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Accurate monitoring of steel plate coating thickness is crucial in construction quality control and durability assessments. To address this challenge, this study introduces a terahertz time-domain reflection spectroscopy based on a BP neural network model to achieve a quantitative visualization characterization of coating thickness. The BP neural network eliminates the inherent dependence of terahertz reflection spectroscopy on the refractive index value in thickness calculation. This trained BP neural network model effectively establishes a functional relationship between signal feature parameters and the corresponding thickness values. Additionally, the proposed model can innovatively measure different coating materials' refractive indexes, revealing the corresponding values for the black paint, white paint, epoxy resin, and rubber as 2.212, 1.967, 1.924, and 2.185, respectively. The experimental results demonstrate the trained BP neural network model possesses remarkable accuracy in predicting coating thickness within the scanning area, achieving a precision level exceeding 96%. This method enables the visualization of coating thickness and the extraction of thickness characterization values. Furthermore, using the thickness imaging results as a reference, the method can accurately identify the thickness abnormalities across the scanning area, locating the position and size of potential defects such as internal scratches and foreign object defects. This innovative approach offers a superior means of monitoring and assessing the thickness distribution quality of the steel plate coating layer materials. [ABSTRACT FROM AUTHOR]

Calcium sulphoaluminate cement (CSA) has excellent anti-chloride penetration performance; therefore, a straight substitution of CSA for Portland cement to conduct marine engineering construction will significantly reduce the adverse effects of chloride ions (Cl−) on marine resource utilisation. Recent studies have focused on the chloride binding capacity, but relatively few investigations have examined the effects of Cl− on CSA. In this study, the effects of premixed Cl− on CSA properties were studied by setting time, hydration heat, linear shrinkage, and compressive strength. In addition, the mechanism of the chloride binding ability of CSA was analysed and explained using automatic potentiometric titration, X-ray diffraction, thermogravimetric analysis, and mercury intrusion porosimetry. The results showed that Cl− reduces the setting time and accelerates the hydration process of CSA cement. Cl− can improve the internal pore structure of materials at a water/binder ratio (w/b) of 0.5. The excellent chloride binding ability of CSA, owing to the formation of Kuzel's salts or Friedel's salts, was interpreted by the binding of Cl− and the synthesised hydration product, i.e., monosulphoaluminate (AFm). [ABSTRACT FROM AUTHOR]

Tetrahydrofurfuryl alcohol (THFA) is a kind of high value‐added compound in industry, which can be obtained from biomass chemical engineering. However, Synthesis of THFA under mild condition with green hydrogen donors remains a big challenge. In this article, a supported Ni catalyst derived from Ni−Al hydrotalcite‐like compounds (HTs) as precursors for the reduction of furfuryl alcohol (FA) into THFA with NaBH4 as reducing agent in water was first reported. As a result, Ni/Al2O3−HT exhibited high catalytic activity for the transformation, and THFA was achieved in 100 % yield at 60 °C for 60 min. Moreover, Ni/Al2O3−HT could be recycled at least seven times without the loss of its activity. Under optimized conditions, the reduction reaction of several furan and ketone compounds was investigated. A possible mechanism for the reduction of FA to afford THFA was also proposed. [ABSTRACT FROM AUTHOR]