Understanding molecular negative ion production for use in pathology. The project aims to increase the yield of molecular negative ion sources by improving our understanding of the formation of ion beams from plasma sources and expand our knowledge of molecular negative ion generation in plasma environments leading to brighter ion beams. For example, understanding cancer requires cellular level tools to map how cells are changing. These maps are made using ion beams which are scanned across cell ....Understanding molecular negative ion production for use in pathology. The project aims to increase the yield of molecular negative ion sources by improving our understanding of the formation of ion beams from plasma sources and expand our knowledge of molecular negative ion generation in plasma environments leading to brighter ion beams. For example, understanding cancer requires cellular level tools to map how cells are changing. These maps are made using ion beams which are scanned across cells to remove material that is analysed at the atomic and molecular level. Ion beams are produced from plasma sources, but much of their operation is not understood. Such improved ion beams are expected to enable inexpensive and fast cellular level pathology at even small hospitals to tackle cancer for society’s benefit.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
Integrated Farm Modelling to Improve Resilience and Sustainable Prosperity. This project aims to improve farm resilience, farm management, and economic decision-making in Australia and internationally. It expects to generate new interdisciplinary knowledge to integrate our understanding of agro-ecosystems and innovative tools to assess their status and manage their operations more effectively. Expected outcomes include the ability to inform farmers, bankers, and land managers about the trade-off ....Integrated Farm Modelling to Improve Resilience and Sustainable Prosperity. This project aims to improve farm resilience, farm management, and economic decision-making in Australia and internationally. It expects to generate new interdisciplinary knowledge to integrate our understanding of agro-ecosystems and innovative tools to assess their status and manage their operations more effectively. Expected outcomes include the ability to inform farmers, bankers, and land managers about the trade-offs between resilience and efficiency on farms. This should provide significant benefits, including the ability to minimize financial risks to farmers and banks, allow better investment decisions, and achieve sustainable long-term outcomes for both private and public well-being.Read moreRead less
Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proa ....Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proactive sewer management including network-wide real-time control. The project aims to generate significant social, environmental and economic benefits by enabling utilities to better protect public and environmental health, reduce sewer odour and greenhouse gas emissions, and extend sewer asset life.Read moreRead less
A novel physical-digital approach for the assessing a large critical asset. This project aims to deliver an artificial intelligence-enabled decision-making tool to maintain and manage the floating covers of vast lagoons that treat raw sewage. The cover harvests the biogas released from the anaerobic digestion of sewage for electric power generation that exceeds the plant’s requirement. The approach involves an innovative thermographic technique and exploits transfer learning to adapt neural netw ....A novel physical-digital approach for the assessing a large critical asset. This project aims to deliver an artificial intelligence-enabled decision-making tool to maintain and manage the floating covers of vast lagoons that treat raw sewage. The cover harvests the biogas released from the anaerobic digestion of sewage for electric power generation that exceeds the plant’s requirement. The approach involves an innovative thermographic technique and exploits transfer learning to adapt neural networks trained on lab-scale and synthetic data to field implementation. The outcome is a machine learning framework to optimise biogas harvesting and renewable energy generation, and to avoid structural failure, that is capable of continuous improvement to take into account improved data and/or modelling capabilities.Read moreRead less
Reducing direct greenhouse gas emissions from urban wastewater systems. This project aims to develop a systematic framework for water utilities to monitor and reduce direct greenhouse gas (GHG) emissions from wastewater systems. A standardised monitoring protocol will be developed to conduct an unprecedented nationwide sampling campaign. The obtained data, with microbial characterisation and mechanism analysis, will be used to develop novel models for accurate prediction of GHG emissions. Expect ....Reducing direct greenhouse gas emissions from urban wastewater systems. This project aims to develop a systematic framework for water utilities to monitor and reduce direct greenhouse gas (GHG) emissions from wastewater systems. A standardised monitoring protocol will be developed to conduct an unprecedented nationwide sampling campaign. The obtained data, with microbial characterisation and mechanism analysis, will be used to develop novel models for accurate prediction of GHG emissions. Expected outcomes include protocol to accurately monitor emissions, models to predict emission under various conditions, and mitigation guideline for typical plant configurations. The anticipated benefit is a significant reduction in GHG emissions from urban water industry and support it to meet net-zero-emission goal by 2050.Read moreRead less
CropVision: A next-generation system for predicting crop production. Accurate and timely production estimates are essential to Australia’s grain producers and industry to better deal with down side risk caused by climate extremes and market volatilities. However, current systems for predicting crop production are inaccurate and unreliable. This project aims to develop a next generation system for advance and high accuracy predictions for yield, crop type and area at field scale. This will be don ....CropVision: A next-generation system for predicting crop production. Accurate and timely production estimates are essential to Australia’s grain producers and industry to better deal with down side risk caused by climate extremes and market volatilities. However, current systems for predicting crop production are inaccurate and unreliable. This project aims to develop a next generation system for advance and high accuracy predictions for yield, crop type and area at field scale. This will be done by integrating the state of the art global climate models (GCM), biophysical crop modelling, and high-resolution earth observation technologies. This project will deliver a next generation crop prediction system to predict crop production at field scale for improved decision-making and enhancing resilience.Read moreRead less
Deep Learning Augmented Intelligent Grinding Mill Simulation and Design. Comminution is a key operation in mineral processing that utilises grinding mills to reduce the size of ore for further mineral enrichment processing. The aim of this project is to provide a step change improvement in the operational efficiency and service life of grinding mills through the development of advanced numerical models to simulate the grinding mill process. The outcome will be a hierarchical deep learning progra ....Deep Learning Augmented Intelligent Grinding Mill Simulation and Design. Comminution is a key operation in mineral processing that utilises grinding mills to reduce the size of ore for further mineral enrichment processing. The aim of this project is to provide a step change improvement in the operational efficiency and service life of grinding mills through the development of advanced numerical models to simulate the grinding mill process. The outcome will be a hierarchical deep learning program to select optimal model parameters from which computational algorithms will optimise grinding mill geometries. This research project will deliver substantial improvements to equipment used to process our most valuable exports and result in immediate industry impact.Read moreRead less
A Quantum Matterwave Vortex Gyroscope for Ultrastable Rotation Sensing. This project aims to investigate the basic science underpinning a new rotation sensing technology based on matterwave vortices. Current gyroscopes are susceptible to long-term calibration drifts, which limit their applicability on long timescales where re-calibration is not practical or possible. This project expects to build a matterwave vortex gyroscope and demonstrate that it offers unparalleled long-term stability over ` ....A Quantum Matterwave Vortex Gyroscope for Ultrastable Rotation Sensing. This project aims to investigate the basic science underpinning a new rotation sensing technology based on matterwave vortices. Current gyroscopes are susceptible to long-term calibration drifts, which limit their applicability on long timescales where re-calibration is not practical or possible. This project expects to build a matterwave vortex gyroscope and demonstrate that it offers unparalleled long-term stability over `classical’ gyroscopes based on mechanical and/or optical technology. This could deliver new navigation capabilities, benefitting Australia’s defence forces and nascent space technology industry, as well as enabling slow timescale precision gravimetry for mineral exploration, hydrology, and geology. Read moreRead less
Protein biosensors for detecting smoke exposure of grapes. Bush fires and controlled burns that take place in the vicinity of vineyards can lead to grape contamination with tasteless phenolic glucosides. Their hydrolysis during wine making leads to “smoke taint” – an unpleasant medicinal taste that can render wine undrinkable. We will apply a combination of organic synthesis, protein engineering and directed evolution to develop protein-based biosensors of phenolic glucosides. These biosensors w ....Protein biosensors for detecting smoke exposure of grapes. Bush fires and controlled burns that take place in the vicinity of vineyards can lead to grape contamination with tasteless phenolic glucosides. Their hydrolysis during wine making leads to “smoke taint” – an unpleasant medicinal taste that can render wine undrinkable. We will apply a combination of organic synthesis, protein engineering and directed evolution to develop protein-based biosensors of phenolic glucosides. These biosensors will be used to devise a simple portable colorimetric test that can be performed in the vineyard or the winery. The ability to rapidly determine the level of grape contamination with phenolic glucosides would give Australian wine growers and wine makers a powerful tool to mitigate the effects of bushfires.Read moreRead less