Back to the river: behavioural patterns of Eurasian beavers recolonising central Italy.

Adsorption potential of microplastics for extracellular nucleic acids in natural and synthetic waters.

Transition metal sulfides offer multiple favorable properties as electrode materials in supercapacitors owing to their diverse redox chemistry, high theoretical capacitance, and different topologies. They exhibit better electrochemical properties when paired with carbon materials. The effective fabrication of a FeS/g-C3N4 nanocomposite, in which the FeS nanoparticles are evenly adhered to a conductive g-C3N4 framework, was accomplished in this study. The hybrid system improves charge transfer and structural stability by combining the pseudocapacitive properties of FeS with the large area, layered structure, and conductivity of g-C3N4. The g-C3N4 matrix has a high capacity to inhibit the agglomeration of FeS nanoparticles, boost the exposure of electroactive groups, and facilitate rapid ion/electron movements. Consequently, the FeS/g-C3N4 electrode outperforms the immaculate FeS with a high specific capacitance (Csp) of 802.5 F g−1 at 1 A g−1 and 475 F g−1 at 5 A g−1. Further long-term cycling studies reveal the outstanding stability of the electrode with 72.34% capacitance retention despite 5000 cycles. Besides, the composite exhibits exceptional energy and power densities, with an efficient energy density (ED) of 17.83 Wh kg−1 at a power density (PD) of 200 W kg−1 and 10.56 Wh kg−1 at 1.0 kW kg−1. This excellent electrochemical performance is owing to the synergistic effect of FeS and g-C3N4, which increases redox activity, enhances charge transfer and minimizes internal resistance. Our findings show that FeS/g-C3N4 might serve as a feasible option for long-term, high-performance supercapacitor electrodes in next-generation energy storage applications.

Spiro-OMeTAD is a widely used hole transport material in perovskite solar cells, contributing significantly to their high-power conversion efficiencies. In this study, Electron Paramagnetic Resonance (EPR) spectroscopy was employed to investigate F4TCNQ as a molecular dopant for Spiro-OMeTAD. The doping efficiency of F4TCNQ was examined by EPR spectroscopy by varying its concentration from 0.5 to 6 mol% in two different solvents: chloroform and chlorobenzene. Spiro-OMeTAD films prepared at these dopant concentrations in chloroform were additionally characterized with UV/VIS spectroscopic and ellipsometry measurements. EPR analysis of both solutions and films revealed that F4TCNQ doping is more effective in chloroform than in chlorobenzene, indicating a strong solvent influence on the doping efficiency of spiro-OMeTAD by F4TCNQ. Furthermore, an ambient air stability study was performed on F4TCNQ-doped spiro-OMeTAD films and compared with films containing conventional additives such as tBP, LiTFSI, and FK209. The results demonstrate that F4TCNQ serves as an efficient single dopant alternative to traditional additive mixtures. Results are discussed in the context of EPR spectroscopy as a powerful tool for identifying effective dopants for hole transport material thin films and elucidating the role of solvent-dopant interactions in determining doping efficiency.

How do plants, lacking a central nervous system, translate environmental stimuli into physiological actions within milliseconds? Vesicular trafficking acts as a cellular core signal and material transport hub that facilitates this rapid adaptation, yet its dynamic nature has long remained a "black box". Traditional imaging approaches have struggled not only with optical resolution (the "unseen"), but critically with a lack of quantitative precision (the "immeasurable") and the inability to track molecular history (the "unknown age"). This review synthesizes a new paradigm that unlocks this black box by integrating advanced chemical biology with deep learning computational analysis. We detail how multimodal strategies combining pH-sensitive probes (e.g., pHluorin), covalent tags (HaloTag), and fluorescent timers visualize molecular events with unprecedented fidelity. Furthermore, we explore how integrating next generation FRAP/FCS variants (DeepFRAP, FCSNet) with deep learning allows for the rigorous mathematical modeling of vesicle kinetics. By resolving long-standing controversies such as endocytic stoichiometry and secretory sorting logic, this quantitative framework maps nanoscale membrane dynamics to organismal phenotypes, ultimately refining our understanding of plant stress resilience and signal transduction.

Layered NbSe2 has attracted extensive interest as a prototypical system where multiband superconductivity coexists with a charge-density wave (CDW) order. Here, using self-consistent phonon theory to incorporate anharmonic renormalization, CDW critical temperatures in the bulk and monolayer 2H-NbSe2 are calculated to be 66 and 116 K, respectively, in good agreement with reported experiments. First-principles anharmonic lattice dynamics combined with Peierls–Boltzmann transport theory reveals that strong phonon anharmonicity, arising from low-energy special soft phonon modes mediated by the CDW behavior, results in a low lattice thermal conductivity (κL) with weak temperature dependence. Strikingly, four-phonon (4ph) interactions contribute to a dramatic suppression of κL, particularly in the in-plane direction, reinforcing the critical role of strong phonon anharmonicity. These results provide a detailed microscopic understanding of CDW transition and thermal transport in CDW materials.

To continuously improve the efficiency of the construction project delivery process, various innovative methods and technologies have been developed and adopted in the past decades. Among these methods, modular construction has become a popular option due to its short on-site installation time generated by off-site prefabrication. However, the process of modular construction requires a highly integrated system to accurately connect multiple phases, including material packaging, transportation logistics, locating and tracking, and on-site installation. Accordingly, this process typically poses a significant challenge for contractors to efficiently manage the materials needed for daily tasks. This paper introduces a construction material management system that integrates every phase from off-site packaging to on-site installation. The integrated system was developed based on Logistic Chain and Building Information Modeling (BIM) using a three-layer framework, namely material packaging, inventory management, and material locating and tracking. The new system utilizes recent innovative technologies for transparent consolidation and highly efficient operation of off-site inventory management and on-site visualization. The developed system was further examined in a real-world case study project. The material handling time was then analyzed and compared with benchmark data without using the integrated system. The results indicated that the newly developed system was able to effectively reduce the time of locating materials and the rate of missing materials during on-site installation. In addition, this case study project added value to the verification of the broader system’s capabilities for inventorying, tracking, and visualizing construction materials. The findings of this project provide valuable knowledge and insight into improving construction efficiency through an integrated material management system. Future research is needed to expand the applicability of multiple framework designs and assess the cost–benefit analysis for production-scale and commercial use.

Self-assembled monolayers (SAMs) have emerged as a new generation of hole transport materials (HTMs) for perovskite solar cells (PSCs), particularly in inverted architectures. Compared to conventional HTMs, SAMs demonstrate superior power conversion efficiency (PCE) and enhanced operational stability. However, the current discovery of SAMs still relies heavily on empirical trial-and-error approaches, suffering from long development cycles, high costs, and low success rates. Here we present a novel machine learning (ML) platform for accelerated SAM discovery and design. We constructed a comprehensive feature space combining RDKit molecular descriptors and Morgan fingerprints, and then systematically evaluated various ML algorithms. Multiple evaluation metrics were used to assess model reliability. The results demonstrate that the RDKit-based XGBoost model achieved optimal performance with a root-mean-square error (RMSE) of 1.862, a coefficient of determination (R2) of 0.5058, a Pearson correlation coefficient (r) of 0.8161 and a mean absolute error (MAE) of 1.528. Then, SHapley Additive exPlanations (SHAP) analysis further elucidated the structure-property relationships between key molecular features and photovoltaic performance. The SHAP values revealed that the top five most important features were all RDKit descriptors, specifically EState_VSA5, fr_benzene, EState_VSA2, SlogP_VSA1, and Chi0v. The external validation using recently reported SAM molecules demonstrated remarkable prediction accuracy. The relative errors between predicted and experimental PCE values were mostly within 10%, with the minimum being only 0.55%. Meanwhile, three new SAM molecules were designed based on the model, with the highest predicted PCE approaching 27%. Therefore, this work provides an efficient digital solution for SAM development, offering valuable guidance for accelerating the discovery of next-generation photovoltaic materials.

Water-quality responses and management-oriented spatial thresholds in a complex river-estuary continuum.

Lead-free perovskite solar cells have become attractive as they are more environmentally friendly than their lead-based counterparts. Among these lead-free perovskite materials is MASnI2Br, which has attracted considerable attention due to its environmentally friendly advantages and beneficial optoelectronic properties. However, further enhancement is required in order to improve the power conversion efficiencies. In this study, an MASnI2Br-based perovsdkite solar cell is designed and optimized using SCAPS-1D simulations. An extensive iterative simulation approach is carried out to optimize critical parameters such as electron affinity, energy bandgap, layer thickness and doping concentration for both transport layers. In addition, the thickness of the MASnI2Br absorbing layer is optimized. With the improved device setup, the maximum achievable power conversion efficiency is 24%. Furthermore, by matching the optimized electronic structure with realistic transport materials, CBTS and TiO2 are identified as suitable hole and electron transport layers, respectively. The proposed TiO2/MASnI2Br/CBTS perovskite solar cell has a power conversion efficiency of about 23.6%.

Commercial deployment of perovskite solar cells is still hampered by the high price of the conventional hole transport material spiro-OMeTAD and the Au rear electrode used in state-of-the-art n-i-p devices. Here, we demonstrate that judicious management of hole transport simultaneously reduces material costs and pushes device efficiency to a record value of 25.03% (certified 24.44%) for Cu-electrode-based n-i-p perovskite solar cells. Diluting the pristine spiro-OMeTAD precursor 4-fold with a volatile cosolvent preserves film morphology and electronic properties while reducing the consumption of a costly organic semiconductor. We further introduce a solution-processed proton-coupled electron-transfer strategy to in situ create a p-p+ homojunction hole transport layer, which helps build up an Ohmic contact with a low-cost Cu rear electrode and accelerates hole extraction. Replacing Au with Cu lowers the electrode cost by more than 4 orders of magnitude without compromising stability: unencapsulated cells retain 93% of their initial efficiency after 700 h of operation under continuous illumination. Our results demonstrate a practical pathway to economically viable, high-performance perovskite solar cells and advance the prospects for commercial manufacturing.

Nonlinear transport in narrow band-gap materials has recently attracted significant attention, being commonly recognized as a useful tool to study a variety of complex physical effects related to Berry phase. Here we demonstrate that a mundane, commonly overlooked mechanism stemming from tunneling between charge puddles, can drive substantial nonlinearities in these narrow band gap materials. As a test bed, we use an epitaxial topological HgTe layer, underscoring that even good crystalline quality materials suffer from this issue. Indeed, we show that signatures of electrical transport through a network of charge puddles are not limited to the planar magnetoresistance, but also dominate transport. Our findings highlight the need for utmost caution when interpreting nonlinear electrical transport phenomena, as harmonic distortion of the electrical signal, caused by charge puddles, is unavoidable in any realistic narrow-gap system, complicating the identification of other proposed effects related to the Berry phase.

Machine-learning potentials (MLPs) face significant challenges in sampling anharmonic lattice dynamics due to computational bottlenecks. This work presents an active learning (AL) framework that integrates pretrained potentials with committee models to overcome these limitations. This approach achieves a 59.9% reduction in force errors while maintaining exceptional transferability across diverse carbon allotropes. The optimized potential model reveals distinct anharmonic regimes: in diamond, the longitudinal acoustic phonons exhibit a temperature-induced sign reversal in their lifetime scaling exponent (from n = -1.54 at 200 K to n = 0.17 at 800 K), marking a fundamental transition from Umklapp scattering to fluctuation-induced localization where thermal disorder preferentially suppresses low-frequency phonon propagation; in bilayer graphene, the strongly negative Grüneisen parameters of flexural acoustic (ZA) phonons [γ(q) = -33.7 to -8.4] reveal anomalous vibrational stiffening under volume expansion, originating from stress release in the interlayer coupling that enhances in-plane restoring forces. These findings establish a general strategy for MLPs development and uncover emergent phonon phenomena, providing new pathways for controlling thermal transport in quantum materials and nanoscale devices.

We measure the temperature profile and investigate the thermal conductivity of suspended monoisotopic hexagonal boron nitride (h10BN) heterostructures by combining suspended microbridge technique and Raman spectroscopy. The thermal conductivities exceed 1650 W.m-1.K-1 at room temperature, significantly higher than in previous reports, highlighting the crucial influence of the measurement conditions on the experimental results. By including more data points, we refine our models beyond the accuracy of conventional approaches. Our results show a striking deviation of thermal transport from the classical diffusion regime described by Fourier's law: while the temperature profiles are linear above 300 K, they become clearly nonlinear below this temperature, indicating a strong non-diffusive heat transport regime. This behavior underscores the need for a new theoretical framework to fully account for heat transport in two-dimensional materials. Ultimately, our findings pave the way for innovative heat dissipation technologies and challenge conventional paradigms in nano-heat engineering. This study establishes a practical framework linking Raman-based temperature mapping, the number of measurement points, and thermal simulations to reliably determine the in-plane thermal conductivity of 2D materials.

Two-dimensional (2D) materials have garnered notable research interest due to their extraordinary properties. Assembling two or more 2D materials into heterostructures introduces properties that are not present in any individual components, leading to a spectrum of nanodevices and applications. The lifetime and performance of nanodevices can be largely dictated by the working temperatures, and the heat dissipation in 2D materials and heterostructures is vital to the reliability and functionality of devices. However, mechanical effects encountered can potentially impact thermal transport. A comprehensive understanding of the interplay between mechanical loadings and thermal transport in 2D materials and their heterostructures is fundamental to devising effective cooling strategies for devices operating under complex conditions. The tunable thermal properties of these materials offer a platform for designing mechanically adjustable devices and reversible performance optimization. This review starts with a summary of the thermal conductivities (TCs) in various 2D materials adjusted by mechanical loadings. A brief overview of the underlying tuning mechanism is provided, followed by a discussion on the effect of structural designs. Several potential applications based on the thermo-mechanical correlation are mentioned. Finally, the current limitations and challenges in the field are included, and several suggestions for future research directions are discussed.

To develop high-performance pseudocapacitor devices with superior energy and power output along with excellent cycling durability, we employed kinetically controlled slow precipitation methods to synthesize MnS-Co3S4 and FeS-FeS2/N-doped defect-rich reduced graphene oxide (ND-rGO) as the positrode and negatrode materials, respectively. The MnS-Co3S4 exhibits nanocrystallinity, a uniform microstructure, phase uniformity, surface wettability, a large surface area, and a monomodal pore distribution in the mesopore and macropore region. The FeS-FeS2/ND-rGO exhibits nanocrystallinity, forms a heterocomposite, exhibits uniform microstructure, phase uniformity, and substantial defect density in ND-rGO. Electrochemical analysis of MnS-Co3S4 reveals fast redox kinetics, high charge storage efficiency, low series resistance (∼0.82 Ω), charge-transfer resistance (∼0.53 Ω), relaxation time (1.59 s), and predominantly diffusion-controlled charge storage. Likewise, FeS-FeS2/ND-rGO demonstrates excellent kinetic reversibility and a wide operational window in the negative potential region. The 1.7 V MnS-Co3S4||FeS-FeS2/ND-rGO ASSAPC device exhibits a hybrid charge storage mechanism combining surface and diffusion-controlled processes, high-rate areal- and mass-specific capacity/capacitance, a high specific energy (23 W h kg-1), high power density (3703 W kg-1) with robust cyclic charge storage stability (∼97.8% after 13 000 GCD cycles), and ∼100% energy efficiency under a very high-rate condition. This has been attributed to the synergistic interplay of the microstructural porosity, improved redox activity, enhanced conductivity, S2- ions in the positrode and negatrode, and smooth ion/electron transport in the electrode materials. This study provides key insights into structure-property relationships in sulfide-based hybrid electrodes, underscoring their potential in cost-effective, stable, and high-performance ASSAPC devices for next-generation portable energy storage applications.

Non-equilibrium molecular dynamics study of interfacial phonon transport in energetic materials: Coherent transport of acoustic phonon and N N stretching at bicrystal RDX interface

How microwave puffing regulates the hygroscopic response of non-carbonized bamboo residues toward sustainable utilization.

Evidence of Recent Material Transport within a Binary Asteroid System

A novel AIE fluorescent probe for monitoring of hypochlorous acid and viscosity in biosystem.