Effect of Al/Ni Ratio on the Microstructure and Properties of Nickel-Aluminum Bronze Alloys.

To study the effect of aluminum and nickel elements on the microstructures and properties of the nickel-aluminum bronze (NAB) alloy, four kinds of alloys with different compositions, ZCuAl7-7-4-2, ZCuAl8-6-4-2, ZCuAl9-5-4-2, and ZCuAl10-4-4-2, are prepared by vacuum-melting technology. The effects of different Al/Ni ratios on the microstructures of NAB are investigated using a metalloscope, scanning electron microscopy, transmission electron microscopy, and XPS analysis. The mechanical property is evaluated with microhardness testing and tensile mechanical testing. The corrosion resistance is evaluated using mass-loss testing, electrochemical testing, and corrosion-product characterization. The results show that with the increase of the Al/Ni ratio, the content of precipitated phases increases, while ß' and hard κ, which have a different morphology, appear. As the Al/Ni ratio rises from 1 to 2.5, the hardness increases from 104 HV to 202 HV, and the tensile strength increases by 394 MPa from 356 MPa to 751 MPa, but the elongation decreases substantially from 50.50% to 11.00%. The best corrosion resistance is shown on ZCuAl7-7-4-2, with a corrosion rate of 0.00267 mm/a after 30 d of static immersion corrosion in 3.5 wt.% NaCl solution. Through electrochemical testing and corrosion-product characterization, it is found that ZCuAl7-7-4-2 has the largest polarization resistance Rp, and the selective corrosion of the surface is mild.

Enhanced post-quantum key escrow system for supervised data conflict of interest based on consortium blockchain.

Consortium blockchains offer privacy for members while allowing supervision peers access to on-chain data under certain circumstances. However, current key escrow schemes rely on vulnerable traditional asymmetric encryption/decryption algorithms. To address this issue, we have designed and implemented an enhanced post-quantum key escrow system for consortium blockchains. Our system integrates NIST post-quantum public-key encryption/KEM algorithms and various post-quantum cryptographic tools to provide a fine-grained, single-point-of-dishonest-resistant, collusion-proof and privacy-preserving solution. We also offer chaincodes, related APIs, and invoking command lines for development. Finally, we perform detailed security analysis and performance evaluation, including the consumed time of chaincode execution and the needed on-chain storage space, and we also highlight the security and performance of related post-quantum KEM algorithms on consortium blockchain.

Estimation of the Mixed Layer Depth in the Indian Ocean from Surface Parameters: A Clustering-Neural Network Method.

The effective estimation of mixed-layer depth (MLD) plays a significant role in the study of ocean dynamics and global climate change. However, the methods of estimating MLD still have limitations due to the sparse resolution of the observed data. In this study, a hybrid estimation method that combines the K-means clustering algorithm and an artificial neural network (ANN) model was developed using sea-surface parameter data in the Indian Ocean as a case study. The oceanic datasets from January 2012 to December 2019 were obtained via satellite observations, Argo in situ data, and reanalysis data. These datasets were unified to the same spatial and temporal resolution (1° × 1°, monthly). Based on the processed datasets, the K-means classifier was applied to divide the Indian Ocean into four regions with different characteristics. For ANN training and testing in each region, the gridded data of 84 months were used for training, and 12-month data were used for testing. The ANN results show that the optimized NN architecture comprises five input variables, one output variable, and four hidden layers, each of which has 40 neurons. Compared with the multiple linear regression model (MLR) with a root-mean-square error (RMSE) of 5.2248 m and the HYbrid-Coordinate Ocean Model (HYCOM) with an RMSE of 4.8422 m, the RMSE of the model proposed in this study was reduced by 27% and 22%, respectively. Three typical regions with high variability in their MLDs were selected to further evaluate the performance of the ANN model. Our results showed that the model could reveal the seasonal variation trend in each of the selected regions, but the estimation accuracy showed room for improvement. Furthermore, a correlation analysis between the MLD and input variables showed that the surface temperature and salinity were the main influencing factors of the model. The results of this study suggest that the pre-clustering ANN method proposed could be used to estimate and analyze the MLD in the Indian Ocean. Moreover, this method can be further expanded to estimate other internal parameters for typical ocean regions and to provide effective technical support for ocean researchers when studying the variability of these parameters.

Theranostic iridium(III) complexes as one- and two-photon phosphorescent trackers to monitor autophagic lysosomes.

During autophagy, the intracellular components are captured in autophagosomes and delivered to lysosomes for degradation and recycling. Changes in lysosomal trafficking and contents are key events in the regulation of autophagy, which has been implicated in many physiological and pathological processes. In this work, two iridium(III) complexes (LysoIr1 and LysoIr2) are developed as theranostic agents to monitor autophagic lysosomes. These complexes display lysosome-activated phosphorescence and can specifically label lysosomes with high photostability. Simultaneously, they can induce autophagy potently without initiating an apoptosis response. We demonstrate that LysoIr2 can effectively implement two functions, namely autophagy induction and lysosomal tracking, in the visualization of autophagosomal-lysosomal fusion. More importantly, they display strong two-photon excited fluorescence (TPEF), which is favorable for live cell imaging and in vivo applications.

A density gradient of basic fibroblast growth factor guides directional migration of vascular smooth muscle cells.

The migration of vascular smooth muscle cells (VSMCs) is an important process in many physiological events. It is of paramount importance to control the migration rate and direction of VSMCs by biomaterials. In this paper, a density gradient of basic fibroblast growth factor (bFGF) was fabricated using an injection method and the bio-conjugation between heparin and bFGF. The density of bFGF gradually increased with a slope of 17 ng/cm(2)/mm. Adhesion and migration of VSMCs were studied on the bFGF gradient. The VSMCs exhibited preferential orientation and an enhanced directional migration behavior on the gradient surface. Up to 70% cells migrated towards the region with a higher density of bFGF on the gradient. However, the bFGF gradient had no effect on the cell migration rate.

One-step preparation of graphene-supported anatase TiO2 with exposed {001} facets and mechanism of enhanced photocatalytic properties.

Anatase TiO2 nanosheets supported on reduced graphene oxide (RGO) were synthesized via a one-step, solvothermal method. During the solvothermal step, graphene oxide (GO) was reduced to RGO, and, subsequently, anatase TiO2 with 73.7% exposed {001} facets was grown in situ on the surfaces of the RGO nanosheets. Compared with pure TiO2, the RGO/TiO2 hybrid nanocomposite had improved photoactivity as a result of effective photoinduced electron transfer from TiO2 to the RGO acceptor through interfacial interactions. Trapping tests showed that the oxidation of dye molecules proceeded for about 22% through the reaction with (•)OH radicals, and the remaining 78% occurred via direct interactions with holes. The holes left in TiO2 crystals were the main reason for the enhanced photocatalytic properties of the RGO/TiO2 composite. This paper not only reports the fabrication of highly active photocatalysts but also gives deeper insight into the photocatalytic mechanism of carbon/TiO2 composites.