Heavy metal pollution in farmland creates a problem that does not end when contaminated plants are harvested. Crop residues and plants used to remove metals from polluted soils can themselves contain substantial amounts of mercury, cadmium, lead, nickel and other potentially hazardous elements. If these materials are burned, landfilled or returned directly to farmland, the metals may be released again into the environment.

A new study published in the Journal of Bioresources and Bioproducts reports a scalable strategy for producing multifunctional cellulose-based foam without relying on freeze-drying or solvent exchange. The researchers constructed a hierarchical network from bamboo fibers, TEMPO-oxidized cellulose nanofibrils (TOCNFs) and multiwalled carbon nanotubes (MWCNTs), followed by zinc-ion crosslinking and in-situ polymerization of polyaniline (PANI). The resulting foam combines low density, mechanical robustness and electrical conductivity with electromagnetic interference shielding and thermal protection. The optimized material achieved an EMI shielding effectiveness of 61.56 dB, a specific shielding efficiency of 2,375.2 dB cm²/g, a limiting oxygen index of 56.8% and a thermal conductivity of 0.085 W/(m·K). It also demonstrated electrically controlled heating and infrared camouflage, highlighting the potential of biomass-derived porous networks for multifunctional protection.

The continuous threat of mutating viral strains demands effective broad-spectrum mucosal vaccines, but delivering multivalent antigens across respiratory barriers remains a major challenge. To overcome these physiological hurdles, a research team developed a novel mucosal vaccine platform utilizing gold nanoparticles (AuNPs). By co-displaying multiple Betacoronavirus antigens on AuNPs optimized to penetrate respiratory barriers, this "mosaic" vaccine significantly enhances antigen uptake and retention in the lungs. When administered intranasally alongside an adjuvant, the multivalent AuNP-Mix elicited robust local mucosal immunity, prominently inducing high levels of secretory IgA and activating lung tissue-resident memory T (TRM) cells. This response effectively generated cross-neutralizing antibodies against various strains and established comprehensive, long-lasting mucosal B and T cell memory. This innovative delivery system offers a highly promising strategy for the development of next-generation broad-spectrum mucosal vaccines capable of defending against diverse coronaviruses.

High-entropy ceramics (HECs), enabled by their high-entropy design concept, have demonstrated breakthrough potential in tribology. An invited review published in Journal of Advanced Ceramics systematically evaluates the tribological performance of six major HEC families—carbides, borides, silicides, oxides, nitrides, and MAX phases—revealing significantly enhanced wear resistance and adaptive self-lubrication compared with conventional ceramics. However, the field faces critical bottlenecks including a lack of standardized tribological data, insufficient mechanistic understanding of the high-entropy effect, and high synthesis costs. Future efforts in data-driven design, multi-scale modeling, and cost-effective manufacturing will accelerate the transition of HECs from laboratory research to industrial applications in extreme environments such as aerospace and advanced manufacturing.

Metal halide perovskites (e.g., CsPbBr₃) have emerged as highly promising scintillator materials owing to their superior optoelectronic characteristics. However, their practical deployment is constrained by intrinsic structural instability and nonradiative recombination-induced energy loss. Herein, they show that Ni²⁺ doping constitutes a potent regulatory strategy for synergistically improving the scintillation performance and environmental robustness of CsPbBr₃ perovskite. Various characterizations combined with threotecial calculation indicate that the incorporation of Ni²⁺ dopants triggers lattice contraction, thereby enhancing the resistance to environmental perturbations. Ni-doping also passivates intrinsic defects and traps, leading to marked suppression of nonradiative recombination pathways. This synergy in as-prepared Ni-doped CsPbBr₃ leads to an 11-fold enhancement in photoluminescence intensity and a substantial increase in photoluminescence quantum yield from 56.0% to 93.7%. Notably, it delivers an exceptional light yield of 38428.5 photons MeV⁻¹, a low detection limit of 64.9 nGyₐᵢᵣ s⁻¹, and superior radiation tolerance. Furthermore, a flexible scintillation screen containing Ni-doped CsPbBr₃ enables high-resolution X-ray imaging with a spatial resolution of 16.6 lp mm⁻¹, notably surpassing that of the majority of reported perovskite-based scintillators. This study provides profound insights into the pivotal role of metal doping into halide perovskites for enhancing environmental stability in radiation detection technologies.

We demonstrated a facile FJH strategy to achieve the controlled synthesis of atomically dispersed Cu species via ultrafast heating-cooling process. By systematically regulating the pulse parameters, we successfully anchored isolated Cu species with a well-defined local coordination environment. The optimized photocatalyst exhibits an approximately 10-fold enhancement in photocatalytic CO evolution under simulated solar irradiation, offering a promising new pathway for clean fuel production and carbon capture

A team from the College of Chemistry and Chemical Engineering of Shaanxi University of Science and Technology and Functional Inorganic Materials Energy Conversion Laboratory started from “yarn” as a continuously processable and weave-integrable material unit. They designed a dynamic electrostatic cladding-spinning strategy that integrates a high-strength mechanical skeleton, a photothermal conversion shell, and thermoelectric waste-heat recovery into a single yarn platform.

From drug synthesis planning and production scheduling to facility location problem, combinatorial optimization (CO) is a backbone of efficient operation in science, engineering, and society. Yet building effective solvers still often requires expert modeling and extensive manual tuning. A new review surveys rapid progress in using large language models (LLMs) across three major paradigms — LLM-assisted modeling and solver collaboration, LLM-assisted heuristics, and LLM-based end-to-end solvers — and analyze their workflows, strengths, and limitations. The paper also summarizes application areas such as planning and scheduling, wireless networks and engineering design, and outlines research directions for making LLM-assisted CO more reliable.

A research paper by scientists at Fudan University presented BioPINN-LM, a hybrid framework that combines physics-informed neural networks and multimodal large language models to rapidly predict aortic aneurysm wall stress and generate interpretable biomechanical risk assessments.

The research paper, published on Sept 2, 2026 in the journal Cyborg and Bionic Systems.

Current clinical anti-obesity regimens mainly utilize GLP-1 or PPAR-γ agonists, which are restricted by post-withdrawal weight rebound and inflamed adipose microenvironments respectively. This study fabricates adipocyte-targeted nanocomposite microneedles (LRSGSG@MN) co-delivering rosiglitazone and semaglutide for immuno-metabolic therapy. Lipid carriers deliver rosiglitazone to activate PPAR-γ and mitochondrial biogenesis, while sustained semaglutide polarizes macrophages toward anti-inflammatory M2 to alleviate adipose inflammation, disinhibiting thermogenesis and reinforcing white fat browning. In high-fat-diet obese mice, the patch alleviates adiposity and glucolipid disorders and maintains weight steadily after treatment withdrawal. This work reveals peripheral immunomodulatory effects of semaglutide and establishes a long-acting adipose-targeted microneedle platform for durable obesity intervention.