Researchers at Flinders University have discovered an unexpected way that light can control tiny electronic structures inside advanced materials, a development that could help pave the way for more energy efficient memory devices, sensors and future computing technologies.

The new study, with experts from around the world, seeks inroads into electronic properties and optical science by exploring new energy and material capabilities.

Researchers have developed a greener plasma-based method to create multifunctional nanocomposite films with smart optical and antibacterial properties. The approach enables simultaneous control of vanadium oxide structures and in situ formation of gold nanoparticles, producing materials with temperature-responsive infrared modulation and efficient photothermal antibacterial activity. This work provides a sustainable route toward advanced smart coatings and functional materials.

Researchers have developed a polymer-based thermal interface material (TIM) using vertically aligned carbon fibers bridged by graphene oxide. The composite achieves a through-plane thermal conductivity of 7.61 W/m·K at 25.2 wt% filler loading, with an exceptional enhancement efficiency of 162.9%. It also maintains a low compressive modulus of 6.91 MPa, ensuring excellent compressibility for practical electronic cooling applications.

- Professor Min-Soo Kim’s research team in the School of Computing develops RL-SPH, a reinforcement-learning-based method that independently generates feasible solutions without relying on an external optimization solver to enforce feasibility

- Achieves 100% feasibility across five representative ILP benchmarks, with an average 28.6× lower primal gap than fully feasible baselines

- Trains 14.7× faster than representative learning-based approaches, demonstrating potential for AI-based decision-making in logistics, manufacturing, semiconductor production, and workforce management

Researchers developed a battery-free hydrogel bioelectronic patch that wirelessly monitors periodontal inflammation and releases miRNA therapy in response to disease-related enzyme activity. The device links local inflammation sensing with immune modulation, offering a new approach for integrated monitoring and treatment of periodontitis.

Structures exposed to wind, waves or flowing water can be difficult to model and monitor, especially when reliable measurements are scarce. A research team has developed FSI-PINNs, a physics-informed neural network framework that links fluid pressure with structural motion. Using no more than 1% of a simulated dataset, the method predicted flow fields and beam displacement and identified unknown structural density, offering a possible new tool for engineering problems in data-scarce environments.