Organically-Capped Copper Nanowires for Soft Electronic Skin Sensors. Soft skin-like electronics can enable applications that are impossible to achieve with today's rigid circuit board technologies. However, it is difficult to realise such future soft electronics with traditional materials and conventional manufacturing methodologies. This project aims to synthesise novel organically-capped copper nanowires as electronic inks (e-inks) for developing cost-effective, soft, stretchable conductor (e ....Organically-Capped Copper Nanowires for Soft Electronic Skin Sensors. Soft skin-like electronics can enable applications that are impossible to achieve with today's rigid circuit board technologies. However, it is difficult to realise such future soft electronics with traditional materials and conventional manufacturing methodologies. This project aims to synthesise novel organically-capped copper nanowires as electronic inks (e-inks) for developing cost-effective, soft, stretchable conductor (e-skin) sensors, which are wearable for monitoring blood pulses, body motions and hand gestures in real-time and in situ. This is expected to advance our knowledge in nanotechnology and generate patentable technologies in soft e-skin sensors, and to bring significant scientific and economic gains to Australia.Read moreRead less
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less
Self-assembling nanoporous graphene with dialable pore sizes for green energy production. The biggest barrier to the Sun being our main energy source is it is not always available. This can be overcome by having an economical means of storing solar energy as it is produced. This project will demonstrate such a technology by using nanoporous graphene to support artificial photosynthesis to produce fuel from water and carbon dioxide using sunlight.
On-Chip Detection and Molecular Fingerprinting of Emerging Toxicants. The project aims to address key questions about the development and integration of advanced materials and functional molecules into cutting-edge analytical tools for screening emerging environmental pollutants. This is expected to generate fundamental and applied knowledge in analytical chemistry, using an interdisciplinary approach to engineer materials with precisely tailored properties for ultra-sensitive and selective dete ....On-Chip Detection and Molecular Fingerprinting of Emerging Toxicants. The project aims to address key questions about the development and integration of advanced materials and functional molecules into cutting-edge analytical tools for screening emerging environmental pollutants. This is expected to generate fundamental and applied knowledge in analytical chemistry, using an interdisciplinary approach to engineer materials with precisely tailored properties for ultra-sensitive and selective detection of extremely persistent toxicants in water. Anticipated outcomes are optical materials and functional molecules, integrated into lab-on-a-chip platforms with advanced features for real-life environmental applications – with significant benefits for addressing major environmental and health treats to our society.Read moreRead less
Bioinspired photo–iontronic membranes for smart neuron-mimicking systems. The project aims to address key fundamental questions about the development of bioinspired artificial nanochannels that can precisely mimic current signals and functionalities in neurons. This is expected to generate fundamental and applied knowledge in bioengineered photo–iontronic systems, harnessing a multidisciplinary approach to engineer materials with precisely tailored properties at the nanoscale for unprecedented d ....Bioinspired photo–iontronic membranes for smart neuron-mimicking systems. The project aims to address key fundamental questions about the development of bioinspired artificial nanochannels that can precisely mimic current signals and functionalities in neurons. This is expected to generate fundamental and applied knowledge in bioengineered photo–iontronic systems, harnessing a multidisciplinary approach to engineer materials with precisely tailored properties at the nanoscale for unprecedented dynamic control over ionic current through responsive, adaptable neuron-mimicking nanopores. Anticipated outcomes are advanced materials, integrated into smart architectures to overcome the limitations of solid-state systems for the next generation of integrated circuits, bio-interfacial sensors, and energy generators.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE150100040
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
Advanced capabilities for surface engineering and nanolithography . Advanced capabilities for surface engineering and nanolithography: This project will establish a facility for atomic layer deposition and nanolithography. Strong fabrication and engineering capabilities are key in keeping interdisciplinary research highly competitive. The applications of these cutting-edge surface nanoengineering technologies are enormous and include: development of new materials with new properties for sensing, ....Advanced capabilities for surface engineering and nanolithography . Advanced capabilities for surface engineering and nanolithography: This project will establish a facility for atomic layer deposition and nanolithography. Strong fabrication and engineering capabilities are key in keeping interdisciplinary research highly competitive. The applications of these cutting-edge surface nanoengineering technologies are enormous and include: development of new materials with new properties for sensing, biosensing, optical, photonic, electronic and medical devices, new metamaterials, solar cell, energy production and environmental protection.Read moreRead less
Multi-modal virtual microscopy for quantitative diagnostic pathology. This project will contribute to the next generation of virtual microscopy systems that provide innovative features capable of significantly increasing the adoption of digital imaging technology throughout the field of diagnostic pathology. These tools will especially contribute to the screening and diagnosis of cervical, lung and bladder cancer.
Deep Learning that Scales. Deep learning has dramatically improved the accuracy of a breathtaking variety of tasks in AI such as image understanding and natural language processing. This project addresses fundamental bottlenecks when attempting to develop deep learning applications at scale. First, this project proposes efficient neural architecture search that is orders of magnitude faster than previously reported, abstracting away the most complex part of deep learning. Second, we will desig ....Deep Learning that Scales. Deep learning has dramatically improved the accuracy of a breathtaking variety of tasks in AI such as image understanding and natural language processing. This project addresses fundamental bottlenecks when attempting to develop deep learning applications at scale. First, this project proposes efficient neural architecture search that is orders of magnitude faster than previously reported, abstracting away the most complex part of deep learning. Second, we will design very efficient binary networks, enabling large-scale deployment of deep learning to mobile devices. Thus this project will overcome two primary limitations of deep learning generally, however, and will greatly increase its already impressive domain of practical application.Read moreRead less
Adapting Deep Learning for Real-world Medical Image Datasets. The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collabor ....Adapting Deep Learning for Real-world Medical Image Datasets. The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collaborations with machine learning and medical image analysis research institutions. This should provide significant benefits, such as better understanding of deep learning theory, new deep learning applications that can use previously unexplored data sets, and training for the future Australian workforce.Read moreRead less
From insects to robots: how brains make predictions and ignore distractions. This project aims to address fundamental questions in neuroscience and to integrate this biological understanding with the development of leading-edge robotics. Whether a human catching a ball or a dragonfly feeding in a swarm, brains have the remarkable ability to predict the future location of moving targets. The brain predicts in the presence of distractions and even if the target disappears, for example, when hidden ....From insects to robots: how brains make predictions and ignore distractions. This project aims to address fundamental questions in neuroscience and to integrate this biological understanding with the development of leading-edge robotics. Whether a human catching a ball or a dragonfly feeding in a swarm, brains have the remarkable ability to predict the future location of moving targets. The brain predicts in the presence of distractions and even if the target disappears, for example, when hidden behind another object. This project will investigate how brains use both environmental and internal information to select a target and predict its future location. By implementing bio-inspired computations in hardware, this project aims to provide significant benefits such as improving autonomous systems for defence, health and transportation.Read moreRead less