A research team from the Institute of Advanced Materials (INAM) at the Universitat Jaume I, comprising members of the Electrocatysis and Energy Group (ECATEN) and the Hybrid Catalytic Materials Group (HyCaM), has developed a new methodology for producing advanced catalytic materials for oxidation processes applicable to the chemical and petrochemical industries, as well as the energy sector.

The innovation lies in the modification of conductive supports to significantly improve their catalytic activity and efficiency. The invention has been validated at laboratory scale and in a 100 cm² demonstration prototype. Tests have shown optimal performance in the oxidation of various organic compounds and biomass-derived products, “confirming the material’s stability and its ability to operate efficiently under real-use conditions”, according to the research team.

Electric vehicles (EVs) are crucial for sustainable transport, but their environmental benefit depends heavily on when they charge. Charging during periods when the grid relies on fossil fuels can significantly increase their carbon footprint. New research from Multimedia University reveals that "carbon-aware" charging strategies can unlock substantial emission reductions simply by optimizing charging times.

The study, led by Md Sabbir Hossen and Gobbi Ramasamy from Multimedia University, quantifies the real-world carbon emission reduction potential of smart EV charging. Researchers reconstructed hourly residential charging data and combined it with time-varying grid carbon intensity from the Malaysian Peninsula power system. They then evaluated a reinforcement learning-based carbon-aware smart charging strategy, comparing its performance against both uncontrolled charging and an intelligent but carbon-unaware charging approach, all while delivering identical total energy.

The Power of Carbon Awareness

The findings are compelling: while intelligent charging without carbon awareness failed to reduce total carbon emissions, the carbon-aware strategy achieved a statistically significant reduction of approximately 1.62%. This crucial difference comes from proactively shifting charging demand away from periods when grid electricity is most carbon-intensive. Specifically, evening peak hours were found to be approximately 18% more carbon-intensive than off-peak periods, making targeted load shifting highly effective.

Non-line-of-sight (NLOS) imaging enables recovery of hidden scenes but is constrained by a speed-resolution trade-off in conventional scanning systems. We propose a scanning-free approach based on laser reflective tomography, using a diffuse relay surface as a natural beam expander and requiring only single-point detection. This method achieves twofold higher resolution and 91-fold faster imaging, and enables 3.3 km long-range reconstruction with 3 cm resolution in just 3 minutes.