The Royal Society of Chemistry最新文献

Tailoring the coordinative structure of a single-atom catalyst is a universal yet challenging route toward enhanced electrocatalysis. Herein, a coordinative compound impregnation strategy is reported for the synthesis of a Co-N₃S/C catalyst with asymmetric coordination for the oxygen reduction reaction, which demonstrates excellent performance in a Zn-air battery.

Surfactants with novel molecular architectures are increasingly being explored to achieve enhanced surface activity, stability, and biocompatibility. Among them, peptide-based surfactants have emerged as versatile alternatives to conventional systems due to their structural tunability and eco-friendly nature. In this study, we report the rational design and synthesis of an unconventional peptide-based dicephalic surfactant featuring a unique molecular topology, one long hydrophilic tail and two short hydrophobic heads. This configuration contrasts with traditional dicephalic surfactants, which typically possess a single hydrophobic tail and two hydrophilic heads. The hydrophilic segment comprises a collagen-derived peptide with repeating GXZ tripeptide units (G: glycine; X: proline or glutamic acid; Z: hydroxyproline or arginine), while the N-terminus is modified with di-fluorenylmethoxycarbonyl (DiFm)-functionalized L-lysine, introducing two aromatic hydrophobic heads. The resulting molecule, DiFm-GXZ, undergoes a conformational transition from a polyproline II-type single strand to a triple-helical structure. Remarkably, DiFm-GXZ exhibits excellent surface-active properties, with an exceptionally low critical aggregation concentration (CAC) of 70 µM. Self-assembly studies revealed the formation of unimicellar aggregates (∼20 nm) that further organize into higher-order multimicellar aggregates. Biophysical characterization confirmed that the self-assembly process is primarily governed by π-π stacking among aromatic groups and hydrogen bonding within the peptide backbone. The design strategy demonstrated here introduces a new class of peptide-based dicephalic surfactants with inverse architecture and tunable molecular features, offering valuable insights into the structure-property relationships governing self-assembly and interfacial behavior in peptide surfactant systems.

Niobium oxide (NbO_x)-based threshold switching memristors (TSMs) demonstrate significant promise for hardware implementation of neuromorphic computing, but their threshold stability's susceptibility to external environmental variations remains unclear. This work elucidates the switching mechanism in an NbO_x-TSM incorporating a low-thermal-conductivity CdTe₂ interlayer, which operates via the Poole-Frenkel (PF) emission model. Our investigation reveals that a double interlayer structure yields the highest effective thermal resistance, thereby most effectively reducing the threshold voltage. By implementing this structure, we enhanced the switching stability by 30.9%. Furthermore, increasing the thickness of the double-sided interlayers from 3 nm to 9 nm improved the stability by an additional 24.7% while simultaneously lowering the threshold voltage. The impact of the interlayer thickness on oscillatory behavior was systematically analyzed within a leaky integrate-and-fire (LIF) neuron circuit, where the observed frequency saturation phenomenon provides critical guidance for thermal engineering design. Capitalizing on these findings, we developed a multimodal, integrated memristor-based system for electrocardiogram (ECG) arrhythmia detection that leverages device thickness and temperature characteristics to achieve a classification accuracy rate of 90.0%. This work underscores the significant value of such physically interpretable devices for the hardware realization of neuromorphic computing.

Flexible pressure sensing systems have shown great promise in applications such as personalized healthcare and human-machine interaction (HMI), due to their ability to conform to dynamic surfaces and sensitively transduce mechanical stimuli. Real-world environments often introduce challenges such as signal noise, baseline drift, and electromagnetic interference, which limit sensing accuracy. Integrating artificial intelligence (AI) algorithms provides practical solutions for enhancing signal processing, feature extraction, and system adaptability. This review summarizes recent advances in high-performance pressure sensor design and AI algorithm development, with an emphasis on their synergistic integration. Three representative human-centric application scenarios are discussed, along with key challenges, emerging trends, and future prospects for intelligent pressure sensing systems. Continued interdisciplinary innovation is expected to drive the evolution of intelligent pressure sensors, enabling broader applications and enhanced user experiences.

The RAS family proteins, including NRAS, are key regulators of intracellular signaling, acting as molecular switches that control essential cellular processes including proliferation and survival. Oncogenic NRAS mutations exert distinct effects on protein function. We employed Gaussian accelerated molecular dynamics simulations and Markov state models, complemented by principal component analysis and correlation network analysis, to delineate the comprehensive conformational landscapes of GTP-bound wild-type NRAS and its oncogenic G12D, Q61R, and C118S mutants. Our findings reveal that these mutations significantly alter the structural dynamics of the switch I and switch II domains. The Q61R mutation tends to stabilize the overall NRAS conformation. Furthermore, mutations induce specific changes in the protein's internal communication networks. These insights into the dynamic properties of oncogenic NRAS mutants provide a robust mechanistic foundation for understanding aberrant signaling and guiding the rational design of novel anti-cancer therapeutics.

We describe a palladium-catalyzed reductive Heck cyclization of alkene-tethered carbamoyl chlorides for the synthesis of CH₃- and CH₂D-functionalized oxindoles. Notable features of this transformation include its robust scalability and good functional group tolerance. The utility of this approach is further underscored by its successful adaptation to one-pot procedures, offering diverse synthetic pathways to medicinally relevant architectures.

Bisphosphonates are pharmaceutical compounds commonly used in the treatment of osteoporosis, Paget's disease, and multiple myeloma. Their lipophilicity was evaluated using a sensor array composed of poly(vinyl chloride) (PVC)-based ion-selective membranes (ISMs), modified with a polyaniline (PANI) layer that affects surface properties and acts as an anion-exchanger. The lipophilicity of bisphosphonates including ibandronate, clodronate, risedronate, and alendronate was analyzed in both standard and commercial samples. The influence of membrane composition (presence or absence of an anion-exchanger) and PANI deposition conditions (monomer form and/or salt content) on membrane surface properties (lipophilicity and signal stability) was investigated and confirmed using surface-wetting characterization, SEM-EDS mapping and potentiometry. Principal component analysis (PCA) enabled discrimination among the bisphosphonates based on their lipophilicity and revealed distinct contributions of individual ISMs in both standard and commercial samples.

In this paper, a electrode based on 3D-printed carbon black (3D-CB), and coated with a hydroxyethylcellulose/chitosan (HEC/CH) bilayer and finished by copper electrodeposition, is presented for the electrochemical sensing of ammonia nitrogen (AN) in water. Measurements were performed using square-wave voltammetry (SWV) in borate buffer (pH 9) under optimized conditions. The electrochemical method displayed good linear relationship between 0.7 and 20.4 mg L^-1 of AN with limits of detection (LOD) and quantitation (LOQ) of 0.014 and 0.043 mg L^-1 respectively, good precision (RSD ≤≃4.18% intra/inter-day, n = 10), and practical throughput (∼70 analyses per h). Accuracy in real waters was evaluated through standard-addition and spike-recovery experiments, yielding ∼99.8% recoveries. Statistical analysis was used to compare the obtained results to the expected values and no significant difference was observed between added and found concentrations. Therefore, the proposed 3D-CB/HEC-CH@Cu SWV method presents a viable alternative for the efficient, low-cost and safe determination of ammoniacal nitrogen in the water quality control process.

The extensive utilization of synthetic detergents presents a substantial threat to the global environment. Inspired by traditional practices in Asia-such as using rice-washing water for cleaning-this study develops a green, non-toxic, and surfactant-free detergent. The innovative detergent was fabricated using natural collagen extracted from delimed bovine hide trimmings as the core component, requiring no chemical modification. It forms in situ Pickering emulsions on contaminated surfaces, effectively encapsulating and removing oil stains. Interfacial desorption energy measurements indicate that the collagen detergent adsorbs irreversibly at the oil-water interface (approximately 2.2 × 10⁷K_BT). The collagen detergent achieves a comparable cleaning efficiency of up to 90% on both human skin and various material surfaces, in comparison with commercial products. More importantly, it is non-irritating to the eyes and skin and exhibits no toxicity toward cells, seeds, lettuce seedlings, and zebrafish. By combining high detergency with exceptional biocompatibility and environmental safety, this approach offers a compelling alternative to conventional surfactants. Remarkably, the detergent is produced solely from delimed bovine split trimmings, demonstrating the potential of collagen valorization for next-generation sustainable cleaning agents that align with ecological preservation and public health priorities.

In the present research, a novel cloud point extraction (CPE) method was developed for the separation and preconcentration of toxic Cu(II), Ni(II), Pb(II), and Cd(II) ions in environmental water and vegetable samples, prior to their determination by flame atomic absorption spectrometry (FAAS). The ligand 2-(2-(4-fluorobenzyl)-1H-benzo[d]imidazole-1-yl)acetohydrazide (FB-BIAH) was employed for the first time as an analytical complexing agent for the aforementioned metal ions, and Triton X-114 (TX-114) was preferred as the nonionic surfactant. Within the scope of optimizing CPE conditions, experimental parameters, such as pH, FB-BIAH and surfactant amounts, and incubation temperature and time, as well as centrifugation speed and duration, were systematically investigated. The optimal conditions for the simultaneous quantitative recovery of analyte ions were established as pH 7.0, an FB-BIAH amount of 2.5 mg, a TX-114 quantity of 25 mg, an incubation temperature of 60 °C, and an incubation time of 30 min. Under optimal conditions, the proposed method was successfully applied to river water and seawater, as well as different vegetable samples such as lettuce, parsley, and pepper. The results obtained demonstrated that the analyte ions could be reliably determined in complex matrices and that the method exhibited high analytical performance. Due to its simplicity, rapid applicability, environmentally friendly nature, and cost-effectiveness, the proposed CPE-FAAS method represents a promising approach for the routine analysis of toxic heavy metals in environmental water and food samples.