Discovery Early Career Researcher Award - Grant ID: DE200100326
Funder
Australian Research Council
Funding Amount
$425,231.00
Summary
Mass transfer enhancement for hydrate based carbon capture and cold storage. This project aims to generate the knowledge and techniques required to increase carbon dioxide (CO2) uptake in hydrate based carbon capture from current levels of 15.4% to up to 90% of its rated capacity. This marked improvement stems from identification of the mechanism of CO2-water mass transfer in CO2 hydrate formation and engineering of structurally modified porous hydrogels as the substrate of CO2 hydrates. Encapsu ....Mass transfer enhancement for hydrate based carbon capture and cold storage. This project aims to generate the knowledge and techniques required to increase carbon dioxide (CO2) uptake in hydrate based carbon capture from current levels of 15.4% to up to 90% of its rated capacity. This marked improvement stems from identification of the mechanism of CO2-water mass transfer in CO2 hydrate formation and engineering of structurally modified porous hydrogels as the substrate of CO2 hydrates. Encapsulation will be developed in a way that CO2 may be transported by CO2 hydrates in a concentrated form. Successful completion of the project will offer technical evaluation of a novel CO2 capture and transport solution with lower operational energy consumption and capital cost than incumbent carbon capture technologies.Read moreRead less
Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a hig ....Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a high theoretical value, as the questions we shall address are of independent interest to pure mathematicians.Read moreRead less
Geological sequestration of carbon dioxide in deep saline aquifers: coupled flow-mechanical considerations. Deep saline aquifers have been routinely proposed as sites for long-term, large-scale storage of carbon dioxide (CO2) emissions, as an option to assist the abatement of global warming. This project investigates expected engineering behaviour of deep saline aquifer reservoirs and their stability following CO2 sequestration.
Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a hig ....Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a high theoretical value, as the questions we shall address are of independent interest to pure mathematicians.
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Industrial Transformation Research Hubs - Grant ID: IH230100005
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub in Zero-emission Power Generation for Carbon Neutrality. This Hub aims to develop sustainable zero-emission power generation technologies to transform gaseous waste (mainly CO2) from our energy and manufacturing sectors into valuable products and create scalable pathways to market for driving industry transformation. This Hub expects to harvest renewable energy from the environment by using zero-emission power generators and then store it in green and safer batteries for convert ....ARC Research Hub in Zero-emission Power Generation for Carbon Neutrality. This Hub aims to develop sustainable zero-emission power generation technologies to transform gaseous waste (mainly CO2) from our energy and manufacturing sectors into valuable products and create scalable pathways to market for driving industry transformation. This Hub expects to harvest renewable energy from the environment by using zero-emission power generators and then store it in green and safer batteries for converting gaseous waste from sectors that cannot easily avoid emission into useful chemicals, which in turn realize carbon neutrality and negativity. The outcomes of this Hub are likely to be transformative for industry, the economy, and society in new-type renewable energy resources through decreasing environmental pollutants. Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100098
Funder
Australian Research Council
Funding Amount
$230,000.00
Summary
A comprehensive gas/vapour sorption facility for the fast advancement of decarbonised energy technologies. Solutions to clean energy production, storage and use are critical to Australia’s prosperity, yet there is a significant lack of targeted research facilities for the development of the highly needed materials and technologies for powering a sustainable Australia. This facility will bring research efforts closer to practical solutions.
Cohort discovery and activity mining for policy impact prediction. Cohort discovery and activity mining for policy impact prediction. This project aims to develop an intelligent systematic framework to predict policy impacts on Australian patients, by discovering inherent patient cohorts and assessing the impact of the policies on these cohorts. The proposed methods lay the theoretical foundations for building intelligent automated tools for policy assessment. Expected outcomes are data-driven p ....Cohort discovery and activity mining for policy impact prediction. Cohort discovery and activity mining for policy impact prediction. This project aims to develop an intelligent systematic framework to predict policy impacts on Australian patients, by discovering inherent patient cohorts and assessing the impact of the policies on these cohorts. The proposed methods lay the theoretical foundations for building intelligent automated tools for policy assessment. Expected outcomes are data-driven patient group discovery, which could more precisely identify the patient cohorts most likely to benefit from a specific policy; and a model to predict the efficacy of policy options, which could increase the sustainability of the national health system by enabling smarter, more efficient policy decision-making.Read moreRead less
Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an ....Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.Read moreRead less
Multiscale engineering of durable absorber coatings for solar thermal power. This project aims to advance the long-term stability and efficiency of high-temperature absorber coatings for Concentrated Solar Power (CSP) plants. Solar energy is a vast and largely untapped resource in Australia. The project will design superior light absorbers and scalable and low-cost approaches for their fabrication. Optimal absorber properties will be achieved by multi-scale engineering of the coating composition ....Multiscale engineering of durable absorber coatings for solar thermal power. This project aims to advance the long-term stability and efficiency of high-temperature absorber coatings for Concentrated Solar Power (CSP) plants. Solar energy is a vast and largely untapped resource in Australia. The project will design superior light absorbers and scalable and low-cost approaches for their fabrication. Optimal absorber properties will be achieved by multi-scale engineering of the coating composition and micro-texturing via modelling of the light absorption and heat transport within these complex nanocomposite structures. The intended outcome of the project is a set of commercially competitive absorber coatings, with superior performance and durability, that support the development of CSP as a competitive technology for energy generation.Read moreRead less
Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research ....Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research will include new data privacy models, new privacy-preserving data mining algorithms, and a prototype of cloud data mining software. These will help businesses cut costs for data mining and privacy protection, and provide significant benefits toward helping Australia achieve its national cyber security strategy and potentially provide economic impact from commercialisation of new software technology for the industry partner.Read moreRead less