Plant based foods: Towards sustainable and acceptable meat analogues. The project aims to address the need for engineering plant-based food products to deliver a sensory experience akin to meat. The project expects to generate new knowledge on the structural drivers for emulating meat-like texture and taste within burger products. Expected outcomes of this project include new ingredients and food characterisation methodologies, including rheology and sensory, which can be employed in rational ....Plant based foods: Towards sustainable and acceptable meat analogues. The project aims to address the need for engineering plant-based food products to deliver a sensory experience akin to meat. The project expects to generate new knowledge on the structural drivers for emulating meat-like texture and taste within burger products. Expected outcomes of this project include new ingredients and food characterisation methodologies, including rheology and sensory, which can be employed in rational food structure design. This should provide significant benefits in enhancing the consumer acceptance of plant-based foods that is required to support the rapidly growing market opportunity for them and sustainable food production.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190100413
Funder
Australian Research Council
Funding Amount
$384,000.00
Summary
Hybrid nanowire-nanoantenna infrared photodetectors. This project aims to demonstrate room temperature hybrid nanowire-nanoantenna infrared photodetectors by integrating plasmonic nanoantennas on semiconductor nanowire arrays. It is expected that such novel device architectures will not only bring enhanced performance in responsivity, detectivity, and photoresponse bandwidth, but also additional functionalities such as selective wavelength and tunable polarisation, which may significantly outper ....Hybrid nanowire-nanoantenna infrared photodetectors. This project aims to demonstrate room temperature hybrid nanowire-nanoantenna infrared photodetectors by integrating plasmonic nanoantennas on semiconductor nanowire arrays. It is expected that such novel device architectures will not only bring enhanced performance in responsivity, detectivity, and photoresponse bandwidth, but also additional functionalities such as selective wavelength and tunable polarisation, which may significantly outperform current infrared technology. The outcomes will provide a new device platform for next-generation, large-scale, reduced-cost, high-performance imaging systems in self-driving navigation, object identification, spectroscopy, and other high-end defence and civilian applications.Read moreRead less
Miniaturised biosensors with high selectivity . This project aims to develop a technological platform for the fabrication of miniaturised and flexible sensors that enable the quantitative detection of important bioactive compounds such as fatty acids and biogenic amines. By utilising multi-enzymatic reactions in solid phase and engineering task-specific inks, chemiresistive sensors will be printed seamlessly as a whole. The sensors will respond to complex target biomolecules via a series of enzy ....Miniaturised biosensors with high selectivity . This project aims to develop a technological platform for the fabrication of miniaturised and flexible sensors that enable the quantitative detection of important bioactive compounds such as fatty acids and biogenic amines. By utilising multi-enzymatic reactions in solid phase and engineering task-specific inks, chemiresistive sensors will be printed seamlessly as a whole. The sensors will respond to complex target biomolecules via a series of enzymatic reactions through which the analyte will convert to much simpler, reactive and hence measurable molecules. This project will enable to design miniaturised sensors for point-of-care detection of biomolecules that cannot be yet evaluated by the end users.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
Robust learning of dynamic systems. Robots and other autonomous machines use models of the real world to predict the result of their actions and make decisions, but existing methods used for machine-learning are unreliable in many cases and can be easily fooled. This project aims to make machine-learning of dynamic system models reliable, accurate, and secure. The outcomes of this project will be new models and algorithms that ensure safety and increase accuracy of models learned from data. This ....Robust learning of dynamic systems. Robots and other autonomous machines use models of the real world to predict the result of their actions and make decisions, but existing methods used for machine-learning are unreliable in many cases and can be easily fooled. This project aims to make machine-learning of dynamic system models reliable, accurate, and secure. The outcomes of this project will be new models and algorithms that ensure safety and increase accuracy of models learned from data. This project will benefit robotics, control engineering, infrastructure automation, and other fields that demand the capability to model physical systems from limited data. It will also improve cybersecurity by making learning algorithms resilient to deliberate attacks with false data.Read moreRead less