Biomass offers a renewable source of carbon for producing energy and valuable chemicals, but conventional thermochemical conversion can be limited by energy consumption, heating efficiency and product selectivity. In a review published in the Journal of Bioresources and Bioproducts, researchers examine how electromagnetic induction heating can address some of these challenges. The article surveys its applications in biomass pyrolysis, gasification, reforming and the catalytic upgrading of biomass-derived platform molecules. The review highlights reported improvements in heating rates and energy efficiency, as well as the potential of magnetic catalysts to influence reaction performance. It also identifies important barriers to industrial implementation, including reactor scale-up, incomplete multiphysics modelling and the need for long-term operational validation.

Three-dimensional shape sensing is critical for soft robotics, medical navigation, and intelligent perception systems, yet existing high-performance approaches typically rely on multicore fibers or multiple sensing channels. Researchers from Northwest University have developed a deformation-encoding strategy based on femtosecond-laser-inscribed misplaced orthogonal eccentric scatterers, enabling a standard single-mode fiber to reconstruct complex 3D shapes using only a single interrogation channel. The work establishes a new pathway toward miniaturized, high-density, and highly integrated optical fiber sensing systems.

Infrared adaptive optical systems that correct aberrations via deformable mirrors are critical for astronomy, defense, and industry fields. To this end, scientists in China invented a chain‑ring dual‑network chalcogenide glass that combine broadband infrared-transparent with polymer-like flexibility, which overcomes the long-standing material trade-off. Based on this novel material, they fabricated infrared deformable lenses with real‑time aberration correction, opening new pathways for infrared adaptive optical technology.

Motion correction in live imaging has long posed a critical challenge, as the rhythmic pulsations caused by breathing, heartbeat, and limb movements induce complex rigid and non-rigid deformations that severely compromise high-fidelity, long-term monitoring of large-scale neuronal populations. Now, through the development of an adaptive motion correction framework, a research team from Zhejiang University and Hangzhou City University has successfully overcome the accuracy and computational bottlenecks of traditional algorithms. The discovery is published in the journal PhotoniX.