A new study led by Nigerian researchers suggests a simple ingredient could make diesel engines cleaner: water. By blending precise amounts of water with diesel fuel, scientists have shown that emissions of several harmful pollutants can be dramatically reduced without major engine modifications.

Researchers at Okayama University of Science (OUS) have developed a new histological staining technique that allows direct visualization of ancient proteins within fossil tissues, preserving their microstructural context. This innovative approach enables scientists to verify the authenticity of endogenous proteins—those that originated from the ancient organism itself—before performing complex molecular analyses, reducing contamination risks that have long challenged paleoproteomic studies. Tested on Pleistocene elephant fossils from Japan, the method successfully detected Type I collagen using Van Gieson’s staining, with findings confirmed by mass spectrometry. The study also revealed that bone preserves proteins better than dentine, offering valuable guidance for future fossil analysis. This simple yet powerful technique could revolutionize how researchers screen fossils for preserved proteins, paving the way for future investigations into even older specimens, including dinosaurs.

Researchers from the University of Melbourne have discovered a sustainable new use for lignite, also known as brown coal, showing how it can clean up toxic heavy metals from wastewater and then be reused as a light‑driven catalyst for breaking down pollutants.

A research team from the Harbin Institute of Technology has developed a new analytical method to accurately calculate the performance of high-torque permanent magnet motors. This approach successfully accounts for the armature magnetic field, which often ignored in traditional methods and leads to significant calculation errors. The new model demonstrates high precision in calculating critical performances like air-gap flux density, back EMF, and output torque, providing a reliable tool for optimizing high-performance motor design.

Artificial intelligence (AI) technology is revolutionizing antimicrobial drug development. In response to increasingly severe antimicrobial resistance challenges, AI can efficiently predict pathogen evolutionary trends, identify potential drug targets, and accelerate compound design and optimization, thereby significantly shortening the development timeline for antimicrobial agents. This correspondence focuses on the applications of AI in phenotype-driven target identification and validation, rational molecular design, and lead compound optimization for antimicrobial drug development, while highlighting current limitations and providing perspectives on future directions.

A research team from Sichuan University, in collaboration with Southeast University and the Hong Kong University of Science and Technology (Guangzhou), has proposed a novel dual three-phase four-level space vector pulse width modulation (DTP-FL SVPWM) strategy to improves the efficiency and precision of high-power motor drives. The proposed strategy is designed for the developed dual three-phase open-winding permanent magnet synchronous motors (DTP-OW-PMSM). This technology achieves high modulation precision and low switching frequency. On this basis, the current harmonics caused by the DC-link voltage deviations are reduced by compensating for the duty ratio.

Researchers at National Institute of Technology Puducherry develop a centroid-synthesized virtual voltage vector method for induction motor drives, cutting switching losses while maintaining dynamic performance.