Study on atmospheric corrosion behaviour and mechanism of Q235 steel after passivation

Q235 steel components have poor corrosion resistance and are susceptible to erosion by corrosive media, so they are generally passivated before being put into service. This paper investigates the corrosion behaviour and corrosion mechanism of passivated Q235 steel in atmospheric environments through macro and micro morphological characterisation and electrochemical simulation analysis

Microstructure and Tensile Properties of HPDC Mg–RE Alloys with Varying Y Additions

This paper is an invited submission to IJMC selected from presentations at the Light Metals Technology Conference (LMT2023) held July 10 to 12, 2023, in Melbourne, Australia, based upon the original presentation.Supplementary Information is available online at: https://link.springer.com/article/10.1007/s40962-024-01266-z#Sec17 .High-pressure die-casting Mg–2.6RE–xY (EW) alloys with Y contents between 0 and 3% (in wt%) were investigated for their microstructure and tensile properties. In the Y-containing alloy, the intermetallic phases at the grain boundaries consisted of skeletal Mg12RE phase, bulk Mg24Y5 phase and irregular Mg3Y phase, while {011} twins were observed in the Mg12RE phase. The yield strength was improved by Y addition at both room temperature and high temperatures. Compared with Y-free alloy, the yield strength of 3% Y alloy increased from 143.1 to 174.8 MPa and improved by 22.2% at room temperature, while it was increased from 72.2 to 104.6 MPa and enhanced by 44.9% at 300 °C. The area fraction of intermetallic phase increased dramatically from 14.5 to 18.4% with 3% Y addition. Second phase strengthening was the major contributor to the yield strength increase at ambient temperature. The increment of the area fraction of the high-thermally stable Mg–RE intermetallic phases with Y addition contributed to the consequent improvement in yield strength at high temperatures. At ambient temperature, the mechanism for the fracture of EW alloys was a ductile and quasi-cleavage fracture blend.Innovate UK (Project reference: 10004694)

Topological dilaton black holes

In four-dimensional spacetime, when the two-sphere of black hole event horizons is replaced by a two-dimensional hypersurface with zero or negative constant curvature, the black hole is referred to as a topological black hole. In this paper we present some exact topological black hole solutions in the Einstein-Maxwell-dilaton theory with a Liouville-type dilaton potential.Comment: 8 pages, Revtex, no figure

Pipeline offline trough cleaning technology

In the process of contemporary industrial pipeline installation, most pipelines must be cleaned before being put into use due to production and operation process requirements. This paper takes the offline trough cleaning of pipelines as the research object, and explores the evolution process of the metal microstructure under this cleaning method and the best cleaning conditions under the influence of the three factors of concentration, temperature and time

Exploring the impact of random telegraph noise-induced accuracy loss in Resistive RAM-based deep neural network

For Resistive RAM (RRAM)-based deep neural network, Random telegraph noise (RTN) causes accuracy loss during inference. In this work, we systematically investigated the impact of RTN on the complex deep neural networks (DNNs) with different datasets. By using 8 mainstream DNNs and 4 datasets, we explored the origin that caused the RTN-induced accuracy loss. Based on the understanding, for the first time, we proposed a new method to estimate the accuracy loss without going through time-consuming RTN simulation. The method was verified with other 10 DNN/dataset combinations that were not used for establishing the method. Finally, we discussed its potential adoption for the co-optimization of the DNN architecture and the RRAM technology, paving ways to RTN-induced accuracy loss mitigation for future neuromorphic hardware systems

Effect of Nd on the Microstructure and Mechanical Properties of Mg-La-Ce Alloys at Ambient and Elevated Temperatures

The microstructures and tensile properties were investigated for high-pressure die-cast Mg1.6La1.0Ce alloy with different Nd contents from 0 to 3 wt.%. The results showed that fine dendritic and segmented dendritic microstructures were observed in the as-cast alloys, but the eutectic morphology changed from lamellar for low Nd-containing alloys to continuous fibrous with dendritic α-Mg in eutectics for high Nd-containing alloys. The compositions of the eutectic phase were also transferred from Mg12(La, Ce) in the alloys without Nd to Mg12(La, Ce, Nd) in the alloys with Nd addition. When the concentration of Nd was greater than 2 wt.%, numerous nanoscale Mg-Nd intermetallic phases precipitated at the grain boundaries and eutectic area. The addition of Nd was also found to increase tensile strength significantly at ambient temperature and elevated temperatures. For the alloy without Nd, the yield strength and ultimate tensile strength (UTS) was 135.6 MPa and 189.9 MPa at ambient temperature and 56.3 MPa and 57.4 MPa at 300 °C, respectively. When adding 3 wt.% Nd, the yield strength increased to 161.9 MPa at ambient temperature and 75.4 MPa at 300 °C. The UTS increased to 181.9 MPa at ambient temperature and 90.4 MPa at 300 °C. The significant improvement in strength was attributed to the strengthening from the refined structure and the dispersion of second-phases of intermetallic compounds

Millennial atmospheric CO2 changes linked to ocean ventilation modes over past 150,000 years

Ice core measurements show diverse atmospheric CO2 variations—increasing, decreasing or remaining stable—during millennial-scale North Atlantic cold periods called stadials. The reasons for these contrasting trends remain elusive. Ventilation of carbon-rich deep oceans can profoundly affect atmospheric CO2, but its millennial-scale history is poorly constrained. Here we present a well-dated high-resolution deep Atlantic acidity record over the past 150,000 years, which reveals five hitherto undetected modes of stadial ocean ventilation with different consequences for deep-sea carbon storage and associated atmospheric CO2 changes. Our data provide observational evidence to show that strong and often volumetrically extensive Southern Ocean ventilation released substantial amounts of deep-sea carbon during stadials when atmospheric CO2 rose prominently. By contrast, other stadials were characterized by weak ventilation via both Southern Ocean and North Atlantic, which promoted respired carbon accumulation and thus curtailed or reversed deep-sea carbon losses, resulting in diminished rises or even declines in atmospheric CO2. Our findings demonstrate that millennial-scale changes in deep-sea carbon storage and atmospheric CO2 are modulated by multiple ocean ventilation modes through the interplay of the two polar regions, rather than by the Southern Ocean alone, which is critical for comprehensive understanding of past and future carbon cycle adjustments to climate change

Time-Dependent Variability in RRAM-based Analog Neuromorphic System for Pattern Recognition

For the first time, this work investigated the time dependent variability (TDV) in RRAMs and its interaction with the RRAM-based analog neuromorphic circuits for pattern recognition. It is found that even the circuits are well trained, the TDV effect can introduce non-negligible recognition accuracy drop during the operating condition. The impact of TDV on the neuromorphic circuits increases when higher resistances are used for the circuit implementation, challenging for the future low power operation. In addition, the impact of TDV cannot be suppressed by either scaling up with more synapses or increasing the response time and thus threatens both real-time and general-purpose applications with high accuracy requirements. Further study on different circuit configurations, operating conditions and training algorithms, provides guidelines for the practical hardware implementation

Distributed and asynchronous data collection in cognitive radio networks with fairness consideration

Abstract-As a promising communication paradigm, Cognitive Radio Networks (CRNs) have paved a road for Secondary Users (SUs) to opportunistically exploit unused licensed spectrum without causing unacceptable interference to Primary Users (PUs). In this paper, we study the distributed data collection problem for asynchronous CRNs, which has not been addressed before. We study the Proper Carrier-sensing Range (PCR) for SUs. By working with this PCR, an SU can successfully conduct data transmission without disturbing the activities of PUs and other SUs. Subsequently, based on the PCR, we propose an Asynchronous Distributed Data Collection (ADDC) algorithm with fairness consideration for CRNs. ADDC collects a snapshot of data to the base station in a distributed manner without the time synchronization requirement. The algorithm is scalable and more practical compared with centralized and synchronized algorithms. Through comprehensive theoretical analysis, we show that ADDC is order-optimal in terms of delay and capacity, as long as an SU has a positive probability to access the spectrum. Furthermore, we extend ADDC to deal with the continuous data collection issue, and analyze the delay and capacity performances of ADDC for continuous data collection, which are also proven to be order-optimal. Finally, extensive simulation results indicate that ADDC can effectively accomplish a data collection task and significantly reduce data collection delay