A review by Professor Abdul Shukor JURAIMI’s team from Universiti Putra Malaysia points out that hyperspectral imaging technology boasts advantages of non-contact operation, high precision, and early detection. Compared with traditional manual visual inspection, it can complete detection within 10–30 days after rice sowing—a critical period when weeds are most competitive—with an identification accuracy generally exceeding 90%. For example, regarding Echinochloa crus-galli and weedy rice (Oryza sativa f. spontanea), the most common weeds in rice fields, researchers achieved identification accuracies of 100% and 92%, respectively, by analyzing spectral data with intelligent algorithms. This accurate identification lays the foundation for targeted weeding: combined with UAVs and prescription mapping technology, it enables site-specific herbicide application, reducing pesticide usage by up to 50%. This not only cuts costs but also alleviates environmental burdens. The relevant article has been published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2025619).

Two novel 56π-electron fullerene derivatives, bearing bulky functional groups and named C₆₀-TFB and C₆₀-TFP, were developed and employed as electron transport layers in inverted perovskite solar cells (IPSCs). These new fullerene derivatives demonstrate excellent resistance to dimerization and effective defect passivation, which helps prevent the interdiffusion of iodide ions from the perovskite layer and silver atoms from the cathode. Consequently, the optimized IPSC achieved a high efficiency of 25.93% along with significantly enhanced stability.

Researchers from the University of Jaffna and Imperial College London have uncovered critical insights into optimizing Na₂FeSiO₄, a low-cost, abundant cathode material for sodium-ion batteries (SIBs). Published in Front. Energy, their computational study pinpoints ideal dopants and reveals favorable ion transport properties, bringing SIBs— a sustainable alternative to lithium-ion batteries—closer to large-scale energy storage applications.

Recently, a research team led by Professor Li-sheng Geng from Beihang University published a paper titled "Femtoscopy can tell whether Zc(3900) and Zcs3985 are resonances, virtual states, or bound states" in Science Bulletin. This study demonstrates for the first time that the femtoscopic technique can effectively distinguish whether the tetraquark candidates Zc(3900)/Zcs3985 near the D0D*-/D0Ds*- thresholds are resonances, virtual states, or bound states, which helps deepen the understanding of the non-perturbative nature of Quantum Chromodynamics.

A research team of mathematicians and computer scientists has used machine learning to reveal new mathematical structure within the theory of finite groups. By training neural networks to recognise simplicity in algebraic data, the team discovered and proved a new theorem on the necessary properties of generators of finite simple groups. This work demonstrates how artificial intelligence can assist in formulating and even proving conjectures in pure mathematics. The 2-generator representation furthers earlier work of one of the authors with M. Kim using Cayley Tables, showing that simplicity has interesting data structure.

As electric vehicles (EVs) zoom into the mainstream—thanks to pioneers like Tesla and a global push to ditch fossil fuels—the power grid is feeling the strain from surging charging demands. Traditional setups struggle with reliability, costs, and environmental impacts, especially when integrating intermittent solar photovoltaic (PV) systems. Enter the game-changer: EV charging stations (EVCS) fused with PV panels and battery energy storage systems (BESS). This research tackles the chaos by optimizing station placement and operations in distribution networks, ensuring efficient power flow while curbing emissions and expenses. By addressing these hurdles, it paves the way for sustainable transport that doesn't overload our aging grids, making EVs a practical choice for everyone from city commuters to long-haul drivers.