91社区

An undergraduate student is sought to carry out AI driven modeling research on designing next-generation energy materials in collaboration with Profs. Bevan & Grutter. The project will encompass the modeling of chemical surface reactivity via state-of-the-art computational methods. The goal of this research is to devise new methods for improving the scrubbing of CO2, through the use of electrochemical devices and materials. This project tackles applications relating to electrocatalytic metals and metal oxides for fuel production and carbon capture. The catalytic operation of such metal oxides is dominated by electron localization and delocalization phenomena, which is essential to their operational efficiency in the aforementioned applications. By utilizing and developing AI augmented simulation tools on electrocatalysis, the intern will gain experience in understanding how fundamental processes determine the overall high-level operational limitations of new energy technologies. This research process is based on the famed "Bell Labs Model", whereby a key scientific problem is tackled/solved with the aim of enabling a new important technology (or suite thereof). In this project, the key fundamental problem is the electrochemical reduction of CO2 and associated electron transfer mechanisms. The intern will work under the close training guidance of a senior doctoral student, as well as the faculty member, and gain expertise in device modeling, physics/chemistry, materials science, and high-performance computing

Simulating electrochemical reactions augmented by AI methods.

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Simulating electrochemical reactions augmented by AI methods.

Simulating electrochemical reactions augmented by AI methods.

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We are developing new sol-gel bioactive glasses to improve performance of both orthopedic and dental materials. The glasses contain titanium, an element that we found can improve enamel hardness and mineral formation by stem cells. During the summer we will be optimizing glass formulations both to be used as coating on metallic implants used in orthopedics (titanium, stainless steel) and as particles in toothpastes to improve enamel hardness and whiteness. For more information on this work, take a look at our first paper published on the topic:

Prepare sol-gel bioactive glasses; develop tests to measure erosion, remineralization, hardness and whiteness in enamel and dentin treated with the glasses; characterize the teeth after treatment; prepare coatings on metallic implants and characterize them.

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Poly(etheretherketone) is a strong and inert polymer used in craniofacial reconstruction and spine applications. While its excellent mechanical property and radiolucency make it a great candidate for broader orthopedic and dental applications, its lack of integration with surrounding tissues greatly hamper its potential clinical translation. In this project we modify the surface of PEEK with proteins and possibly inorganic materials to improve its integration with soft tissues. A few different methods will be explored in the summer and the materials will be characterized with a range of physico-chemical and spectroscopic methods to determine the best candidates for further in-vitro and in-vivo studies. For more PEEK-related work from the group, please read the following articles (especially the most recent one, on soft tissue integration).

Surface modification of PEEK discs and characterization using a variety of physico-chemical and spectroscopic techniques.

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Minerals can deposit on the surface of cardiovascular tissues (blood vessels and heart valves) due to pathologies such as diabetes, chronic kidney disease and atherosclerosis, or due to aging. When minerals form on these normally soft tissues, the risk for cardiac events increases, since blood pressure increases and heart valves malfunction. We recently found that men and women differ in terms of the types of minerals formed on heart valves. We are now extending this study to more patients to try and identify patterns and differences beyond mineral types, and to see if other factors beyond sex may have an effect on the minerals formed in cardiovascular disease. This work may help identify new methods to detect and cure these diseases. For more information, please read this article from the group, and references therein:

Characterize calcified cardiovascular tissues with techniques including FTIR, Raman, microCT, and SEM. Data and image analysis.

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The aim of this SURE project is to build on a prototype design by further developing an automated biofabrication instrument based on a 91社区-led technology. By assembling together of-the-shelf-tools, this SURE project will focus on software development to enable automated gel aspiration-ejection (GAE) for generating tissue-like bioinks based on fibrillar collagen and other proteins.

A computer/software engineering student will help progress/develop software to advance the automated biofabrication device.

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Similar to hydrocarbons, phosphorus is a limited resource. Phosphorus fertilizer is produced from non-renewable phosphate rock. This phosphate rock is concentrated, then leached to produce phosphoric acid. A waste product of phosphoric acid production is 鈥減hosphogypsum鈥�. Phosphogypsum is calcium sulphate dihydrate that is contaminated with heavy metals and radioactive elements. Phosphoric acid is used to produce many different phosphorus fertilizers. Our lab is recovering phosphorus from different waste sources, including municipal biosolids and manure. Our approach is to produce effective phosphorus fertilizers from these waste sources, and then test their effectiveness with 鈥減ot tests鈥� in the Macdonald campus greenhouses. We are looking for a summer student to assist with creating synthetic soils with our recovered phosphorus fertilizers, to characterize these synthetic soils for their phosphorus availability and heavy metal leaching potential. These tasks require benchtop inorganic chemistry techniques. After soil characterization, we will run a 鈥減ot test鈥� with spring wheat or another grass. This test will be undertaken at the Macdonald Farm Horticultural Center. The SURE student will help graduate students by traveling to Macdonald Farm to maintain (water) and monitor the pots. Once completed, the solids and the crops will be analyzed to compare the effect of phosphorus fertilizer with synthetic phosphorus fertilizer. We are also keen to recruit a Bioresource Engineering student who could be based in the West Island to monitor the crop test, and commute downtown for the soil production, soil analysis, and crop analysis work.

Assist graduate students with - recovered phosphorus fertilizer production, - production of different synthetic soils, - materials analysis of the different soils, - starting, operating (watering and other tasks), and cleaning up a "pot test" to be conducted at the Macdonald Farm greenhouse, - analyzing the crop production and leaf elemental analysis

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The effects of climate change are irreversible and will worsen in the decades to come. Reducing fossil fuel consumption, via using electric vehicles (EVs), is a key factor in controlling climate change. The batteries designed so far, do not have the ability to completely replace fossil fuels due to their insufficient energy storage capacity, cyclability, and general efficiency. LiCoPO4 (LCP) is a commercial cathode material that has a high energy density and operates at higher voltages (near 4.8 V versus Li). It could thus be used as a next-generation electrode materials for commercial lithium-ion batteries.. However, LCP is an electronic and ionic insulator which hinders its use as a cathode material. The aim of this project is to modify the LCP particles with carbon-based coating agents, using wet chemistry synthesis methods, to increase its conductivity and performance as lithium-ion battery cathode materials.

Synthesis of LiCoPO4 powders, carbon coating of LiCoPO4 powders, electrochemical testing of carbon-coated LiCoPO4 powders in lithium half-cells.

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The objective of this project is to combine a programmable robotic arm with a machine learning (ML) tool to develop an automatic image capture and AI-aided image analysis module. The images are real-time diffraction patterns and/or topological features obtained from in-situ characterization during the synthesis of nanomaterials. The module will then be linked to the fabrication process to enable real-time processing parameter and condition adjustment to enable predictive, high-quality nanomaterial synthesis.

Literature review on relevant topics; Implement deep learning image classification and object detection techniques to analyze image and characterization data; Programming of the robotic arm.

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