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An undergraduate student is sought to carry out AI driven modeling research on designing next-generation energy materials. 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. 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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The objective of this project is to build and test a new 3D printer architecture powered by light. The project aims at building a demonstrator for the technology, to be built according to a series of constrains.

Review various existing 3D printing platform and evaluation of the possibility to adapt them for the current architecture. Design missing parts Integration of the various components and system into the printer. Test the working capabilities of the prototype.

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Heart valve calcification is a disease that increases morbidity and mortality in patients affected by atherosclerosis, diabetes, and the elderly. While men are more likely to have valvular calcification than women, the disease is more fatal in women than in men. We have recently found that minerals found in heart valves of women are different than those found in men (see recent paper by my group, Gourgas et al). We are analyzing more valves and building in-vitro models to understand better the reasons of these differences and what this could mean in terms of diagnosis and treatment of this pathology.

Analyze calcifications in cardiac valves, help with the synthesis and analysis of in-vitro model of heart valve.

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Upconversion nanoparticles (UCNPs) allow transforming incoming near infrared (NIR) light into UV and visible light. This can be very useful in biomedical applications, sine NIR light can penetrate deep through tissues and is non carcinegonic, while UV light can be used to break chemical bonds and, for example, release drugs (see my work with Jalani as first author, JACS). We have embedded UCNPs into a microneedle patch with the goal of use the UCNPs to release a hormone that women need to take during cycles of in-vitro fertilization (IVF). Light controlled, non painful, automatically triggered hormonal release will greatly enhance the success of IVF.

Microneedle synthesis, loading, and characterization. Loading hormones inside UCNPs and characterize release.

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Elastin is the polymer that is responsible for the elasticity of arterial walls and several other tissues in our body. Unlike most other molecules in our body, elastin is not regenerated, and it just gets degraded over our life span. In diseases like arterial calcification, minerals deposit on the elastin layer and stiffen the arteries, which increases burden on the heart and leads to potentially fatal heart complications. In this project we are studying how elastin fibers self assemble, which is something that is still not fully understood. This knowledge could help us create better models of the elastin layer in arterial walls, which we could use to study diseases, or even, further down the line, create grafts that could be used to replace damaged arteries. For more info on our previous work on elastin calcification, check out articles from my lab with first authors Gourgas and Zhang.

We are self-assembling elastin on electrospun fibers of a polymer called PLGA. Tasks for the student include optimizing electrospinning parameters, characterizing and performing mechanical tests on elastin materials, and possibly modeling diseases (elastin degradation, calcification) on elastin materials.

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In this project, we will synthesize and test novel electrolyte materials for high-energy Li-ion batteries for electric vehicles.

1. Perform literature survey 2. Synthesize and test new electrolyte materials for Li-ion batteries 3. Theoretically model the electrolyte materials

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The pyrometallurgical industry is at a crossroad. In 2021 [11], steel and iron carbothermal pyrometallurgy accounted for ~10% of the world CO2 emissions. In 2014, aluminium pyrometallurgy produced approximately ~1% of mankind CO2 emissions. The present project is an ongoing collaboration between Shell and Rio Tinto to design substitutes for traditional carbon sources used in steel and aluminium carbothermal pyrometallurgy with reduced CO2 impact biosourced carbons.

-Literature review -Design of laboratory procedures -Design of laboratory equipment -Wet synthesis of materials -Pyrolysis experiments -Thermogravimetric analysis -Differential scanning calorimetry -Life cycle assessment

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Development of high-performance nanomaterials and nanodevices are increasingly more dependent on atomic-precision synthesis. However, most of atomic-precision synthesis techniques suffer from poor productivity and high cost, as often the desired fabrication conditions and processing parameters are not known a prior and are determined by many trial-and-error runs. To address such limitation, one way is to integrate in-situ monitoring and characterization into the synthesis process, from which the key structural and property information can be extracted to automate real-time processing parameter and condition adjustments. This project aims to create a machine learning powered image analysis toolkit for such structural and property information extraction.

Learning relevant machine learning packages; Programming to implement deep learning image classification and object detection techniques to analyze image and characterization data; Literature review to extract image and characterization data.

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Lithium is a strategic element, currently being a major component of the move to greener transport. This project will investigate the potential of using phosphoric acid to extract lithium from spodumene, one of the major minerals being targeted for hard rock mining. Phosphoric acid has shown promise in removing silicate gangue from other deposits, and this work will investigate its applicability to lithium extraction. The effectiveness of the process will be assessed by, among other techniques, surveying the effect of leaching conditions on lithium dissolution and solid composition changes with powder X-ray diffraction.

Undertake a statistical design of experiments to determine the optimum operating conditions for lithium extraction at the lab (bench) scale Chemical analysis of the feed and products

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This project will investigate the use of magnetite coated with carbon as an extractant for heavy metal ions from aqueous systems. The project will assess the factors associated with coating the magnetite, activating the carbon, extraction and subsequent extractant recovery through magnetic separation.

Conduct a review of metal ion extraction using activated carbon Determine the optimum process route to develop the magnetic extractants Assess the extraction capacity of the extractants for different metals Characterise the extractants through techniques including scanning electron microscopy

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Graphite is a strategic mineral as it is a popular anode material for electric vehicle batteries. Mined graphite contains impurities that must be separated or leached to produce a high-quality graphite product. This project will investigate the utility of phosphoric acid and condensed phosphates to provide an alternate, more sustainable graphite refining process than the current industry standards. The lixiviant chemistry and leaching process effects will be assessed by characterizing the leach solution chemistry, and solids characterization by powder x-ray diffraction, Raman spectroscopy, light microscopy, and energy dispersive spectroscopy.

Generating pH, Eh, and ion composition analysis with analytical tools. Undertake a statistical design of experiments to determine the optimum leaching process conditions for upgrading concentrated graphite ore at the lab (bench) scale

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Slimes coating is when fine particles of one mineral coat the surface of a larger, different, mineral. This has a negative impact on flotation efficiency in mineral processing. One main mechanism behind slimes coating is proposed to be differences in the zeta potential of the different minerals. This project will investigate the surface properties of minerals, and the flotation response of coarse and fine particles as part of an assessment into the slimes coating phenomena.

Microflotation studies of fine and coarse particle at different pH values and reagent addition Surface chemistry analyses using zeta potential and inverse gas chromatography (among others) Particle-particle image capture

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