Studies on the degradation process of waste polyethylene terephthalate (PET) have become increasingly mature, but there are relatively few studies on the separation of degradation products. The products contain many components and the separation of which is difficult. Therefore, the study on phase equilibrium thermodynamics of bis-2-hydroxyethyl terephthalate (BHET) is of great theoretical significance and practical value to provide basic data for the BHET crystallization separation. In this work, the degraded products were purified and characterized. The solubility of BHET in methanol, ethanol, ethylene glycol, water and the mixture of ethylene glycol + water were determined by static method. The experimental results were correlated with different models, such as ideal solution (IS) model, λh equation, Apelblat equation and NRTL model. Based on the van't Hoff equation, the mixing Gibbs energy, enthalpy and entropy were calculated. From this work, the basic data which can be used to guide the crystallization process of BHET were obtained, including solubility data, correlation model and thermodynamic properties.

Polyoxymethylene dimethyl ethers are recognized as the prospective diesel additive to decrease the pollutant emission from the light-duty vehicles, which can be polymerize form the monomer of dimethoxymethane (DMM). The industrial synthesis of DMM is mainly involved two-step process: methanol is oxidized to form the formaldehyde in fixed bed reactor and then reacted with the generated formaldehyde through acetalization in continuous stirred-tank reactor. Due to huge energy consumption, this typical synthesis route of DMM needs to be upgraded and more green routes should be determined. In this review, four state-of-the-art one-step direct synthetic routes, including two upgrading routes (methanol direct oxidation and direct dehydrogenation) and two green routes (methanol diethyl ether direct oxidation and carbon oxides direct hydrogenation), have been summarized and compared. Combination with the reaction mechanism and catalytic performance on the different catalysts, the challenges and opportunities for every synthetic route are proposed. The relationships between catalyst structure and property in different synthesis strategy are also investigated and then the suggestions of the design of catalyst are given about future research directions that efforts should be made in. Hopefully, this review can bridge the gap between newly developed catalysts and synthesis technology to realize their commercial applications in the near future.

Enzyme-polymer conjugates are complex molecules with great practical significance. This work was designed to develop a novel enzyme-polymer conjugate by covalently coupling a zwitterionic polymer with side dimethyl chains (pID) to Candida rugosa lipase (CRL) via the reaction between the anhydrides of polymer chains with the amino groups of the enzyme. The resulting two CRL-pID conjugates with different pID grafting densities were investigated in term of the catalytic activity, stability and structural changes. In comparison with native CRL, both the CRL conjugates displayed 2.2 times higher activity than the native enzyme, and showed an increase in the maximum reaction rate (V_max) and a decrease in the Michaelis constant (K_m), thus resulting in about three-fold increases in the catalytic efficiency (k_cat/K_m). These are mainly attributed to the activation of lipase by the hydrophobic alky side chains. Moreover, the thermostability and pH tolerance of the lipase conjugates were significantly enhanced due to the stabilizing effect of the zwitterion moieties. For instance, a five-fold increase of the enzyme half-life at 50℃ for the high-pID conjugated CRL was observed. Spectroscopic studies reveal that the pID conjugation protected the enzyme in the changes in its microenvironment and conformation, well correlating with enhanced activity and stability of lipase conjugates. The findings indicate that enzyme conjugation to the zwitterionic polymer is promising for improving enzyme performance and deserves further development.

Sodium-contained compounds are promising sintering additives for the low-temperature preparation of reaction bonded SiC membranes. Although sodium-based sintering additives in various original states were attempted, their effects on microstructure and surface properties have rarely been studied. In this work, three types of sodium-based additives, including solid-state NaA zeolite residue (NaA) and liquid-state dodecylbenzene sulfonate (SDBS) and water glass (WG), were separately adopted to prepare SiC membranes, and the microstructure, surface characteristics and filtration performance of these SiC membranes were comparatively studied. Results showed that the SiC membranes prepared with liquid-state SDBS and WG (S-SDBS and S-WG) showed lower open porosity yet higher bending strength compared to those prepared with solid-state NaA (S-NaA). The observed differences in bending strength were further interpreted by analyzing the reaction process of each sintering additive and the composition of the bonding phase in the reaction bonded SiC membranes. Meanwhile, the microstructural differentiation was correlated to the original state of the additives. In addition, their surface characteristics and filtration performance for oil-in-water emulsion were examined and correlated to the membrane microstructure. The S-NaA samples showed higher hydrophilicity, lower surface roughness (1.80 μm) and higher rejection ratio (99.99%) in O/W emulsion separation than those of S-WG and S-SDBS. This can be attributed to the smaller mean pore size and higher open porosity, resulting from the originally solid-state NaA additives. Therefore, this work revealed the comprehensive effects of original state of sintering additives on the prepared SiC membranes, which could be helpful for the application-oriented fabrication by choosing additives in suitable state.

The emerging one-dimensional wire-shaped supercapacitors (SCs) with structural advantages of low mass/volume structural advantages hold great interests in wearable electronic engineering. Although graphene fiber (GF) has full of vigor and tremendous potentiality as promising linear electrodefor wire-shaped SCs, simultaneously achieving its facile fabrication process and satisfactory electrochemical performance still remains challenging to date. Herein, two novel types of graphene hybrid fibers, namely ferroferric oxide dots (FODs)@GF and N-doped carbon polyhedrons (NCPs)@GF, have been proposed via a simple and efficient chemical reduction-induced fabrication. Synergistically coupling the electroactive units (FODs and NCPs) with conductive graphene nanosheets endows the fiber-shaped architecture with boosted electrochemical activity, high flexibility and structural integrity. The resultant FODs@GF and NCPs@GF hybrid fibers as linear electrodes both exhibit excellent electrochemical behaviors, including large volumetric specific capacitance, good rate capability, as well as favorable electrochemical kinetics in ionic liquid electrolyte. Based on such two linear electrodes and ionogel electrolyte, a high-performance wire-shaped SC is effectively assembled with ultrahigh volumetric energy density (26.9 mW·h·cm^-3), volumetric power density (4900 mW·cm^-3) and strong durability over 10,000 cycles under straight/bending states. Furthermore, the assembled wire-shaped SC with excellent flexibility and weavability acts as efficient energy storage device for the application in wearable electronics.

It is difficult to separate the methanol and hydrocarbons in the propylene oxide (PO) purification process due to their forming azeotrope. As for this, a novel PO separation process, in that the deionized water is employed as extractant and 1,2-propylene glycol (MPG) that is formed from the PO hydrolysis reaction is recovered, is presented in this work. The salient feature of this process is that both the non-catalyzed reactions of PO hydrolysis to form MPG and dipropylene glycol (DPG) are simultaneously considered and MPG by-product with high purity is obtained in virtue of the deionized water as reflux liquid and side take-off in MPG column. In addition, the ionic liquid (IL) extractant is screened through the conductor-like screening model for segment activity coefficient (COSMO-SAC) and the comparisons of separation efficiency between the IL and normal octane (nC₈) extractant for the separation of PO and 2-methylpentane are made. With the non-random two-liquid (NRTL) thermodynamic model, the simulation and optimization design for the full flow sheet are performed and the effects of the key operation parameters such as solvent ratio, theoretical stages, feeding stage etc. on separation efficiency are detailedly discussed. The results show that the mass purity and the mass yield of PO can be up to 99.99% and 99.0%, and the condenser duty, reboiler duty and PO loss in the process with IL extractant can be decreased by 69.66%, 30.21% and 78.86% compared to ones with nC₈. The total annual cost (TAC) calculation also suggests that the TAC would be significantly reduced if using IL in replace of nC₈ for the investigated process. The presented results would provide a useful guide for improving the quality of PO product and the economic efficiency of industrial plant.

Catalytic pyrolysis of digestate to produce aromatic hydrocarbons can be combined with anaerobic fermentation to effectively transform and utilize all biomass components, which can achieve the meaningful purpose of transforming waste into high-value products. This study explored whether catalytic pyrolysis of digestate is feasible to prepare aromatic hydrocarbons by analyzing the thermogravimetric characteristics, pyrolysis characteristics, and catalytic pyrolysis characteristics of digestate. For digestate pyrolysis, an increase in temperature was found to elevate the CO, CH₄, and monocyclic aromatic hydrocarbon (benzene, toluene, and xylene; BTX) content, whereas it decreased the contents of phenols, acids, aldehydes, and other oxygenates. Furthermore, the catalytic pyrolysis process effectively inhibited the acids, phenols, and furans in the liquid, whereas the yield of BTX increased from 25.45% to 45.99%, and the selectivity of xylene was also increased from 10.32% to 28.72% after adding ZSM-5. ZSM-5 also inhibited the production of nitrogenous compounds.

In this study, different sizes of microcapsules with alginate and bentonite as natural macromolecular materials were prepared to investigate the release property of Pseudomonas putida Rs-198. The characteristics of three microcapsules were evaluated by SEM, FTIR, TG-DSC, XRD and wall thickness. The sizes of three microcapsules (MA, MB, and MC) were 1270.50, 831.79 and 42.52?μm, respectively. First, the encapsulation efficiency of three MA, MB, and MC microcapsules were 82.20%, 90.41%, and 85.84%, respectively. Second, the contact angles of MA and MB samples were similar, while smaller microcapsules MC have higher contact angle (85.05°), indicating poor hydrophilia and decreasing the swelling degrees. Third, the release cumulant of Rs-198 and macromolecule BSA linear stage was fitted to self-established mathematic model. Results show that the microcapsule size had a considerably positive effect on release detail. The large microcapsule possessed strong leak-tightness for Rs-198 as a slow-release microbial agent. Furthermore, the porosity of microcapsules determined their swelling and release and may affect bacterial growth and survival. In conclusion, the Rs-198 microcapsule with different sizes will be pertinently selected based on the characteristics of agricultural production requirements.

To improve performance of membrane electrode assembly (MEA) at large current density region, efficient mass transfer at the cathode is desired, for which a feasible strategy is to lower catalyst layer thickness by constructing high loading Pt-alloy catalysts on carbon. But the high loading may induce unwanted particle aggregation. In this work, H-PtNi/C with 33% (mass) Pt loading on carbon and monodisperse distribution of 3.55?nm PtNi nanoparticles, was prepared by a bimodal-pore route. In electrocatalytic oxygen reduction reaction (ORR), H-PtNi/C displays an activity inferior to the low Pt loading catalyst L-PtNi/C (13.3% (mass)) in the half-cell. While in H₂-O₂ MEA, H-PtNi/C delivers the peak power density of 1.51?W·cm^?2 and the mass transfer limiting current density of 4.4?A·cm^?2, being 21% and 16% higher than those of L-PtNi/C (1.25?W·cm^?2, 3.8?A·cm^?2) respectively, which can be ascribed to enhanced mass transfer brought by the thinner catalyst layer in the former. In addition, the same method can be used to prepare PtFe alloy catalyst with a high-Pt loading of 36% (mass). This work may lead to a range of catalyst materials for the large current density applications, such as fuel cell vehicles.

In this study, biochar (BC) derived from pomelo was prepared via a high-temperature calcination method to modify the graphitic carbon nitride (g-C₃N₄) to synthesize the BC/g-C₃N₄ composite for the degradation of the tetracycline (TC) antibiotic under visible light irradiation. The experimental results exhibit that the optimal feeding weight ratio of biochar/urea is 0.03:1 in BC/g-C₃N₄ composite could show the best photocatalytic activity with the degradation rate of tetracycline is 83% in 100?min irradiation. The improvement of photocatalytic activity is mainly attributed to the following two points: (i) the strong bonding with π-π stacking between BC and g-C₃N₄ make the photogenerated electrons of light-excited g-C₃N₄ transfer to BC, quickly and improve the separation efficiency of carriers; (ii) the introduction of BC reduces the distance for photogenerated electrons to migrate to the surface and increases the specific surface area for providing more active sites. This study provides a sustainable, economical and promising method for the synthesis of photocatalytic materials their application to wastewater treatment.

Air pollution control poses a major problem in the implementation of municipal solid waste incineration (MSWI). Accurate prediction of nitrogen oxides (NO_x) concentration plays an important role in efficient NO_x emission controlling. In this study, a modular long short-term memory (M-LSTM) network is developed to design an efficient prediction model for NO_x concentration. First, the fuzzy C means (FCM) algorithm is utilized to divide the task into several sub-tasks, aiming to realize the divide-and-conquer ability for complex task. Second, long short-term memory (LSTM) neural networks are applied to tackle corresponding sub-tasks, which can improve the prediction accuracy of the sub-networks. Third, a cooperative decision strategy is designed to guarantee the generalization performance during the testing or application stage. Finally, after being evaluated by a benchmark simulation, the proposed method is applied to a real MSWI process. And the experimental results demonstrate the considerable prediction ability of the M-LSTM network.

Vacuum gas oil (VGO) is the most important feedstock for hydrocracking processes in refineries, but its molecular composition cannot be fully acquired by current analysis techniques owing to its complexity. In order to build an accurate and reliable molecular-level kinetic model for reactor design and process optimization, the molecular composition of VGO has to be reconstructed based on limited measurements. In this study, a modified stochastic reconstruction-entropy maximization (SR-REM) algorithm was applied to reconstruct VGOs, with generation of a general molecule library once and for all via the SR method at the first step and adjustment of the molecular abundance of various VGOs via the REM method at the second step. The universality of the molecule library and the effectiveness of the modified SR-REM method were validated by fifteen VGOs (three from the literature) from different geographic regions of the world and with different properties. The simulated properties (density, elemental composition, paraffin-naphthene-aromatics distribution, boiling point distribution, detailed composition of naphthenes and aromatics in terms of ring number as well as composition of S-heterocycles) are in good agreement with the measured counterparts, showing average absolute relative errors of below 10% for each property.

The continuous use of chemical dyes in various industries, and their discharge into industrial effluents, results in severe problems to human life and water pollution. Laccases have the ability to decolorize dyes and toxic chemicals in industrial effluents as green biocatalysts. Their possible industrial applications have been limited by poor reusability, low stability, and loss of free laccase action. In this research, laccase was immobilized on zeolitic imidazolate framework coated multi-walled carbon nanotubes (Laccase@ZIF-8@MWCNTs) via metal affinity adsorption to develop an easy separable and stable enzyme. The optimum reaction conditions for immobilized laccase are at a pH of 3.0 and a temperature of 60?℃. The immobilized laccase was enhanced in storage and thermal stability. The results indicated that Laccase@ZIF-8@MWCNTs still maintained 68% of its original activity after 10 times of repeated use. Most importantly, the biocatalytic system was applied for decolorization of different dyes (20?mg·L^?1) without a mediator, and up to 97.4% for Eriochrome black T and 95.6% Acid red 88 was achieved in 25 min. Biocatalysts with these properties may be used in a variety of environmental and industrial applications.

The catalytic hydrogenation of 2-nitro-4-acetylamino anisole (NMA) is a less-polluting and efficient method to produce 2-amino-4-acetamino anisole (AMA). However, the kinetics of catalytic hydrogenation of NMA to AMA remains obscure. In this work, the kinetic models including power-law model and Langmuir-Hinshelwood-Hougen-Watson (LHHW) model of NMA hydrogenation to AMA catalyzed by Raney nickel catalyst were investigated. All experiments were carried out under the elimination of mass transfer resistance within the temperature range of 70–100 ℃ and the hydrogen pressure of 0.8–1.5 MPa. The reaction was found to follow 0.52-order kinetics with respect to the NMA concentration and 1.10-order kinetics in terms of hydrogen pressure. Based on the LHHW model, the dual-site dissociation adsorption of hydrogen was analyzed to be the rate determining step. The research of intrinsic kinetics of NMA to AMA provides the guidance for the reactor design and inspires the catalyst modification.

The ultra-deep desulfurization of oil needs to be solved urgently due to various problems, including environmental pollution and environmental protection requirements. Oxidative desulfurization (ODS) was considered to be the most promising technology. The facile synthesis of highly efficient and stable HPW-based heterogeneous catalysts for oxidative desulfurization is still a challenging task. In this paper, pentamethylene hexamine (PEHA) and phosphotungstic acid (HPW) were combined by a simple one-step method to prepare a heterogeneous catalyst of PEHA-HPW for the production of ultra-deep desulfurization fuel oil. The composite material exhibited excellent catalytic activity and high recyclability, which could reach a 100% dibenzothiophene (DBT) removal rate in 30 min and be recycled at least 5 times. Experiments and DFT simulations were used to better examine the ODS mechanism of PEHA-HPW. It was proved that the rich amino groups on the surface of PEHA-HPW play a crucial role. This work provides a simple and feasible way for the manufacture of efficient HPW-based catalysts.

Refractory antibiotics in domestic wastewater are hard to be completely eliminated by conventional methods, and then lead to severe environmental contamination and adverse effects on public health. In present work, advanced oxidation processes (AOPs) are adopted to remove the antibiotic of sulfachloropyridazine (SCP). Nanosized Mn₂O₃ was fabricated on the SBA-15 material to catalytically activate potassium peroxydisulfate (PDS) to generate reactive oxygen radicals of ?OH and SO₄^- for SCP degradation. The effects of location and size of Mn₂O₃ were explored through choosing either the as-made or template-free SBA-15 as the precursor of substrate. Great influences from the site and size of Mn₂O₃ on the oxidation activity were discovered. It was found that Mn₂O₃ with a large size at the exterior of SBA-15 (Mn-tfSBA) was slightly easier to degrade SCP at a low manganese loading of 1.0–2.0?mmol?g^?1; however, complete SCP removal could only be achieved on the catalyst of Mn₂O₃ with a refined size at the interior of SBA-15 (Mn-asSBA). Moreover, the SO₄^- species were revealed to be the decisive radicals in the SCP degradation processes. Exploring the as-made mesoporous silica as a support provides a new idea for the further development of environmentally friendly catalysts.

The regeneration of fluidized catalytic cracking (FCC) catalysts is an essential process in petroleum processing. The current study focused the regeneration reaction characteristics of spent fluidized catalytic cracking catalyst (SFCC) at different atmospheres with influences on pore evolution and activity, for a potential way to reduce emission, produce moderate chemical product (CO), and maintain catalyst activity. The results show that regeneration in air indicates a satisfaction on removing coke on the catalyst surface while giving a poor effect on eliminating the coke inside micropores. This is attributed that the combustion in air led to a higher temperature and further transformed kaolinite phase to silica-aluminum spinel crystals, which tended to collapse and block small pores or expand large pores, with similar results observed in pure O₂ atmosphere. Nevertheless, catalysts regenerated in O₂/CO₂ diminished the combustion damage to the pore structure, of which the micro porosity after regeneration increased by 32.4% and the total acid volume rose to 27.1%. The regeneration in pure CO₂ displayed low conversion rate due to the endothermic reaction and low reactivity. The coexistence of gasification and partial oxidation can promote regeneration and maintain the original structure and good reactivity. Finally, a mechanism of the regeneration reaction at different atmospheres was revealed.

Aniline is a vital industrial raw material. However, highly-toxic aniline wastewater usually deteriorated effluent quality, posed a threat to human health and ecosystem safety. Therefore, this study reported a novel internal circulation iron-carbon micro-electrolysis (ICE) reactor to treat aniline wastewater. The effects of reaction time, pH, aeration rate and iron-carbon (Fe/C) ratio on the removal rate of aniline and the chemical oxygen demand were investigated using single-factor experiments. This process exhibited high aniline degradation performance of approximately 99.86% under optimal operating conditions (reaction time = 20 min, pH = 3, aeration rate = 0.5 m³·h^-1, and Fe/C = 1:2). Based on the experimental results, the response surface method was applied to optimize the aniline removal rate. The Box-Behnken method was used to obtain the interaction effects of three main factors. The result showed that the reaction time had a dominant effect on the removal rate of aniline. The highest aniline removal rate was obtained at pH of 2, aeration rate of 0.5 m³·h^-1 and reaction time of 30 min. Under optional experimental conditions, the aniline content of effluent was reduced to 3 mg·L^-1 and the removal rate was as high as 98.24%, within the 95% confidence interval (97.84%-99.32%) of the predicted values. The solution was treated and the reaction intermediates were identified by high-performance liquid chromatography, ultraviolet-visible spectroscopy, Fourier-transform infrared spectroscopy, gas chromatography-mass spectrometry, and ion chromatography. The main intermediates were phenol, benzoquinone, and carboxylic acid. These were used to propose the potential mechanism of aniline degradation in the ICE reactor. The results obtained in this study provide optimized conditions for the treatment of industrial wastewater containing aniline and can strengthen the understanding of the degradation mechanism of iron-carbon micro-electrolysis.

A correct and timely fault diagnosis is important for improving the safety and reliability of chemical processes. With the advancement of big data technology, data-driven fault diagnosis methods are being extensively used and still have considerable potential. In recent years, methods based on deep neural networks have made significant breakthroughs, and fault diagnosis methods for industrial processes based on deep learning have attracted considerable research attention. Therefore, we propose a fusion deep-learning algorithm based on a fully convolutional neural network (FCN) to extract features and build models to correctly diagnose all types of faults. We use long short-term memory (LSTM) units to expand our proposed FCN so that our proposed deep learning model can better extract the time-domain features of chemical process data. We also introduce the attention mechanism into the model, aimed at highlighting the importance of features, which is significant for the fault diagnosis of chemical processes with many features. When applied to the benchmark Tennessee Eastman process, our proposed model exhibits impressive performance, demonstrating the effectiveness of the attention-based LSTM FCN in chemical process fault diagnosis.

Rotating packed bed (RPB) is one of the most effective gas–liquid mass transfer enhancement reactors, its effective specific mass transfer area (a_e) is critical to understand the mass transfer process. By using the NaOH–CO₂ chemical absorption method, the a_e values of three RPB reactors with different rotor sizes were measured under different operation conditions. The results showed that the high gravity factor and liquid flow rate were major affecting factors, while the gas flow rate exhibited minor influence. The radius of packing is the dominant equipment factor to affect a_e value. The results indicated that the contact area depends on the dispersion of the liquid phase, thus the centrifugal force of rotating packed bed greatly influenced the a_e value. Moreover, the measured a_e/a_p (effective specific mass transfer area/specific surface area of packing) values were fitted with dimensionless correlation formulas. The unified correlation formula with dimensionless bed size parameter can well predict the experimental data and the prediction errors were within 15%.