Corrosion Behavior of 10 ppi TAD3D/5A05Al Composite in a Chloride Environment.

This study utilizes desalted and denitrated treated aluminum dross (TAD) as a raw material, along with kaolin and 10 ppi (pores per inch) polyurethane foam as a template. The slurry is converted into an aluminum dross green body with a three-dimensional network structure using the impregnation method. A three-dimensional network aluminum dross ceramic framework (TAD3D) is created at a sintering temperature of 1350 °C. The liquid 5A05 aluminum alloy at a temperature of 950 °C infiltrates into the voids of TAD3D through pressureless infiltration, resulting in TAD3D/5A05Al composite material with an interpenetrating phase composite (IPC) structure. The corrosion behavior of TAD3D/5A05 composite material in sodium chloride solution was examined using the salt spray test (NSS) method. The study shows that the pores of the TAD3D framework, produced by sintering aluminum dross as raw material, are approximately 10 ppi. The bonding between TAD3D and 5A05Al interfaces is dense, with strong interfacial adhesion. The NSS corrosion time ranged from 24 h to 360 h, during which the composite material underwent pitting corrosion, crevice corrosion and self-healing processes. Results from Potentiodynamic Polarization (PDP) and Electrochemical Impedance Spectroscopy (EIS) indicate that, as corrosion progresses, the Ecorr of TAD3D/5A05Al decreases from -0.718 V to -0.786 V, and Icorr decreases from 0.398 µA·cm-2 to 0.141 µA·cm-2. A dense oxide film forms on the surface of the composite material, increasing the anodic Tafel slope and decreasing the cathodic Tafel slope, thus slowing down the rates of cathodic and anodic reactions. Factors such as lower interface corrosion resistance or a relatively weak passivation film at the interface do not significantly diminish the corrosion resistance of TAD3D and 5A05Al. The corrosion resistance of the composite material initially decreases and then increases.

Klobuchar, NeQuickG, BDGIM, GLONASS, IRI-2016, IRI-2012, IRI-Plas, NeQuick2, and GEMTEC Ionospheric Models: A Comparison in Total Electron Content and Positioning Domains.

Global navigation satellite systems (GNSS) provide a great data source about the ionosphere state. These data can be used for testing ionosphere models. We studied the performance of nine ionospheric models (Klobuchar, NeQuickG, BDGIM, GLONASS, IRI-2016, IRI-2012, IRI-Plas, NeQuick2, and GEMTEC) both in the total electron content (TEC) domain-i.e., how precise the models calculate TEC-and in the positioning error domain-i.e., how the models improve single frequency positioning. The whole data set covers 20 years (2000-2020) from 13 GNSS stations, but the main analysis involves data during 2014-2020 when calculations are available from all the models. We used single-frequency positioning without ionospheric correction and with correction via global ionospheric maps (IGSG) data as expected limits for errors. Improvements against noncorrected solution were as follows: GIM IGSG-22.0%, BDGIM-15.3%, NeQuick2-13.8%, GEMTEC, NeQuickG and IRI-2016-13.3%, Klobuchar-13.2%, IRI-2012-11.6%, IRI-Plas-8.0%, GLONASS-7.3%. TEC bias and mean absolute TEC errors for the models are as follows: GEMTEC--0.3 and 2.4 TECU, BDGIM--0.7 and 2.9 TECU, NeQuick2--1.2 and 3.5 TECU, IRI-2012--1.5 and 3.2 TECU, NeQuickG--1.5 and 3.5 TECU, IRI-2016--1.8 and 3.2 TECU, Klobuchar-1.2 and 4.9 TECU, GLONASS--1.9 and 4.8 TECU, and IRI-Plas-3.1 and 4.2 TECU. While TEC and positioning domains differ, new-generation operational models (BDGIM and NeQuickG) could overperform or at least be at the same level as classical empirical models.

Effect of Silicon Source (Fly Ash, Silica Dust, Gangue) on the Preparation of Porous Mullite Ceramics from Aluminum Dross.

Aluminum dross (AD) is a waste product produced during aluminum processing and can be used to prepare mullite ceramic materials. However, the research on the preparation of mullite porous ceramics entirely from solid waste is still in the development stage. In this paper, porous mullite ceramics were successfully fabricated using a solid-phase sintering process with AD and different silicon sources (fly ash, silica dust, and gangue) as raw materials. The bulk density, apparent porosity, and compressive strength of the specimens were obtained, and the phase compositions and microstructures of the sintered specimens were measured using XRD and SEM, respectively. The average activation energy of the phase transition of fly ash, silica dust, and gangue as silicon sources were 984 kJ/mol, 1113 kJ/mol, and 741 kJ/mol, respectively. The microstructures of the mullite in the specimens were prisms, random aggregates, and needle-shaped, respectively. The formation of needle-shaped mullite combined with the substrate enhanced the mechanical strength of the porous mullite ceramics. The apparent porosity, density, and compressive strength of the specimens with gangue as the silicon source were 33.13%, 1.98 g/cm3, and 147.84 MPa, respectively, when sintered at 1300 °C for 2 h.

CNN-Based Heart Sound Classification with an Imbalance-Compensating Weighted Loss Function.

Heart sound auscultation is an effective method for early-stage diagnosis of heart disease. The application of deep neural networks is gaining increasing attention in automated heart sound classification. This paper proposes deep Convolutional Neural Networks (CNNs) to classify normal/abnormal heart sounds, which takes two-dimensional Mel-scale features as input, including Mel frequency cepstral coefficients (MFCCs) and the Log Mel spectrum. We employ two weighted loss functions during the training to mitigate the class imbalance issue. The model was developed on the public PhysioNet/Computing in Cardiology Challenge (CinC) 2016 heart sound database. On the considered test set, the proposed model with Log Mel spectrum as features achieves an Unweighted Average Recall (UAR) of 89.6%, with sensitivity and specificity being 89.5% and 89.7% respectively. This work proposes a CNN-based model to enable automated heart sound classification, which can provide auxiliary assistance for heart auscultation and has the potential to screen for heart pathologies in clinical applications at a relatively low cost.

Hydrolysis Behavior and Kinetics of AlN in Aluminum Dross during the Hydrometallurgical Process.

In this study, the hydrolysis behavior and kinetics of AlN in aluminum dross (AD) were investigated in order to better identify the steps controlling the AlN hydrolysis reaction and the factors influencing the hydrolysis rate to enhance the removal efficiency of AlN. The hydrolysis behavior of AlN, including AlN content, phase composition, chemical composition, microstructure, and element distribution, was determined by a leaching test, X-ray diffraction, X-ray fluorescence, scanning electron microscopy, and energy dispersive spectroscopy, respectively. The results showed that increasing the leaching liquid-solid ratio as well as the temperature was helpful for the removal efficiency of AlN. When the liquid--solid ratio was 4:1, temperature was 90 °C, and leaching time was 300 min, the removal efficiency of AlN reached 89.05%. The kinetics were described using the unreacted core model, and when the temperature was 30-40, 50-70, and 80-90 °C, the hydrolysis reaction rate of AlN was controlled by boundary layer diffusion, chemical reaction control, and product layer diffusion control, respectively.

Waste to Wealth Strategy: Preparation and Properties of Lightweight Al2O3-SiO2-Rich Castables Using Aluminum Dross Waste.

Aluminum dross is a well-known industrial waste generated in the aluminium industry, and its recycling and reuse is still a worldwide issue. Herein, aluminum dross waste (ADW) was recycled to progressively replace the aggregate fraction of clay at 70, 75, 80, 85, and 90 wt% for the fabrication of Al2O3-SiO2-rich porous castable refractories. Their physical properties and mechanical behavior were assessed by the measurement of linear shrinkage rate, bulk density, apparent porosity, cold crushing strength, and thermal conductivity. The microstructure and phase evolutions were analyzed via scanning electron microscopy (SEM) and X-ray diffraction (XRD). The incorporation of 85 wt% of ADW allowed the development of a waste-containing conventional refractory castable with improved properties as compared to those of the other samples. The sustainable refractory castable exhibited decent thermal conductivity and physical and mechanical characteristics, and is suitable for application as reheating furnace lining. It is a "green" practice to partially replace the traditional raw materials with industrial waste in the manufacture of conventional refractory castables and provides environmental and economic benefits.

Sub-Auroral and Mid-Latitude GNSS ROTI Performance during Solar Cycle 24 Geomagnetic Disturbed Periods: Towards Storm's Early Sensing.

Geomagnetic storms-triggered by the interaction between Earth's magnetosphere and interplanetary magnetic field, driven by solar activity-are important for many Earth-bound aspects of life. Serious events may impact the electroenergetic infrastructure, but even weaker storms generate noticeable irregularities in the density of ionospheric plasma. Ionosphere electron density gradients interact with electromagnetic radiation in the radiofrequency domain, affecting sub- and trans-ionospheric transmissions. The main objective of the manuscript is to find key features of the storm-induced plasma density behaviour irregularities in regard to the event's magnitude and general geomagnetic conditions. We also aim to set the foundations for the mid-latitude ionospheric plasma density now-casting irregularities. In the manuscript, we calculate the GPS+GLONASS-derived rate of TEC (total electron content) index (ROTI) for the meridional sector of 10-20∘ E, covering the latitudes between 40 and 70∘ N. Such an approach reveals equatorward spread of the auroral TEC irregularities reaching down to mid-latitudes. We have assessed the ROTI performance for 57 moderate-to-severe storms that occurred during solar cycle 24 and analyzed their behaviors in regard to the geomagnetic conditions (described by Kp, Dst, AE, Sym-H and PC indices).

Machine Learning-Driven Drug Discovery: Prediction of Structure-Cytotoxicity Correlation Leads to Identification of Potential Anti-Leukemia Compounds.

In vitro cytotoxicity screening is a crucial step of anticancer drug discovery. The application of deep learning methodology is gaining increasing attentions in processing drug screening data and studying anticancer mechanisms of chemical compounds. In this work, we explored the utilization of convolutional neural network in modeling the anticancer efficacy of small molecules. In particular, we presented a VGG19 model trained on 2D structural formulae to predict the growth-inhibitory effects of compounds against leukemia cell line CCRF-CEM, without any use of chemical descriptors. The model achieved a normalized RMSE of 15.76% on predicting growth inhibition and a Pearson Correlation Coefficient of 0.72 between predicted and experimental data, demonstrating a strong predictive power in this task. Furthermore, we implemented the Layer-wise Relevance Propagation technique to interpret the network and visualize the chemical groups predicted by the model that contribute to toxicity with human-readable representations.Clinical relevance-This work predicts the cytotoxicity of chemical compounds against human leukemic lymphoblast CCRF-CEM cell lines on a continuous scale, which only requires 2D images of the structural formulae of the compounds as inputs. Knowledge in the structure-toxicity relationship of small molecules will potentially increase the hit rate of primary drug screening assays.

A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation.

Using the Global Navigation Satellite System (GNSS), it is difficult to provide continuous and reliable position service for vehicle navigation in complex urban environments, due to the natural vulnerability of the GNSS signal. With the rapid development of the sensor technology and the reduction in their costs, the positioning performance of GNSS is expected to be significantly improved by fusing multi-sensors. In order to improve the continuity and reliability of the vehicle navigation system, we proposed a multi-sensor tight fusion (MTF) method by combining the inertial navigation system (INS), odometer, and barometric altimeter with the GNSS technique. Different fusion strategies were presented in the open-sky, insufficient satellite, and satellite outage environments to check the performance improvement of the proposed method. The simulation and real-device tests demonstrate that in the open-sky context, the error of sensors can be estimated correctly. This is useful for sensor noise compensation and position accuracy improvement, when GNSS is unavailable. In the insufficient satellite context (6 min), with the help of the barometric altimeter and a clock model, the accuracy of the method can be close to that in the open-sky context. In the satellite outage context, the error divergence of the MTF is obviously slower than the traditional GNSS/INS tightly coupled integration, as seen by odometer and barometric altimeter assisting.

Thermo-Mechanical Coupling Analyses for Al Alloy Brake Discs with Al2O3-SiC(3D)/Al Alloy Composite Wear-Resisting Surface Layer for High-Speed Trains.

In the present work, a theoretical model of three-dimensional (3D) transient temperature field for Al alloy brake discs with Al2O3-SiC(3D)/Al alloy wear-resisting surface layer was established. 3D transient thermo-stress coupling finite element (FE) and computational fluid dynamic (CFD) models of the brake discs was presented. The variation regularities of transient temperature and internal temperature gradient of the brake discs under different emergency braking conditions were obtained. The effects of initial braking velocity (IBV) and thickness of Al2O3-SiC(3D)/Al alloy composite wear-resisting layer on the maximum friction temperature evolution of the disc were discussed. The results indicated the lower temperature and thermal stress distributed uniformly on the wear-resisting surface, which was dominated by high conductivity and cooling ability of the Al alloy brake disc. The maximum friction temperature was not obviously affected by the thickness of the wear-resisting layer. The maximum friction temperature of the brake discs increased with the increase of the IBV, the maximum friction temperature and thermal stress of the brake discs is about 517 °C and 192 MPa at IBV = 97 m/s considering air cooling, respectively. The lower thermal stress and fewer thermal cracks are produced during the braking process, which relatively decrease the damage. The friction behavior of the tribo-couple predicted using FE method correlated well with the experimental results obtained by sub-scale testing.

The First Result of Relative Positioning and Velocity Estimation Based on CAPS.

The Chinese Area Positioning System (CAPS) is a new positioning system developed by the Chinese Academy of Sciences based on the communication satellites in geosynchronous orbit. The CAPS has been regarded as a pilot system to test the new technology for the design, construction and update of the BeiDou Navigation Satellite System (BDS). The system structure of CAPS, including the space, ground control station and user segments, is almost like the traditional Global Navigation Satellite Systems (GNSSs), but with the clock on the ground, the navigation signal in C waveband, and different principles of operation. The major difference is that the CAPS navigation signal is first generated at the ground control station, before being transmitted to the satellite in orbit and finally forwarded by the communication satellite transponder to the user. This design moves the clock from the satellite in orbit to the ground. The clock error can therefore be easily controlled and mitigated to improve the positioning accuracy. This paper will present the performance of CAPS-based relative positioning and velocity estimation as assessed in Beijing, China. The numerical results show that, (1) the accuracies of relative positioning, using only code measurements, are 1.25 and 1.8 m in the horizontal and vertical components, respectively; (2) meanwhile, they are about 2.83 and 3.15 cm in static mode and 6.31 and 10.78 cm in kinematic mode, respectively, when using the carrier-phase measurements with ambiguities fixed; and (3) the accuracy of the velocity estimation is about 0.04 and 0.11 m/s in static and kinematic modes, respectively. These results indicate the potential application of CAPS for high-precision positioning and velocity estimation and the availability of a new navigation mode based on communication satellites.

Smart Device-Supported BDS/GNSS Real-Time Kinematic Positioning for Sub-Meter-Level Accuracy in Urban Location-Based Services.

Using mobile smart devices to provide urban location-based services (LBS) with sub-meter-level accuracy (around 0.5 m) is a major application field for future global navigation satellite system (GNSS) development. Real-time kinematic (RTK) positioning, which is a widely used GNSS-based positioning approach, can improve the accuracy from about 10-20 m (achieved by the standard positioning services) to about 3-5 cm based on the geodetic receivers. In using the smart devices to achieve positioning with sub-meter-level accuracy, a feasible solution of combining the low-cost GNSS module and the smart device is proposed in this work and a user-side GNSS RTK positioning software was developed from scratch based on the Android platform. Its real-time positioning performance was validated by BeiDou Navigation Satellite System/Global Positioning System (BDS/GPS) combined RTK positioning under the conditions of a static and kinematic (the velocity of the rover was 50-80 km/h) mode in a real urban environment with a SAMSUNG Galaxy A7 smartphone. The results show that the fixed-rates of ambiguity resolution (the proportion of epochs of ambiguities fixed) for BDS/GPS combined RTK in the static and kinematic tests were about 97% and 90%, respectively, and the average positioning accuracies (RMS) were better than 0.15 m (horizontal) and 0.25 m (vertical) for the static test, and 0.30 m (horizontal) and 0.45 m (vertical) for the kinematic test.

Multifunctional graphene sensors for magnetic and hydrogen detection.

Multifunctional graphene magnetic/hydrogen sensors are constructed for the first time through a simple microfabrication process. The as-fabricated graphene sensor may act as excellent Hall magnetic detector, demonstrating small linearity error within 2% and high magnetic resolution up to 7 mG/Hz(0.5). Meanwhile the same graphene sensor is also demonstrated as high-performance hydrogen sensor with high gas response, excellent linearity, and great repeatability and selectivity. In particular, the graphene sensor exhibits high hydrogen response up to 32.5% when exposed to 1000 ppm hydrogen, outperforming most graphene-based hydrogen sensors. In addition the hydrogen-sensing mechanism of Pd-decorated graphene is systematically explored through investigating its transfer characteristics during gas detection. Our work demonstrates that graphene is a terrific material for multifunctional sensing, which may in principle reduce the complexity of manufacturing process, lower the number of sensors required in the sensing systems, and potentially derive new and more powerful functions.

Graphene/Si CMOS hybrid hall integrated circuits.

Graphene/silicon CMOS hybrid integrated circuits (ICs) should provide powerful functions which combines the ultra-high carrier mobility of graphene and the sophisticated functions of silicon CMOS ICs. But it is difficult to integrate these two kinds of heterogeneous devices on a single chip. In this work a low temperature process is developed for integrating graphene devices onto silicon CMOS ICs for the first time, and a high performance graphene/CMOS hybrid Hall IC is demonstrated. Signal amplifying/process ICs are manufactured via commercial 0.18 um silicon CMOS technology, and graphene Hall elements (GHEs) are fabricated on top of the passivation layer of the CMOS chip via a low-temperature micro-fabrication process. The sensitivity of the GHE on CMOS chip is further improved by integrating the GHE with the CMOS amplifier on the Si chip. This work not only paves the way to fabricate graphene/Si CMOS Hall ICs with much higher performance than that of conventional Hall ICs, but also provides a general method for scalable integration of graphene devices with silicon CMOS ICs via a low-temperature process.

High-mobility graphene on liquid p-block elements by ultra-low-loss CVD growth.

The high-quality and low-cost of the graphene preparation method decide whether graphene is put into the applications finally. Enormous efforts have been devoted to understand and optimize the CVD process of graphene over various d-block transition metals (e.g. Cu, Ni and Pt). Here we report the growth of uniform high-quality single-layer, single-crystalline graphene flakes and their continuous films over p-block elements (e.g. Ga) liquid films using ambient-pressure chemical vapor deposition. The graphene shows high crystalline quality with electron mobility reaching levels as high as 7400 cm(2) V(-1) s(-1) under ambient conditions. Our employed growth strategy is ultra-low-loss. Only trace amounts of Ga are consumed in the production and transfer of the graphene and expensive film deposition or vacuum systems are not needed. We believe that our research will open up new territory in the field of graphene growth and thus promote its practical application.