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.

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.

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.

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.

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.

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 size and distribution of tidal creeks affects salt marsh restoration.

Salt marshes are changeable and important ecosystems that currently face various threats, including global climate change and human activities. The influence of these factors can result in the degradation of salt marshes. Tidal creeks, which are an important source of nutrients and other substances for salt marsh vegetation, play an important role in the health of salt marshes. In this study, the morphological characteristics of tidal creeks and the characteristics of two typical plants, Suaeda glauca (SG) and Phragmites communis (PC), in the Yellow River Delta, China were investigated to determine the effect of tidal creeks on these plants. Aerial photography and field measurements of tidal creeks were carried out from May to July 2018 in the study area. At the same time, nine line-intercepts were set in the vertical direction of tidal creeks to investigate plants. The results showed that different grades of tidal creek exerted no significant influence on the growth of either S. glauca or P. communis. However, unlike grade, the size of a creek and the distance from it had marked effects on these plants. The cross-sectional area of a tidal creek had a significant positive impact on the density of S. glauca (r = 0.39, p = 0.02). For P. communis, the depth of a tidal creek had a strong correlation with this species' density (r = 0.51, p = 0.04) and height (r = 0.63, p = 0.01). Meanwhile, there was a negative relationship between the distance from tidal creeks and the height of S. glauca (r = -0.52, p = 0.02). Conversely, the height (r = 0 0.90, p = 0.00) and density (r = 0.62, p = 0.01) of P. communis were positively affected by its vertical distance from tidal creeks. We found that the subtidal zone near a tidal creek was more conducive to the recovery and growth of S. glauca, and that areas further away from a tidal creek, located in the intertidal and subtidal zones, were more conducive to the recovery and growth of P. communis. The parameters associated with tidal creeks in the subtidal zone (cross sectional area 4.55 m2, distance 0-10 m) were beneficial for the growth of S. glauca. For P. communis, relevant features in the intertidal and subtidal zones (depth 0.40-0.45 m, distance 20-60 m) are useful. Our results suggest that attention should be paid to the effects of size and distribution of tidal creeks during the process of salt marsh restoration. This work also provides practical guidance for the restoration of native salt marshes in China.

Halogen Vacancies Enable Ligand-Assisted Self-Assembly of Perovskite Quantum Dots into Nanowires.

Interest has been growing in defects of halide perovskites in view of their intimate connection with key material optoelectronic properties. In perovskite quantum dots (PQDs), the influence of defects is even more apparent than in their bulk counterparts. By combining experiment and theory, we report herein a halide-vacancy-driven, ligand-directed self-assembly process of CsPbBr3 PQDs. With the assistance of oleic acid and didodecyldimethylammonium sulfide, surface-Br-vacancy-rich CsPbBr3 PQDs self-assemble into nanowires (NWs) that are 20-60 nm in width and several millimeters in length. The NWs exhibit a sharp photoluminescence profile (≈18 nm full-width at-half-maximum) that peaks at 525 nm. Our findings provide insight into the defect-correlated dynamics of PQDs and defect-assisted fabrication of perovskite materials and devices.

Moving sum of number of positive patient result as a quality control tool.

BACKGROUND: Recently, the total prostate-specific antigen (PSA) assay used in a laboratory had a positive bias of 0.03 µg/L, which went undetected. Consequently, a number of post-prostatectomy patients with previously undetectable PSA concentrations (defined as <0.03 µg/L in that laboratory) were being reported as having detectable PSA, which suggested poorer prognosis according to clinical guidelines. METHODS: Through numerical simulations, we explored (1) how a small bias may evade the detection of routine quality control (QC) procedures with specific reference to the concentration of the QC material, (2) whether the use of 'average of normals' approach may detect such a small bias, and (3) describe the use of moving sum of number of patient results with detectable PSA as an adjunct QC procedure. RESULTS: The lowest QC level (0.86 µg/L) available from a commercial kit had poor probability (<10%) of a bias of 0.03 µg/L regardless of QC rule (i.e. 1:2S, 2:2S, 1:3S, 4:1S) used. The average number of patient results affected before error detection (ANPed) was high when using the average of normals approach due to the relatively wide control limits. By contrast, the ANPed was significantly lower for the moving sum of number of patient results with a detectable PSA approach. CONCLUSIONS: Laboratory practitioners should ensure their QC strategy can detect small but critical bias, and may require supplementation of ultra-low QC levels that are not covered by commercial kits with in-house preparations. The use of moving sum of number of patient results with a detectable result is a helpful adjunct QC tool.

Engineering of CH3 NH3 PbI3 Perovskite Crystals by Alloying Large Organic Cations for Enhanced Thermal Stability and Transport Properties.

The number of studies on organic-inorganic hybrid perovskites has soared in recent years. However, the majority of hybrid perovskites under investigation are based on a limited number of organic cations of suitable sizes, such as methylammonium and formamidinium. These small cations easily fit into the perovskite's three-dimensional (3D) lead halide framework to produce semiconductors with excellent charge transport properties. Until now, larger cations, such as ethylammonium, have been found to form 2D crystals with lead halide. Here we show for the first time that ethylammonium can in fact be incorporated coordinately with methylammonium in the lattice of a 3D perovskite thanks to a balance of opposite lattice distortion strains. This inclusion results in higher crystal symmetry, improved material stability, and markedly enhanced charge carrier lifetime. This crystal engineering strategy of balancing opposite lattice distortion effects vastly increases the number of potential choices of organic cations for 3D perovskites, opening up new degrees of freedom to tailor their optoelectronic and environmental properties.

Detecting long-term drift in reagent lots.

BACKGROUND: Between-reagent lot verification is a routine laboratory exercise in which a set of samples is tested in parallel with an existing reagent lot and a candidate reagent lot (before the candidate lot is committed to test patient samples). The exercise aims to verify and maintain consistency in the analytical performance of a test. We examined the limitations of a routine between-reagent lot verification procedure in detecting long-term analytical drift and looked for a more sensitive alternative. METHOD: Via numerical simulations, we examined the statistical power of the current regression-based (weighted Deming regression) procedure for between-reagent lot verification in detecting proportional bias and constant bias. An alternative procedure applying the Student t-test to separately examine cumulative regression slopes and intercepts across multiple reagent lots was proposed and evaluated by numerical simulations. RESULTS: The regression-based procedure had poor statistical power in detecting proportional bias and constant bias when small numbers of samples were used in each between-reagent lot verification exercise. Furthermore, the method failed to detect long-term drifts in analytical performance. The proposed approach based on the Student t-test can detect long-term (cumulative) drifts in regression slopes and intercepts. This method detected a mild downward drift in the serum sodium assay in our hospital that was missed by routine between-reagent lot verification. CONCLUSIONS: The proposed method objectively and systematically detects long-term proportional and constant bias separately. However, the statistical power of this procedure remains unsatisfactory when used with small sample sizes. Sharing of information between laboratories may provide sufficient statistical power to detect clinically important analytical shifts.

Particulate matter assessment of a wetland in Beijing.

To increase the knowledge on the particulate matter of a wetland in Beijing, an experimental study on the concentration and composition of PM10 and PM2.5 was implemented in Beijing Olympic Forest Park from 2013 to 2014. This study analyzed the meteorological factors and deposition fluxes at different heights and in different periods in the wetlands. The results showed that the mean mass concentrations of PM10 and PM2.5 were the highest at 06:00-09:00 and the lowest at 15:00-18:00. And the annual concentration of PM10 and PM2.5 in the wetland followed the order of dry period (winter)>normal water period (spring and autumn)>wet period (summer), with the concentration in the dry period significantly higher than that in the normal water and wet periods. The chemical composition of PM2.5 in the wetlands included NH4(+), K(+), Na(+), Mg(2+), SO4(2-), NO3(-), and Cl(-), which respectively accounted for 12.7%, 1.0%, 0.8%, 0.7%, 46.6%, 33.2%, and 5.1% of the average annual composition. The concentration of PM10 and PM2.5 in the wetlands had a significant positive correlation with relative humidity, a negative correlation with wind speed, and an insignificant negative correlation with temperature and radiation. The daily average dry deposition amount of PM10 in the different periods followed the order of dry period>normal water period>wet period, and the daily average dry deposition amount of PM2.5 in the different periods was dry period>wet period>normal water period.

Impacts of aquatic macrophytes configuration modes on water quality.

Constructed wetland technology is regarded as an important ecological restoration technology and used widely in sewage disposal. In order to give them a wider scope of application and to improve their performance in water restoration, the current experiment was designed. Four aquatic macrophytes (dwarf cattail (TM), yellow-flowered iris (WI), water shallot (ST) and watermifoil (MS)) were picked and planted in artificial floating islands (AFIs) in different configurations (TM + WI, ST + MS and TM + WI + MS) and two patterns, radiation pattern (RP) and annular pattern (AP), for a 60-day experiment. Then, water quality and growth were monitored every 10 days. The results indicate that the different configurations performed diversely on waste water purification. First, a composite plant configuration removed more pollutant than a single one with the same total increment of biomass. Second, the plant configuration of MS + ST was most effective in total nitrogen (TN), total phosphorus (TP) or PO4(3-) removal, and TM + IW + MS was good at chemical oxygen demand (COD) and NO3(-) removal. However, different patterns comprised from the same species had a certain effect on absorption of pollutants. Generally speaking, plant configurations with a RP were better than an AP in purification. Accordingly, these provided the methods for the pollution wetland restoration.

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.

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.

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.

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.

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.

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.