Thermoplastic Polyurethane Electrolyte Development for eWindows

Miru Smart Technologies (Miru) is developing the next generation of low-cost, energy-efficient, high-quality eWindows for residential, commercial, and automotive industries. Using scalable and adaptable methodologies, electrochromic windows have the potential to yield significant gains in energy efficiency by offsetting user climate control requirements while simultaneously providing a high-quality consumer experience. In Q1 2025, Miru recently […]

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Automated gated quantum-dot 3D model generation and tuning for technology-computer aided design of realistic spin-qubit systems

Spin qubits—nanoscale quantum bits made in semiconductor materials—are a promising technology for building future quantum computers. They are highly miniaturized, can work at relatively higher temperatures than competing technologies, and can be made using standard industrial semiconductor-chip fabrication techniques, which makes them ideal for scaling up. However, traditional chip design software is not adequate for […]

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Enhancing Plasma Dynamics Modeling in RF Ion Sources Using Improved PIC Simulations and Refined Cross-Section Data

This study utilizes computational plasma modelling using a Particle-in-Cell computer program to simulate and compare hydrogen and deuterium in a volume-cusp ion source to ascertain why H¯ and D¯ output beams beam production ratio is ~3:1 [3-5]. To the best of our knowledge a comprehensive modelling study does not exist explaining this effect. This project […]

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Enhancing QML trainability in noisy quantum systems

This project will develop novel circuit metrics to predict model performance under realistic noise conditions, offering a practical approach to enhancing QML trainability. The research will investigate optimal parameter resilience across different circuit depths, qubit counts, and problem types, while comparing overparameterized and underparameterized regimes. Additionally, circuit metrics will be developed to predict model performance […]

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Pollution control of gas mixtures: gas monitoring and detection of contaminants usingnovel THz technology Year Two

Electric power plants are the number one toxic air polluters in North America. The emitted pollutants are proven to cause serious health and environmental issues. The emission of Carbon dioxide and of other pollutants, such as nitrogen oxides, sulfur dioxide – major drivers of the human-accelerated global climate change- must be monitored insitu. Our goal […]

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L2M – GradFinder

We are building GradFinder, an online platform that connects students with professors who are actively recruiting for thesis-based graduate programs. Many students struggle to find available positions, and professors are overwhelmed by unqualified inquiries. Our platform streamlines this process, improving access and efficiency on both sides. Through this project, we aim to refine our business […]

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Benchmarking fundamental components of quantum machine learning on full-stack photonic quantum computers

Architectures for quantum computing can only scale effectively with suitable benchmarking techniques. Benchmarking is essential for evaluating the performance of quantum computers, including their algorithms and applications. This principle extends to quantum machine learning techniques, where benchmarking basic quantum machine learning methods on full-stack photonic NISQ devices is crucial. A key challenge involves adapting quantum […]

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The Diagnostic Potential of Co-rotating Interaction Regions in Dense Hot-Star Winds

Wolf-Rayet (WR) stars exhibit strong, high-velocity winds with small-scale stochastic clumps and large-scale structures like Co-rotating Interaction Regions (CIRs). CIRs are spiral-shaped density enhancements, which propagate through the wind and induce variability in spectropolarimetric signals. WR6 (EZ CMa, WN4b) is a well-studied target with a stable 3.76-day periodicity in its wind variations. Recent observations, including […]

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Chelating bis(phosphinidenes) with cyclic alkyl(amino)carbene backbones: synthesis and coordination chemistry

This project focuses on developing new types of catalysts by designing and testing innovative molecules (ligands) that can better interact with metals and tune their properties. Catalysts are chemical species that help speed up chemical reactions, making them more efficient, selective, and sustainable. They are essential in many industries, from pharmaceuticals and petrochemicals to energy […]

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Design Principles of Biological Networks

This project aims to uncover the design principles of biological networks, such as blood vessels in the kidney and brain, by developing automated tools to analyze high-resolution 3D images of human embryo vasculature. Using advanced imaging techniques and deep learning, the research will create efficient methods to study how these networks efficiently transport nutrients and […]

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