About the projects
Fourteen projects received feasibility grants to solve nationally significant challenges through round 2 stage 1 of the CTCP.
Some projects are seeking additional participants or funding to support their expenditure, in line with the grant guidelines on business.gov.au.
You can find project details below under the challenge they responded to.
Each grantee submitted a pitch of 300 words maximum in round 1. We've included them verbatim with only light edits for Australian Government style.
If you would like to contact any of the projects to discuss collaboration or funding opportunities, please email digitalprograms@industry.gov.au. We’ll pass your details on, however there’s no guarantee that you’ll receive a response from the project team. Please include the project title for the project(s) that interests you.
Challenge 1: Improve biosecurity outcomes by enhancing the detection of invasive pests or diseases, and cargo inspection processes
Real-time monitoring of zoonotic diseases in livestock using quantum sensors
Lead applicant: iQ Sense Pty Ltd
iQ Sense is developing a real-time biosensor for livestock disease detection, enhancing Australia’s biosecurity resilience. Using quantum sensing technology, the biosensor continuously monitors key biomarkers for zoonotic diseases, providing early warnings to farmers and veterinarians. The project includes prototype development, field trials, and AI-driven analytics integration. This innovation will reduce disease outbreaks, improve livestock health, and support data-driven biosecurity policies, positioning Australia as a leader in quantum biosensing for agriculture.
QS3-Quantum powered pest detection with selectivity, sensitivity and scale
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.
Quantum-enabled detection of invasive pathogens for improved biosecurity
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.
Combining next generation quantum biosensors for ultrasensitive diagnostics
Lead applicant: Avicena Systems Pty Ltd
The sensitivity of rapid multiplexed fluorescence-based diagnostics is still hampered by poor signal discrimination, even despite highly efficient chemistries like Loop Mediated Isothermal amplification (LAMP). We will validate unique combinations of quantum nanomaterials (upconverting nanoparticles and quantum dots) and detection methods using single photon counting. Frequency and time responses of resonance energy transfers between these nanomaterials will be used to reduce the background signal, while novel conjugation strategies increase the signal. We will validate these tools with Avicena’s automated Sentinel platform for unprecedented scale and speed of detection, while achieving best-in-class sensitivity.
Challenge 2: Improve life expectancy, health outcomes and access to health technology for First Nations peoples
Project Ginan: Quantum eye imaging for remote First Nations communities
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.
Quantum-enhanced medical imaging diagnostics for remote communities
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.
Quantum sensing to improve iron diagnosis in First Nations peoples
Lead applicant: FeBI Technologies Pty Ltd
FeBI Technologies are developing a novel quantum sensing approach to accurately measure iron status. Iron is vital for health, and iron disorders affect up to 1 in 3 people globally. Current iron tests are confounded by chronic health conditions, resulting in misdiagnosis and delayed treatment, which disproportionately impacts First Nations peoples. In partnership with First Nations communities, we will assess the use of our quantum solution to improve health outcomes and access to health technologies. Key activities include community engagement and developing a prototype for testing of clinical blood samples to advance our inexpensive solution from technological readiness (TRL) 4 to TRL5.
Optimising ophthalmic treatments for use in Indigenous communities
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.
Challenge 3: Optimise transport routes, logistics and supply chain operations.
Development of a quantum-based, non-contact weighbridge
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.
Supply chain optimisation with a quantum solver for last-mile delivery
Lead applicant: Q Factorial Pty Ltd
Last-mile delivery is a crucial component of most supply chains, where product is moved from a warehouse to its final destination. We are tailoring our proprietary quantum heuristic specifically for the optimisation of last-mile delivery, creating a commercially viable product (the solver) that helps companies reduce costs and emissions. Initial simulations suggest that our heuristic will achieve a 5–10% improvement in total distance travelled versus incumbent vehicle routing products. We are now recruiting industry partners as part of stage 2, to provide the operational environment for integration and to ensure the solver aligns with real-world constraints.
Quantum circuits for improved logistics and supply chain solutions
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.
Challenge 4: Optimise the performance, sustainability and security of energy networks
Quantum machine learning for predictive optimisation of energy resources
Lead applicant: Silicon Quantum Computing Pty Ltd (SQC)
Schneider Electric are global leaders with a strong presence in home energy management in Australia. Their strategies include using machine learning techniques to optimise consumer energy resources for a reduction in electricity cost. SQC has developed a quantum processor which acts as an AI accelerator, atomically engineered to improve the accuracy of machine learning for sparse data sets and time-series data. Combining SQC’s quantum hardware with Schneider’s AI systems will improve capacity to predict user load and when to switch back and forth to solar energy generation. This will enable better decision-making reducing electricity cost and improving renewable energy utilisation, helping Australia meet its 82% renewables target by 2030.
Quantum solutions for energy networks
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.
Quantum timing for secure and scalable energy networks
Lead applicant: Quantx Labs Pty Ltd
This project focuses on the practical integration of quantum clocks to eliminate GNSS-based timing vulnerabilities in distributed energy systems. By combining QuantX’s quantum clock expertise with Siemens Australia’s advanced energy technologies, we will assess a space-independent, alternative timing infrastructure for next-generation power networks. Central to this effort is our design and testing using the Siemen’s digital twin of Australia’s energy grid. Our primary outcome will be a technology roadmap for integrating quantum timing into energy networks, bridging the gap between theoretical research and real-world implementation, resulting in resilient, scalable and secure energy solutions.