Amine intercalation is an efficient way to fine-tune and enhance the properties of layered alpha-zirconium phosphate (alpha-ZrP), however, its impact on the proton conduction properties of alpha-ZrP has been rarely explored. In this contribution, a long-chain alkylamine, dodecylamine (DDA), was successfully intercalated into alpha-ZrP nanoplates. The intercalation was seen to exert both positive and negative impacts on the proton-transport capabilities of alpha-ZrP. When the intercalant concentration was low, the hydrophobic long-chain alkyl groups of anchored DDA molecules hindered the diffusion of water, causing suppressed proton conduction. With a high DDA concentration, enhanced proton conduction was observed in the intercalated alpha-ZrP, due to the existence of expanded interlayer spacing and free DDA, which facilitated the diffusion and accommodation of water molecules, leading to an increase in carrier concentration and the formation of hydrogen-bonding networks. The optimized DDA-intercalated alpha-ZrP (alpha-ZrP-DDA (1 : 4)) showed a proton conductivity of 1.11 & times; 10-4 S cm-1 at 303 K and 98% relative humidity (RH), which was one order of magnitude higher than that of alpha-ZrP. Moreover, a humidity sensor based on alpha-ZrP-DDA (1 : 4) was fabricated, which could distinguish deep, normal and fast breathing, indicating its potential for practical monitoring of human breath. Our work demonstrates that amine intercalation is an efficient strategy for modulating proton-transport behavior in alpha-ZrP, thereby broadening its potential applications.
Polycrystalline SnSe is more favorable for practical applications compared with its single-crystalline counterpart due to its easier scalability and mechanical robustness. However, its TE performance is limited by poor electrical transport properties, resulting in a low carrier concentration and modest power factor. Here, we demonstrate both theoretically and experimentally that alkali metal Li doping serves as an effective carrier engineering strategy to overcome performance limitations. First-principles calculations reveal that Li acts as an efficient acceptor, inducing a significant charge transfer and modifying the electronic structure. Experimentally, doping Li increases the carrier concentration 2 orders of magnitude up to 1.8 & times; 1019 cm-3, resulting in significantly enhanced electrical conductivity and a peak power factor of 7.1 mu W cm-1 K-2. Eventually, a high zT value of similar to 2.0 at 823 K is achieved in Li-doped SnSe. This work offers important insight for the rational design of high-performance polycrystalline SnSe.
Mulched drip irrigation with appropriate strategies is recommended for effectively reclaiming saline soils in the Hetao Irrigation District of China. This study investigated soil water-salt dynamics and crop growth under different irrigation strategies through soil box experiments, scenario simulation experiments and field validation experiments, with particular focus on two drip irrigation strategies: single 30-mm irrigation and split irrigation (15 mm on Days 1 and 15). Hydrus-2D was used to simulate the distribution of water and salt. The results demonstrated that soil water content (SWC) fluctuated under mulched drip irrigation, with higher amounts near the drip emitter. The highest SWCs with the single and split irrigations were 0.22 and 0.19 cm3 & centerdot;cm-3, respectively. The split irrigation strategy better maintained SWC within the 0-25 cm depth range. Simulation experiments further revealed that increasing irrigation amounts to 40 or 50 mm effectively sustained soil water content, while producing salt leaching effects largely comparable to the 30-mm irrigation. The lower soil salinity (0.53 g & centerdot;kg-1) was recorded with split irrigation. However, no significant differences in salinity were observed between thetested mulched drip-irrigation strategies within the 0-15 cm soil depth. Field validation experiments demonstrated that split irrigation resulted in significantly greater plant height, stem diameter and leaf area index compared to the single irrigation at about 30 days after sowing. It was concluded that with a limited 30-mm irrigation, split drip irrigation effectively delays soil water depletion, performs better than a single drip irrigation by enhancing overall soil water content and promoting desalination, and thereby facilitating improved crop growth. (c) The Author(s) 2026. Published by Higher Education Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0)
Accurate prediction of the L-H transition power threshold is essential for achieving steady-state high-performance burning plasmas in future fusion reactors. In this study, we develop a machine learning-based regression framework to predict the plasma power loss across the separatrix, Ploss, at the onset of the L-H transition. The model is trained on 3308 EAST discharges; from each discharge, we extract exactly one sample at the onset of its first L-H transition. Three ensemble learning models-random forest, XGBoost, and CatBoost-are systematically compared. As a benchmark, we compare our results with the empirical ITPA scaling law, which was derived from the high-density branch of the L-H power threshold in favorable ion del B drift configurations of ITER-like plasmas. On our present EAST database, which spans both high-density and low-density regimes and includes discharges with both favorable and unfavorable del B drift directions, the CatBoost model attains the highest predictive accuracy and yields significantly lower errors than the multivariate linear regression baseline. Model interpretation is performed using SHAP (SHapley Additive exPlanations). The SHAP rankings indicate that the key variables appearing in empirical L-H scaling relations (S, n & strns;e, and BT) remain the dominant predictors, while the plasma current Ip is consistently identified as an additional leading contributor. Equilibrium-related and geometry-related parameters ( delta top, delta bot, q95, kappa) also exhibit non-negligible contributions. Underexplored spatial variables such as ZLX show a notable impact on the power threshold within the present EAST database. These results suggest that the machine-learning analysis can reproduce the main dependencies embodied in conventional scaling laws, while also indicating additional effects that are not explicitly encoded in the Martin scaling. The present framework provides an alternative data-driven approach for predicting the L-H transition, which may be particularly useful for exploring how multiple coupled control parameters jointly influence the L-H power threshold in complex, reactor-relevant operating scenarios.
Herein, Fe3O4 magnetic nanoparticles (Fe3O4 MNPs) were synthesized via a one-step counter-coprecipitation method, and Prussian blue (PB) nanoparticles were subsequently modified in situ on the surface of Fe3O4 MNPs. The obtained PB/Fe3O4 composite magnetic nanoparticles were characterized by transmission electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The results demonstrated that PB/Fe3O4 exhibited excellent peroxidase-like catalytic activity and followed Michaelis-Menten kinetics in the presence of H2O2 and 3,3 ',5,5 '-tetramethylbenzidine. Taking advantage of the intrinsic peroxidase-like activity of PB, Fe3O4 MNPs, and their synergistic effects, a novel nitrite (NO2-) signal-enhanced electrochemical sensing platform was developed by first modifying a magnetic glassy carbon electrode (MGCE) with PB and then drop-casting the PB/ Fe3O4 composite nanoparticles. The resulting PB/ Fe3O4/PB/MGCE sensor exhibited high sensitivity and selectivity toward NO2- detection. Under optimized conditions, the sensor achieved a detection limit of 0.03588 mu M (S/N = 3). Furthermore, the proposed peroxidase-like signal-enhanced electrochemical sensor was successfully applied to detect NO2- in sausage, bacon, and pickled mustard tuber samples. Overall, this novel signal-enhanced electrochemical sensing strategy offers great potential for applications in food quality control and safety monitoring.
