摘要：Identification of the catalyst characteristics correlating with the key performance parameters including selectivity and stability is key to the rational catalyst design. Herein we focused on the identification of property-performance relationships in the methanol-to-olefin(MTO) process by studying in detail the catalytic behaviour of MFI, MEL and their respective intergrowth zeolites. The detailed material characterization reveals that both the high production of propylene and butylenes and the large Me OH conversion capacity correlate with the enrichment of lattice Al sites in the channels of the pentasil structure as identified by 27 Al MAS NMR and 3-methylpentane cracking results. The lack of correlation between MTO performance and other catalyst characteristics, such as crystal size, presence of external Brønsted acid sites and Al pairing suggests their less pronounced role in defining the propylene selectivity. Our analysis reveals that catalyst deactivation is rather complex and is strongly affected by the enrichment of lattice Al in the intersections, the overall Al-content, and crystal size. The intergrowth of MFI and MEL phases accelerates the catalyst deactivation rate.

摘要：The design and synthesis of highly active non-noble metal oxide catalysts, such as transition- and rare-earth-metal oxides, have attracted significant attention because of their high efficiency and low cost and the resultant potential applications for the degradation of volatile organic compounds(VOCs). The structure-activity relationships have been well-studied and used to facilitate design of the structure and composition of highly active catalysts. Recently, non-noble metal oxides with porous structures have been used as catalysts for deep oxidation of VOCs, such as aromatic hydrocarbons, aliphatic compounds, aldehydes, and alcohols, with comparable activities to their noble metal counterparts. This review summarizes the growing literature regarding the use of porous metal oxides for the catalytic removal of VOCs, with emphasis on design of the composition and structure and typical synthetic technologies.

摘要：Matrix expression of finite orthogonal wavelet transform of finite impulse response signal is more valuable for theoretical analysis and understanding. However, clear deduction for matrix expression has not been provided yet. In this paper, the formulation to generate the re-lated matrix is put forward and the theorem on the orthogonality of this matrix proved. This effort deploys a basis for more deeper and wider applications in chemical processes. *

摘要：A series of quaternary ammonium ionic liquids(ILs)were synthesized and employed as catalysts for the production of poly(isosorbide carbonate)(PIC)from diphenyl carbonate and isosorbide via a melt polycondensation *** relationship between the anions of the ILs and the catalytic activities was investigated,and the readily‐prepared IL tetraethylammonium imidazolate(TEAI)was found to exhibit the highest catalytic *** optimizing the reaction conditions,a PIC with a weight‐average molecular weight(Mw)of25600g/mol was obtained,in conjunction with an isosorbide conversion of92%.As a means of modifying the molecular flexibility and thermal properties of the PIC,poly(aliphatic diol‐co‐isosorbide carbonate)s(PAIC)s were successfully synthesized,again using TEAI,and polymers with Mw values ranging from29000to112000g/mol were obtained.13C NMR analyses determined that the PAIC specimens had random microstructures,while differential scanning calorimetry demonstrated that each of the PAICs were amorphous and had glass transition temperatures ranging from50to115°*** analyses found Td‐5%values ranging from316to332°C for these *** on these data,it is evident that the incorporation of linear or cyclohexane‐based diol repeating units changed the thermal properties of the PIC.

摘要：With the increasing complexity of industrial processes, the high-dimensional industrial data exhibit a strong nonlinearity, bringing considerable challenges to the fault diagnosis of industrial processes. To efficiently extract deep meaningful features that are crucial for fault diagnosis, a sparse Gaussian feature extractor(SGFE) is designed to learn a nonlinear mapping that projects the raw data into the feature space with the fault label dimension. The feature space is described by the one-hot encoding of the fault category label as an orthogonal basis. In this way, the deep sparse Gaussian features related to fault categories can be gradually learned from the raw data by SGFE. In the feature space,the sparse Gaussian(SG) loss function is designed to constrain the distribution of features to multiple sparse multivariate Gaussian distributions. The sparse Gaussian features are linearly separable in the feature space, which is conducive to improving the accuracy of the downstream fault classification task. The feasibility and practical utility of the proposed SGFE are verified by the handwritten digits MNIST benchmark and Tennessee-Eastman(TE) benchmark process,respectively.

摘要：Effective utilization of water and energy is the key factor of sustainable development in process industries, and also an important science and technology problem to be solved in systems engineering. In this paper,two new methods of optimal design of water utilization network with energy integration in process industries are presented, that is, stepwise and simultaneous optimization methods. They are suitable for both single contaminant and multi-contaminant systems, and the integration of energy can be carried out in the whole process system, not only limited in water network, so that energy can be utilized effectively. The two methods are illustrated by case study.

摘要：The paper presents a procedure to design water network. First of all, water reuse system, water regeneration reuse system (including regeneration recycle) and wastewater treatment system are designed separately. But the interaction between different parts demands that each part is designed iteratively to optimize the whole water network. Therefore, on the basis of the separated design a water netvrork superstructure including reuse, regeneration and wastewater treatment is established from the system engineering point of view. And a multi-objective adaptive simulated annealing genetic algorithm is adopted to simultaneously integrate the overall water netvrork to balance the economic and environmental effects. The algorithm overcomes the defect of local optimum of simulated annealing (SA), avoids the pre-maturation of genetic algorithm (GA) and finds a set of solutions (pareto front) in acceptable computer time. Prom the pareto front, a point with minimum fresh water consumption will be extended to zero discharge as our ultimate goal.

摘要：Materials development has historically been driven by human needs and desires, and this is likely to con- tinue in the foreseeable future. The global population is expected to reach ten billion by 2050, which will promote increasingly large demands for clean and high-ef ciency energy, personalized consumer prod- ucts, secure food supplies, and professional healthcare. New functional materials that are made and tai- lored for targeted properties or behaviors will be the key to tackling this challenge. Traditionally, advanced materials are found empirically or through experimental trial-and-error approaches. As big data generated by modern experimental and computational techniques is becoming more readily avail- able, data-driven or machine learning (ML) methods have opened new paradigms for the discovery and rational design of materials. In this review article, we provide a brief introduction on various ML methods and related software or tools. Main ideas and basic procedures for employing ML approaches in materials research are highlighted. We then summarize recent important applications of ML for the large-scale screening and optimal design of polymer and porous materials, catalytic materials, and energetic mate- rials. Finally, concluding remarks and an outlook are provided.

摘要：Due to their unique surface chemistry,highly adjustable metal components,hydrophilicity,and high carrier concentrations,MXenes are applied in a variety of *** to other two-dimensional(2D)materials,building heterostructures with additional materials to form a 3D porous architecture for MXenes can significantly enhance their functionality and ***,the open structures and well-defined pathways of these 3D structured MXenes can improve ionic and electronic transport,thereby promoting their applications in electrochemical energy storage,sensing,catalysis,and *** this review,the recent efforts made on preparing 3D porous MXenes with heterostructures,focusing on MXenes/C,MXenes/inorganics,and MXenes/polymers were *** discussion covers aspects ranging from the design to synthesis of 3D porous MXenes,and their applications in photocatalysis,environmental monitoring and electrochemical energy *** review is concluded by presenting the prospects and insights on exploring the relationships between the porosity formation mechanisms,properties and applications of the 3D porous MXenes *** review can provide meaningful guidance for the design,fabrication and application of 3D porous MXenes in high-performance materials and devices.

摘要：Cholesteric liquid crystal(CLC)particles can adaptively respond to constant changes in external stimuli and thus are widely used in solvent-sensing,pattern fabrication,and *** studies discussed the color change at the center of the particles for various ***,few studies analyzed the color change of the brush structure of particles in response to various applications because of the complicated birefringence *** this paper,we present a novel integrated sensing system based on the synergetic color change from the center and the brush structure of CLC *** system provides abundant and additional sensing information relative to the traditional *** particles are prepared by mixing reactive mesogens,a reactive chiral dopant,a non-reactive LC molecule,and a photoinitiator by using a microfluidic device and subsequent *** CLC particles exhibit gorgeous color at the center and brush structure upon various solvent stimuli because of the Bragg reflection and the birefringence effect,which is explained by the possible color-changing mechanism introduced in this *** proof-of-concept applications,such color-changing polymer particles are demonstrated in multi-solvent-sensing detection and pattern *** study provides new insights into the development of stimuli-responsive advanced functional materials with tailorable nanostructures toward technological applications ranging from sensing to display.