Small Methods最新文献

Early stages of nanoparticle (NP) formation in gas-phase synthesis processes, such as chemical vapor synthesis (CVS), involve (trans-)formations of molecular species (precursors), small clusters (nuclei), or amorphous intermediates before forming the final NP product. These transformations may be probed using in situ and operando X-ray absorption spectroscopy (XAS), enabling the observation of local structure evolution under CVS conditions. However, this is challenging due to the very dilute sample system, that is, NPs in the gas phase, coupled with high temperatures required for particle formation, deteriorating the signal-to-noise ratio. Here, we present an experimental setup specially tailored to overcome these challenges, enabling in situ and operando XAS measurements of sufficient quality to perform quantitative data analysis. The major focus is a comprehensive understanding of the formation of iron oxide NPs in CVS. Quantitative XANES analysis reveals controlled changes of oxidation states of iron under varying oxygen partial pressures, while EXAFS analysis using reverse Monte Carlo (RMC) simulations provides detailed insight into local structure around the iron atom probed as a function of process temperatures. The mean square displacements available from RMC analysis may be used to estimate the temperature of NPs in the gas phase or to determine their Debye temperatures.

Molecular catalysts with well-defined active sites and structural tunability are proposed as promising electrocatalysts for alkaline oxygen evolution reaction (OER). However, poor alkaline resistance, low atomic utilization, limited mass transfer resulted in rapid activity degradation and unstable catalytic performance of molecular catalysts in alkaline environments. Herein, a three-in-one spacer strategy was designed to develop highly alkali-resistant phthalocyanine-based covalent organic frameworks (COFs) by integrating a spacer with hydrophilic groups and stable piperazine linkages in skeletons, which endows COF with high alkaline resistance, high atomic utilization and effective mass transfer. As a result, the COF shows a surprising activity with an ultra-low overpotential of 77 mV and a long-term durability of exceeding 290 h at 500 mA cm^-2 in 6 M KOH and seawater at 80°C in an anion exchange membrane electrolyzer. To the best of our knowledge, the unprecedented stability and activity exceeds all organic catalysts. Theoretical and experimental studies reveal that the hydrophilic units not only increase the mass transfer, but also can facilitate the *OH deprotonation on the Co sites, which further improve the catalytic activity.

Aqueous manganese batteries are emerging as safe, low-cost options for large-scale energy storage but are limited by sluggish Mn²⁺ diffusion and poor reversibility. Here, we report an interlayer-engineered 1T-phase MoSe₂ cathode enabling fast, reversible hybrid storage of Mn²⁺ and H⁺ ions. Controlled chemical exfoliation induces a metallic phase transition and expands the interlayer spacing, creating a favorable environment for multivalent ion transport. The exfoliated MoSe₂ delivers 153.4 mAh g^-1 at 0.1 A g^-1 and retains 92.5% capacity after 1800 cycles. Kinetic analysis shows a reduced ion migration barrier compared with bulk MoSe₂, highlighting the role of phase engineering and interlayer expansion. Spectroscopic and electrochemical analyses reveal a reversible Mn²⁺/H⁺ co-intercalation mechanism. A full cell paired with a Mn metal anode delivers 165.3 mAh g^-1 and retains 89.9% of its capacity after 2000 cycles, demonstrating the practical feasibility of a rechargeable aqueous Mn-metal battery. This work establishes phase-engineered layered dichalcogenides as a platform for aqueous multivalent batteries and provides design principles to overcome kinetic limitations.

Prussian Blue (PB) is an attractive electrochromic cathode material for aqueous electrochromic energy-storage smart windows, but its performance remains limited by the low areal capacity of thin-coatings deposited on planar transparent conductive oxides. Here, we overcome this limitation by combining galvanostatic electrodeposition with 3D-nanostructured ITO electrodes, enabling conformal growth of PB with high-loadings, while maintaining mechanical stability and fast electrochemical response. The resulting electrodes sustain charge densities up to 100 mC/cm² at relatively high rates. When integrated into Zn/PB smart window devices, they enable fast and homogeneous coloration/bleaching with enhanced optical contrast and charge storage capacity, while also exhibiting high cyclability. Device configurations based on reversible Zn electrodeposition onto a transparent ITO counter electrode enable improved control over optical contrast and electric field distribution, while a three-electrode architecture incorporating a sacrificial Zn anode provides a route toward in situ regeneration of the electrochromic cathode and extended device lifetime.

Lithium rich manganese layered oxides (LRMs) are promising cathode materials for high energy lithium-ion batteries owing to their high capacity and low cost, yet their practical applications are limited by lattice degradation and unstable cathode electrolyte interphase (CEI) evolution during cycling. Herein, a fluorine enriched multifunctional Li_1.2Mn_0.54Ni_0.13Co_0.13O₂(LRM) is constructed through Na⁺, F^-, and Al³⁺ synergistic regulation to achieve bulk surface stabilization. The introduction of Na⁺ broadens Li interlayer spacing and accelerates Li⁺ transport, while Al-O bonding stabilizes the local electronic structure, suppresses cation disorder and Jahn-Teller distortion, and alleviates lattice strain. Furthermore, the preformed fluorine enriched surface region reinforces the outer lattice through the formation of robust F-TM bonds, promoting the generation of a uniform and stable CEI layer, mitigating electrolyte decomposition and interfacial reactions. The optimized NFA-LRM delivers a high discharge capacity of 318.7 mAh g^-1 at 0.1 C, with reversible capacities of 140.6 and 108.5 mAh g^-1 at 5 C and 10 C, respectively, and retains 96.29% capacity after 250 cycles at 2 C. This work provides a bulk and surface synergistic strategy for high energy LRMs with stabilized oxygen chemistry and durable interfacial stability.

Antimicrobial peptides (AMPs) are critical candidates for addressing the global antibiotic resistance crisis. AI-driven quantitative models capable of directly predicting peptide antimicrobial activity, specifically minimum inhibitory concentration (MIC), are gaining scientific prominence by providing precise guidance for the rational design of AMPs. To assess their real-world, out-of-the-box performance, we conducted a retrospective benchmark of 10 publicly released quantitative AMP prediction tools spanning classical machine learning and contemporary deep learning approaches. Using an external dataset and reconstructed native datasets, we evaluated absolute MIC regression, retrospective reproducibility, directional prediction patterns, ranking capability, and virtual-screening enrichment. Most released tools exhibited poor absolute MIC regression and limited transferability to the external benchmark, while selected tools retained useful relative-ranking and enrichment capabilities. Retrospective evaluation further revealed marked differences in implementation-level reproducibility among the released tools. Error-stratified analyses identified systematic associations between prediction errors and peptide residue composition, together with a general compression of the predicted activity range. Collectively, these findings characterize the practical performance boundaries of currently accessible quantitative AMP prediction tools and support their use primarily as early-stage screening filters rather than precise substitutes for experimental MIC measurements.

Rehabilitation medicine is an essential component of universal health coverage, while emerging electronic skin offers new opportunities for portable and personalized healthcare. However, flexible pressure sensors still face trade-offs among sensitivity, detection range, and stability, and gas sensors remain challenged by low-concentration detection and environmental robustness. Herein, a biomimetic "Thalia dealbata" microstructured hydrophobic polypyrrole/polydimethylsiloxane (S@PPy/PDMS) composite sensor was fabricated through a one-step template method and controllable in situ polymerization. The biomimetic PDMS microstructure enhances pressure response, while conductive and NH₃-sensitive PPy enables dual-mode pressure and gas sensing on a single flexible platform. The sensor exhibits a wide pressure range of 0-25 kPa, a high sensitivity of 3.617 kPa^{- 1}, and excellent durability over 19 500 compression-release cycles. It also detects NH₃ concentrations as low as 1 ppm with stable performance over 60 days. The dual-functional sensor enables complementary monitoring of mechanical physiological signals, including respiration, pulse, and body motion, together with metabolic information from exhaled NH₃. A five-channel sensor array further decodes numerical gestures with 100% accuracy via machine learning and wireless communication. Integrating respiratory mechanical sensing with exhaled NH₃ detection, this platform offers potential for longitudinal, noninvasive multiparametric monitoring, particularly for CKD assessment, human-machine interfaces, smart wearables, assistive technologies, and telemedicine.

Aqueous ammonium-ion batteries (AAIBs) are promising energy storage systems, while the relatively large size and tetrahedral geometry of NH₄ ⁺ present challenges for its transport within electrodes. Herein, poly(5,8-diaza-1,4-naphthoquinone) (PANQ) has been synthesized to facilitate NH₄ ⁺ transport in AAIBs. The π-conjugated PANQ possesses a rigid, linear molecular structure. The straight intermolecular slits with uniformly distributed carbonyl sites form railway-like NH₄ ⁺ pathways, enabling rapid ion transport through the dynamic formation and disruption of hydrogen bonds. The PANQ electrode delivers a high capacity of 286.8 mAh g^-1 at 1 A g^-1 in a 2 mol L^-1 ammonium acetate electrolyte. Thanks to the rapid NH₄ ⁺ transport pathways, the electrode displays an excellent rate capability, retaining 161.7 mAh g^-1 at 80 A g^-1. Moreover, it displays exceptional cycling stability over 10 000 cycles at 20 A g^-1. The PANQ electrode was employed as the anode in a PANQ//NiCo-LDH AAIB (NiCo-LDH represents the Ni-Co layered double hydroxide cathode), retaining an energy density of 25.2 Wh kg^-1 even at an ultrahigh power density of 23 320.2 W kg^-1. This study provides a high-performance electrode candidate for AAIBs and a strategy for constructing rapid ion-transport pathways to enable efficient NH₄ ⁺ storage and superior electrochemical kinetics.

Resolving cancer-associated protein variants remains difficult when variants share similar molecular masses and folded structures. Conventional assays often require labels or provide ensemble-averaged readouts, limiting their ability to resolve subtle variant differences. Here, a YaxAB nanopore workflow is presented for label-free single-molecule current fingerprinting of wild-type Bcl-xL and the cancer-associated single-residue variants N136K and R165W. Individual Bcl-xL proteins were electro-osmotically trapped within the funnel-shaped YaxAB lumen, where they generated characteristic ionic-current events. These events formed reproducible, analyte-specific event populations in normalized current blockade and current noise space, resolving wild-type Bcl-xL, N136K, and R165W as distinct single-molecule current fingerprints. Wild-type Bcl-xL and N136K remained distinct despite a mass difference of only 14 Da, and the fingerprint separation was consistent with combined differences in excluded volume, net charge, and dipole moment. Concentration-dependent capture-rate analysis further supported sub-nanomolar to low-nanomolar detection corresponding to protein amounts in the sub-picomole to low-picomole range, while capture-rate normalization brought the estimated concentrations closer to the nominal concentrations. These results present YaxAB nanopore sensing as a label-free single-molecule workflow for the current fingerprinting of cancer-associated single-residue Bcl-xL variants, with low-concentration detection as a supporting analytical capability.

Raman spectroscopy is a promising tool for microbial identification, yet its implementation in microbiology and clinical workflow is still restricted due to the accompanying additional preparation required to focus on microbial signals. Here, we demonstrate Raman-based bacterial identification directly from unopened, inverted agar plates, the same conditions used during incubation. Our approach enabled sensitive identification using two Escherichia coli variants, differing only in green fluorescent protein (GFP) expression, across diverse media and substrate material conditions, despite the interrogation path traversing 3-4 mm thick background material. We integrated traditional density functional theory (DFT)-based material computation with machine learning analysis, achieving over 97.7% classification accuracy, surpassing the performance of standard measurements from opened plates by 10.8% higher mean accuracy and 0.76% less variance. We further demonstrated Raman mapping-based colony identification via Raman peaks characteristic to GFPmut3 chromophore structure generated by DFT. Our approach is robust to changes in algorithms or substrate materials and promises real-time, non-perturbative monitoring of bacterial growth, biofilm formation, and antimicrobial resistance development.