浅谈氯碱氢的一种深度脱水工艺

概述了氢的主要工业生产方法和实际应用,详细介绍了氯碱氢三级脱水工艺过程,并运用在线分析手段,准确显示了干燥过程中的氯碱氢水分含量变化规律。     

Abrasive waterjet micro-machining of channels in metals: Comparison between machining in air and submerged in water

Abrasive water jet technology can be used for micro-milling using recently developed miniaturized nozzles. Abrasive water jet (AWJ) machining is often used with both the nozzle tip and workpiece submerged in water to reduce noise and contain debris. This paper compares the performance of submerged and unsubmerged abrasive water jet micro-milling of channels in 316L stainless steel and 6061-T6 aluminum at various nozzle angles and standoff distances. The effect of submergence on the diameter and effective footprint of AWJ erosion footprints was measured and compared. It was found that the centerline erosion rate decreased with channel depth due to the spreading of the jet as the effective standoff distance increased, and because of the growing effect of stagnation as the channel became deeper. The erosive jet spread over a larger effective footprint in air than in water, since particles on the jet periphery were slowed much more quickly in water due to increased drag. As a result, the width of a channel machined in air was wider than that in water. Moreover, it was observed that the instantaneous erosion rate decreased with channel depth, and that this decrease was a function only of the channel cross-sectional geometry, being independent of the type of metal, the jet angle, the standoff distance, and regardless of whether the jet was submerged or in air, in either the forward or backward directions. It is shown that submerged AWJM results in narrower features than those produced while machining in air, without a decrease in centerline etch rate.     

Power Input Prediction in Agitated Gas‐Liquid Contactors with Non‐coalescent Batch

Volumetric mass transfer coefficients, k_La, just as power input are considered as essential parameters for mechanically agitated gas‐liquid contactors in relation to their optimization and design. The knowledge of power input is crucial for the prediction of other mass transfer characteristics. A power input correlation is created for the industrial design of the process with a non‐coalescent batch that would be appropriate for a broad range of operational conditions. The recommended resulting correlation is able to predict the power input for impellers in industrial‐scale design for a significant scope of operational conditions.     

Catalytic supercritical water oxidation of tri-n-butyl phosphate: Process optimization by response surface methodology and cytotoxicity assessment

Catalytic supercritical water oxidation (SCWO) of an organophosphate flame retardant, namely tri-n-butyl phosphate (TNBP) was studied. Firstly, copper oxide nanoparticles (NPs) were synthesized in SCW and their properties were characterized by various analyses. Afterwards, their catalytic performance was investigated under different conditions including reaction temperature (400–500 °C), TNBP volume percentage in the feed (1–4%), oxidant ratio (0–2) and reaction time (50–150 min) based on response surface methodology (RSM). The synthesized CuO NPs had an average particle size of 30 nm with a narrow distribution. According to RSM analysis, the reaction temperature and time are the most significant factors; whereas, the impact of the other factors, especially TNBP volume percentage in the feed, was found to be negligible. Overall, excellent performance was achieved under optimal conditions found by the RSM, which was reaction temperature of 500 °C, TNBP volume percentage of 4%, oxidant ratio of 1.5, and reaction time of 90 min. The TOC removal efficiency as an indicator of TNBP degradation was about 99%. Finally, in vitro cell viability assays for the cytotoxicity evaluation of fresh and SCW-treated solution were applied. The results of MTT showed that SCWO converts TNBP into by-product that did not induce any cytotoxicity.     

Additive manufacturing of bipolar plates for hydrogen production in proton exchange membrane water electrolysis cells

Water electrolysis is a process that can produce hydrogen in a clean way when renewable energy sources are used. This allows managing large renewable surpluses and transferring this energy to other sectors, such as industry or transport. Among the electrolytic technologies to produce hydrogen, proton exchange membrane (PEM) electrolysis is a promising alternative. One of the main components of PEM electrolysis cells are the bipolar plates, which are machined with a series of flow distribution channels, largely responsible for their performance and durability. In this work, AISI 316L stainless steel bipolar plates have been built by additive manufacturing (AM), using laser powder bed fusion (PBF-L) technology. These bipolar plates were subjected to ex-situ corrosion tests and assembled in an electrolysis cell to evaluate the polarization curve. Furthermore, the obtained results were compared with bipolar plates manufactured by conventional machining processes (MEC). The obtained experimental results are very similar for both manufacturing methods. This demonstrates the viability of the PBF-L technology to produce metal bipolar plates for PEM electrolyzers and opens the possibilities to design new and more complex flow distribution channels and to test these designs in initial phases before scaling them to larger surfaces.     

Effects of structural parameters on water film properties of transpiring wall reactor

Corrosion and salt deposition problems severely restrict the industrialization of supercritical water oxidation. Transpiring wall reactor can effectively weaken these two problems by a protective water film. In this work, methanol was selected as organic matter, and the influences of vital structural parameters on water film properties and organic matter removal were studied via numerical simulation. The results indicate that higher than 99% of methanol conversion could be obtained and hardly affected by transpiration water layer, transpiring wall porosity and inner diameter. Increasing layer and porosity reduced reactor center temperature, but inner diameter's influence was lower relatively. Water film temperature reduced but coverage rate raised as layer, porosity, and inner diameter increased. Notably, the whole reactor was in supercritical state and coverage rate was only approximately 85% in the case of one layer. Increasing reactor length affected slightly the volume of the upper supercritical zone but enlarged the subcritical zone.     

A highly active composite electrocatalyst Ni–Fe–P–Nb2O5/NF for overall water splitting

This work demonstrates a facile Nb₂O₅-decorated electrocatalyst to prepare cost-effective Ni–Fe–P–Nb₂O₅/NF and compared HER & OER performance in alkaline media. The prepared electrocatalyst presented an outstanding electrocatalytic performance towards hydrogen evolution reaction, which required a quite low overpotential of 39.05 mV at the current density of ?10 mA cm^?2 in 1 M KOH electrolyte. Moreover, the Ni–Fe–P–Nb₂O₅/NF catalyst also has excellent oxygen evolution efficiency, which needs only 322 mV to reach the current density of 50 mA cm^?2. Furthermore, its electrocatalytic performance towards overall water splitting worked as both cathode and anode achieved a quite low potential of 1.56 V (10 mA cm^?2).     

冷链条件下气调包装酱卤鸭肉制品货架期预测模型的建立

目的 以气调包装酱卤鸭肉制品为研究对象,在冷链温度范围内建立一套准确、高效的货架期预测模型。方法 利用选择性培养基测定不同温度下产品各微生物数量,确定4~25℃条件下产品优势腐败菌。对乳酸菌数量与感官评定值进行了回归分析确定最小腐败量Ns。分别采用修正的Gompertz方程和平方根方程建立一、二级模型,并通过预测值与实测值对比验证模型的可靠性。结果 确定了4~25℃条件下产品优势腐败菌为乳酸菌,最小腐败量Ns=6.14(lg(cfu /g))。一、二级模型拟合度均良好,三种温度下模型预测值与实际值间的差异均在30％左右,波动幅度在10%以内。结论 实现了对4~25℃内任何时间点产品剩余货架期的预测,为冷链条件下气调包装酱卤鸭肉制品品质的变化提供了理论指导。     

Human mobility synthesis using matrix and tensor factorizations

Human mobility prediction is of great advantage in route planning and schedule management. However, mobility data is a high-dimensional dataset in which multi-context prediction is difficult in a single model. Mobility data can usually be expressed as a home event, a work event, a shopping event and a traveling event. Previous works have only been able to learn and predict one type of mobility event and then integrate them. As the tensor model has a strong ability to describe high-dimensional information, we propose an algorithm to predict human mobility in tensors of location context data. Using the tensor decomposition method, we extract human mobility patterns with multiple expressions and then synthesize the future mobility event based on mobility patterns. The experiment is based on real-world location data and the results show that the tensor decomposition method has the highest accuracy in terms of prediction error among the three methods. The results also prove the feasibility of our multi-context prediction model.