Haploid plants, which carry only a single set of chromosomes, are typically sterile, making them valuable but difficult to use in breeding. 

Theanine, a unique amino acid responsible for tea's refreshing taste and calming effect, plays a central role in determining tea quality. 

Bright squeezed light, combining quantum noise reduction with high optical power, is a valuable resource for quantum sensing. To achieve this goal, scientists in China developed a nonclassical hybrid passive–active power stabilization technique that extends the stabilization bandwidth to MHz frequencies. They experimentally realized −5.5 dB squeezing at 1 mW across the kHz–MHz band. The novelty technique enables the new possibilities in quantum metrology and precision measurement.

Laser-driven near-infrared II (NIR-II) light sources comprising luminescent ceramics represent a promising research frontier. A non-equivalent cation substitution strategy was presented to fabricate high-efficiency translucent MgO:Ni²⁺,Cr³⁺ NIR-II luminescent ceramics. The co-doping of Cr³⁺ induces structural distortion at Ni²⁺-occupied octahedral sites, effectively breaking the parity-forbidden d-d transition constraint while enabling efficient energy transfer from Cr³⁺ to Ni²⁺. When integrated into laser-driven NIR-II light sources, the system achieves record-breaking performance of 214 mW output power under 21.43 W/mm² blue laser excitation.

Researchers have found a new way to turn low-frequency light into higher-frequency terahertz waves using special quantum materials called topological insulators. By placing these materials inside tiny ring-shaped structures that boost light signals, they created both even and odd harmonics—something rarely seen before. This breakthrough could lead to better ways of generating terahertz light, which is useful for imaging, communication, and exploring new physical effects in advanced materials.

Bochum, Germany, October 29, 2025, Researchers from Research Center for Future Energy Materials and Systems at the Ruhr University Bochum, Software for Chemistry & Materials BV, and Vrije Universiteit Amsterdam have demonstrated that modern universal machine learning interatomic potentials (uMLIPs) can now accurately describe systems ranging from single molecules to bulk solids, representing a significant leap forward for uMLIPs in materials science. The study introduces the 0123D dataset, comprising 40,000 diverse structures specifically designed to benchmark model performance across all dimensionalities.