A single component photoimaging system with styrene copolymers having t-BOC-protected quinizarin dye precursors and photoacid generating groups in a single polymer chain

A styrene monomer tBQSt, having a tert-butyloxycarbonyloxy (t-BOC)-protected quinizarin dye precursor as a pendent, has been copolymerized with N-(tosyloxy)maleimide (TsOMI) to obtain a dual functional polymer P(tBQSt/TsOMI). The polymer P(tBQSt/TsOMI), as a single component photoimaging system without using an external photoacid generator (PAG), was applied for fluorescent photopatterning by dry process based on the chemical amplification (CA) process. The TsOMI units in the polymer chains were responsible for photochemical generation of p-toluenesulfonic acid by UV exposure and the acid generated in the solution cast polymer film induced the catalytic deprotection of acid labile t-BOC groups of the quinizarin dye precursors. Accordingly, the quinizarin moieties were regenerated in the polymer chains by the CA process, thereby recovering the original color and fluorescence of the quinizarin dye. Fluorescent patterns were readily delineated on the thin polymer films by imagewise UV exposure even without a wet development process.     

Fluorescent selectivity for small molecules of two coordination polymers based on a tetracarboxylate ligand

Two coordination polymers [Cd(tptc)_0.5(4,4′–bibp)]_n (1) and {[Zn₃(Htptc)₂(phen)₂]·1.5H₂O}_n (2) (H₄tptc = terphenyl-3,3″,5,5″-tetracarboxylic acid, 4,4′-bibp = 4,4′-bis(imidazolyl)biphenyl, and phen = 1,10-phenanthroline) were synthesized under solvothermal conditions. Complex 1 displays a 3D structure with a Schläfli symbol of {4⁴.6²}{4⁸.6²⁰}. Complex 2 possesses a 2D layer network, incorporating [Zn₃(COO)₆] second building units (SBUs), which is packed into a 3D supramolecular architecture by π ⋯ π interactions. Both of them exhibit strong luminescence characteristics. It is worth to note that complexes 1 and 2 show potential application to detect small organic molecules.     

Profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties

This paper reports how the economic performance of a chemical process plant is affected by material flow uncertainties from the plant inlet and outlet. Two chance-constrained optimization models were proposed. The models were tested using case studies of an existing gas processing plant. Profit optimization for the case studies was made with respect to the reliability of holding the process constraints at a certain confidence level [0.5, 1]. The optimal profit change for uncertainty from the plant inlet within the confidence interval [0.96, 1] was 86%. On the other hand, the optimal profit change for uncertainty from the plant outlet was only 2% for the same confidence level interval considered. This suggests that the uncertainty from the plant inlet has a major impact on the overall economic performance of the plant. Sensitivity analysis showed how uncertain parameters from both plant sides can affect the overall profit significantly.     

基于LSNPE算法的化工过程故障检测

复杂化工过程通常具有多个操作模态,而且采集的数据不服从单一的高斯或非高斯分布。针对化工过程的多模态和复杂数据分布问题,将局部标准化（local standardized,LS）策略应用于邻域保持嵌入（neighborhood preserving embedding,NPE）算法,提出了一种新的基于局部标准化邻域保持嵌入（local standardized neighborhood preserving embedding,LSNPE）算法的故障检测方法。首先,使用LSNPE算法提取高维数据的低维子流形,进行维数约减,同时保持邻域结构不变。其次,通过特征空间中样本的局部离群因子（local outlier factor,LOF）构造监控统计量并确定其控制限。相较于监控多模态化工过程的多模型策略,提出的LSNPE方法不需要过程先验知识的支持,只需建立一个全局的监控模型。最后,通过数值仿真及Tennessee Eastman（TE）过程仿真研究验证了本文提出方法的有效性。     

Growth of carbon nanotubes on natural organic precursors by chemical vapor deposition

Some plant tissues are rich in transition metal Fe. So, we explored the use of black jew’s-ear fungus and black sesame seeds as catalyst precursors to prepare carbon nanotubes by chemical vapor deposition. Each catalyst particle arises from the metal content of a single cell of the precursor, hence the distribution of catalyst particles is uniform. Their size and composition are almost identical. Carbon nanotube arrays can grow when black sesame seeds are used as catalyst precursors. Carbon nanotubes with diameters 80 nm and length greater than 100 μm can grow when black jew’s-ear fungus are used.     

干/湿相转化法制备复合型聚合物电解质的研究

采用干 /湿相转化法制备了用于锂离子电池的复合型聚合物隔膜。通过扫描电镜和吸液实验研究了添加不同无机纳米粉料对由该法制得的聚合物隔膜孔径及结构的影响。用 8种隔膜组装了电池 ,测试了其电化学性质。结果证实无机纳米材料的加入导致了隔膜形成后在孔径大小、孔径分布和孔隙率等结构参数上的差异 ,添加无机纳米材料的隔膜具有适宜的孔结构和较好的充放电性能 ,具有实际应用价值     

Multiwalled carbon nanotubes functionalized with maleated poly(propylene) by a dry mechano-chemical process

Ball milling was used to graft maleated polypropylene (MAPP) on the surface of multiwalled carbon nanotubes (MWCNTs), with a view to preparing MWCNT/polypropylene composites with improved matrix/nanotube compatibility. The occurrence of the grafting reaction was evaluated by FTIR spectroscopy and the yield was quantified by thermogravimetric analysis, as a function of the milling time. Dispersion experiments confirmed the nanotube surface modification of the nanotubes since functionalized MWCNTs remained stably dispersed in an ethanol/xylene solution for more than 48 h after sonication. No evidences of significant structural damage after the mechano-chemical treatment were shown by Raman spectroscopy. Moreover, a layer attributable to the presence of grafted MAPP chains on MWCNT walls was clearly detected by transmission electron microscopy. The average thickness of this amorphous layer was evaluated and compared with quantitative TGA data.     

Polygeneration of hydrogen and power based on coal gasification integrated with a dual chemical looping process: Thermodynamic investigation

This paper assesses, from a thermodynamic perspective, the conversion of coal to power and hydrogen through gasification simultaneously with a dual chemical looping processes, namely chemical looping air separation (CLAS) and water–gas shift with calcium looping CO₂ absorption (WGS-CaL). CLAS offers an advantage over other mature technologies in that it can significantly reduce its capital cost. WGS-CaL is an efficient method for hydrogen production and CO₂ capture. The three major factors, oxygen to coal (O/C), steam to coal (S/C) and CaO to coal (Ca/C) were analyzed. Moreover, the comparisons of this suggested process and the traditional processes including integrated gasification combined cycle (IGCC), integrated gasification combined cycle with carbon capture and storage (IGCC-CCS) and integrated gasification combined cycle with calcium-based chemical looping (IGCC-CaL) were discussed. And, the exergy destruction analysis of this suggested process has also been calculated.     

基于约翰逊转换的鲁棒化工过程监控方法

化工厂中一个小故障可能导致大事故,从而造成生命财产损失和环境破坏。为了防止小故障演变成大事故,化学工业需要有效的过程监控来及时检测故障和诊断故障原因。传统化工过程监控方法主元分析法(Principal Component Analysis, PCA)假设数据服从高斯分布,实践中有时并不满足该条件。此外,其使用方差、协方差捕捉数据非线性变化时,鲁棒性较差。本工作提出一种改进的主元分析法—基于约翰逊转换的鲁棒过程监控方法。首先引入约翰逊正态转换(Johnson Transformation)使过程数据服从高斯分布;其次使用鲁棒性强的斯皮尔曼相关系数(Spearman Correlation Coefficient)矩阵代替传统主元分析法的协方差矩阵提取特征向量,构造特征空间;最后将过程数据投影到特征空间,使用T2和SPE统计量实施过程监控。将此方法应用于TE过程故障案例,并与PCA和核主元分析法(Kernel Principal Component Analysis, KPCA)对比,验证了此方法的有效性。     

Phase formation during the sintering process of a chromium ore-concentrate having a titanium-containing additive and during the firing process of the periclase-spinellide products based on it

Conclusions It was shown that the interaction occurring between the titanium-containing sintering additive and the chromium ore-concentrate during the firing process leads to the formation of the solid solutions of titanium dioxide in spinellide and the titanates of the trivalent metals [(Cr_1–x–yAl_xFe_y)₂TiO₅], that are localized mainly in the form of films and inclusions at the surface of the spinellide grains.The disappearance of the titanates during the firing process of the periclase-spinellide products obtained using the aforementioned chromium ore-concentrate and periclase can be attributed to the interaction of the free magnesium oxide with the titanates and the subsequent dissolution of the intermediate spinellide in the original spinellide.Thus, a complete and uniform appropriation (distribution) of the titanium dioxide additive in the form of a solid solution in the spinellide is ensured by introducing an excess quantity (with respect to the composition of the spinellide) of magnesium oxide into the charge.It is advisable to carry out a detailed study of the effect of the content of titanium dioxide in the spinellide on the physical and technological properties and the service characteristics of the refractories.Translated from Ogneupory, No. 7, pp. 2–5, July, 1993.     

Developing a talent training model related to chemical process safety based on interdisciplinary education in China

While chemical industrial development in China is growing rapidly, the corresponding safety training resources remain inadequate, which may often lead to increased risk of chemical accidents. These accidents are often associated with the negligence of safety management, poor safety hazard awareness, and lack of safety practice. In order to alleviate these prominent risk factors in chemical industries in China, our study develops a talent training model related to chemical process safety. First, we propose an approach for establishing the “talent training model” related to chemical process safety, consisting of three steps: analyzing the current status and existing problems of talent training related to chemical process safety, determining the theoretical basis and training objectives for developing interdisciplinary talents, and designing a new talent training model. Second, we establish a talent training model using the proposed method, which includes a comprehensive curriculum system, a diversified teaching pattern, and a quintuple evaluation method. Furtherly, we determine the expected outcomes of the talent training model. The research results provide an innovative chemical process safety training method that is applicable nationwide, also it works as a reference for other rapidly developing countries in the chemical process industry to improve safety within the chemical industry.     

A CNN approach based on correlation metrics to chemical process fault classifications with limited labelled data

This paper proposes a novel correlation metrics-based convolutional neural network (CNN) classification model for chemical process fault diagnoses, creating a heuristic representation concerning process variable locations in grey correlation space (GCS) in terms of the copula entropy to guide the learning of classifiers. The proposed method based on correlation metrics can help solve the problem of insufficient information caused by a lack of labelled data. Specifically, variable correlations are fused into a heuristic matrix to provide prior knowledge for network learning in compensating data information before the CNN is employed to build the classifier for mining features in GCS. Driven by this mechanism, fault classifications in the case of small numbers of fault samples are successfully implemented. With successful simulation experiments carried out on the Tennessee Eastman (TE) process platform, we found that in GCS, different fault samples can represent hugely different features, while data resulting from the same fault rarely contribute to different ones. This observation lays a solid foundation for constructing superior fault classifiers. In addition, compared with conventional approaches, the proposed method has demonstrated better fault classification performances in the case of limited labelled fault samples.     

Study of chemical activation process of a lignocellulosic material with KOH by XPS and XRD

Chemical activation of carbons is currently a very common method for obtaining activated carbons with very high surface areas. KOH is one of the most effective agents employed for this purpose. However, the reaction mechanism of this kind of activation it is not yet completely elucidated, although some models have been proposed. In this paper, an activated charcoal was obtained from a lignocellulosic material by impregnation with different amounts of KOH. The activation process was studied by X-ray photoelectron spectroscopy and X-ray diffraction. These techniques point to the formation of different potassium compounds at the carbon surface (mainly K₂CO₃ and different oxides) and show the dependence between surface area development in the carbons and the amount of K₂CO₃ formed during the activation process.     

Photoswitching electrospun nanofiber based on a spironaphthoxazine-isophorone-based fluorescent dye system

A bistable photoswitching photochromic spironaphthoxazine/isophorone-based fluorescent dye system was investigated. The photoregulated fluorescence switching behavior of a spironaphthoxazine/isophorone dye loaded poly(methyl methacrylate) nanofiber was also studied. Reversible modulation of fluorescence intensity was achieved using alternating irradiation with UV and visible light. The erasable and rewritable optical storage based on spironaphthoxazine/isophorone dye loaded poly(methyl methacrylate) nanofiber has been developed.     

Fault diagnosis of complex chemical process based on multi-scale ADCRC feature learning

The time series and multi-scale characteristics of complex industrial process data are always important factors affecting the performance of fault diagnosis. In this study, a new fault diagnosis model based on multi-scale attention dilated causal residual convolution (ADCRC) is proposed. Aiming at the temporal nature of industrial data, the ADCRC module is developed to extract time series features, in which the ADCRC module is composed of dilated causal convolution (DCC), attention mechanism (AM), and residual connection, DCC is used to extract time series features, AM adjusts the weight of features according to attention distribution to obtain more important feature information, and residual connection is used to enhance the training accuracy of model. For the multi-scale characteristics of original data, MS-ADCRC model based on ADCRC module is developed for multi-scale feature extraction, in which multiple ADCRC modules extract multi-scale features of data in parallel. Finally, the proposed MS-ADCRC model is tested on the Tennessee-Eastman data set. Compared with other existing models, the results show that the proposed MS-ADCRC model has more advantages in fault diagnosis feature learning.     

Fault monitoring based on mutual information feature engineering modeling in chemical process

A large amount of information is frequently encountered when characterizing the sample model in chemical process. A fault diagnosis method based on dynamic modeling of feature engineering is proposed to effectively remove the nonlinear correlation redundancy of chemical process in this paper. From the whole process point of view, the method makes use of the characteristic of mutual information to select the optimal variable subset. It extracts the correlation among variables in the whitening process without limiting to only linear correlations. Further, PCA (Principal Component Analysis) dimension reduction is used to extract feature subset before fault diagnosis. The application results of the TE (Tennessee Eastman) simulation process show that the dynamic modeling process of MIFE (Mutual Information Feature Engineering) can accurately extract the nonlinear correlation relationship among process variables and can effectively reduce the dimension of feature detection in process monitoring.     

Covalent fixation of hydroxyethyl sulphone dye on cotton by the use of crosslinking agent via a pad-batch process

A trifunctional reactive crosslinker, 2,4,6-tri{ρ-[(2'-sulphatoethyl)sulphonyl]phenylamino}-1,3,5-triazine (Tri-SES) was synthesised and co-applied with hydrolysed Cl Reactive Black 5 (hydroxyethyl sulphone dye) to cotton to achieve dye-fibre covalent bonding via a cold pad-batch process. Several factors affecting the dye—crosslinker-cotton covalent fixation reactions have been studied and are discussed in this paper. It was found that the dye fixation was strongly dependent on the alkali type and concentration. Very high fixation values ( ca. 97%) were obtained under the optimised conditions.