Critical Technologies Challenge Program round 2 projects

Lead applicant: Avicena Systems Pty Ltd

Avicena will develop and validate a prototype quantum dot plate reader to rapidly screen multiple samples for biosecurity threats. The technology will combine quantum-dot molecular assays with advanced optical detection to identify high-priority invasive diseases, including H5N1 and Lumpy Skin Disease Virus, under operationally relevant conditions. The project will deliver a working prototype designed to improve the speed, accuracy and reliability of biosecurity screening and support earlier decision-making at the border. and across cargo, livestock and quarantine settings.

Lead applicant: iQ Sense Pty Ltd

iQ Sense is developing a continuous, on-farm biosensor to detect zoonotic diseases in cattle, addressing Australia's biosecurity challenge. The system pairs a passive under-skin ear implant with an external eartag reader containing a quantum cascade laser. Stage 2 will build integrated demonstrator units and validate them in a controlled Q Fever and Leptospirosis challenge study in cattle, replacing slow laboratory testing with real-time disease surveillance.

Lead applicant: FeBI Technologies Pty Ltd

FeBI Technologies are developing a novel quantum sensing approach to accurately measure iron status. The project will advance the technology from TRL 5 to TRL 6 by developing an integrated prototype to measure clinical blood samples, compare results against current clinical iron tests, and demonstrate the technology with First Nations partners and Aboriginal Health Practitioners.

Lead applicant: Q Factorial Pty Ltd

Q Factorial will develop and demonstrate a commercially deployable hybrid quantum-classical optimisation platform for dynamic route planning, fleet utilisation and last-mile delivery. The platform will be validated using real-world freight operator data and workflows, progressing from TRL 5 to TRL 7 to support more efficient supply chain operations.

Lead applicant: QuantX Labs Pty Ltd

QuantX Labs Pty Ltd will develop and demonstrate a next-generation quantum clock that maintains grid synchronisation independently of external signals while also enabling stable and resilient renewable-based energy networks. It will deliver a network compatible prototype and validate its performance in an operational environment.

Lead applicant: Silicon Quantum Computing Pty Ltd (SQC) 

Silicon Quantum Computing, Schneider Electric and UNSW will advance the deployment of quantum-enhanced AI in critical energy infrastructure. The project will deliver a production-ready hybrid quantum-classical platform to improve forecasting, support renewables integration and strengthen Australian capability in quantum-enhanced AI.

Lead applicant: Data Effects Pty Ltd

Growing trade and tourism have led to an increase in both complexity and incidence of pathogen outbreaks. Existing surveillance technologies are hampered by the time and cost of running laboratory assays. This project aims to develop a real-time alert leveraging single-protein detection quantum tool based on quantum optical measurement with THz protein fingerprinting capability. Adding this capability to Data Effects’ existing surveillance infrastructure and capabilities will facilitate improvements to response times, more-targeted selection of samples to assay and improved real-time modelling during outbreaks. The combination of all these factors will allow for an increase in surveillance efficacy while also providing a reduction of cost.

Lead applicant: Iugotec Pty Ltd

This project will greatly enhance invasive pest detection capabilities in Australia by harnessing emerging quantum technology to develop a game-changing biosecurity pest detection technology. Our technology will enable species-specific pest detection at scale in an economic package. Key project activities will address limitations with current sensing technology, and develop a novel integrated solution that significantly improves pest detection performance and cost-effectiveness in large scale biosecurity operations.

Lead applicant: Angel Eyecare Pty Ltd

Project Ginan is revolutionising eye care for First Nations communities. Using cutting-edge photonic chip technology, this project is turning large and costly eye scanning machines into small, portable devices that can travel anywhere. These advanced medical imaging tools will help detect serious eye conditions early, before vision is lost. Co-designed with First Nations communities, the new device will be tested to handle tough environments, ensuring it works where it is needed most. Project Ginan is making world-class eye care accessible to First Nations people – elevating vision outcomes and sharing the precious gift of sight with all Australians, no matter where they live.

Lead applicant: Nova Eye Medical Limited

This project will develop a quantum-enhanced optical tweezers system for early glaucoma detection, advancing the technology from TRL 4 to TRL 5 through laboratory-based feasibility testing. The system will use high-precision laser measurements to analyse intraocular fluid viscosity, providing a non-invasive, highly sensitive diagnostic tool. Engagement with First Nations communities will ensure culturally appropriate applications for remote healthcare settings. This project will enhance early detection, improve vision care access, and support future commercialisation of quantum-enabled biomedical sensing technology.

Lead applicant: Q-CTRL Pty Ltd

Remote First Nations communities face limited access to high-quality medical imaging, delaying urgent diagnoses. Portable wireless ultrasound devices increase accessibility, but come at the cost of reduced image quality. Making this a more viable clinical tool in remote communities necessitates advanced image reconstruction exceeding the capabilities of existing software solutions. Our project aims to enable clinical-grade image reconstruction with enhanced clarity through the application of novel quantum computing solutions which overcome these shortcomings. Delivered by a multidisciplinary consortium, this advanced research will deliver real outcomes, bridging the healthcare gap and supporting earlier diagnoses for remote communities. 

Lead applicant: Advanced Navigation Pty Ltd

Our project aims to develop sovereign capabilities in producing high-quality ferroelectric films integrated with photonic integrated circuits using pulsed laser deposition. This will result in ultra-fast electro-optic quantum switches for applications in navigation, quantum computing and AI. CSIRO will lead material development and characterisation, while Advanced Navigation will conduct market analysis and collaborate on the PIC switch architecture. The project will enhance navigation systems, reduce costs and improve supply chain resilience. Post-demonstrator, we will scale up to wafer scale, commercialise the technology, and position Australia as a leader in PICs for telecom, quantum, and navigation.

Lead applicant: Atomionics Australia Pty Ltd

Atomionics Australia, the University of Queensland and Exotopic will revolutionise transport logistics with the development of a non-contact, quantum-based weighbridge. This innovative technology will accurately measure mass, centre of mass and mass distribution of heavy vehicles, aircraft and containers, driving unprecedented operational efficiency and significantly enhancing safety across diverse transportation sectors. Leveraging advanced quantum gravimeters, our solution offers a novel approach to mass parameter determination unlocking capabilities currently beyond reach with conventional methods. The project will demonstrate vehicle mass measurements with the quantum weighbridge and deliver a market-ready business case for Australia.

Lead applicant: Diraq Pty Ltd

The Hamilton Consortium will identify opportunities for using quantum computers in workloads associated with the performance, sustainability, and security of energy networks with a primary emphasis on power systems. To achieve this, Diraq and UNSW’s Real-time Simulations Lab (RTS@UNSW) will integrate Diraq's quantum computing systems with real-time simulations of energy networks. With the support of our partners Macquarie University, AEMO, and Opal-RT, we will also evaluate algorithms that are beneficial to the market, operations, planning, and other aspects related to the power system, leveraging current industry practices.