This project will aim to develop safe and high-energy-density solid-state Li metal batteries (SSLMBs) by constructing a stable Li/solid electrolyte (SE) interface and using high performance composite SEs based on sulfides and halides. The project includes three main directions: (1) design and synthesis of highly conductive and electrochemically stable composite electrolytes; (2) stabilizing the interface […]

The proposed project mainly focuses on developing an innovative gas/liquid contacting technology that is of critical importance to a wide range of process industries and environmental-management operations. Successful development and implementation of this project are expected to: • Reduce the environmental impact of a variety of operations that are needed to meet human needs and […]

This four-month research project proposal aims to contribute to bioremediation projects carried out by the partner industry by evaluating the biodegradability of some halogenated aromatic compounds, such as dichloroaniline (DCA), and chloroaniline (CA), present in a contaminated site. Through some biodegradability tests, we will verify and better understand how native microbes from the mentioned site […]

Underground mining operations are very energy intensive and could require significant use of fossil fuel burning on site for electrification and heat provision, if situated in off-grid areas. Conventionally, these power plants employ diesel gen-sets that can convert only about 35% of the combustion energy to qualified work and discard about 65% of the energy […]

The freight trucking industry is in a transformational phase by adopting smart mobility options to reduce operational costs and minimize carbon foot print. The autonomous truck platooning is a major step in this regard and the goal of this research project is to assess the readiness of the bridges for the peculiar loading conditions due […]

This research project will investigate how modern Remotely Piloted Aircraft Systems (also referred to as RPAS, drones, UAVs or UASs) can optimize surveillance missions and target characterization through the integration of Full Motion Video (FMV) cameras. FMV data will be processed and analyzed including the use of Artificial Intelligence (AI) algorithms. The large amount of […]

Virus transmission from one person to the next is heightened during physical activity and team and given the unique circumstances created by the COVID-19 pandemic, the demand for face coverings have exploded in all sectors of society. This project investigates Evolution Sports and Athletic Gear’s sports face covering prototype to evaluate the performance of these […]

Research in organizational behavior studies suggest that racial discrimination and bias exist in the workplace. Although explicit forms of racism are in decline, new forms of racial discrimination (i.e., implicit and unconscious) continue to compromise the inclusion and diversity in organizations. One of the challenges that HR specialists face is evaluating employees’ unconscious bias. This […]

This project aims to explore the application of remotely piloted aircraft systems (RPAS, aka drones) to assess forest health, explore early identification of disease and infestation and provide quantitative post-harvest analysis. The use of drones for this type of assessment has the potential to improve the overall picture of forest health, aid in decision-making regarding […]

This grant proposes to look at innovation in materials and assembly which are afforded by our new design and fabrication technology so that Patkau architects can take this material innovation and move it to a conceived and completed project.

TRUSTSPHERE is a secure digital connection allowing patients to securely donate data and for researchers to ethically access patient’s data. The TRUSTSPHERE Consortium will create a links from mobile devices to providers, patients, and their families which will be tested and implemented to help with adopting this tool for management of children with Type 1 […]

Unsupervised machine learning has recently been introduced into the field of quantum many-body physics. A strategy based on generative models has been particularly successful in the data-driven learning of quantum states. In this proposal, we aim to adapt this technology to applications in quantum chemistry. The primary focus of this research will be on the […]