Ambient Electrochemical C-N Coupling via Co-electrolysis of N2 and CO2. To overcome the hurdles in N2 fixation (massive energy consumption and CO2 emission), investigators creatively hypothesize that the simultaneous electrocatalytic coupling of N2 and CO2 would enable the selective formation of N-products and thus realize their conversion into N--fertilizers and acetamides. Based on the CI's recent discoveries, this project will develop an innovative / sustainable system, which could promote th ....Ambient Electrochemical C-N Coupling via Co-electrolysis of N2 and CO2. To overcome the hurdles in N2 fixation (massive energy consumption and CO2 emission), investigators creatively hypothesize that the simultaneous electrocatalytic coupling of N2 and CO2 would enable the selective formation of N-products and thus realize their conversion into N--fertilizers and acetamides. Based on the CI's recent discoveries, this project will develop an innovative / sustainable system, which could promote the N2 fixation along with CO2 conversion process, a significant alternative approach to simplify the pathways of C-N bond formation. It will thereby contribute to mitigation of greenhouse emissions and create an ecofriendly protocol/technology for distributed production of C-N products under ambient conditions. Read moreRead less
Carbon-free Energy Storage and Conversion Using Ammonia as a Mediator. This project aims to develop essential technologies for ammonia-mediated energy storage, hydrogen production, and electricity generation. This project expects to generate new understandings on designing novel multi-atom-cluster catalysts for the critical ammonia synthesis, electrolysis, and oxidation processes using interdisciplinary approaches. The expected outcomes of this project include multi-functional electrocatalysts, ....Carbon-free Energy Storage and Conversion Using Ammonia as a Mediator. This project aims to develop essential technologies for ammonia-mediated energy storage, hydrogen production, and electricity generation. This project expects to generate new understandings on designing novel multi-atom-cluster catalysts for the critical ammonia synthesis, electrolysis, and oxidation processes using interdisciplinary approaches. The expected outcomes of this project include multi-functional electrocatalysts, fundamental insights of principles for electrocatalyst design, and prototype technologies. This should provide significant benefits for the harvest of clean energy, the safe utilization of hydrogen, and the development of carbon-free fuels, which are essential for optimizing the energy structure of Australia.Read moreRead less
Controlling and Understanding Interface Chemistry for Energy Conversions. This project aims to develop a promising electrocatalyst technology platform, based on novel 2D material architectures that have applications ranging from hydrogen generation via water splitting through to carbon dioxide reduction. The project is expected to generate advanced knowledge for the rational design of electrocatalysts and to promote the development of renewable energy technologies. Expected outcomes include a cl ....Controlling and Understanding Interface Chemistry for Energy Conversions. This project aims to develop a promising electrocatalyst technology platform, based on novel 2D material architectures that have applications ranging from hydrogen generation via water splitting through to carbon dioxide reduction. The project is expected to generate advanced knowledge for the rational design of electrocatalysts and to promote the development of renewable energy technologies. Expected outcomes include a clear understanding of the relevant fundamental science and mechanisms, a framework for designing and optimising for specific applications, and a demonstration of prototype devices. This project is of great benefit for addressing Australia’s energy and environmental concerns and boosting national economic growth as well.Read moreRead less
Bioinspired Nanoionic Materials for Watt-scale Nano-Hydroelectric Generator. Inspired by electric eels, this project aims to develop next generation flexible and eco-friendly power sources that can directly generate electricity from water droplets for self-powered, light-weight wearable electronics. The goal will be achieved by designing a new class of nanoionic materials for nano-hydroelectric generators, through optimizing the ion diffusion channel, interfacial architecture, electrode configu ....Bioinspired Nanoionic Materials for Watt-scale Nano-Hydroelectric Generator. Inspired by electric eels, this project aims to develop next generation flexible and eco-friendly power sources that can directly generate electricity from water droplets for self-powered, light-weight wearable electronics. The goal will be achieved by designing a new class of nanoionic materials for nano-hydroelectric generators, through optimizing the ion diffusion channel, interfacial architecture, electrode configuration, and power management systems. The expected outcomes will be new nanoionic materials for a wide range of end uses in portable power supply with much higher capacity compared with conventional thin film batteries, significant advances in wearable electronics, and advancing knowledge in energy conversion sector.
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Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an ....Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.Read moreRead less
Adversarial Learning of Hybrid Representation. This project aims to design and implement a foundational deep representation learning framework for early detection, classification and defense of emerging malware by capturing their underlying behaviours via structured and unstructured heterogeneous information through hybrid representation learning, behaviour graph mining, and symbolic adversarial learning to discover and defend unknown malware families, thereby significantly boosting the accuracy ....Adversarial Learning of Hybrid Representation. This project aims to design and implement a foundational deep representation learning framework for early detection, classification and defense of emerging malware by capturing their underlying behaviours via structured and unstructured heterogeneous information through hybrid representation learning, behaviour graph mining, and symbolic adversarial learning to discover and defend unknown malware families, thereby significantly boosting the accuracy and robustness of existing classifiers and detectors. The resulting representation learning framework will enhance the national security to protect user privacy, reducing the multi-million-dollar loss caused by fraudulent transactions, and defending against cyber attacks.Read moreRead less
Extending Remaining Useful Life of Second-life Battery Energy Systems. The project aims to develop a framework to reuse second-life battery packs with different degradation levels. This includes a novel machine learning and online battery state estimation algorithm that does not require past use case historical data of the SLBs, an advanced control algorithm to balance the energy in each battery pack and an optimized modular inverter architecture with integrated voltage boosting capability to ma ....Extending Remaining Useful Life of Second-life Battery Energy Systems. The project aims to develop a framework to reuse second-life battery packs with different degradation levels. This includes a novel machine learning and online battery state estimation algorithm that does not require past use case historical data of the SLBs, an advanced control algorithm to balance the energy in each battery pack and an optimized modular inverter architecture with integrated voltage boosting capability to manage the batteries and meet the control objectives. This benefits not only the environment through delayed e-waste or recycling cycles but also helps the Australian manufacturing sector through a circular economy of energy products and services.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
Deep analytics of non-occurring but important behaviours. This project aims to build a systematic theory for the deep analytics of complex and important occurring and non-occurring behaviours. Behaviours that should occur but do not take place, called non-occurring behaviours (NOB), are widely evident but easily overlooked, such as missed important medical treatments. While often occurring behaviours are focused, such NOB may be associated with significant effects such as a threat to health. Thi ....Deep analytics of non-occurring but important behaviours. This project aims to build a systematic theory for the deep analytics of complex and important occurring and non-occurring behaviours. Behaviours that should occur but do not take place, called non-occurring behaviours (NOB), are widely evident but easily overlooked, such as missed important medical treatments. While often occurring behaviours are focused, such NOB may be associated with significant effects such as a threat to health. This project expects to fill the knowledge gaps in representing, analysing and evaluating NOB complexities and impact, with significant benefits for the evidence-based detection, prediction and risk management of covert NOB applications and their important effects.Read moreRead less
High temperature corrosion induced by multiple secondary oxidants . Heat resisting chromia-forming alloys passivate successfully in clean, dry air at temperatures up to about 950°C. However, this performance is degraded by secondary oxidants (carbon, sulphur, chlorine, water vapour), leading to corrosion failure in important industries. The project aims to investigate the effect of these secondary oxidants on corrosion behaviour of chromia-forming alloys, to identify interactions between multipl ....High temperature corrosion induced by multiple secondary oxidants . Heat resisting chromia-forming alloys passivate successfully in clean, dry air at temperatures up to about 950°C. However, this performance is degraded by secondary oxidants (carbon, sulphur, chlorine, water vapour), leading to corrosion failure in important industries. The project aims to investigate the effect of these secondary oxidants on corrosion behaviour of chromia-forming alloys, to identify interactions between multiple oxidants within the scale, to establish the mechanisms of oxide scale penetration by foreign species, and to evaluate scales on different alloy types. The results will provide a basis for improved design/selection of heat resisting chromia-forming alloys, key to power generation industries.Read moreRead less