Matrix-free phosphorescent carbon nanodot inks enable scalable, invisible printing with ultrahigh resolution and high fidelity, highlighting their potential for large-scale information storage and time-delayed display applications.

This study presents a comprehensive exploration of fermented oats (FO) as a next-generation skincare ingredient with dual anti-inflammatory and skin barrier-restoring functions. By utilizing Saccharomyces cerevisiae fermentation, the authors successfully enhanced the bioactive composition of oats, significantly increasing β-glucan, proteins, flavonoids, amino acids, and their derivatives. These biochemical improvements translate into potent biological activity, positioning FO as a multifunctional soothing and repairing ingredient for sensitive and photodamaged skin. A major highlight of this research is its multi-model validation across cellular assays, zebrafish embryos, and 3D reconstructed skin. FO demonstrated a marked ability to modulate inflammatory pathways, including a 79.87% inhibition of TNF-α/TNFR1 binding, suppression of LPS-induced nitric oxide release, and reduction of neutrophil recruitment. These results collectively establish FO as a robust anti-inflammatory agent capable of suppressing both cytokine- and TRPV1-mediated inflammatory responses. Equally noteworthy is FO’s impact on skin barrier repair. In UVB-irradiated 3D skin models, FO significantly upregulated key structural proteins—including loricrin, filaggrin, transglutaminase 1, and caspase-14—which are essential for epidermal reinforcement, differentiation, and natural moisturizing factor formation. The ingredient also enhanced hydration by increasing both skin moisture content and AQP3 expression.

Overall, this study highlights fermented oats as an innovative, solvent-free, bioactivated skincare ingredient that simultaneously alleviates inflammation, repairs barrier damage, and improves hydration. Its strong mechanistic support and multi-level experimental confirmation underscore its potential as an effective soothing and repairing ingredient for sensitive skin formulations.

Electrocatalytic nitrate reduction reaction (NO₃RR) represents a sustainable and environmentally benign route for ammonia (NH₃) synthesis. However, NO₃RR is still limited by the competition from hydrogen evolution reaction (HER) and the high energy barrier in the hydrogenation step of nitrogen-containing intermediates. Here, we report a selective etching strategy to construct RuM nanoalloys (M = Fe, Co, Ni, Cu) uniformly dispersed on porous nitrogen-doped carbon substrates for efficient neutral NH₃ electrosynthesis. Density functional theory calculations confirm that the synergic effect between Ru and transition metal M modulates the electronic structure of the alloy, significantly lowering the energy barrier for the conversion of *NO₂ to *HNO₂. Experimentally, the optimized RuFe-NC catalyst achieves 100% Faraday efficiency with a high yield rate of 0.83 mg h⁻¹ mg_cat⁻¹ at a low potential of − 0.1 V vs. RHE, outperforming most reported catalysts. In situ spectroscopic analyses further demonstrate that the RuM-NC effectively promotes the hydrogenation of nitrogen intermediates while inhibiting the formation of hydrogen radicals, thereby reducing HER competition. The RuFe-NC assembled Zn-NO₃⁻ battery achieved a high open-circuit voltage and an outstanding power density and capacity, which drive selective NO₃⁻ conversion to NH₃. This work provides a powerful synergistic design strategy for efficient NH₃ electrosynthesis and a general framework for the development of advanced multi-component catalysts for sustainable nitrogen conversion.

Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human–machine interfaces for real-time health monitoring, clinical diagnosis, and robotic applications. Nevertheless, it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility, adhesion, self-healing, and environmental robustness with excellent sensing metrics. Herein, we report a multifunctional, anti–freezing, self-adhesive, and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes (CoN CNT) embedded in a polyvinyl alcohol–gelatin (PVA/GLE) matrix. Fabricated using a binary solvent system of water and ethylene glycol (EG), the CoN CNT/PVA/GLE organogel exhibits excellent flexibility, biocompatibility, and temperature tolerance with remarkable environmental stability. Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range (40%-95% RH). Freeze-tolerant conductivity under sub-zero conditions (−20 °C) is attributed to the synergistic role of CoN CNT and EG, preserving mobility and network integrity. The CoN CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 kPa⁻¹ in the detection range from 0 to 20 kPa, ideal for subtle biomechanical motion detection. A smart human–machine interface for English letter recognition using deep learning achieved 98% accuracy. The organogel sensor utility was extended to detect human gestures like finger bending, wrist motion, and throat vibration during speech.

As emerging two-dimensional (2D) materials, carbides and nitrides (MXenes) could be solid solutions or organized structures made up of multi-atomic layers. With remarkable and adjustable electrical, optical, mechanical, and electrochemical characteristics, MXenes have shown great potential in brain-inspired neuromorphic computing electronics, including neuromorphic gas sensors, pressure sensors and photodetectors. This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved. Key bottlenecks such as insufficient long-term stability under environmental exposure, high costs, scalability limitations in large-scale production, and mechanical mismatch in wearable integration hinder their practical deployment. Furthermore, unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neuromorphic signal conversion demand urgent attention. The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.

Lithium-ion batteries (LIBs), while dominant in energy storage due to high energy density and cycling stability, suffer from severe capacity decay, rate capability degradation, and lithium dendrite formation under low-temperature (LT) operation. Therefore, a more comprehensive and systematic understanding of LIB behavior at LT is urgently required. This review article comprehensively reviews recent advancements in electrolyte engineering strategies aimed at improving the low-temperature operational capabilities of LIBs. The study methodically examines critical performance-limiting mechanisms through fundamental analysis of four primary challenges: insufficient ionic conductivity under cryogenic conditions, kinetically hindered charge transfer processes, Li⁺ transport limitations across the solid-electrolyte interphase (SEI), and uncontrolled lithium dendrite growth. The work elaborates on innovative optimization approaches encompassing lithium salt molecular design with tailored dissociation characteristics, solvent matrix optimization through dielectric constant and viscosity regulation, interfacial engineering additives for constructing low-impedance SEI layers, and gel-polymer composite electrolyte systems. Notably, particular emphasis is placed on emerging machine learning-guided electrolyte formulation strategies that enable high-throughput virtual screening of constituent combinations and prediction of structure–property relationships. These artificial intelligence-assisted rational design frameworks demonstrate significant potential for accelerating the development of next-generation LT electrolytes by establishing quantitative composition-performance correlations through advanced data-driven methodologies.

Professor Tonggang Jiu's team at Shandong University achieved a significant improvement in the efficiency and stability of perovskite solar cells by regulating the NiO_x/perovskite interface chemistry by introducing a novel self-assembling molecule, (4-(2,7-dibromo-9,9-dimethylacridin-10(9H)-yl)butylphosphonic acid (2Br-4PADMAc), into the NiO_x/perovskite interface. This effectively suppressed Ni^>3+ generation and interfacial redox reactions, optimized energy level matching, and promoted high-quality film crystallization. Compared to the traditional molecule 2PACz, 2Br-4PADMAc exhibits stronger interfacial anchoring and a larger molecular dipole moment, which can improve hole transport efficiency and reduce PbI₂ accumulation. The inverse perovskite solar cell modified with this molecule achieved a photoelectric conversion efficiency of 25.28% and excellent stability. This research provides a new strategy for optimizing the efficiency and stability of NiO_x-based perovskite solar cells through interfacial molecule design. The article was published as an open access research article in CCS Chemistry, the flagship journal of the Chinese Chemical Society.

Researchers have unveiled a new generation of sustainable carbon materials poised to revolutionize environmental protection and energy technologies. The study highlights advanced forms of carbon, including graphene, carbon nanotubes (CNTs), carbon dots (CDs), biochar, and aerogels, showing that these materials play essential roles in removing harmful pollutants, cleaning water, storing energy, and catalyzing chemical reactions with minimal environmental impact.