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.

A new review published in Carbon Research highlights an innovative way for Australia to confront its food waste crisis while cutting greenhouse gas emissions: transforming food scraps into biochar.

A team of researchers has developed a powerful new method to measure how much carbon mango orchards can store, using artificial intelligence and satellite imagery. Their approach could help farmers and policymakers better understand the role of fruit trees in tackling climate change.