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Field of Research : Materials engineering
Field of Research : Computational chemistry
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  • Active Funded Activity

    Discovery Projects - Grant ID: DP240103085

    Funder
    Australian Research Council
    Funding Amount
    $461,140.00
    Summary
    Sustainable Electrocatalytic Synthesis of Urea. Urea is a critical chemical for agriculture, the chemical industry and pollution control, yet current production methods are unsustainable. This project aims to design high-efficiency catalysts for electrochemical urea synthesis from theoretical studies. This project expects to generate new knowledge of chemistry and catalysis from new reaction mechanisms and materials. Expected outcomes include optimum catalysts with high conversion efficiency and .... Sustainable Electrocatalytic Synthesis of Urea. Urea is a critical chemical for agriculture, the chemical industry and pollution control, yet current production methods are unsustainable. This project aims to design high-efficiency catalysts for electrochemical urea synthesis from theoretical studies. This project expects to generate new knowledge of chemistry and catalysis from new reaction mechanisms and materials. Expected outcomes include optimum catalysts with high conversion efficiency and reactant selectivity. The novel catalysts have the potential to deliver improved catalytic performance and controllable reaction reactants. This could deliver significant benefits to the crop production increase, cost reduction of chemical industry, and environmental pollution reduction.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP240100753

    Funder
    Australian Research Council
    Funding Amount
    $529,615.00
    Summary
    Autonomous Discovery of Green Inhibitors. The project aims to develop autonomous material design by integrating evolutionary algorithms and robotic experimentation. The project expects to pioneer a new method of materials discovery that could cut discovery times to 20% of traditional methods. Its expected to have significance through its discovery of new classes of corrosion inhibitors that are safe to both humans and the environment. The expected outcomes of this project will be a rapid disc .... Autonomous Discovery of Green Inhibitors. The project aims to develop autonomous material design by integrating evolutionary algorithms and robotic experimentation. The project expects to pioneer a new method of materials discovery that could cut discovery times to 20% of traditional methods. Its expected to have significance through its discovery of new classes of corrosion inhibitors that are safe to both humans and the environment. The expected outcomes of this project will be a rapid discovery methodology that can be used across materials science and new classes of safe corrosion inhibitors. This should provide significant benefits to workplace n safety and the environmental impact of the coatings industry while also increasing the rapid of innovation of new materials.
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