It is known that salt ions are abundant in the natural environment where natural gas hydrates are located; thus, it is essential to investigate the self-preservation effect of salt ions on methane hydrates. The dissociation behaviors of gas hydrates formed from various NaCl concentration solutions in a quartz sand system at 268.15 K were investigated to reveal the microscopic mechanism of the self-preservation effect under different salt concentrations. Results showed that as the salt concentration rises, the initial rate of hydrate decomposition quickens. Methane hydrate hardly shows self-preservation ability in the 3.35% (mass) NaCl and seawater systems at 268.15 K. Combined the morphology of hydrate observed by the confocal microscope with results obtained from in situ Raman spectroscopy, it was found that during the initial decomposition stage of gas hydrate below the ice point, gas hydrate firstly converts into liquid water and gas molecules, then turns from water to solid ice rather than directly transforming into solid ice and gas molecules. The presence of salt ions interferes with the ability of liquid water to condense into solid ice. The results of this study provide an important guide for the mechanism and application of the self-preservation effect on the storage and transport of gas and the exploitation of natural gas hydrates.

In response to the lack of reliable physical parameters in the process simulation of the butadiene extraction, a large amount of phase equilibrium data were collected in the context of the actual process of butadiene production by acetonitrile. The accuracy of five prediction methods, UNIFAC (UNIQUAC Functional-group Activity Coefficients), UNIFAC-LL, UNIFAC-LBY, UNIFAC-DMD and COSMO-RS, applied to the butadiene extraction process was verified using partial phase equilibrium data. The results showed that the UNIFAC-DMD method had the highest accuracy in predicting phase equilibrium data for the missing system. COSMO-RS-predicted multiple systems showed good accuracy, and a large number of missing phase equilibrium data were estimated using the UNIFAC-DMD method and COSMO-RS method. The predicted phase equilibrium data were checked for consistency. The NRTL-RK (non-Random Two Liquid-Redlich-Kwong Equation of State) and UNIQUAC thermodynamic models were used to correlate the phase equilibrium data. Industrial device simulations were used to verify the accuracy of the thermodynamic model applied to the butadiene extraction process. The simulation results showed that the average deviations of the simulated results using the correlated thermodynamic model from the actual values were less than 2% compared to that using the commercial simulation software, Aspen Plus and its database. The average deviation was much smaller than that of the simulations using the Aspen Plus database (>10%), indicating that the obtained phase equilibrium data are highly accurate and reliable. The best phase equilibrium data and thermodynamic model parameters for butadiene extraction are provided. This improves the accuracy and reliability of the design, optimization and control of the process, and provides a basis and guarantee for developing a more environmentally friendly and economical butadiene extraction process.

Ensuring the consistency of electrode structure in proton-exchange-membrane fuel cells is highly desired yet challenging because of wide-existing and unguided cracks in the microporous layer (MPL). The first thing is to evaluate the homogeneity of MPL with cracks quantitatively. This paper proposes the homogeneity index of a full-scale MPL with an area of 50 cm², which is yet to be reported in the literature to our knowledge. Besides, the effects of the carbon material and surfactant on the ink and resulting MPL structure have been studied. The ink with a high network development degree produces an MPL with low crack density, but the ink with high PDI produces an MPL with low crack homogeneity. The polarity of the surfactant and the non-polarity of polytetrafluoroethylene (PTFE) are not mutually soluble, resulting in the heterogeneous PTFE distribution. The findings of this study provide guidelines for MPL fabrication.

The separation of aromatic/aliphatic hydrocarbon mixtures is crucial in the petrochemical industry. Pervaporation is regarded as a promising approach for the separation of aromatic compounds from alkanes. Developing membrane materials with efficient separation performance is still the main task since the membrane should provide chemical stability, high permeation flux, and selectivity. In this study, the hyperbranched polymer (HBP) was deposited on the outer surface of a polyvinylidene fluoride (PVDF) hollow-fiber ultrafiltration membrane by a facile dip-coating method. The dip-coating rate, HBP concentration, and thermal cross-linking temperature were regulated to optimize the membrane structure. The obtained HBP/PVDF hollow-fiber-composite membrane had a good separation performance for aromatic/aliphatic hydrocarbon mixtures. For the 50%/50% (mass) toluene/n-heptane mixture, the permeation flux of optimized composite membranes could reach 1766 g·m^-2·h^-1, with a separation factor of 4.1 at 60 ℃. Therefore, the HBP/PVDF hollow-fiber-composite membrane has great application prospects in the pervaporation separation of aromatic/aliphatic hydrocarbon mixtures.

Copper-based metal-organic frameworks (Cu-MOFs) are a promising multiphase catalyst for catalyzing C-S coupling reactions by virtue of their diverse structures and functions. However, the unpleasant odor and instability of the organosulfur, as well as the mass-transfer resistance that exists in multiphase catalysis, have often limited the catalytic application of Cu-MOFs in C-S coupling reactions. In this paper, a Cu-MOFs catalyst modified by cetyltrimethylammonium bromide (CTAB) was designed to enhance mass transfer by increasing the adsorption of organic substrates using the long alkanes of CTAB. Concurrently, elemental sulfur was used to replace organosulfur to achieve a highly efficient and atom-economical multicomponent C-S coupling reaction.

The coal-to-ethanol process, as the clean coal utilization, faces challenges from the energy-intensive distillation that separates multi-component effluents for pure ethanol. Referring to at least eight columns, the synthesis of the ethanol distillation system is impracticable for exhaustive comparison and difficult for conventional superstructure-based optimization as rigorous models are used. This work adopts a superstructure-based framework, which combines the strategy that adaptively selects branches of the state-equipment network and the parallel stochastic algorithm for process synthesis. High-performance computing significantly reduces time consumption, and the adaptive strategy substantially lowers the complexity of the superstructure model. Moreover, parallel computing, elite search, population redistribution, and retention strategies for irrelevant parameters are used to improve the optimization efficiency further. The optimization terminates after 3000 generations, providing a flowsheet solution that applies two non-sharp splitting options in its distillation sequence. As a result, the 59-dimension superstructure-based optimization was solved efficiently via a differential evolution algorithm, and a high-quality solution with a 28.34% lower total annual cost than the benchmark was obtained. Meanwhile, the solution of the superstructure-based optimization is comparable to that obtained by optimizing a single specific configuration one by one. It indicates that the superstructure-based optimization that combines the adaptive strategy can be a promising approach to handling the process synthesis of large-scale and complex chemical processes.

Fabric multifunctionality offers resource savings and enhanced human comfort. This study innovatively integrates cooling, heating, and antimicrobial properties within a Janus fabric, surpassing previous research focused solely on cooling or heating. Different effects are achieved by applying distinct coatings to each side of the fabric. One graphene oxide (GO) coating exhibits exceptional light-to-heat conversion, absorbing and transforming light energy into heat, thereby elevating fabric temperature by 15.4 ℃, 22.7 ℃, and 43.7 ℃ under 0.2, 0.5, and 1 sun irradiation, respectively. Conversely, a hydrogel coating on one side absorbs water, facilitating heat dissipation through evaporation upon light exposure, reducing fabric temperature by 5.9 ℃, 8.4 ℃, and 7.1 ℃ in 0.2, 0.5, and 1 sun irradiation, respectively. Moreover, both sides of Janus fabric exhibit potent antimicrobial properties, ensuring fabric hygiene. This work presents a feasible solution to address crucial challenges in fabric thermal regulation, providing a smart approach for intelligent adjustment of body comfort in both summer and winter. By integrating heating and cooling capabilities along with antimicrobial properties, this study promotes sustainable development in textile techniques.

This work provides an overview of distillation processes, including process design for different distillation processes, selection of entrainers for special distillation processes, system integration and intensification of distillation processes, optimization of process parameters for distillation processes and recent research progress in dynamic control strategies. Firstly, the feasibility of using thermodynamic topological theories such as residual curve, phase equilibrium line and distillation boundary line to analyze different separation regions is discussed, and the rationality of distillation process design is discussed by using its feasibility. Secondly, the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process. The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications. Next, a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced. Finally, the improvement of dynamic control strategies for different distillation processes in recent years is summarized. This work focuses on the application of process intensification and system optimization in the design of distillation process, and analyzes the challenges, prospects, and development trends of distillation technology in the separation of multicomponent azeotropes.

The pyrolysis process of Shendong coal (SD) was first studied by combining the characteristics of thermal gravimetric (TG), pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) and Gray-King assay (G-K). The results show that the order of coke yields is G-K (76.35% (mass))>TG (73.11% (mass))>Py (70.03% (mass)). G-K coke yield caused by condensation reaction and secondary reaction accounts for 3.08% (mass) and 3.24% (mass), respectively. Compared with slow pyrolysis, fast pyrolysis has stronger fracture ability to coal molecules and can obtain more O-compounds, mono-ring aromatics and aliphatics. Especially, the content of phenolics increases significantly from 15.49% to 35.17%, but the content of multi-ring aromatics decreases from 23.13% to 2.36%. By comparing the compositions of Py primary tar and G-K final tar, it is found that secondary reactions occurred during G-K pyrolysis process include the cleavage of alkane and esters, condensation of mono-ring aromatics with low carbon alkene, ring opening, isomerization of tri-ring aromatics, hydrogenation of aromatics and acids.

The particle residence time distribution (RTD) and axial dispersion coefficient are key parameters for the design and operation of a pressurized circulating fluidized bed (PCFB). In this study, the effects of pressure (0.1-0.6 MPa), fluidizing gas velocity (2-7 m·s^-1), and solid circulation rate (10-90 kg·m^-2·s^-1) on particle RTD and axial dispersion coefficient in a PCFB are numerically investigated based on the multiphase particle-in-cell (MP-PIC) method. The details of the gas-solid flow behaviors of PCFB are revealed. Based on the gas-solid flow pattern, the particles tend to move more orderly under elevated pressures. With an increase in either fluidizing gas velocity or solid circulation rate, the mean residence time of particles decreases while the axial dispersion coefficient increases. With an increase in pressure, the core-annulus flow is strengthened, which leads to a wider shape of the particle RTD curve and a larger mean particle residence time. The back-mixing of particles increases with increasing pressure, resulting in an increase in the axial dispersion coefficient.

Heat integration is important for energy-saving in the process industry. It is linked to the persistently challenging task of optimal design of heat exchanger networks (HEN). Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem, it is not easy to find solutions of high quality for large-scale problems. The reinforcement learning (RL) method, which learns strategies through ongoing exploration and exploitation, reveals advantages in such area. However, due to the complexity of the HEN design problem, the RL method for HEN should be dedicated and designed. A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods. An insightful state representation of the HEN structure as well as a customized reward function is introduced. A Q-learning algorithm is applied to update the HEN structure using the ϵ-greedy strategy. Better results are obtained from three literature cases of different scales.

Crude oil scheduling optimization is an effective method to enhance the economic benefits of oil refining. But uncertainties, including uncertain demands of crude distillation units (CDUs), might make the production plans made by the traditional deterministic optimization models infeasible. A data-driven Wasserstein distributionally robust chance-constrained (WDRCC) optimization approach is proposed in this paper to deal with demand uncertainty in crude oil scheduling. First, a new deterministic crude oil scheduling optimization model is developed as the basis of this approach. The Wasserstein distance is then used to build ambiguity sets from historical data to describe the possible realizations of probability distributions of uncertain demands. A cross-validation method is advanced to choose suitable radii for these ambiguity sets. The deterministic model is reformulated as a WDRCC optimization model for crude oil scheduling to guarantee the demand constraints hold with a desired high probability even in the worst situation in ambiguity sets. The proposed WDRCC model is transferred into an equivalent conditional value-at-risk representation and further derived as a mixed-integer nonlinear programming counterpart. Industrial case studies from a real-world refinery are conducted to show the effectiveness of the proposed method. Out-of-sample tests demonstrate that the solution of the WDRCC model is more robust than those of the deterministic model and the chance-constrained model.

In order to provide basic design parameters for the industrial pyrolysis process, the transformation behavior of nitrogen was investigated using wheat straw as raw material. The distributions of nitrogen in pyrolysis char, oil, and gas were obtained and the nitrogenous components in the products were analyzed systematically by X-ray photoelectron spectroscopy (XPS), pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) and thermogravimetric-Fourier transform infrared spectrometry (TG-FTIR). The nitrogen distribution ranges of the pyrolysis char, oil, and gas were 37.34%–54.82%, 32.87%–40.94% and 10.20%–28.83%, respectively. More nitrogen was retained in char at lower pyrolysis temperature and the nitrogen distribution of oil was from rise to decline with increasing temperature. The most abundant N-containing compounds in three-phase products were pyrrole-N, amines, and HCN, respectively. In addition, the transformation mechanism of nitrogen from wheat straw to pyrolysis products was concluded.

Methane (CH₄) as a substitute for other mineral fuels plays a crucial role in reducing energy consumption and preventing environmental pollution. The present study employs a solvothermal method to fabricate a porous framework Co-metal-organic framework (Co-MOF) containing two distinct secondary building units (SBUs): an anionic [Co₂(μ₂-OH)(COO)₄(H₂O)] and a neutral [CoN₂(COO)₂]. Notably, within the anionic SBUs, the coordinated water molecules induce the generation of divergent unsaturated Co(II) centers in the unidirectional porous channels, thereby creating open metal sites. The adsorption performance of Co-MOF towards pure component gases was systematically investigated. The results demonstrated that Co-MOF exhibits superior adsorption capacity for C₂-C₃ hydrocarbons compared to CH₄, which offers the potential for efficient adsorption and separation of CH₄ from C₂-C₃ hydrocarbons. The gas selectivity separation ratios of Co-MOF for C₂H₆/CH₄ and C₃H₈/CH₄ were calculated using the ideal adsorbed solution theory method at 273/298 K and 0.1 MPa. The results revealed that Co-MOF achieved remarkable equilibrium separation selectivity for CH₄ and C₂-C₃ hydrocarbon gases among non-modified MOFs, signifying the potential of the synthesized Co-MOF for efficient recovery and purification of CH₄ from C₂-C₃ hydrocarbons. Breakthrough experiments further demonstrate the ability of Co-MOF to purify methane from C₂-C₃ hydrocarbons in practical gas separation scenarios. Additionally, molecular simulation calculations further substantiate the propensity of anionic SBUs to interact with C₂-C₃ hydrocarbon compounds. This study provides a novel paradigm for the development of porous MOF materials in the application of gas mixture separation.

Magnesium-ion batteries (MIBs) have attracted extensive attention due to their high theoretical capacity, superior safety, and low cost. Nonetheless, the development of MIBs is hindered by the lack of cathode materials with long cycle life and rate capability. MXene stands out as a prime choice for MIB cathode or collector for anode-free magnesium batteries (AFMBs) because of its larger surface area, adjustable surface properties, and good electrical conductivity. In this paper, we summarized the preparation and layering methods of MXene and discussed the prospects of MXene as a cathode or collector for MIBs. This review will be immensely beneficial in critically analyzing the synthesis techniques and the applications of MXene material as MIB cathode or AFMB collector. In addition, the challenges of the preparation and layering were concluded, along with raising the research strategies of MXene for storing Mg ions.

Solid polymer composite electrolytes possess the benefits of superior compatibility with electrodes and good thermal characteristics for more secure energy storage equipment. Herein, a new gel polymer electrolyte (GPE) containing NH₂-MIL-53(Al), [PP₁₃][TFSI], LiTFSI, and PVDF-HFP was prepared using a simple method of solution casting. The effects of encapsulating different ratios of ionic liquid ([PP₁₃][TFSI]) into the micropores of functionalized metal-organic frameworks (NH₂-MIL-53(Al)) on the electrochemical properties were compared. XRD, SEM, nitrogen adsorption-desorption isotherms, and electrochemical measurements were conducted. This GPE demonstrates a superior ionic conductivity of 8.08×10^-4 S·cm^-1 at 60 ℃ and can sustain a discharge specific capacity of 156.6 mA·h·g^-1 at 0.2 C for over 100 cycles. This work might offer a potential approach to alleviate the solid-solid contact with the solid-state electrolyte and electrodes and broaden a new window for the creation of all-solid-state batteries.

Efficiently modulating the velocity distribution and flow pattern of non-Newtonian fluids is a critical challenge in the context of dual shaft eccentric mixers for process intensification, posing a significant barrier for the existing technologies. Accordingly, this work reports a convenient strategy that changes the kinetic energy to controllably regulate the flow patterns from radial flow to axial flow. Results showed that the desired velocity distribution and flow patterns could be effectively obtained by varying the number and structure of baffles to change kinetic energy, and a more uniform velocity distribution, which could not be reached normally in standard baffle dual shaft mixers, was easily obtained. Furthermore, a comparative analysis of velocity and shear rate distributions is employed to elucidate the mechanism behind the generation of flow patterns in various dual-shaft eccentric mixers. Importantly, there is little difference in the power number of the laminar flow at the same Reynolds number, meaning that the baffle type has no effect on the power consumption, while the power number of both unbaffle and U-shaped baffle mixing systems decreases compared with the standard baffle mixing system in the transition flow. Finally, at the same rotational condition, the dimensionless mixing time of the U-shaped baffle mixing system is 15.3% and 7.9% shorter than that of the standard baffle and the unbaffle mixing system, respectively, which shows the advantage of the U-shaped baffle in stirring rate.

In order to remove hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), the main impurity, in process of polymorphic transformation of octrahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX), the solubility of β-HMX and RDX in acetonitrile (ACN) + water in the temperature range of 288.15-333.15 K and in nitric acid (HNO₃) + water in the temperature range of 298.15-333.15 K were measured by laser dynamic method. The results showed that the solubility of both β-HMX and RDX in binary mixed solvents increased monotonously as the temperature increase at a given solvent composition or with increasing of mole fraction of solvent (ACN and nitric acid). Solubility data were well correlated by the modified Apelblat equation, Jouyban-Acree model, Yaws equation and van't Hoff equation, and the Yaws equation achieved the best fitting results according to the relative error and the mean square error root. Furthermore, the solubility of β-HMX and RDX in binary mixed solvent was compared, based on the solubility difference and the solvent's own properties, the best separation degree of β-HMX and RDX was found when the mole fraction of nitric acid was 0.22 at room temperature, which provided data support for HMX crystallization in mixed solvent. The solubility differences between RDX and β-HMX in mixed solvents were explained from the formation of intermolecular and intramolecular hydrogen bonds.

In this work, we utilize a cocrystallization technique to solve the problem of high hygroscopicity of the high-energy oxidant ammonium dinitramide (ADN). For this purpose, a non-hygroscopic oxidant, triaminoguanidine nitrate (TAGN), is selected as the cocrystallization ligand. The ADN/TAGN system is simulated by using Material Studio 5.5 software, and the DFT of ADN and TAGN molecules are calculated by Gaussian09 software. The most stable molar ratio of the ADN/TAGN cocrystallization is determined to be 1:1, and the hydrogen bonding between the H atom of ADN and the O atom in the TAGN is the driving force for the formation of cocrystals in this system. Moreover, the electrostatic potential interaction pairing energy difference (△E_pair) < 0 kJ·mol^-1 (-12.71 kJ·mol^-1) for n_ADN:n_TAGN = 1:1 again indicates cocrystallization at this molar ratio. The crystal structure and crystal morphology is predicted. And the hygroscopicity of ADN/TAGN cocrystal at 20 °C and 40% relative humidity is calculated to be only 0.45%. The mechanism of hygroscopicity is investigated by examining the roughness of each crystal surface. Overall, the more hygroscopic it is in terms of surface roughness, with the roughest crystal surface (0 1 $\overline{2}$) having a hygroscopicity of 1.78, which corresponds to a saturated hygroscopicity of 0.61%. The results show that the (0 0 1) crystal surface has the smallest band gap (1.06 eV) and the largest sensitivity. Finally, the oxygen equilibrium value for the ADN/TAGN system is calculated to be -8.2%.