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D-p-hydroxyphenylglycine (D-HPG) is an important intermediate for the synthesis of sweeteners and drugs. An innovative continuous chromatographic process was developed to recover D-HPG from crystallization mother liquor, with the aim of reducing the process cost and improving the quality of D-HPG. The thickening properties of different nanofiltration membranes on mother liquor were investigated by pre-treatment test, and the Applexion NF200 nanofiltration membrane was selected to enrich D-HPG. The separation properties of different resins were analyzed by single column experiment, and the separation degree of Applexion XA945 resin to D-HPG and ammonium sulfate could reach 16. Based on the results, the way of sequential simulated moving bed separation was further studied. The results showed that after separation by the sequential simulated moving bed, the average purity of D-HPG in feeding was increased from 42.2% to 96.3%, and the average yield was 91%. The continuous chromatographic system is a promising method for the recovery of D-HPG from crystallization mother liquor. Compared with the traditional process, the new process not only ensures the total yield of D-HPG, but also greatly reduces the process cost and improves the product quality.

To apply anti-marine biofouling agents in the fields of marine engineering and ships, not only the antifouling effectiveness, but also their impact on the corrosion safety of engineering structural materials should be seriously considered and evaluated. Effects of the addition of an agent that would be applied to the anti-marine biofouling of the ship’s sea-access structure on the corrosion behavior and rate of two representative ship metal structural materials, TA24 titanium alloy and 907A alloy steel, in seawater environment were studied. From the comprehensive analysis and evaluation of corrosion morphology, weight loss rate, open circuit potential, polarization curve and alternating-current impedance, it could be obtained that the agent had little effect on the corrosion behavior of these two materials and would not accelerate the corrosion significantly.

A closed gas-up reactor was selected for self-cultured Chlorella pyrenoidosa, the ventilation of carbon dioxide from carbon source obtained by univariate optimization was 2%, and the sodium nitrate of nitrogen source was 10 g/L. More suitable medium components were obtained through the uniform design of Chlorella pyrenoidosa culture medium: K2HPO4 of 0.6 g/L, MgSO4 of 0.2 g/L, NaNO3 of 11 g/L, K2SO4 of 0.8 g/L, ammonium ferric citrate of 0.006 g/L, CaCl2 of 0.05 g/L, vitaminB1 of 0.11 g/L, EDTANa2 of 0.01 g/L, Na2WO4 of 0.08×10–3 g/L, NiCl2 of 0.02×10–3 g/L; In the experiment, a suitable light source with intermediate white light and surrounding colored light was used, and the oxygen was maintained at about 20% with an oxygen scavenger, under which 8.648 g/L dry cell was obtained finally. The protein content of Chlorella pyrenoidosa is as high as 58 g/100 g, and the amino acid and mineral elements of Chlorella pyrenoidosa is also rich by analysis. We studied the replacement of wormwood powder with Chlorella pyrenoidosa, and produced Chlorella pyrenoidosa qingtuan.

The quality of molten iron not only has a significant impact on the strength, toughness, smelting cost and service life of cast iron but also directly affects the satisfaction of users. The establishment of timely and accurate blast furnace molten iron quality prediction models is of great significance for the improvement of the production efficiency of blast furnace. In this paper, Si, S and P content in molten iron is taken as the important index to measure the quality of molten iron, and the 989 sets of production data from a No.1 blast furnace from August to October 2020 are selected as the experimental data source, predicting the quality of molten iron by the I-GWO-CNN-BiLSTM model. First of all, on the basis of the traditional data processing method, the missing data values are classified into correlation data, temporal data, periodic data and manual input data, and random forest, the Lagrangian interpolation method, the KNN algorithm and the SVD algorithm are used to complete them, so as to obtain a more practical data set. Secondly, CNN and BiLSTM models are integrated and I-GWO optimized hyperparameters are used to form the I-GWO-CNN-BiLSTM model, which is used to predict Si, S and P content in molten iron. Then, it is concluded that using the I-GWO-CNN-BiLSTM model to predict the molten iron quality can obtain high prediction accuracy, which can provide data support for the regulation of blast furnace parameters. Finally, the MCMC algorithm is used to analyze the influence of the input variables on the Si, S and P content in molten iron, which helps the steel staff control the quality of molten iron in a timely manner, which is conducive to the smooth running of blast furnace production. [ABSTRACT FROM AUTHOR]

Blast furnace ironmaking plays an important role in modern industry and the development of the economy. A reasonable ingredient scheme is crucial for energy efficiency and emission reduction in blast furnace production. Determining the right blast furnace ingredients is a complicated process; therefore, this study examines the optimization of the ingredient ratio. In this paper a model of the blast furnace ingredients is established by considering cost of per ton iron, CO2 emissions, and the theoretical coke ratio as the objective functions; ingredient parameters, process parameters, main and by-product parameters as variables; and the blast furnace smelting theory and equilibrium equation as constraints. Then, the model is solved by using an improved grey wolf optimization algorithm and an improved multi-objective grey wolf optimization algorithm. Using the data collected from the steel mill, the conclusion is that multi-objective optimization can consider the indexes of each target, so that the values of all the targets are excellent; we also compared the multi-objective solution results with the original production scheme of the steel mill, and we found that using the blast furnace ingredient scheme optimized in this study can reduce the cost of iron per ton, CO2 emissions per ton, and the theoretical coke ratio in blast furnace production by 350 CNY/t, 1000 kg/t, and 20 kg/t, respectively, compared with the original production plan. Thus, steel mill decision makers can choose the blast furnace ingredients according to different business strategies and the actual needs of steel mills can be better met. [ABSTRACT FROM AUTHOR]

Based on ground monitoring data, we explored the spatiotemporal characteristics and drivers of PM 2.5 in the Yangtze River Economic Belt (YREB) in 2018 using spatial autocorrelation analysis and geodetector modeling methods. The results showed that:① the PM 2.5 concentration in the YREB posed the obvious characteristics of low values in summer and high values in winter, seasonal variation in spring and autumn, monthly U-shaped variation, and daily pulse variation. The low value area was mainly concentrated in the south bank of the upper reaches, whereas the high value area was located in the north of the middle-lower reaches of the YREB. ② PM 2.5 pollution in the YREB had a stable positive spatial correlation, and the local association pattern showed a significant HH and LL spatial convergence. ③ The spatial correlation of PM 2.5 in the YREB decreased with the increase in geographical distance, and its spatial autocorrelation threshold was approximately 870 km, within which the spatial agglomeration of PM 2.5 pollution was strong. ④ The influences of natural and anthropogenic factors on PM 2.5 had significant spatial differences. Altitude, relief, and population density were the high impact factors of PM 2.5 pollution in the YREB. The interaction of factors had a far greater explanatory power on PM 2.5 pollution than that of single factors. The dominant interaction factor was industrial structure ∩ altitude, which reflected the complexity of the drivers of air pollution in the YREB.

A practical and eco-friendly strategy for the radical-mediated decarboxylative [3 + 2] and [4 + 2] annulation of enynals and γ,σ-unsaturated N -(acyloxy)phthalimides through the photoactivation of an electron donor-acceptor (EDA) complex has been developed. A wide range of primary, secondary, and tertiary alkyl N -hydroxyphthalimide (NHP) esters can be used as suitable substrates for the synthesis of fused ketones without any transition-metal catalysts or oxidants. This protocol features a broad substrate scope, excellent selectivity, and clean reaction conditions.