General systems modelling of hydrogen production network in Australia. The project aims at further developing a general framework for systems modelling and applying the framework to investigate the feasibility and sustainability of large-scale hydrogen production in Australia. Two pathways proposed in this project are to be examined: 1) hybrid plants sourcing hydrogen from fossil fuels and solar thermal energy and 2) hydrogen production network producing hydrogen from 100% renewable energy. The ....General systems modelling of hydrogen production network in Australia. The project aims at further developing a general framework for systems modelling and applying the framework to investigate the feasibility and sustainability of large-scale hydrogen production in Australia. Two pathways proposed in this project are to be examined: 1) hybrid plants sourcing hydrogen from fossil fuels and solar thermal energy and 2) hydrogen production network producing hydrogen from 100% renewable energy. The project involves building systems models and using these models to determine optimal operational parameters and conditions with the goal of maintaining export of high-end energy resources to Japan and other countries as well as using hydrogen domestically while minimising the environment effects of hydrogen production.Read moreRead less
Solar-thermal desalination system for parallel water-electricity generation. This project aims to develop a multi-functional solar-thermal desalination device to simultaneously produce clean water and electricity. Interfacial solar evaporation-based desalination technology has the unique advantage of using solar light as the sole energy source for affordable clean water production. However, its absolute evaporation rate is still too low for practical application and all of the latent heat releas ....Solar-thermal desalination system for parallel water-electricity generation. This project aims to develop a multi-functional solar-thermal desalination device to simultaneously produce clean water and electricity. Interfacial solar evaporation-based desalination technology has the unique advantage of using solar light as the sole energy source for affordable clean water production. However, its absolute evaporation rate is still too low for practical application and all of the latent heat released from vapor condensation during desalination is wasted. Solving these two critical issues by the study of energy nexus, design and fabrication of advanced photothermal materials and desalination devices could accelerate practical adoption of this technology and benefit millions of people who desperately need clean water. Read moreRead less
Cost-effective metal selenide materials for solid-state devices. Thermoelectric materials, directly converting thermal energy into electrical energy, offer a green and sustainable solution for the global energy dilemma. This project aims to develop cost-effective metal selenide materials for high-efficiency solid-state devices using a novel industry-level approach, coupled with nanostructure and band engineering strategies. The key breakthrough is to design high-performance metal selenide thermo ....Cost-effective metal selenide materials for solid-state devices. Thermoelectric materials, directly converting thermal energy into electrical energy, offer a green and sustainable solution for the global energy dilemma. This project aims to develop cost-effective metal selenide materials for high-efficiency solid-state devices using a novel industry-level approach, coupled with nanostructure and band engineering strategies. The key breakthrough is to design high-performance metal selenide thermoelectric materials with engineered chemistry and unique structures for new generation thermoelectrics. The expected outcomes will lead to an innovative technology for harvesting electricity from waste heat or sunlight, which will place Australia at the forefront of energy and manufacturing technologies.Read moreRead less
Carbon dioxide in water nanoemulsions for carbon sequestration. The project will address a key objection to geological carbon dioxide (CO2) sequestration by removing the risk of long-term leakage to drinking water aquifers or to atmosphere. By injecting a nano-emulsion of CO2-in-water, the project seeks to show complete reaction to permanently stable solid carbonate occurs within weeks, eliminating the need for secure caprock or extended seal integrity monitoring. New knowledge will be generated ....Carbon dioxide in water nanoemulsions for carbon sequestration. The project will address a key objection to geological carbon dioxide (CO2) sequestration by removing the risk of long-term leakage to drinking water aquifers or to atmosphere. By injecting a nano-emulsion of CO2-in-water, the project seeks to show complete reaction to permanently stable solid carbonate occurs within weeks, eliminating the need for secure caprock or extended seal integrity monitoring. New knowledge will be generated using innovative approaches to create and stabilise CO2-in-water nano-emulsions and demonstrate the fast conversion of CO2 into stable minerals. The benefits are significant in opening potential sequestration targets to include areas without secure caps, reduced cost and elimination of long-term leakage riskRead moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
Fluid Transport in Materials of Nanoscale Dimensions. This project aims to transform the modelling of fluid transport in materials of nanoscale dimension by determining the coupled interfacial heat and mass-transfer barriers, which critically influence the transport. The outcome will not only be new knowledge on the effects of inherent structural distortion and of the barriers on the fluid flow, but also cutting-edge techniques to estimate system size-dependent transport coefficients in nanoscal ....Fluid Transport in Materials of Nanoscale Dimensions. This project aims to transform the modelling of fluid transport in materials of nanoscale dimension by determining the coupled interfacial heat and mass-transfer barriers, which critically influence the transport. The outcome will not only be new knowledge on the effects of inherent structural distortion and of the barriers on the fluid flow, but also cutting-edge techniques to estimate system size-dependent transport coefficients in nanoscale systems. These will be achieved through a combination of targeted molecular dynamics simulations and experiment, and will have far-reaching implications for nanotechnology and emerging processes in catalysis, gas separation, human health and nanofluidics, and enable design of more efficient systems.Read moreRead less
Unlocking Mass Mobile Video Analytics with Advanced Neural Memory Networks. This project will develop neural memory architectures and dense spatial-temporal bundle adjustment to predict movement, behaviour, and perform multi-sensor fusion across large asynchronous video feeds. This capability will allow us to better interrogate and analyse mass video information recorded from the vast number of smartphones, action cameras, and surveillance cameras which exist at public events of interest. Outcom ....Unlocking Mass Mobile Video Analytics with Advanced Neural Memory Networks. This project will develop neural memory architectures and dense spatial-temporal bundle adjustment to predict movement, behaviour, and perform multi-sensor fusion across large asynchronous video feeds. This capability will allow us to better interrogate and analyse mass video information recorded from the vast number of smartphones, action cameras, and surveillance cameras which exist at public events of interest. Outcomes include the ability to ingest multiple video feeds into a dense and dynamic 3D reconstruction for knowledge representation and discovery, and analysis of events and behaviour through new spatio-temporal analytic approaches. This will offer significant benefits for video forensic analysis, policing, and emergency response.Read moreRead less
Challenging big data for scalable, robust and real-time recommendations. With the advent of big data era, recommender systems are facing unprecedented challenges with respect to the four dimensions of big data: big volume, low veracity, high velocity and high variety. This project aims to develop a new generation of cost-effective techniques for scalable, robust and real-time recommendations utilising big data. This project aims to address these challenges to achieve scalable, robust and real-ti ....Challenging big data for scalable, robust and real-time recommendations. With the advent of big data era, recommender systems are facing unprecedented challenges with respect to the four dimensions of big data: big volume, low veracity, high velocity and high variety. This project aims to develop a new generation of cost-effective techniques for scalable, robust and real-time recommendations utilising big data. This project aims to address these challenges to achieve scalable, robust and real-time recommendations. This project will devise a series of cost-effective machine learning methods and schemes to deliver an end-to-end recommender framework. This project has the potential to significantly reduce the energy consumption of large-scale recommender systems as well as facilitating an increase in the use of recommendation applications for big data.Read moreRead less
Short Sequence Representation Learning with Limited Supervision . Predicting events based on short text and video data is widely found in real-world applications such as online crime detection, cyber-attack identification, and public security protection. However, to develop such an effective prediction model is very difficult due to the problems such as limited supervision, heterogeneous multiple sources, and missing and low-quality data. This project is to tackle these challenges. Expected outc ....Short Sequence Representation Learning with Limited Supervision . Predicting events based on short text and video data is widely found in real-world applications such as online crime detection, cyber-attack identification, and public security protection. However, to develop such an effective prediction model is very difficult due to the problems such as limited supervision, heterogeneous multiple sources, and missing and low-quality data. This project is to tackle these challenges. Expected outcome of this project will lay a theoretical foundation for effective short sequence representation learning and build next-generation intelligent systems. This should benefit our society and economy through the applications of multimodality-integrated video technologies for cybersecurity and public safety. Read moreRead less
Boosting Carbon Dioxide Reduction via Surface and Interface Engineering . This project will develop innovative catalysts for the reduction of CO2 into carbon fuels via cost effective computational design. The approach aims at engineering catalytic surface and interface to modulate the coordination environment around catalytic active copper atom. The expected outcomes will be high performance catalyst materials that can significantly boost the conversion of CO2 into valuable fuels. The new knowle ....Boosting Carbon Dioxide Reduction via Surface and Interface Engineering . This project will develop innovative catalysts for the reduction of CO2 into carbon fuels via cost effective computational design. The approach aims at engineering catalytic surface and interface to modulate the coordination environment around catalytic active copper atom. The expected outcomes will be high performance catalyst materials that can significantly boost the conversion of CO2 into valuable fuels. The new knowledge achieved in this project will dramatically advance the development of sustainable carbon cycle, providing solutions to the global energy supply and environmental issues. The smarter energy and environmental technologies will potentially result in the enhancements to the quality of the everyday lives of Australian.Read moreRead less