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AbstractCorrosion has become an increasingly serious hazard in modern industry and daily life, which makes the development of efficient and environmentally friendly corrosion inhibitors (CIs) extremely critical. In this study, the corrosion inhibition performance of Michelia alba leaf extract (MAE) on Cu in 0.5 M H2SO4 was investigated by polarization curve test (Tafel), electrochemical impedance spectroscopy (EIS), scanning electron microscope (SEM), X-ray photoelectron spectroscopy (XPS) and theoretical calculations. The results of the EIS showed that the corrosion inhibition efficiency reached 94.72%. Tafel tests showed that the corrosion inhibition of Cu by MAE was reflected by a significant decrease in the corrosion current density and a significant increase in the charge transfer resistance. SEM showed that the number of corrosion pits on the Cu surface decreased and the depth of the pits became shallower with the addition of MAE. Theoretical calculations explained the adsorption mechanism between MAE and Cu surface, and the reduction of diffusion coefficient indicated that MAE could reduce the diffusion of corrosion ions. This study provides a theoretical basis for new green corrosion inhibitors. [ABSTRACT FROM AUTHOR]

In this work, a novel approach involving coating fine PEEK powder on prepreg is introduced to improve wedge peel strength and reduce interlaminar voids. CF/PEEK laminates with resin interleaving are in situ consolidated by laser-assisted fiber placement. The morphology of the powdered surface is obtained using an optical profilometer, and the surface roughness and volume of added resin are calculated accordingly. Interface and surface temperature are measured during the layup process. Thermal history indicates that very short bonding time is the dominating factor for voids and limited interlayer strength. Laminate porosity and microscopic features are characterized with an optical microscope. The porosity of resin-interleaved laminates decreases to 3.7%, while the resin content only increases by 4.5% in the meantime. This is because interlayer resin particles rapidly melt under laser heating and quickly fill the voids between layers. The wedge peel strength of resin-interleaved laminates can increase by 30.1% without a repass treatment. This could be attributed to the increase in resin intimate contact and reduction in interlayer voids. [ABSTRACT FROM AUTHOR]

This paper studied favorable low-temperature plasma (LTP) surface treatment modes for Carbon Fiber Reinforced Polymer (CFRP)/Al7075 single-lap joints using complex experimental methods and analyzed the failure modes of the joints. The surface physicochemical properties of CFRP after LTP surface treatment were characterized using scanning electron microscopy (SEM), contact angle tests, and X-ray photoelectron spectroscopy (XPS). The influence mechanism of LTP surface treatment on the bonding properties of CFRP/Al7075 single-lap Joint was studied. The results of the complex experiment and range analysis showed that the favorable LTP surface treatment parameters were a speed of 10 mm/s, a distance of 10 mm, and three repeat scans. At these parameters, the shear strength of the joints reached 30.76 MPa, a 102.8% improvement compared to the untreated group. The failure mode of the joints shifted from interface failure to substrate failure. After low-temperature plasma surface treatment with favorable parameters, the CFRP surface exhibited gully like textures, which enhanced the mechanical interlocking between the CFRP surface and the adhesive. Additionally, the surface free energy of CFRP significantly increased, reaching a maximum of 78.77 mJ/m2. XPS results demonstrated that the low-temperature plasma surface treatment led to a significant increase in the content of oxygen-containing functional groups, such as C-O, C=O, and O-C=O, on the CFRP surface. [ABSTRACT FROM AUTHOR]

The objective of this study is to extract amino acids from fish processing discards for the preparation of highly effective and degradable corrosion inhibitors. The composition of fish processing discards extract (FPDE) was characterized by HPLC and FTIR. The results showed that the main components of FPDE are amino acids and contain a large number of unsaturated functional groups. Electrochemical techniques (electrochemical impedance spectroscopy (EIS) and Tafel), surface analysis (XPS and AFM), and molecular dynamics simulations (MDS) were conducted to investigate the corrosion inhibition mechanism of FPDE for carbon steel in 1 mol/L HCl. As shown by electrochemical tests, FPDE exhibits mixed-type corrosion inhibition with a maximum inhibition efficiency of 93.3%. FPDE exhibits excellent corrosion inhibition properties on carbon steel surfaces by forming a high coverage film through chemisorption and physisorption. Indeed, the advantages of remarkable inhibition efficiency and facile extraction methods allow FPDE to become a promising corrosion inhibitor for practical applications. [ABSTRACT FROM AUTHOR]

This study utilized Schizochytrium extract (SE) to explore its protective effect on carbon steel in a 0.5 mol/L H2SO4 solution. The main functional groups of SE were investigated by Fourier infrared spectroscopy (FTIR) and x-ray photoelectron spectroscopy (XPS). The following conclusions were drawn from electrochemical tests: A corrosion inhibition efficiency of 88.7% was achieved when 1000 mg/L SE was added to a 0.5 mol/L H2SO4 solution. The corrosion inhibition efficiency of SE increased with the increase in corrosion inhibitor concentration but decreased with the increase in temperature. From the polarization curves, the primary function of SE is to prevent metal dissolution at the anode. The morphology of the corroded steel surface was investigated using atomic force microscopy (AFM) and scanning electron microscopy (SEM) techniques, and a smoother metal surface was observed when SE was added to the H2SO4 solution. Parameters such as dipole moments, Mullikan charges, equivalent surfaces (ESP) and binding energies of the four constituent molecules present in SE were calculated using quantum chemical calculations (QC) and molecular dynamics simulations (MS). It was found that the functional groups that play the role of adsorption are mainly carboxyl groups. In addition, Langmuir adsorption isotherms showed that the extracts could adhere to the metal surface and form a long-lasting protective film, thus effectively inhibiting corrosion. [ABSTRACT FROM AUTHOR]

In recent years, with the continuous development of the capital market and intelligent internet of things (IIoTs) technologies, investors have focused more on IIoTs enterprises' stocks. Since the stocks of IIoTs enterprises have the characteristics of heavy capital flows and high stock price volatility, the effective prediction of IIoTs stock price changes plays an extremely important role in improving investment returns and controlling investment risks. According to the above characteristics, our model takes stock trend fluctuations and time series indicator changes into consideration and comprehensively captures IIoTs stock information from both the temporal domain and the spatial domain. Specifically, the proposed model is a dual-view model that incorporates selected trading indicators to predict the closing prices of stocks. In the first view, an RNN model is designed to enlarge the receptive field of the model. In the second view, we introduce an attention mechanism to extract the influences of individual stock trends on the forecasting target. To verify the validity of this prediction method, we compare it with six other stock prediction methods. The results show that on the Ping An (601318) and IFLYTEK (002230) datasets, our method achieves the best results, that is, the lowest RMSE values. [ABSTRACT FROM AUTHOR]

Along with the IoT technology, the importance of indoor positioning is increasing, but the accuracy of the traditional fingerprint positioning algorithm is negatively affected by the complex indoor environment. This issue of low indoor spatial geolocation localization accuracy when the signal is collected away from the present stage occurs due to the signal instability of the iBeacon in the traditional fingerprint localization algorithm, which generates a variety of factors such as object blocking and reflection, multipath effect, etc., as well as the scarcity of reference fingerprint data points. In response, this study proposes an inverse distance-weighted optimization WKNN algorithm for indoor localization based on the GM(1,1) model. By implementing GM(1,1) model pre-process leveling, the original fingerprint library was reconstructed into a large-capacity fingerprint database using the inverse distance-weighted interpolation method. The local inverse distance-weighted interpolation was used for interpolation, combined with the WKNN algorithm to complete the coordinate solution in real time. This effectively solved the issue of low localization accuracy caused by the large fluctuation of the received signal strength (RSS) sampling measurement data and the existence of few reference fingerprint datapoints in the fingerprint database. The results show that this algorithm reduced the average positioning error by 5.9% compared with ordinary kriging (OK) interpolation leveling and reduced the average positioning error by 18.2% compared with the indoor spatial location accuracy of the original fingerprint database, which can effectively improve the positioning accuracy and provide technical support for indoor location and navigation services. [ABSTRACT FROM AUTHOR]

The shell of viviparid snail extract (SVSE) was prepared by a simple and environmentally friendly hydrolysis method and the corrosion inhibition of carbon steel (CS) by SVSE in 1 M HCl was investigated. HPLC and FTIR analysis showed that the main component of SVSE was a mixture of various amino acids. The results of electrochemical and surface analysis showed that SVSE is a hybrid corrosion inhibitor with a corrosion inhibition efficiency of 95.23%. In addition, the adsorption behavior of SVSE on CS surfaces was also investigated in depth by adsorption isotherms, quantum chemistry (QC) and molecular dynamics simulations (MDS). [ABSTRACT FROM AUTHOR]

Corrosion is the process of damaging materials, and corrosion of metallic materials frequently results in serious consequences. The addition of corrosion inhibitors is the most effective means of preventing metal corrosion. Until now, researchers have made unremitting efforts in the research of high-efficiency green corrosion inhibitors, and research on biomass corrosion inhibitors in a class of environmentally friendly corrosion inhibitors is currently quite promising. This work presents the classification of green biomass corrosion inhibitors in detail, including plant-based corrosion inhibitors, amino acid corrosion inhibitors, and biosurfactant corrosion inhibitors, based on the advantages of easy preparation, environmental friendliness, high corrosion inhibition efficiency, and a wide application range of biomass corrosion inhibitors. This work also introduces the preparation methods of biomass corrosion inhibitors, including hydrolysis, enzymatic digestion, the heating reflux method, and microwave extraction. In addition, the corrosion inhibition mechanisms of green biomass corrosion inhibitors, including physical adsorption, chemisorption, and film-forming adsorption, and evaluation methods of biomass corrosion inhibitors are also explicitly described. This study provides valuable insights into the development of green corrosion inhibitors. [ABSTRACT FROM AUTHOR]