this industry, which will matter in the long run to create a green society.

The material physics of graphite, a predominant component in lithium-ion batteries, are currently not well understood, slowing improvements in the development of battery technologies. We are developing a machine learning based image pre-processing pipeline to prepare graphite microscopy images for further analysis, removing noise from the data and identifying particles at different reaction stages. With a processed data set, further work to learn graphite properties can be expedited and more informed development of lithium-ion batteries at all stages of life is possible.

Carbon capture and storage (CCS) technologies are a promising solution to addressing the substantial emissions originating from hard-to-abate industries. However, there are many existing CO₂ capture systems, and some may be better suited depending on the properties of the flue gas stream. We are developing process simulations of existing and emerging CO₂ capture systems to evaluate their cost and performance across different industrial flue gas streams, and in doing so we will identify which CO₂ capture systems are best suited for specific industrial processes. By benchmarking the cost-performance analysis of the various CO₂ capture systems, we hope to guide future implementation of CCS technologies to be as cost effective and energy efficient as possible.

A significant challenge in the battle against climate change lies in mitigating the substantial greenhouse gas emissions originating from hard-to-abate industrial sectors, which collectively contribute to nearly one-third of global emissions. Among the promising solutions to address these emissions, carbon capture and storage (CCS) technologies stand out as crucial decarbonization enablers by being able to significantly reduce emissions from existing industrial plants without disrupting vital industrial processes. However, since many of the industrial emissions are at high temperatures (300 to >1,400°C), conventional CCS technologies require cooling the flue gas to enhance the capture efficiency, which in turn requires more energy and leads to wasted low-grade heat. We are developing process simulations of emerging CCS technologies (such as molten salt) that offer the potential to operate the capture process at temperatures closer to those of the emissions. By evaluating their cost and performance across different industrial flue gas streams in comparison to conventional CCS technologies, we will identify which CCS technologies are best suited for specific industrial processes and help guide the growing implementation of CCS.