In pharmaceutical manufacturing, there is a widespread presence of industrial waste liquids containing methyl ethyl ketone, isopropanol, and n-heptane. This work employs extractive distillation to separate this multiazeotropic system. Firstly, the conventional extractive distillation process (CED) is designed, and the optimal parameters of the three-objective trade-off are obtained by multi-objective optimization. Then, the side-stream distillation, intermediate reboiler and heat integration enhancement methods are introduced to reduce energy consumption and costs. The results demonstrate that the double side-stream extractive distillation with intermediate reboiler and heat integration process (DSSEDIR-HI) shows the best economic and environmental performance. Compared to the CED process, the total annual cost is reduced by 23.9 %, CO2 emissions are decreased by 42.5 %, and thermodynamic efficiency is improved by 68.4 %. This study provides a sustainable pathway for the separation of methyl ethyl ketone/isopropanol/n-heptane mixture.

Methyl tert-butyl ether (MTBE) is an important chemical feedstock and fuel additive with significant applications in the chemical and petrochemical industries. However, the MTBE production process often forms an MTBE/methanol (MeOH) azeotrope, making separation challenging. In previous work, we proposed an effective extractive distillation separation process. This work aims to develop an alternative, highly efficient pressure-swing distillation (PSD) process. First, based on thermodynamic analysis, two conventional PSD processes were proposed and optimized to minimize the total annual cost (TAC) and CO2 emissions while maximizing thermodynamic efficiency. Subsequently, eight intensified separation processes incorporating heat integration, vapor recompression heat pump, and solar energy were designed. Finally, the comprehensive performance of all schemes was evaluated from economic, environmental, energy, and exergy (4E) perspectives. Results indicate that PSD2 outperforms PSD1, with the dual heat pump-solar energy intensified sequence (PSD2-HP-SE) being the optimal scheme, achieving reductions in TAC, CO2 emissions, total energy consumption, and exergy loss by 49.34%, 100%, 100%, and 72.61%, respectively, and an increase in thermodynamic efficiency by 68.17%.

In the synthesis of liquid crystal monomers and the industrial production of norgestrel in the pharmaceutical industry, wastewater containing tetrahydrofuran and ethanol is generated, necessitating the recovery and reuse of these high-value organic compounds. This study identified dimethyl sulfoxide (DMSO) as the entrainer with optimal separation performance and sustainability through phase diagram analysis and ecotoxicity assessment. The mechanism by which DMSO enhances the separation of the ternary azeotrope was investigated via quantum chemical calculations. A three-column extractive distillation (TCED) process and an extractive dividing-wall column (EDWC) process were designed. Using the total annual cost, carbon dioxide emissions, and process route index as objective functions, both processes were optimized separately using the second-generation nondominated sorting genetic algorithm. The results indicate that the EDWC process exhibits a superior performance. The sustainability of the EDWC process was further demonstrated using the Eco-indicator 99 method based on a life cycle assessment. Exergy analysis results show that the exergy loss of the EDWC process is reduced by 25.77% compared with the TCED process. Finally, three control structures were designed for the EDWC process, and subsequent dynamic control performance tests revealed that the model predictive control scheme delivered the best control performance. The main contribution of this work lies in providing a multiscale analysis ranging from intermolecular interactions to process optimization and control, offering valuable insights for the practical industrial application of the EDWC process.

Acetonitrile (ACN) is an important organic compound and versatile chemical intermediate. Recovering ACN from pharmaceutical waste liquids can reduce production costs and mitigate environmental hazards. At atmospheric pressure, ACN forms an azeotrope with water, and extractive distillation is one of the most effective separation methods. In this study, the conductor-like screening model-segment activity coefficient (COSMO-SAC) was employed to identify deep eutectic solvents (DESs) prepared using choline chloride (ChCl) as the hydrogen bond acceptor and oxalic acid (OA) and glycolic acid (GA) as hydrogen bond donors for separating the ACN-water azeotrope. Vapor-liquid equilibrium (VLE) experiments demonstrate that adding 25 mol % DESs significantly enhances the relative volatility of ACN to water. The nonrandom two-liquid (NRTL) model was used to correlate the experimental data with satisfactory accuracy. Quantum chemical calculations were performed to analyze the types, sites, and strengths of weak interactions between DESs and azeotropic components. Results confirm that interactions between DESs and water are stronger than those with ACN, thereby reducing the activity coefficient of water in the liquid phase and enabling azeotrope separation.

In the chemical industry, wastewater often contains ternary azeotropic mixtures with multiple azeotropes, presenting challenges for separation due to their complex phase equilibrium. This work investigates the separation of a benzene/n-propanol/water mixture, which contains three binary azeotropes and one ternary azeotrope, using a reactive extractive distillation process. Firstly, the separation sequence is designed using ternary phase diagrams. Then, a multi-objective genetic algorithm is employed to optimize the total annual cost, CO2 emissions and extraction efficiency as objective functions. Subsequently, mechanical vapor recompression heat pump is designed for application in double column reactive extractive distillation process. Finally, feed preheating and heat exchanger network is designed for the heat pump assisted reactive extractive distillation process. The results indicate that the application of mechanical vapor recompression heat pump in the reactive extractive distillation process can significantly improve both economic and environmental performance. The double column reactive extractive distillation process, which is designed with heat pump, feed preheating and heat exchanger network, demonstrated optimal economic and environmental performance. Compared to conventional double column reactive extractive distillation processes, the total annual cost is reduced by 25.6%, and CO2 emissions is decreased by 52.0%.

This study established a rate-based model for the ternary amine (MEA/MDEA/AMP) CO2 capture process and employed a multiobjective genetic algorithm to achieve coordinated optimization of solvent formulation and process parameters. The basic process for CO2 capture using a ternary amine blend is constructed, and the absorber intercooler (AIC) configuration and split-flow (SF) configuration are designed. The results indicate that the AIC process is suitable for higher-concentration absorbents, achieving a 12.25% reduction in liquid-to-gas ratio compared to the basic process and 5.53% reduction in total annual cost (TAC). The SF process significantly decreases the water content in the gas phase of the stripper column, leading to a 22.75% reduction in TAC. When combined, the effects demonstrate cumulative superposition, resulting in a 27.11% reduction in TAC and a 37.39% reduction in carbon emissions. The integration of a multiobjective genetic algorithm for parameter optimization provides an efficient solution for improving composite amine-based carbon capture technology.

The process of separating ethylene glycol and 1,2-butanediol with reactive distillation is intricate, with many variables involved, leading to a time-consuming and inefficient optimization process. To expedite the optimization process, this study proposes a new parallel stochastic algorithm framework. This research shows that the framework is 36.8 times faster than the serial framework. The reactive distillation-assisted separation process of ethylene glycol and 1,2-butanediol is optimized using the parallel stochastic algorithm framework. The optimization process duration is 810 min. Based on the optimal design, the process is further intensified by incorporating the dividing wall column and intermediate reboiler. Compared to the base process, the intensified process exhibited reductions of 8.89 %, 10.18 %, and 9.83 % in total capital cost, total operating cost, and total annual cost, respectively.

Benzyl methyl ether (BME) was developed as an extractant for separating dimethyl carbonate (DMC) from methanol (ME). The study evaluated the performance of extractive distillation columns (EDWC) with single and two walls through experiments and simulations. The two-wall EDWC demonstrated superior separation efficiency, achieving ME and DMC purities above 99.9% under optimal conditions: solvent-to-feed ratio of 8, 45 theoretical stages, atmospheric pressure, extraction section/azeotropic separation section sideline at the 34th plate, azeotropic separation/DMC purification section sideline at the 20th plate, 12 theoretical stages in the common rectification section, and vapor split ratios of 0.42 (extraction section/azeotropic separation section) and 0.27 (azeotropic separation/DMC purification section). Experimental results aligned well with the simulations. The EDWC with two walls, which integrates the extraction section, azeotropic separation section, and DMC purification section with shared reboiler heating, offers significant potential to replace current DMC/ME separation processes and reduce production costs.

Dividing wall reactive extractive distillation (DWRED), as an intensified configuration of double-column reactive extractive distillation (DCRED), has previously failed to achieve energy-saving and decarbonization objectives. To address this challenge, this study integrates process intensification strategies-feed preheating (FP), intermediate reboiler (IR), flash vapor circulation heat pump (FVCHP), and heat exchanger network (HEN)-into the DWRED configuration, using the benzene/n-propanol/water system as a case study. Six intensified DWRED configurations are proposed and optimized using the non-dominated sorting genetic algorithm (NSGA-II), with the objectives of minimizing total annual cost (TAC), minimizing CO2 emissions (ECO2), and maximizing extraction efficiency. Compared to the DCRED configuration, the four proposed DWRED intensified configurations demonstrate improved economic and environmental performance. The heat exchanger network-heat pumpdividing wall reactive extractive distillation (HEN-HP-DWRED) configuration achieves a 53% reduction in total operating cost (TOC), an 18% reduction in TAC, a 59% reduction in ECO2, and a 41% decrease in high-pressure steam consumption. This study demonstrates that integrating multiple process intensification techniques significantly enhances the economic and environmental performance of the DWRED configuration. The proposed process intensification strategies provide a viable pathway for the development of sustainable DWRED processes.

Methyl ethyl ketone (MEK) and methanol (MeOH) are byproducts obtained during the destructive distillation of wood, forming an azeotrope that is challenging to separate using conventional distillation. Three ionic liquids (ILs) ([N2222][Ac], [HMMIM][Ac], and [N4441][Ac]) are selected as entrainers for separating the MEK/MeOH azeotrope via extractive distillation. The separation mechanisms of three ILs are analyzed using four quantum chemical computational methods: molecular dynamics simulations combined with density functional theory calculations, van der Waals surface penetration analysis, independent gradient model based on Hirshfeld partition analysis, and atoms in molecules analysis. The results indicate that [N2222][Ac] exhibits the best separation performance. Three ILs extractive distillation processes are developed, employing multiobjective optimization and multicriteria decision-making to obtain the optimal solution. The eco-indicator 99 (EI99) framework is utilized for life cycle assessment. The results indicate that the [N2222][Ac] process exhibits the lowest total operation cost (TOC), total annual cost (TAC), CO2 emissions (E CO2), and EI99 points, as well as the highest extraction efficiency. Flash vapor circulation heat pump (FVCHP) is implemented to intensify the [N2222][Ac] process. FVCHP-assisted [N2222][Ac] process achieves a TOC reduction of 49.6%, a TAC reduction of 11.9%, an E CO2 reduction of 62.7%, and an EI99 points reduction of 71.6%. This study encompasses multiple perspectives, including separation mechanisms, process scale performance, and life cycle assessment, providing a systematic evaluation approach for the application of ILs in azeotropic separations.

Investigating the molecular configuration of Naomaohu subbituminous coal (NSBC), a typical oil-rich coal in China, is crucial for optimizing its conversion processes. In this study, tetrahydrofuran (THF) was used as the solvent to study thermal dissolution (TD) of NSBC at 100-300 degrees C, and five soluble portions (SPn, n = 1-5) were obtained. The effects of THF on NSBC structure were analyzed by integrated two-dimensional gas chromatography/time-of-flight mass spectrometry (GCxGC/TOF-MS), X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectrum (FTIR). The results show that THF primarily disrupts intermolecular entanglements and aliphatic ether bonds (Cal-O) in the coal's macromolecular structure at 100-250 degrees C, meanwhile preserving the aromatic ring skeleton. THF forms stable hydrogen bonds with oxygen-containing functional groups in the coal, thereby facilitating the cleavage of aryl ether bonds (Car-O). At 300 degrees C, THF breaks hydrogen bonds and it-it interactions between benzene rings, resulting in the extraction of a higher quantity of highly polar and condensed polycyclic aromatic compounds. With the increase of TD temperature, the phenols in SPn showed an obvious increasing trend, and naphthol was observed at 300 degrees C. GCxGC/TOF-MS successfully isolated and identified a large number of low-concentration substances in SPn, such as seven isomers of C8H10O and six isomers of C9H12O at 100 degrees C. The distributions of carbon number (CN) and double bond equivalent (DBE) values of oxygen-containing compounds within the SPn were systematically examined. These findings contribute valuable insights into the thermochemical behavior of oil-rich coal and the efficacy of THF in modifying coal's macromolecular structure.

In the industrial synthesis of isobutyl acetate (IbAC) from isobutyl alcohol (IbOH) and acetic acid, excess IbOH forms an azeotrope with IbAC. Extractive distillation is widely used for azeotrope separation, yet conventional solvents are often toxic and volatile. Biobased solvents, being biodegradable and ecofriendly, offer a promising alternative. Screening with the conductor-like screening model for segment activity coefficient identified cinene and alpha-pinene as effective entrainers to break the IbOH-IbAC azeotrope. Ternary vapor-liquid equilibrium experiments confirmed that both solvents, when added at 20 mol %, eliminated the azeotrope. The nonrandom two-liquid model accurately correlated the experimental data. However, alpha-pinene formed a new azeotrope with IbOH at an atmospheric pressure. Toxicity assessment showed cinene has lower mammalian toxicity but higher aquatic toxicity than those of conventional solvents. Quantum chemical calculations revealed that stronger van der Waals interactions between cinene and IbAC reduce the activity coefficient of IbAC, facilitating separation.

Polymethoxy butyl ether (BTPOMn), a novel diesel additive developed for suppressing incomplete combustion emissions, was synthesized via an optimized batch slurry method employing n-butanol and trioxane (TOX) over NKC-9 acid cation-exchange resin (90–110 °C). A comprehensive kinetic model elucidated the reaction mechanism, addressing competitive pathways governing both main product formation and key side reactions—specifically polyoxymethylene hemiformals (HDn) and polyoxymethylene glycols (MG) generation. As the first detailed kinetic investigation of BTPOMn synthesis, this work provides a fundamental dataset and a robust predictive model that are crucial for process intensification and reactor design. Hybrid optimization integrating genetic algorithms with nonlinear least-squares regression achieved robust parameter estimation, with model predictions showing excellent agreement with experimental data. Thermal effects significantly influenced reaction rates, enhancing decomposition and propagation processes with increasing temperature. Optimal catalyst loading was identified at 3 and 6 wt.%, balancing reaction acceleration and byproduct suppression. Temperature-dependent equilibrium revealed chain length regulation through growth and depolymerization processes. This mechanistic understanding enables predictive reactor design for cleaner fuel additive synthesis. It provides critical insights for developing emission-control technologies in diesel engine systems.

During the alcoholysis of polyvinyl acetate to produce polyvinyl alcohol, large volumes of wastewater containing methanol (MeOH) and methyl acetate (MA) are generated. Due to the azeotropic nature of the MeOH-MA mixture under atmospheric pressure, their separation via conventional distillation is highly challenging. Extractive distillation presents a promising alternative; however, traditional entrainers often suffer from high volatility, toxicity, and significant energy requirements. Deep eutectic solvents (DESs), characterized by low vapor pressure, biodegradability, and ease of regeneration, have emerged as green alternatives. This study aims to identify efficient DESs for separating the MeOH/MA azeotrope. Guided by conductor-like screening model for segment activity coefficient (COSMO-SAC) model predictions, three choline chloride (ChCl)-based DESs-DES1 (ChCl:urea), DES2 (ChCl:ethylene glycol), and DES3 (ChCl:glycerol)-were selected and evaluated through vapor-liquid equilibrium (VLE) experiments at 101.3 kPa. The addition of 20 mol% DESs significantly enhanced the relative volatility of MA with respect to MeOH. The VLE data were well correlated using the non-random twoliquid (NRTL) model. To elucidate the separation mechanism, molecular dynamics simulations were performed to identify stable DES-MeOH/MA cluster configurations. Electrostatic potential (ESP) analysis, electron density difference mapping, van der Waals surface penetration, Hirshfeld surface (HS) analysis, the independent gradient model based on Hirshfeld partition (IGMH), and electron localization function (ELF) analyses revealed that hydrogen bonding plays a dominant role in selectivity. Finally, a quantitative structure-activity relationship (QSAR) based toxicity assessment confirmed that all three DESs exhibit substantially lower toxicity than conventional extractants. These findings underscore the potential of DESs as green entrainers for the efficient and sustainable separation of the MeOH/MA azeotropic system.

In chemical reaction processes, yield prediction frequently faces challenges, such as multi-variable coupling, significant nonlinearity, and the limited accuracy of traditional mechanistic models. This study develops a datadriven prediction model that integrates the genetic algorithm (GA) with CatBoost to address these challenges. Four variables, including reactant ratio (n-butanol to trioxane), reaction temperature, reaction time, and catalyst concentration, were selected as model inputs based on 88 sets of experimental data. The model outputs focused on the yield of polymethoxy dibutyl ether with a polymerization degree of 1 (BTPOM1) and the total yield of polymethoxy dibutyl ether with polymerization degrees of 1 to 8 (BTPOM1–8). The model achieved automatic optimization of CatBoost on hyperparameters by combining a hybrid-coding genetic algorithm. The results demonstrated that the GACatBoost model significantly outperformed GAAdaBoost for both datasets: for BTPOM1, it reduced the mean squared error (MSE) by 50.1%, mean absolute error (MAE) by 40.6%, and mean absolute percentage error (MAPE) by 17.8% relative to GAAdaBoost. For BTPOM1–8, the reductions were more pronounced, with MSE decreasing by 54.0%, MAE by 45.0%, and MAPE by 33.8% compared to GAAdaBoost. Additionally, the GACatBoost model significantly outperformed three classical machine learning algorithms: Support Vector Regression (SVR), Random Forest (RF), and KNearest Neighbor (KNN). Feature importance analysis revealed that reaction time and reaction temperature are the key factors influencing BTPOMn yield. This research provides a feasible approach for accurate synthesis yield prediction and process optimization under small sample conditions. It is particularly valuable for early-stage laboratory research where experimental data is often limited.

This study develops energy-efficient processes for producing pentane blowing agent (PBA) from light naphtha, addressing the challenge of valorizing C5-C6 fractions with limited utility. A novel heat-integrated dividing wall column (HI-DWC) configuration is designed, combining the advantages of the dividing wall column (DWC) with heat integration (HI). Five distillation configurations for producing PBA-double column (DC), DWC, heat integrated double column (HI-DC), HI-DWC, and heat exchanger network-heat integrated dividing wall column (HEN-HI-DWC)-are evaluated using multiobjective optimization. The results demonstrate that the HI-DWC configuration effectively eliminates the remixing effect of intermediate components, enabling complete HI and achieving energy-saving benefits that surpass those of individual process intensification methods. The HEN-HI-DWC configuration achieves the highest performance, reducing total operating cost by 55.5% and total annual cost by 20.8%, cutting CO2 emissions by 55.6% and improving thermodynamic efficiency by 129.5% compared to the DC configuration. This approach provides a sustainable and economically viable solution for light naphtha utilization.

Low-transition temperature mixtures (LTTMs) have been proposed as green solvents for the separation of ethanol (EtOH)/ethyl propionate (EtPa) azeotropes. COSMO-SAC model was used to screen LTTMs, and ammonium acetate, ethylammonium chloride, and choline chloride were selected as hydrogen bond acceptors to form LTTMs with ethylene glycol. Liquid-liquid phase equilibrium experiments were carried out for the screened LTTMs and the separation system to confirm the validity of the selected solvents. And the distribution coefficients of EtOH in the three LTTMs were all greater than 1.2, and the selectivity for EtOH ranged from 6 to 50. The separation mechanism at the molecular level was revealed through quantum chemical calculations and wave function analysis. The thermodynamic behavior of the EtOH/EtPa/LTTMs system and the role of hydrogen bonding interactions were systematically investigated. The results indicated that electrostatic forces are the main molecular interactions, and the stronger interaction of LTTMs with ethanol is the basis for achieving the azeotropic separation.

The gasoline fractionation scheme used in catalytic cracking has a significant impact on the blended gasoline's octane number. This study proposes an improved three-cut fractionation scheme for the fluid catalytic cracking gasoline fractionator and optimizes the process with respect to evaluation metrics such as total annual cost (TAC), light gasoline recovery, and CO2 emissions (ECO2). To achieve energy efficiency and reduce emissions in the process, the dividing wall column is employed for process intensification. In comparison to the cascaded binary columns process, the middle cracked naphtha recovery of the FCC-DWC-M has increased by 1.96%, the TAC has decreased by 22.15%, and the ECO2 has decreased by 26.18%. Finally, the study investigates the dynamic characteristics of the FCC-DWC-M process, establishes a control scheme, and examines its performance while experiencing disturbances in feed flow rates of ±10% and ±20%. The findings indicate exceptional control performance of the FCC-DWC-M process.