Photoacoustic computed tomography can provide rich optical contrast over extended penetration depth of biological tissues. However, its capability of multi-scale multi-contrast structural and functional imaging is limited by the inherent size-dependent sensitivity, narrow bandwidth and high material rigidity of the state-of-the-art piezoelectric transducer arrays. The team from Jinan University has proposed a novel sheet-like focusing dual-frequency fiber ultrasound transducer, avoiding the use of multiple transducers to simultaneously capture photoacoustic signals of different frequencies. This design enables deep penetration, high resolution, and precise functional imaging at the entire brain scale and also screening for malignant brain tumors.

Biomass-derived materials are emerging as powerful enablers for sustainable solid-state batteries (SSBs), offering structurally tunable, chemically versatile, and environmentally benign alternatives to conventional battery components. This review critically examines recent advances in the use of bio-derived carbons, polymers, and composites across key SSBs elements, including electrodes, solid electrolytes, binders, and separators. Biomass-derived carbons produced via pyrolysis, hydrothermal carbonization, and molten-salt methods provide hierarchical porosity and controllable graphitization, enabling efficient ion transport, catalytic activity, and mechanical buffering in electrode architectures. Biopolymers such as cellulose, lignin, and chitosan serve as functional matrices for solid polymer and gel electrolytes, enhancing ionic conductivity, interfacial stability, and mechanical integrity, while their intrinsic microstructures can also template low-tortuosity inorganic ceramic electrolytes. In addition, bio-based binders, separators, and electrolyte additives help address critical challenges, including dendrite growth, polysulfide shuttling, and interfacial degradation. Remaining barriers, such as feedstock variability, impurity control, multifunctional performance trade-offs, and scalable processing, are discussed alongside emerging opportunities enabled by artificial intelligence-assisted materials design. By synthesizing fundamental design principles and recent progress, this review highlights how biomass-derived materials can accelerate the development of high-performance, safe, and truly sustainable next-generation SSBs.

A resilience-focused deep reinforcement learning strategy reduced cumulative network performance loss by up to 79.7% relative to conventional signal control in benchmark tests and required up to 45.7% fewer behavioral-adjustment iterations to reach a new equilibrium under severe disruption.

(IDAHO FALLS, Idaho) – For the first time, researchers from Idaho National Laboratory, the Grainger College of Engineering at the University of Illinois Urbana-Champaign, and Purdue University used a geographically distributed control system to remotely and automatically adjust the power of a research reactor in real time, with the reactor’s own safety systems retaining full control throughout. Working with PUR1, a low-power research reactor at Purdue, the team first demonstrated remote power adjustments through an automatic adjustment system called a digital control loop, then made the loop further autonomous using a reinforcement learning model running in software that simulates how physical forces interact within the reactor. The demonstration linked three sites operating together in real time: high-performance computing systems in Idaho, the PUR1 reactor in Indiana, and a Microsoft Azure cloud environment in Virginia.