Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100131
Funder
Australian Research Council
Funding Amount
$150,000.00
Summary
Biomaterials characterisation facility. The convergence of nanotechnology and biotechnology offers new opportunities to prepare nanoengineered materials for applications in biomedicine. The Biomaterials Characterisation Facility will provide equipment to characterise such nanoengineered materials to underpin advances in therapeutic drug delivery and tissue engineering.
Industrial Transformation Research Hubs - Grant ID: IH130200004
Funder
Australian Research Council
Funding Amount
$3,966,350.00
Summary
ARC Research Hub for transforming the mining value chain. ARC Research Hub for transforming the mining value chain. This Research Hub aims to transform the mining value chain to make significant improvements to industry practices through enhancing ore deposit discovery, mineral processing, and environmental management of ores and waste materials. The Hub will bring together a team of world-class researchers, industry partners and research facilities to develop end-user driven solutions to improv ....ARC Research Hub for transforming the mining value chain. ARC Research Hub for transforming the mining value chain. This Research Hub aims to transform the mining value chain to make significant improvements to industry practices through enhancing ore deposit discovery, mineral processing, and environmental management of ores and waste materials. The Hub will bring together a team of world-class researchers, industry partners and research facilities to develop end-user driven solutions to improve profitability and productivity in Australia’s mining industry.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE180100001
Funder
Australian Research Council
Funding Amount
$345,475.00
Summary
Pushing the limits of fluorescence microscopy with adaptive optics. This project aims to establish an adaptive optics, super-resolution optical microscopy facility to image cellular events with the highest possible spatial resolution, in a whole cell or tissue context. Sophisticated computer-controlled deformable mirrors will be used to correct the way light is distorted as it passes through specimens, thereby overcoming aberrations found in thick and complex samples. This adaptive optics system ....Pushing the limits of fluorescence microscopy with adaptive optics. This project aims to establish an adaptive optics, super-resolution optical microscopy facility to image cellular events with the highest possible spatial resolution, in a whole cell or tissue context. Sophisticated computer-controlled deformable mirrors will be used to correct the way light is distorted as it passes through specimens, thereby overcoming aberrations found in thick and complex samples. This adaptive optics system will enable researchers to study complex behaviour of biological specimens, at the optical resolution limit in plant and animal tissues, leading to basic biology and biotechnology outcomes in biofuels, biomaterials and biomedicines.Read moreRead less
Advanced Materials from Automated Synthesis of Sequence-Defined Polymers. The project aims to develop industrially scalable and environmentally friendly methods for synthesis of sequence-defined multiblock copolymers (polymer chains containing segments of different polymer types) using automated synthesis methods. The materials to be explored will be largely based on renewable biomass-derived monomeric building blocks. Such polymers are able to undergo microphase separation into spatially period ....Advanced Materials from Automated Synthesis of Sequence-Defined Polymers. The project aims to develop industrially scalable and environmentally friendly methods for synthesis of sequence-defined multiblock copolymers (polymer chains containing segments of different polymer types) using automated synthesis methods. The materials to be explored will be largely based on renewable biomass-derived monomeric building blocks. Such polymers are able to undergo microphase separation into spatially periodic compositional patterns, thereby providing access to a vast range of nano-engineered materials. This would enable design and synthesis of new advanced materials, making use of renewable resources and supporting the circular economy, with diverse potential applications ranging from nanomedicine to materials science.Read moreRead less
Physics-aware machine learning for data-driven fire risk prediction. The 2019/20 Australian fire season was unprecedented in its extent, impact, and the response of fire agencies. In this project, we aim to answer the question: was the scale of these fires driven by known drivers of fire (drought, weather, fuels and ignitions), or were fundamentally new undescribed processes and phenomena involved? We will accomplish this by developing an innovative, physics-aware machine learning model of fire ....Physics-aware machine learning for data-driven fire risk prediction. The 2019/20 Australian fire season was unprecedented in its extent, impact, and the response of fire agencies. In this project, we aim to answer the question: was the scale of these fires driven by known drivers of fire (drought, weather, fuels and ignitions), or were fundamentally new undescribed processes and phenomena involved? We will accomplish this by developing an innovative, physics-aware machine learning model of fire risk and spread, trained and validated on a two-decade satellite fire record. The predictive ability of the model will be tested on the 2019/20 fire season to determine if novel drivers of fire can be identified, and the model itself will be operationalised into a novel short-to-mid term fire risk prediction tool. 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
The Great Barrier Reef in 2100. Our research aims to answer fundamental geomorphic questions about the future of coral reefs, focusing on the Great Barrier Reef (GBR). We will develop cutting-edge, fully open-source numerical models to quantify the eco-morphodynamic evolution of the GBR under IPCC climate-change scenarios. Our geomorphic numerical models will consider biotic/abiotic feedbacks including synergistic effects of multiple stressors such as waves, temperature, acidification and sedime ....The Great Barrier Reef in 2100. Our research aims to answer fundamental geomorphic questions about the future of coral reefs, focusing on the Great Barrier Reef (GBR). We will develop cutting-edge, fully open-source numerical models to quantify the eco-morphodynamic evolution of the GBR under IPCC climate-change scenarios. Our geomorphic numerical models will consider biotic/abiotic feedbacks including synergistic effects of multiple stressors such as waves, temperature, acidification and sediment transport, at individual reef scales. We will model the future of the GBR’s ecosystem-services, allowing for a quantum leap in the geomorphic knowledge and understanding of coral reef ecosystems. Expected outcomes include a gamechanger tool for future management of the GBR.Read moreRead less
Deep-sea coral ocean-climate records of the last glacial and recent eras. The project aims to predict the ocean carbon dioxide sink’s long-term capacity and future trajectories of global warming and increasing carbon dioxide. This project will use geochemical proxies encoded in the skeletons of deep-sea corals in the Perth Canyon, Tasman seas, and Antarctica, in the heart of the ocean-climate system, to reveal continuous long-term records of environmental change at annual-decadal resolution for ....Deep-sea coral ocean-climate records of the last glacial and recent eras. The project aims to predict the ocean carbon dioxide sink’s long-term capacity and future trajectories of global warming and increasing carbon dioxide. This project will use geochemical proxies encoded in the skeletons of deep-sea corals in the Perth Canyon, Tasman seas, and Antarctica, in the heart of the ocean-climate system, to reveal continuous long-term records of environmental change at annual-decadal resolution for our recent past (hundreds to thousands of years) and the Last Glacial Maximum. These records are expected to provide a more accurate understanding of Earth’s long-term responses to anthropogenic carbon dioxide emissions and global warming.Read moreRead less
DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting th ....DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting the attractiveness and evolving the system. The project expects to advance deep learning and yield novel DeepHoney technologies with associated publications and open-source software. This should benefit science, society, and the economy by building the next generation of active cyber defence systems. Read moreRead less