Coastal distribution and driving factors for blue carbon fractions in the surface soil of a warm-temperate salt marsh in China.

A better understanding of blue carbon (BC) sequestration can not only contribute to a better elucidation of global carbon cycle processes but can also lay the foundation for the incorporation of BC ecosystems into regional and global carbon offset schemes. In this study, the surface soils of seven plots along a landward to seaward distance gradient were analyzed for the concentrations and stocks of soil organic carbon (SOC), soil inorganic carbon (SIC), dissolved organic carbon (DOC), and dissolved inorganic carbon (DIC), as well as soil physical (bulk density, texture, moisture), chemical (pH, electrical conductivity), and microbiological (phospholipid fatty acid) properties in the coastal wetlands. Correlation, variation partition and random forest (RF) analyses were used to identify key variables correlating with BC fraction distribution patterns. The results suggested that SIC, DIC, and DOC, exhibited similar landward-increasing trends but the driving factors were distinct from each other. Based on correlation and RF analysis, both SIC and DIC were closely related to soil moisture and clay contents, but microbial indicators of arbuscular mycorrhizal fungi and actinomycete, were found to be associated with SIC, and abiotic properties played less important but still substantial roles in predicting DIC dynamics. In contrast with the other three investigated BC fractions, SOC showed a slight tendency toward enrichment in the seaward direction, and SIC was identified as the main driving factor. DOC showed no significant correlations with the other BC fractions, and its variation could not be explained well by the selected edaphic parameters. The soils in the YRD's tidal Suaeda salsa salt marshes showed a significant negative coupled SOC-SIC correlation, which was potentially related to divergent sedimentary processes and potential biotransformation between SOC and SIC. These results highlight the importance of integrating multiple BC fractions and their interactions into attempts to explore key mechanisms of BC cycling.

Data-driven machine learning prediction of glass transition temperature and the glass-forming ability of metallic glasses.

The limited glass-forming ability (GFA) poses a significant challenge for the practical applications of metallic glasses (MGs). The development of high-GFA MGs typically involves trial-and-error processes to screen materials with a large critical diameter (Dmax), which serves as a criterion for determining the GFA. The formation and stability of MGs are influenced by the glass transition temperature (Tg). Over the past decade, the emergence of machine learning (ML) has shown great promise in the exploration of high-GFA materials. However, the contribution of material features to Tg and Dmax predictions, as well as their correlations, remains ambiguous, posing a challenge to achieving high prediction accuracy. Herein, we present a comprehensive dataset consisting of 1764 datapoints for Tg and 1296 datapoints for Dmax. The governing rules for GFA have been established through feature significance analysis. The light gradient boosting (LGB) model exhibits remarkable accuracy in predicting Tg, utilizing sixteen features, achieving a coefficient of determination (R2) score of 0.984 and a root mean square error (RMSE) of 20.196 K. An integrated ML model, based on the weighted voting of three basic models, is developed to enhance the accuracy of Dmax prediction, achieving an R2 score of 0.767 and an RMSE of 2.331 mm. Additionally, a GFA rule is proposed to explore materials with large Dmax values, defined by satisfying the criteria of a thermal conductivity difference ranging from 0.60 to 1.32 and an entropy density exceeding 1.05. Our work provides valuable insights into Tg and Dmax predictions and facilitates the exploration of potential high-GFA MGs through the implementation of a well-established ML model and GFA rules.

Tailoring B, N-Enriched Carbon Nanosheets via a Gelation-Assisted Strategy for High-Capacity and Fast-Response Capacitive Desalination.

Designing high-performance carbonous electrodes for capacitive deionization with remarkable salt adsorption capacity (SAC) and outstanding salt adsorption rate (SAR) is quite significant yet challenging for brackish water desalination. Herein, a unique gelation-assisted strategy is proposed to tailor two-dimensional B and N-enriched carbon nanosheets (BNCTs) for efficient desalination. During the synthesis process, boric acid and polyvinyl alcohol were cross-linked to form a gelation template for the carbon precursor (polyethyleneimine), which endows BNCTs with ultrathin thickness (∼2 nm) and ultrahigh heteroatoms doping level (14.5 atom % of B and 14.8 atom % of N) after freeze-drying and pyrolysis. The laminar B, N-doped carbon enables an excellent SAC of 42.5 mg g-1 and fast SAR of 4.25 mg g-1 min-1 in 500 mg L-1 NaCl solution, both of which are four times as much as those of activated carbon. Moreover, the density functional theory (DFT) calculation demonstrates that the dual doping of B and N atoms firmly enhances the adsorption capacity of Na+, leading to a prominent chemical SAC for brackish water. This work paves a new way to rationally integrate both conducive surface morphology and systematic effects of B, N doping to construct high-efficiency carbonaceous electrodes for desalination.

Inhibition of Spartina alterniflora growth alters soil bacteria and their regulation of carbon metabolism.

The state of growth of invasive species has a significant impact on the microbial regulation of the soil carbon (C) cycle. This study focused on the growth of Spartina alterniflora treated with imazapyr in the Tiaozini wetland of Jiangsu Province, China. The changes in soil bacterial structure, bacterial C metabolic activity, soil C, and regulation mechanism of soil C metabolic activity by biotic and abiotic factors were investigated. The results showed that soil bacterial diversity eventually decreased significantly (p < 0.05) along with significant changes in microbial structure (p < 0.05). Significant changes in soil physicochemical properties due to S. alterniflora growth inhibition were the key factors affecting the changes in the soil bacterial taxa composition (p < 0.05). Abiotic factors showed a greater effect on metabolic activities related to C fixation and biosynthesis of bacterial taxa than biotic factors (self-regulation). Additionally, bacterial taxa regulated soil C emission and degradation to a greater extent than abiotic factors. This study provides important information for understanding the regulators of C cycling in coastal wetland soil during the control of S. alterniflora invasion by imazapyr; moreover, it provides a scientific basis for the government to establish a prevention and control policy for S. alterniflora invasion. Understanding the complex interplay between abiotic and biotic factors is essential for developing effective strategies to manage soil C and mitigate the impacts of climate change.

Accurate and efficient machine learning models for predicting hydrogen evolution reaction catalysts based on structural and electronic feature engineering in alloys.

Predictive materials design of high-performance alloy electrocatalysts is a grand challenge in hydrogen production via water electrolysis. The vast combinatorial space of element substitutions in alloy electrocatalysts offers a wealth of candidate materials, but presents a significant challenge in terms of experimental and computational exploration of all possible options. Recent scientific and technological developments in machine learning (ML) have offered a new opportunity to accelerate such electrocatalyst materials design. Herein, by incorporating both the electronic and structural properties of alloys, we are able to construct accurate and efficient ML models and predict high-performance alloy catalysts for the hydrogen evolution reaction (HER). We have identified the light gradient boosting (LGB) algorithm as the best-performed method, with an excellent coefficient of determination (R2) value reaching 0.921 and the corresponding root-mean-square error (RMSE) being 0.224 eV. The average marginal contributions of alloy features towards ΔGH* values are estimated to determine the importance of various features during the prediction processes. Our results indicate that both the electronic properties of constituent elements and the structural adsorption site features play the most critical roles in the ΔGH* prediction. Furthermore, 84 potential alloys with |ΔGH*| values less than 0.1 eV are successfully screened out of 2290 candidates selected from the Material Project (MP) database. It is reasonable to expect that the ML models with structural and electronic feature engineering developed in this work would provide new insights in future electrocatalyst developments for the HER and other heterogeneous reactions.

Deep Generative Model for Inverse Design of High-Temperature Superconductor Compositions with Predicted Tc > 77 K.

Identifying new superconductors with high transition temperatures (Tc > 77 K) is a major goal in modern condensed matter physics. The inverse design of high Tc superconductors relies heavily on an effective representation of the superconductor hyperspace due to the underlying complexity involving many-body physics, doping chemistry and materials, and defect structures. In this study, we propose a deep generative model that combines two widely used machine learning algorithms, namely, the variational auto-encoder (VAE) and the generative adversarial network (GAN), to systematically generate unknown superconductors under the given high Tc condition. After training, we successfully identified the distribution of the representative hyperspace of superconductors with different Tc, in which many superconductor constituent elements were found adjacent to each other with their neighbors in the periodic table. Equipped with the conditional distribution of Tc, our deep generative model predicted hundreds of superconductors with Tc > 77 K, as predicted by the published Tc prediction models in the literature. For the copper-based superconductors, our results reproduced the variation in Tc as a function of the Cu concentration and predicted an optimal Tc = 129.4 K, when the Cu concentration reached 2.41 in Hg0.37Ba1.73Ca1.18Cu2.41O6.93Tl0.69. We expect that such an inverse design model and comprehensive list of potential high Tc superconductors would greatly facilitate future research activities in superconductors.

Rapid detection of Staphylococcus aureus using a novel multienzyme isothermal rapid amplification technique.

Staphylococcus aureus is a common pathogen that causes various infections. Therefore, it is crucial to develop a fast and easy detection method for diagnosing and preventing S. aureus infections. In this study, MIRA assay was developed and validated (specificity; 100%) for the detection of S. aureus with nuc as the target gene. The reaction temperature and reaction time were then optimized, and the best reaction was at 40°C, 20 min. The assay could detect S. aureus in only 25 min. Additionally, the limit of detection of MIRA was 5 × 102 CFU/ml, 10-fold lower than that of the traditional PCR. Furthermore, this assay efficiently detected 219 S. aureus of 335 strains obtained from different bacterial samples (detection accuracy; 99.40%). In conclusion, this study provides a rapid and easy-to-operate method for the detection of S. aureus, and thus can be used for the timely diagnosis and prevention of S. aureus infection.

Remote Raman Detection of Trace Explosives by Laser Beam Focusing and Plasmonic Spray Enhancement Methods.

Remote Raman spectroscopy is a technique that can detect and identify different target molecules through Raman vibrational modes from a remote distance. However, the current remote Raman technique is restricted by poor detection sensitivity, and it is still extremely challenging for trace explosive detection. Here, in order to achieve trace explosive detection from a remote distance, we innovatively propose two enhanced Raman spectroscopy methods by using a plasmonic spray and a laser beam focusing/Raman signal collecting instrument. In brief, a facile convex lens can converge the laser beam and collect Raman scattering signals, and a plasmonic spray can be used for surface-enhanced Raman scattering. Under the combination of the above enhancement methods, we achieve remote Raman detection of a variety of trace explosives with a concentration of ∼1 µg/cm2 from a distance of 30 m. These novel methods demonstrate a simple approach that significantly improves the capability of remote detection of trace chemicals for further applications.

Carrier Separation Enhanced by High Angle Twist Grain Boundaries in Cesium Lead Bromide Perovskites.

Grain boundaries (GBs) have a profound impact on mechanical, chemical, and physical properties of polycrystalline materials. Comprehension of atomic and electronic structures of different GBs in materials can help to understand their impact on materials' properties. Here, with aberration-corrected scanning transmission electron microscopy (STEM), the atomic structure of a 90° twist GB s in CsPbBr3 is determined, and its impact on electron-hole pair separation is predicted. The 90° twist GB has a coherent interface and the same chemical composition as the bulk except for the lattice twist. Density functional theory (DFT) calculation results indicate that the twist GB has an electronic structure similar to that of the bulk CsPbBr3. An electronic potential at the GBs enhances the separation of photogenerated carriers and promotes the motion of electrons across the GBs. These results extend the understanding of atomic and electronic structure of GBs in halide perovskites and propose a potential strategy to eliminate the influence of GBs by GB engineering.

Design of a Double-Layer Electrothermal MEMS Safety and Arming Device with a Bistable Mechanism.

Considering the safety of ammunition, safety and arming (S&A) devices are usually designed in pyrotechnics to control energy transfer through a movable barrier mechanism. To achieve both intelligence and miniaturization, electrothermal actuators are used in MEMS S&A devices, which can drive the barrier to an arming position actively. However, only when the actuators' energy input is continuous can the barrier be stably kept in the arming position to wait for ignition. Here, we propose the design and characterization of a double-layer electrothermal MEMS S&A Device with a bistable mechanism. The S&A device has a double-layer structure and four groups of bistable mechanisms. Each bistable mechanism consists of two V-shape electrothermal actuators to drive a semi-circular barrier and a pawl, respectively, and control their engagement according to a specific operation sequence. Then, the barrier can be kept in the safety or the arming position without energy input. To improve the device's reliability, the four groups of bistable mechanisms are axisymmetrically placed in two layers to constitute a double-layer barrier structure. The test results show that the S&A device can use constant-voltage driving or the capacitor-discharge driving to drive the double-layer barrier to the safety or the arming position and keep it on the position passively by the bistable mechanism.

Systematic review and meta-analysis: diagnostic value of different ultrasound for benign and malignant thyroid nodules.

Background: Conventional ultrasound and contrast-enhanced ultrasound (CEUS) are commonly used in the diagnosis of benign and malignant thyroid nodules. However, the value of the two methods in the diagnosis of benign and malignant thyroid nodules remains controversial. Methods: PubMed, Medline, EBSCO, Science Direct, Cochrane Library, China National Knowledge Infrastructure (CNKI) database and manual journal retrieval were searched from January 2000 to January 2022, to include research on conventional ultrasound or CEUS in the diagnosis of benign and malignant thyroid nodule related clinical studies. Meta-analysis was conducted using RevMan5.3 and Stata Corp to analyze the sensitivity and specificity of conventional ultrasound and CEUS in the diagnosis of benign and malignant thyroid nodules with 95% confidence interval (CI) as indicators. Heterogeneity of the results was evaluated by Q test and I2 in RevMan5.3. Deek's method was used to evaluate publication bias. Results: A total of 1,378 nodules were included in 11 literatures, including 535 malignant thyroid nodules and 843 benign thyroid nodules. Heterogeneity tests conducted for CEUS diagnostic sensitivity of the 6 included literatures indicated that there was no heterogeneity among the study groups [Q=2.05, degree of freedom (df) =5.00, I2=0.00%, P=0.84]. The combined sensitivity was 0.87, with 95% confidence interval (CI): 0.82 to 0.90. Heterogeneity tests on the diagnostic specificity of CEUS of the six included literatures suggested that there was heterogeneity among the different study groups (Q=14.27, df =5.00, I2=64.96%, P=0.01). The combined specificity was 0.84 (95% CI: 0.78 to 0.89). Heterogeneity tests performed on the sensitivity of five conventional ultrasound diagnosis articles revealed that there was heterogeneity among different study groups (Q=13.62, df =4.00, I2=70.64%, P=0.01). The combined sensitivity was 0.86 (95% CI: 0.78 to 0.92). Heterogeneity tests on the specificity of conventional ultrasound diagnosis in five included literatures indicated that there was heterogeneity among different study groups (Q=16.94, df =4.00, I2=76.39%, P=0.00). The combined specificity was 0.84 (95% CI: 0.75 to 0.90). There was no bias in the included literature. Discussion: The sensitivity of CEUS in the diagnosis of benign and malignant thyroid nodules was slightly higher than that of conventional ultrasound, which provides a reference for the clinical diagnosis of benign and malignant thyroid nodules.

Consistency between deposition of particulate matter and its removal by rainfall from leaf surfaces in plant canopies.

The leaf surfaces of plants are important organs for retaining particulate matter (PM). They can be renewed via washout processes (e.g., rainfall), thereby restoring the ability to retain new PM. Most of the current studies have focused on the mechanisms of rainfall characteristics on the renewal of PM on plant leaf surfaces and interspecific differences, while the effects of different leaf heights on PM renewal within the same plant canopy have been less studied. In addition, the dynamics of PM during rainfall, especially the water-soluble ions (WSII) component, are often neglected. This research used Salix matsudana, a tree species with a significant natural height difference between the upper and lower leaves of its canopy, as its study object. Using artificially simulated rainfall, the rainfall intensity was quantified as low, medium, and high (i.e., 30 mm/h, 45 mm/h, and 60 mm/h), and the rainfall process was divided into three sub-stages: pre (0-20 min), mid (20-40 min), and post (40-60 min). The experimental setup was divided into upper (2 m) and lower leaves (1 m) according to the height of the canopy. The concentration and distribution of water-insoluble PM (WIPM) were obtained using the elution weighing method, whereas WSII were obtained using ion chromatography. The dynamics of WIPM and WSII during the removal of PM from the leaf surface by rainfall were studied at different canopy heights, and the results showed that the composition and proportions of WIPM and WSII varied at different stages of the rainfall process and that the concentrations of WIPM and WSII removed from the upper leaves differed slightly from those of the lower leaves. In particular, the concentrations of WIPM and WSII removed from the lower leaves were greater than those from the upper leaves at high rainfall intensity (60 mm/h), showing consistency between rainfall removal of PM from the leaf surface at different heights within the plant canopy and deposition of PM, while at low (30 mm/h) and medium (45 mm/h) rainfall intensities the performance was slightly different.

One-kilojoule pulsed-power generator for laboratory space sciences.

This paper reports on the assembly of a compact, low-cost, pulsed-power facility used for plasma studies. The construction uses two modules placed on opposite sides of the test chamber to minimize the system impedance and improve access to test samples. The stored energy is 1  kJ with a peak current of 135  kA and a 1592  ns quarter-period time. Up until now, an imploding conical-wire array has been studied by using time-integrated (visible) imaging, and time-resolved laser imaging, providing a measure of the plasma jet speed in the range of 170  km/s. Our future plans will continue to investigate high-energy-density plasmas that are relevant to the space environment, fusion, and spectroscopy.

Direct atomic-scale imaging of a screw dislocation core structure in inorganic halide perovskites.

Topological defects such as dislocations in crystalline materials usually have major impacts on materials' mechanical, chemical and physical properties. Detailed knowledge of dislocation core structures is essential to understand their impacts on materials' properties. However, compared with imaging of core structures of edge dislocations, direct imaging of a screw dislocation core is challenging from the traditional edge-on direction because the atomic displacements are parallel to the screw dislocation line. Here, a screw dislocation with a Burgers vector 1/2[110] in orthorhombic CsPbBr3 nanocrystals is directly imaged at the atomic scale with the incident electron beam perpendicular to the dislocation line using aberration-corrected scanning transmission electron microscopy (STEM). The dislocation core is characterized by helical atomic planes along the dislocation line. Quantitative assessments of the change rate of the screw displacements reveal the dislocation line locate at a plane containing Cs and Br atoms. This study reveals the atomic structure of screw dislocation cores in CsPbBr3 and provides useful information for the understanding of structure-property relations of halide perovskites.

Unravelling Structure and Formation Mechanisms of Ruddlesden-Popper-Phase-like Nanodomains in Inorganic Lead Halide Perovskites.

Ultrastable CsPbBr3 nanoplates against electron beam irradiations are fabricated and nanodomains with anomalous high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM) contrasts are observed within CsPbBr3 nanoplates. Atomic resolution energy dispersive X-ray spectroscopy (EDS) mapping, which requires even higher beam currents and may cause significant damages on electron beam sensitive materials, are obtained without any detectable damages or decomposition. Combining HAADF-STEM images, atomic resolution EDS mapping, and image simulations has revealed detailed structure and chemistry of the nanodomains to be induced by Ruddlesden-Popper faults (RP faults) rather than any chemical intermixing or formation of new phases. A formation mechanism is also proposed on the basis of the atomic structure of the nanodomains. This result promotes an atomic-level understanding of inorganic lead halide perovskites and may help to reveal their structure-property relationship.

Self-Assembly and Regrowth of Metal Halide Perovskite Nanocrystals for Optoelectronic Applications.

ConspectusOver the past decade, the impressive development of metal halide perovskites (MHPs) has made them leading candidates for applications in photovoltaics (PVs), X-ray scintillators, and light-emitting diodes (LEDs). Constructing MHP nanocrystals (NCs) with promising optoelectronic properties using a low-cost approach is critical to realizing their commercial potential. Self-assembly and regrowth techniques provide a simple and powerful "bottom-up" platform for controlling the structure, shape, and dimensionality of MHP NCs. The soft ionic nature of MHP NCs, in conjunction with their low formation energy, rapid anion exchange, and ease of ion migration, enables the rearrangement of their overall appearance via self-assembly or regrowth. Because of their low formation energy and highly dynamic surface ligands, MHP NCs have a higher propensity to regrow than conventional hard-lattice NCs. Moreover, their self-assembly and regrowth can be achieved simultaneously. The self-assembly of NCs into close-packed, long-range-ordered mesostructures provides a platform for modulating their electronic properties (e.g., conductivity and carrier mobility). Moreover, assembled MHP NCs exhibit collective properties (e.g., superfluorescence, renormalized emission, longer phase coherence times, and long exciton diffusion lengths) that can translate into dramatic improvements in device performance. Further regrowth into fused MHP nanostructures with the removal of ligand barriers between NCs could facilitate charge carrier transport, eliminate surface point defects, and enhance stability against moisture, light, and electron-beam irradiation. However, the synthesis strategies, diversity and complexity of structures, and optoelectronic applications that emanate from the self-assembly and regrowth of MHPs have not yet received much attention. Consequently, a comprehensive understanding of the design principles of self-assembled and fused MHP nanostructures will fuel further advances in their optoelectronic applications.In this Account, we review the latest developments in the self-assembly and regrowth of MHP NCs. We begin with a survey of the mechanisms, driving forces, and techniques for controlling MHP NC self-assembly. We then explore the phase transition of fused MHP nanostructures at the atomic level, delving into the mechanisms of facet-directed connections and the kinetics of their shape-modulation behavior, which have been elucidated with the aid of high-resolution transmission electron microscopy (HRTEM) and first-principles density functional theory calculations of surface energies. We further outline the applications of assembled and fused nanostructures. Finally, we conclude with a perspective on current challenges and future directions in the field of MHP NCs.

Cyanamide Passivation Enables Robust Elemental Imaging of Metal Halide Perovskites at Atomic Resolution.

Lead halide perovskites (LHPs) have attracted a tremendous amount of attention because of their applications in solar cells, lighting, and optoelectronics. However, the atomistic principles underlying their decomposition processes remain in large part obscure, likely due to the lack of precise information about their local structures and composition along regions with dimensions on the angstrom scale, such as crystal interfaces. Aberration-corrected scanning transmission electron microscopy combined with X-ray energy dispersive spectroscopy (EDS) is an ideal tool, in principle, for probing such information. However, atomic-resolution EDS has not been achieved for LHPs because of their instability under electron-beam irradiation. We report the fabrication of CsPbBr3 nanoplates with high beam stability through an interface-assisted regrowth strategy using cyanamide. The ultrahigh stability of the nanoplates primarily stems from two contributions: defect-healing self-assembly/regrowth processes and surface modulation by strong electron-withdrawing cyanamide molecules. The ultrahigh stability of as-prepared CsPbBr3 nanoplates enabled atomic-resolution EDS elemental mapping, which revealed atomically and elementally resolved details of the LHP nanostructures at an unprecedented level. While improving the stability of LHPs is critical for device applications, this work illustrates how improving the beam stability of LHPs is essential for addressing fundamental questions on structure-property relations in LHPs.

All-Inorganic Quantum-Dot LEDs Based on a Phase-Stabilized α-CsPbI3 Perovskite.

The all-inorganic nature of CsPbI3 perovskites allows to enhance stability in perovskite devices. Research efforts have led to improved stability of the black phase in CsPbI3 films; however, these strategies-including strain and doping-are based on organic-ligand-capped perovskites, which prevent perovskites from forming the close-packed quantum dot (QD) solids necessary to achieve high charge and thermal transport. We developed an inorganic ligand exchange that leads to CsPbI3 QD films with superior phase stability and increased thermal transport. The atomic-ligand-exchanged QD films, once mechanically coupled, exhibit improved phase stability, and we link this to distributing strain across the film. Operando measurements of the temperature of the LEDs indicate that KI-exchanged QD films exhibit increased thermal transport compared to controls that rely on organic ligands. The LEDs exhibit a maximum EQE of 23 % with an electroluminescence emission centered at 640 nm (FWHM: ≈31 nm). These red LEDs provide an operating half-lifetime of 10 h (luminance of 200 cd m-2 ) and an operating stability that is 6× higher than that of control devices.

The ultralow thermal conductivity and tunable thermoelectric properties of surfactant-free SnSe nanocrystals.

Most studies to date on SnSe thermal transport are focused on single crystals and polycrystalline pellets that are obtained using high-temperature processing conditions and sophisticated instruments. The effects of using sub-10 nm-size SnSe nanocrystals on the thermal transport and thermoelectric properties have not been studied to the best of our knowledge. Here, we report the synthesis of sub-10 nm colloidal surfactant-free SnSe NCs at a relatively low temperature (80 °C) and investigate their thermoelectric properties. Pristine SnSe NCs exhibit p-type transport but have a modest power factor of 12.5 µW m-1 K-2 and ultralow thermal conductivity of 0.1 W m-1 K-1 at 473 K. Interestingly, the one-step post-synthesis treatment of NC film with methylammonium iodide can switch the p-type transport of the pristine film to n-type. The power factor improved significantly to 20.3 µW m-1 K-2, and the n-type NCs show record ultralow thermal conductivity of 0.14 W m-1 K-1 at 473 K. These surfactant-free SnSe NCs were then used to fabricate flexible devices that show superior performance to rigid devices. After 20 bending cycles, the flexible device shows a 34% loss in the power factor at room temperature (295 K). Overall, this work demonstrates p- and n-type transport in SnSe NCs via the use of simple one-step post-synthesis treatment, while retaining ultralow thermal conductivity.

Rail-gap switch with a multistep high-voltage triggering system.

A rail-gap switch with a multistep triggering system was developed. The rail-gap switch consisted of two rail-like electrodes and a knife-edge electrode parallel to each other. It was assembled from many pieces and filled with unpressurized-flowing dry air. Good alignments between all electrodes were achieved by using a special jig and the knife-edge electrode as the spatial reference. Furthermore, to trigger the rail-gap switch, a multistep triggering system was used. The triggering system consisted of three components: an optical trigger-pulse generator, a slow high-voltage trigger-pulse generator using an ignition coil for a car, and finally, a fast high-voltage trigger-pulse generator using a three-stage Marx generator. The triggering system generated a negative high-voltage trigger pulse of less than -40 kV with a falling speed of -6.6 ± 0.4 kV/ns. The falling speed was fast enough to initiate multichannel discharges in the rail-gap switch. Finally, the rail-gap switch was tested using a test bench consisting of a 0.5-µF capacitor bank charged to 20 kV. The rail-gap switch was triggered by the multistep triggering system robustly with a delay of 180 ns. The delay between the time, when the peak current of the test bench occurred, and the trigger pulse was 890 ns with a jitter of 20 ns, i.e., ∼2% uncertainty in time. The inductance of the rail-gap switch was ∼80 nH obtained from the discharge tests. The rail-gap switch with the multistep high-voltage triggering system is suitable for any pulsed-power systems with current rise times in the order of 1 µs.