A research team from Shaanxi Normal University developed a novel catalyst that transforms glycerol waste from bio-diesel production into high-value glyceric acid with remarkable 96.6% selectivity. The innovative Pt-Bi₂O₃ nanosheet catalyst achieves superior performance through a unique synergistic effect: bismuth oxide modifies platinum's electronic structure while controlling glycerol's adsorption orientation. This green upgrade path not only addresses industrial waste challenges but offers a sustainable route to valuable chemicals. The catalyst also shows promising versatility for converting other polyols, opening doors for broader industrial applications.

A recent study published in National Science Review has revealed a previously unknown separated two-phase structure in lithium-manganese-rich cathodes, a breakthrough that could revolutionize the design of high-performance batteries. The discovery allows researchers to precisely manipulate the internal structure of cathodes, offering new opportunities for developing batteries with significantly higher energy density.

Neuroform Atlas Stent (NAS) is used in treating localized dilation of blood vessels in the brain. The stent is designed for placement in vessels of 2.0─4.5 mm diameter. However, studies that assess whether NAS is equally effective in smaller blood vessels are limited. Researchers from China addressed this critical clinical question, and report that even in smaller vessels of diameter less than 2.5 mm, NAS-assisted coiling led to fewer complications and favorable short-term outcomes.

A Chinese research team has developed a new surgical procedure named FENCY ligation, which can be combined with preoperative embolization to safely remove giant plexiform neurofibromas. This technique greatly reduces bleeding and improves surgical outcomes, even in complex areas. Most of the 11 patients reported excellent recovery and high satisfaction, with minimal complications.

Over recent decades, carbon-based chemical sensor technologies have advanced significantly. Nevertheless, significant opportunities persist for enhancing analyte recognition capabilities, particularly in complex environments. Conventional monovariable sensors exhibit inherent limitations, such as susceptibility to interference from coexisting analytes, which results in response overlap. Although sensor arrays, through modification of multiple sensing materials, offer a potential solution for analyte recognition, their practical applications are constrained by intricate material modification processes. In this context, multivariable chemical sensors have emerged as a promising alternative, enabling the generation of multiple outputs to construct a comprehensive sensing space for analyte recognition, while utilizing a single sensing material. Among various carbon-based materials, carbon nanotubes (CNTs) and graphene have emerged as ideal candidates for constructing high-performance chemical sensors, owing to their well-established batch fabrication processes, superior electrical properties, and outstanding sensing capabilities. This review examines the progress of carbon-based multivariable chemical sensors, focusing on CNTs/graphene as sensing materials and field-effect transistors as transducers for analyte recognition. The discussion encompasses fundamental aspects of these sensors, including sensing materials, sensor architectures, performance metrics, pattern recognition algorithms, and multivariable sensing mechanism. Furthermore, the review highlights innovative multivariable extraction schemes and their practical applications when integrated with advanced pattern recognition algorithms.