Au10Ag17(TPP)10(SR)6Cl5 nanocluster: structure, transformation and the origin of its photoluminescence.

Nanocluster photoluminescence (PL) has important practical applications and its rationalization is therefore of significant interest. Here, we report the synthesis, structure determination and photoluminescence of Au10Ag17(TPP)10(SR)6Cl5 (TPP = triphenylphosphine, SR = 3, 5-bis(trifluoromethyl)thiophenol, denoted as Au10Ag17). Au10Ag17 exhibited a low photoluminescence quantum yield (PLQY) of 2.8%, which could be increased 15-fold by removing the two terminal silver atoms to give AgxAu25-x(SR)5(TPP)10Cl22+ (x = 11-13, SR = 2-phenylethylmercaptan, abbrev. Au12Ag13). The discovery of such a PL switch constitutes an interesting opportunity to further understand the origin of fluorescence in nanoclusters.

Detection of marine oil spills from radar satellite images for the coastal ecological risk assessment.

Coastal ecosystems offer substantial support and space for the sustainable development of human society, and hence the ecological risk evaluation of coastal ecosystems is of great significance. In this article, we propose an innovative framework for evaluating coastal ecological risk by considering oil spill risk information and environmental vulnerability information. Specifically, a deep learning based marine oil spill monitoring method is presented to obtain the oil spill risk information from Sentinel-1 polarimetric synthetic aperture radar (PolSAR) images. The environmental vulnerability information is then obtained from biological sample data and habitat information. Finally, a weighted probability model is introduced to utilize the oil spill risk and environmental vulnerability information, to evaluate the coastal ecological risk. In the experimental part, the proposed oil spill monitoring method shows its reliability in global ocean areas, and the proposed model is adopted to evaluate the ecological risk in Jiaozhou Bay, China. The results show that the ecological situation of more than half of the areas in Jiaozhou Bay is unstable, and the areas with high risk are mainly concentrated in the ports, shipping channels, and those areas with high biodiversity. This study provides some new perspectives on ecological risk assessment for coastal ecosystems, facilitating the planning process and the actions to be taken in response to the accidents that occur in the ocean, especially oil spill accidents.

Poly-Hydride [AuI 7 (PPh3 )7 H5 ](SbF6 )2 cluster complex: Structure, Transformation, and Electrocatalytic CO2 Reduction Properties.

Hydride AuI bonds are labile due to the mismatch in electric potential of an oxidizing metal and reducing ligand, and therefore the structure and structure-activity relationships of nanoclusters that contain them are seldom studied. Herein, we report the synthesis and characterization of [Au7 (PPh3 )7 H5 ](SbF6 )2 (abbrev. Au7 H5 2+ ), an Au cluster complex containing five hydride ligands, which decomposed to give [Au8 (PPh3 )7 ]2+ (abbrev. Au8 2+ ) upon exposure to light (300 to 450 nm). The valence state of AuI and H- was verified by density functional theory (DFT) calculations, NMR, UV/Vis and XPS. The two nanoclusters behaved differently in the electrocatalytic CO2 reduction reaction (CO2 RR): Au7 H5 2+ exhibited 98.2 % selectivity for H2 , whereas Au8 2+ was selective for CO (73.5 %). Further DFT calculations showed that the H- ligand inhibited the CO2 RR process compared with the electron-donor H.

Polarimetric SAR Speckle Filtering Using a Nonlocal Weighted LMMSE Filter.

Despeckling is a key preprocessing step for applications using PolSAR data in most cases. In this paper, a technique based on a nonlocal weighted linear minimum mean-squared error (NWLMMSE) filter is proposed for polarimetric synthetic aperture radar (PolSAR) speckle filtering. In the process of filtering a pixel by the LMMSE estimator, the idea of nonlocal means is employed to evaluate the weights of the samples in the estimator, based on the statistical equalities between the neighborhoods of the sample pixels and the processed pixel. The NWLMMSE estimator is then derived. In the preliminary processing, an effective step is taken to preclassify the pixels, aiming at preserving point targets and considering the similarity of the scattering mechanisms between pixels in the subsequent filter. A simulated image and two real-world PolSAR images are used for illustration, and the experiments show that this filter is effective in speckle reduction, while effectively preserving strong point targets, edges, and the polarimetric scattering mechanism.

Multiple Classifiers Based Semi-Supervised Polarimetric SAR Image Classification Method.

Polarimetric synthetic aperture radar (PolSAR) image classification has played an important role in PolSAR data application. Deep learning has achieved great success in PolSAR image classification over the past years. However, when the labeled training dataset is insufficient, the classification results are usually unsatisfactory. Furthermore, the deep learning approach is based on hierarchical features, which is an approach that cannot take full advantage of the scattering characteristics in PolSAR data. Hence, it is worthwhile to make full use of scattering characteristics to obtain a high classification accuracy based on limited labeled samples. In this paper, we propose a novel semi-supervised classification method for PolSAR images, which combines the deep learning technique with the traditional scattering trait-based classifiers. Firstly, based on only a small number of training samples, the classification results of the Wishart classifier, support vector machine (SVM) classifier, and a complex-valued convolutional neural network (CV-CNN) are used to conduct majority voting, thus generating a strong dataset and a weak dataset. The strong training set are then used as pseudo-labels to reclassify the weak dataset by CV-CNN. The final classification results are obtained by combining the strong training set and the reclassification results. Experiments on two real PolSAR images on agricultural and forest areas indicate that, in most cases, significant improvements can be achieved with the proposed method, compared to the base classifiers, and the improvement is approximately 3-5%. When the number of labeled samples was small, the superiority of the proposed method is even more apparent. The improvement for built-up areas or infrastructure objects is not as significant as forests.

Homoleptic Alkynyl-Protected Ag15 Nanocluster with Atomic Precision: Structural Analysis and Electrocatalytic Performance toward CO2 Reduction.

We report the fabrication of homoleptic alkynyl-protected Ag15 (C≡C-t Bu)12 + (abbreviated as Ag15 ) nanocluster and its electrocatalytic properties toward CO2 reduction reaction. Crystal structure analysis reveals that Ag15 possesses a body-centered-cubic (BCC) structure with an Ag@Ag8 @Ag6 metal core configuration. Interestingly, we found that Ag15 can adsorb CO2 in the air and spontaneously self-assembled into one-dimensional linear material during the crystal growth process. Furthermore, Ag15 can convert CO2 into CO with a faradaic efficiency of ca. 95.0 % at -0.6 V and a maximal turnover frequency of 6.37 s-1 at -1.1 V along with excellent long-term stability. Finally, density functional theory (DFT) calculations disclosed that Ag15 (C≡C-t Bu)11 + with one alkynyl ligand stripping off from the intact cluster can expose the uncoordinated Ag atom as the catalytically active site for CO formation.

Multitemporal SAR Image Despeckling Based on a Scattering Covariance Matrix of Image Patch.

This paper presents a despeckling method for multitemporal images acquired by synthetic aperture radar (SAR) sensors. The proposed method uses a scattering covariance matrix of each image patch as the basic processing unit, which can exploit both the amplitude information of each pixel and the phase difference between any two pixels in a patch. The proposed filtering framework consists of four main steps: (1) a prefiltering result of each image is obtained by a nonlocal weighted average using only the information of the corresponding time phase; (2) an adaptively temporal linear filter is employed to further suppress the speckle; (3) the final output of each patch is obtained by a guided filter using both the original speckled data and the filtering result of step 3; and (4) an aggregation step is used to tackle the multiple estimations problem for each pixel. The despeckling experiments conducted on both simulated and real multitemporal SAR datasets reveal the pleasing performance of the proposed method in both suppressing speckle and retaining details, when compared with both advanced single-temporal and multitemporal SAR despeckling techniques.

Detection and prediction of land use/land cover change using spatiotemporal data fusion and the Cellular Automata-Markov model.

The detection and prediction of land use/land cover (LULC) change is crucial for guiding land resource management, planning, and sustainable development. In the view of seasonal rhythm and phenological effect, detection and prediction would benefit greatly from LULC maps of the same seasons for different years. However, due to frequent cloudiness contamination, it is difficult to obtain same-season LULC maps when using existing remote sensing images. This study utilized the spatiotemporal data fusion (STF) method to obtain summer Landsat-scale images in Hefei over the past 30 years. The Cellular Automata-Markov model was applied to simulate and predict future LULC maps. The results demonstrate the following: (1) the STF method can generate the same inter-annual interval summer Landsat-scale data for analyzing LULC change; (2) the fused data can improve the LULC detection and prediction accuracy by shortening the inter-annual interval, and also obtain LULC prediction results for a specific year; (3) the areas of cultivated land, water, and vegetation decreased by 33.14%, 2.03%, and 16.36%, respectively, and the area of construction land increased by 200.46% from 1987 to 2032. The urban expansion rate will reach its peak until 2020, and then slow down. The findings provide valuable information for urban planners to achieve sustainable development goals.

Ligand-controlled exposure of active sites on the Pd1Ag14 nanocluster surface to boost electrocatalytic CO2 reduction.

Advancing catalyst design requires meticulous control of nanocatalyst selectivity at the atomic level. Here, we synthesized two Pd1Ag14 nanoclusters: Pd1Ag14(PPh3)8(SPh(CF3)2)6 and Pd1Ag14(P(Ph-p-OMe)3)7(SPh)6, each with well-defined structures. Notably, in Pd1Ag14(P(Ph-p-OMe)3)7(SPh)6, the detachment of a phosphine ligand from the top silver atom facilitates the exposure of singular active sites. This exposure significantly enhances its selectivity for the electrocatalytic reduction of CO2 to CO, achieving a Faraday efficiency of 83.3% at -1.3 V, markedly surpassing the 28.1% performance at -1.2 V of Pd1Ag14(PPh3)8(SPh(CF3)2)6. This work underscores the impact of atomic-level structural manipulation on enhancing nanocatalyst performance.

Ubiquitination and degradation of plant helper NLR by the Ralstonia solanacearum effector RipV2 overcome tomato bacterial wilt resistance.

The Ralstonia solanacearum species complex causes bacterial wilt in a variety of crops. Tomato cultivar Hawaii 7996 is a widely used resistance resource; however, the resistance is evaded by virulent strains, with the underlying mechanisms still unknown. Here, we report that the phylotype Ⅱ strain ES5-1 can overcome Hawaii 7996 resistance. RipV2, a type Ⅲ effector specific to phylotype Ⅱ strains, is vital in overcoming tomato resistance. RipV2, which encodes an E3 ubiquitin ligase, suppresses immune responses and Toll/interleukin-1 receptor/resistance nucleotide-binding/leucine-rich repeat (NLR) (TNL)-mediated cell death. Tomato helper NLR N requirement gene 1 (NRG1), enhanced disease susceptibility 1 (EDS1), and senescence-associated gene 101b (SAG101b) are identified as RipV2 target proteins. RipV2 is essential for ES5-1 virulence in Hawaii 7996 but not in SlNRG1-silenced tomato, demonstrating SlNRG1 to be an RipV2 virulence target. Our results dissect the mechanisms of RipV2 in disrupting immunity and highlight the importance of converged immune components in conferring bacterial wilt resistance.

Modulation of bulk and surface electronic structures for oxygen evolution by Cr, P co-doped Co3S4.

Co3S4 was doped by Cr in the bulk phase and P on the surface to achieve a low overpotential of 257 mV and a long-term durability over 48 h during the oxygen evolution reaction. This was caused by high-valence metal Cr and non-metal P atom doping enhanced conductivity and optimized adsorption energy of intermediates.

Enhancing Output Signals of Sport Monitors Based on Triboelectric Porous PVDF Nanogenerators via Concaving Cells and Cell-Packing Structures.

Porous triboelectric polymer materials are widely used in portable sensors due to their lightweight and suitable mechanical performance, but their triboelectric properties need to be improved. Here, we propose a two-step strategy to concave the cell and cell-packing structure of triboelectric materials based on porous poly(vinylidene fluoride) (PVDF). The first step is to prepare triboelectric nanogenerators (TENGs) of PVDF with a concave cell-packing structure via oriented phase inversion. The second step is to concave the cells by radial and axial compression. The results reveal that the concavities in the cell structure at the radial direction and in the cell-packing structure at the axial direction improve the output signals of the porous PVDF TENG by ca. 150 and 110%, respectively. By contrast, the concaving in cell structure at the radial direction exerts a positive effect on triboelectric performance only when the radial compression strain is not bigger than 17.5%, especially when the cell wall is thin (ca. 0.85 µm). Meanwhile, the concavity-based strategy eliminates the irreversible deformation behavior of the porous PVDF material, enhancing its elasticity. The stability test shows that the sensor based on those materials is stable under 12,500 cycles, and the variance in the square derivation of output voltage is less than 1% during the cycle friction. Such stable and triboelectric-improved materials are assembled into sports-monitoring devices, providing an idea for the application of TENG in smart sensing.

The smallest superatom Au4(PPh3)4I2 with two free electrons: synthesis, structure analysis, and electrocatalytic conversion of CO2 to CO.

Atomically precise metal nanoclusters (NCs) have emerged as a new class of ultrasmall nanoparticles with both free valence electrons and precise structures (from the metal core to the organic ligand shell) and provide great opportunities to understand the relationship between their structures and properties, such as electrocatalytic CO2 reduction reaction (eCO2RR) performance, at the atomic level. Herein, we report the synthesis and the overall structure of the phosphine and iodine co-protected Au4(PPh3)4I2 (Au4) NC, which is the smallest multinuclear Au superatom with two free e- reported so far. Single-crystal X-ray diffraction reveals a tetrahedral Au4 core stabilized by four phosphines and two iodides. Interestingly, the Au4 NC exhibits much higher catalytic selectivity for CO (FECO: > 60%) at more positive potentials (from -0.6 to -0.7 V vs. RHE) than Au11(PPh3)7I3 (FECO: < 60%), a larger 8 e- superatom, and Au(i)PPh3Cl complex; whereas the hydrogen evolution reaction (HER) dominates the electrocatalysis when the potential becomes more negative (FEH2 of Au4 = 85.8% at -1.2 V vs. RHE). Structural and electronic analyses reveal that the Au4 tetrahedron becomes unstable at more negative reduction potentials, resulting in decomposition and aggregation, and consequently the decay in catalytic performance of Au based catalysts towards the eCO2RR.

Panax Notoginseng polysaccharide stabilized gel-like Pickering emulsions: Stability and mechanism.

In this work, the polysaccharide from Panax Notoginseng (SPNP), a traditional herb in China, was used as an outstanding Pickering stabilizer to fabricate Pickering emulsions. The SPNP was characterized to be a porous network structure with a rough surface surrounded by some nanoparticles. Rheological measurement of the obtained Pickering emulsions demonstrated the formation of emulsion gels. Moreover, the emulsions exhibited excellent storage (14 days), pH (1.0-11.0), ionic strength (0-500 mM), and temperature (4-50 °C) stabilities. In addition, the Pickering emulsions showed a freeze-thaw stability, which is beneficial in food, cosmetic or biomedical applications when they may require freezing for storage and melting before use. Confocal laser scanning microscope (CLSM) and cryo-scanning electron microscopy (cryo-SEM) results showed that SPNPs effectively adsorbed at the oil-water interface by forming a compact three-dimensional (3D) network structure and multilayer anchoring on the surface of the emulsion droplets, thus inhibiting the droplet coalescence and flocculation. This study provides a kind of Pickering emulsions applicable in food, biomedical and cosmetic industries.

Electron transfer and surface activity of NiCoP-wrapped MXene: cathodic catalysts for the oxygen reduction reaction.

NiCoP constructed on a conductive substrate can achieve efficient oxygen reduction reaction (ORR) catalytic activity. Herein, we report the in-situ growth of NiCoP on the surface of an MXene nanosheet (MXene@NiCoP). The MXene nanosheet accelerated the electron transfer and enhanced the surface activity of the NiCoP. Density functional theory calculations indicated that MXene@NiCoP possessed the advantages of a low overpotential and high OH* adsorption energy in the ORR process. MXene@NiCoP proved to be a highly active catalyst for the ORR with a half-wave potential of 0.71 V vs. RHE. The assembled single-chamber air-cathode microbial fuel cell obtained high electricity generation performance.

Monitoring of autoantibodies against CYP4Z1 in patients with colon, ovarian, or prostate cancer.

We have previously monitored the detection of autoantibodies (aAbs) directed against CYP4Z1 in the sera of breast and lung cancer patients. In the present study, the occurence of anti-CYP4Z1 aAbs in patients suffering from colon (n = 100), ovarian (n = 72), or prostate (n = 85) cancer was examined. Determination of aAbs was done using our previously established ELISA method. On average, the levels of anti-CYP4Z1 aAbs detected in sera from all cancer patients were not significantly higher than controls. No correlations were found with respect to gender or tumor stage. However, a subgroup of colon cancer patients with increased anti-CYP4Z1 aAb titers exhibited positive fecal occult blood test (FOBT) results and higher levels of both carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA). These results do not suggest that anti-CYP4Z1 aAbs have value as an independent biomarker for the detection of either colon, ovarian, or prostate cancer. However, they might be useful in combination with other biomarkers for the identification of a subset of colon cancers. Investigations involving a more powered sample size of this subgroup are needed to support this notion.

Effects of ligand tuning and core doping of atomically precise copper nanoclusters on CO2 electroreduction selectivity.

Atomically precise nanoclusters (NCs) provide opportunities for correlating the structure and electrocatalytic properties at atomic level. Herein, we report the single-atom doping effect and ligand effect on CO2 electroreduction (eCO2RR) by comparing monogold-doped Au1Cu24 and homocopper Cu25 NCs protected by triphenylphosphine or/and tris(4-fluorophenyl)phosphine. Catalytic results revealed that the electronic distribution of Cu25 NCs is enormously contracted by doping Au atoms, entitling it to exhibit the unique inhibition of hydrogen evolution reaction. And the inductive effect of ligand strongly favors the formation of formate in eCO2RR. Overall, this work will provide guidance for the rational design of the copper-based catalysts in the eCO2RR.

Online Semisupervised Active Classification for Multiview PolSAR Data.

Polarimetric synthetic aperture radar (PolSAR) data are sequentially acquired and have multiple views obtained from different feature extractors or multiple frequency bands. The fast and accurate classification of PolSAR data in dynamically changing environments is a critical and challenging task. Online learning can handle this task by learning a classifier incrementally from a stream of samples. In this article, we propose an online semisupervised active learning framework for multiview PolSAR data classification, called OSAM. First, a novel online active learning strategy is designed based on the relationships among multiple views and a randomized rule, which allows to only query the labels of some informative incoming samples. Then, in order to utilize both the incoming labeled and unlabeled samples to update the classifiers, a novel online semisupervised learning model is proposed based on co-regularized multiview learning and graph regularization. In addition, the proposed method can deal with the dynamic large-scale multifeature or multifrequency PolSAR data where not only the amount of data but also the number of classes gradually increases in the learning process. Moreover, the mistake bound of the proposed method is derived rigorously. Extensive experiments are conducted on real PolSAR data to evaluate the performance of our algorithm, and the results demonstrate the effectiveness of the proposed method.

Alkynyl and halogen co-protected (AuAg)44 nanoclusters: a comparative study on their optical absorbance, structure, and hydrogen evolution performance.

We report the synthesis, structure, and electrochemical hydrogen evolution reaction (HER) performance of two alkynyl and halogen coprotected AuAg alloy nanoclusters, namely Au24Ag20(tBuPh-CC)24Cl2 (NC 1 for short) and Au22Ag22(tBuCC)16Br3.28Cl2.72 (NC 2 for short). Single crystal X-ray structural analysis revealed that the two nanoclusters possess a rather similar core@shell@shell keplerate metal core configuration to M12@M20@M12 with the main difference in the outermost shell (Au12vs. Au10Ag2). Interestingly, such a subtle difference in the two-metal-atoms results in different optical absorbance features and drastically different HER performances. Both NCs have excellent long-term stability for the HER, but NC 1 possesses superior activity to NC 2, and density functional theory calculations disclosed that the binding energy of hydrogen to form the key *H intermediate for NC 1 is much lower and hence it adopts a more energetically feasible HER pathway.

Effect of Intrinsic Pore Distribution on Ion Diffusion Kinetics of Supercapacitor Electrode Surface.

The electrolyte ion diffusion kinetics have an important impact on electrochemical energy storage. Herein, we report the effect of the intrinsic porosity of NiCoP on accelerating electrolyte ion diffusion kinetics and accommodating volume expansion during the charge/discharge process. The pore distribution model of electrode/electrolyte was designed and optimized by the finite element simulation, demonstrating the visualization and quantitative analysis of the diffusion process of the electrode/electrolyte interface with intrinsic porous structure. When the pore area ratio reached 50.01%, the theoretical diffusion coefficient of 1.41 × 10-11 m2 s-1 would be conducive to the rapid diffusion of electrolytes. The electrode gained a specific capacity of 2805 F g-1 at a current density of 1 A g-1 based on the measured diffusion coefficient (1.79 × 10-10 m2 s-1), superior to 1.44-times that of the pristine electrode. The diffusion barriers of intrinsic porous NiCoP (3.19 eV) and conventional NiCoP (47.10 eV) were calculated by the density functional theory calculations, respectively. The intrinsic porous NiCoP was prepared by the hydrothermal treatment, annealing, and phosphating processes. The pore distribution was regulated by the concentration of NaHCO3 as a pore-forming additive. This work combines simulations and experiments to form a method to optimize diffusion kinetics at the electrode/electrolyte interface.