Projects

The project seeks to develop cost effective neutron detectors, which are critical for fusion power generators, and other applications like radiation monitoring and medical imaging.

One method to mitigate climate change is to remove carbon dioxide that has already been released to the atmosphere. There are many possible methods for carbon dioxide removal (CDR). Some of these are nature-based solutions, such as reforestation. Others are engineered solutions, such as direct air capture (DAC). These methods have different costs and energy… Read more

Decarbonizing cathode materials will directly reduce the emissions from EV manufacturing. Moreover, as carbon emissions are closely associated with high energy consumption, developing technologies that lower energy usage is the key to controlling carbon emissions. As a result, our efforts could potentially lead to a new manufacturing route featuring low energy consumption, low emissions, and… Read more

This project addresses corporate accounting for Scope 2 GHG emissions, which are attributable to purchased electricity and other energy. The objective is to define accounting rules which provide more information. Defining emissions for electricity purchased from the grid can be difficult since the grid is a pool of electricity produced by a variety of generators.

Develop a geospatially resolved tool to identify the best use for agriculture wastes based on GHG benefits, cost, and systems-level impacts.

The goal of the MITEI Geologic Hydrogen Consortium is to advance the state of knowledge about geologic hydrogen and the viability of scaling up its production. We assess the existing data and knowledge gaps which limit evaluation of the role geologic hydrogen might play in the energy system. We integrate the distribution and geologic characteristics… Read more

This project aims to identify sources of fugitive methane emissions and quantify their magnitude from ExxonMobil-owned Oil&Gas sites in the Permian Basin. It is based on an integrated approach that augments measured data with other sources of information. The computational framework combines physics-based and scientific machine learning-based approaches to maximize the suitability of the developed… Read more

This project advances foundational uncertainty quantification and inference methodologies for monitoring subsurface fields relevant to CO2 storage and geothermal reservoir management.

Further developing the SPARC and ARC divertor scenarios simulation database

The project will assess various options for decarbonizing fuels, including biofuels and synthetic fuels with and without CCS, as well as other negative emissions technologies, and develop enhanced representations of these technologies for use in low emissions scenarios. Using the enhanced representation, we will further assess the competition between fuels and electricity in major end… Read more

This project will develop surrogate models for different physical processes that can be used in the context of energy system optimization. This includes models for network stability, dynamical external disturbances and contingencies that can impact the solution of grid optimization. Developing good surrogate models will enable improved and resilient operation of energy infrastructure.