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.

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%.

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.

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.

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.

Ligament cryopreservation enables a prolonged shelf life of allogeneic ligament grafts, which is fundamentally important to ligament reconstruction. However, conventional cryopreservation techniques fail to eliminate the damage caused by ice crystal growth and the toxicity of cryopreservation agents (CPAs). Here, we report a novel CPA vitrification formulation primarily composed of betaine for ligament cryopreservation. Comprehensive optimization was conducted on the methods for vitrification and rewarming, as well as the loading and unloading conditions, based on the critical cooling rate (CCR), critical warming rate (CWR), and permeation properties of the CPA. Using biomechanical and histological level tests, we demonstrate the superior performance of our method in ligament cryopreservation. After 30 days of vitrification cryopreservation, parameters such as the Young's modulus, tensile stress, denaturation temperature, and glycosaminoglycans content of the ligament remained essentially unchanged. This work pioneers the application of ice-free cryopreservation for ligament and holds great potential for improving the long-term storage of ligament, providing valuable insights for future cryopreservation technique development.

The current methods used to industrially produce sinomenine hydrochloride involve several issues, including high solvent toxicity, long process flow, and low atomic utilization efficiency, and the greenness scores of the processes are below 65 points. To solve these problems, a new process using anisole as the extractant was proposed. Anisole exhibits high selectivity for sinomenine and can be connected to the subsequent water-washing steps. After alkalization of the medicinal material, heating extraction, water washing, and acidification crystallization were carried out. The process was modeled and optimized. The design space was constructed. The recommended operating ranges for the critical process parameters were 3.0–4.0 h for alkalization time, 60.0–80.0 °C for extraction temperature, 2.0–3.0 (volume ratio) for washing solution amount, and 2.0–2.4 mol·L^-1 for hydrochloric acid concentration. The new process shows good robustness because different batches of medicinal materials did not greatly impact crystal purity or sinomenine transfer rate. The sinomenine transfer rate was about 20% higher than that of industrial processes. The greenness score increased to 90 points since the novel process proposed in this research solves the problems of long process flow, high solvent toxicity, and poor atomic economy, better aligning with the concept of green chemistry.

Acetic acid and furfural are known as prevalent inhibitors deriving from pretreatment during lignocellulosic ethanol production. They negatively impact cell growth, glucose uptake and ethanol biosynthesis of Saccharomyces cerevisiae strains. Development of industrial S. cerevisiae strains with high tolerance towards these inhibitors is thus critical for efficient lignocellulosic ethanol production. In this study, the acetic acid or furfural tolerance of different S. cerevisiae strains could be significantly enhanced after adaptive evolution via serial cultivation for 40 generations under stress conditions. The acetic acid-based adaptive strain SPSC01-TA9 produced 30.5 g·L^-1 ethanol with a yield of 0.46 g·g^-1 in the presence of 9 g·L^-1 acetic acid, while the acetic acid/furfural-based adaptive strain SPSC01-TAF94 produced more ethanol of 36.2 g·L^-1 with increased yield up to 0.49 g·g^-1 in the presence of both 9 g·L^-1 acetic acid and 4 g·L^-1 furfural. Significant improvements were also observed during non-detoxified corn stover hydrolysate culture by SPSC01-TAF94, which achieved ethanol production and yield of 29.1 g·L^-1 and 0.49 g·g^-1, respectively, the growth and fermentation efficiency of acetic acid/furfural-based adaptive strain in hydrolysate was 95% higher than those of wildtype strains, indicating the acetic acid- and furfural-based adaptive evolution strategy could be an effective approach for improving lignocellulosic ethanol production. The adapted strains developed in this study with enhanced tolerance against acetic acid and furfural could be potentially contribute to economically feasible and sustainable lignocellulosic biorefinery.

At present, commercial Li-ion batteries are hardly to satisfy the growing demand for high energy density, for this purpose, lithium metal batteries have attracted worldwide attention in recent years. However, its practical applications are hindered by the formation of Li dendrites and volume effect during Li plating/stripping process, which leads to a lot of safety hazards. Herein, we first employed MOF-derived V₂O₅ nanoparticles to decorate the carbon fiber cloth (CFC) backbone to acquire a lithiophilic 3D porous conductive framework (CFC@V₂O₅). Subsequently, the CFC@V₂O₅ skeleton was permeated with molten Li to prepare CFC@V₂O₅@Li composite anode. The CFC@V₂O₅@Li composite anode can be stably cycled for more than 1650 h at high current density (5 mA·cm^-2) and areal capacity (5 mA·h·cm^–2). The prepared full cell can initially maintain a high capacity of about 143 mA·h·g^-1 even at a high current density of 5 C, and can still maintain 114 mA·h·g^-1 after 1000 cycles.

To address the hazardous by-product of zinc smelting and resource utilization of jarosite residue, this study applies an electric field-assisted hot acid treatment to completely recycle iron (Fe). This innovative approach aims to enhance the leaching efficiency of Fe from jarosite residue. The introduction of an electric field changes the charge distribution on the surface of the particles to enhance ions and electrons exchange and promotes the collision between particles to strengthen reaction kinetics. Based on the above, the leaching efficiency of Fe in jarosite under sulfuric acid attack has improved observably. The result shows that Fe leaching efficiency reaches 98.83%, which is increased by 28% under the optimal experimental conditions: current density of 30 mA·cm^-2, H₂SO₄ concentration of 1.5 mol·L^-1, solid-liquid ratio of 70 g·L^-1, temperature of 80 °C and time of 12 h. Leaching kinetics calculations show that the apparent activation energy is 16.97 kJ·mol^-1 and the leaching of jarosite residue is controlled by a mixture of chemical reaction and diffusion, as well as the temperature and concentration of the leaching solution have an influence on leaching. This work provides a feasible idea for the efficient leaching of Fe from jarosite residue.

The effects of various contaminants in the electrolytic refinement of indium were investigated using a glow discharge mass spectrometer (GDMS). The effects of several factors such as the indium ion (In³⁺) concentration, the sodium chloride (NaCl) concentration, the current density, the gelatin concentration, the pH, and the electrode distance, were examined. Significant variations in impurity levels concerning gelatin concentration were observed. Both the gelatin and In³⁺ concentration were moderately positively correlated with the Pb content. The Sb concentration was associated positively with the NaCl concentration, while the Ti concentration had an adverse correlation with the NaCl concentration. The Bi element content was positively linked to the electrode distance. As the current density increased, Cu, Pb, and Bi impurities initially rose and then eventually declined. Notably, a critical current density of 45 A·m^-2 was identified in this behavior.

This study delves into the intricate deposition dynamics of submicron particles within electric-flow coupled fields, underscoring the unique challenges posed by their minuscule size, aggregation tendencies, and biological reactivity. Employing an operando investigation system that synergizes microfluidic technology with advanced micro-visualization techniques within a lab-on-a-chip framework enables a meticulous examination of the dynamic deposition phenomena. The incorporation of object detection and deep learning methodologies in image processing streamlines the automatic identification and swift extraction of crucial data, effectively tackling the complexities associated with capturing and mitigating these hazardous particles. Combined with the analysis of the growth behavior of particle chain under different applied voltages, it established that a linear relationship exists between the applied voltage and θ. And there is a negative correlation between the average particle chain length and electric field strength at the collection electrode surface (4.2×10⁵ to 1.6×10⁶ V·m^-1). The morphology of the deposited particle agglomerate at different electric field strengths is proposed: dendritic agglomerate, long chain agglomerate, and short chain agglomerate.

A biochar-supported green nZVI (G-nZVI@MKB) composite was synthesized using mango kernel waste with “dual identity” as reductant and biomass of biochar. The G-nZVI@MKB with a Fe/C mass ratio of 2.0 (G-nZVI@MKB2) was determined as the most favorable composite for hexavalent chromium (Cr(VI)) removal. Distinct influencing parameters were discussed, and 99.0% of Cr(VI) removal occurred within 360 min under these optimized parameters. Pseudo-second order kinetic model and intra-particle diffusion model well depicted Cr(VI) removal process. The XRD, FTIR, SEM, and XPS analyses verified the key roles of G-nZVI and functional groups, as well as the primary removal mechanisms involving electrostatic attraction, reduction, and complexation. G-nZVI@MKB2 exhibited good stability and reusability with only a 16.4% decline in Cr(VI) removal after five cycles. This study offered evidence that mango kernel could be recycled as a beneficial resource to synthesize green nZVI-loaded biochar composite for efficient Cr(VI) elimination from water.

The construction of a stable-membrane tracker has significant implications for the visualization of the membrane in live cells. However, most current plasma trackers are not suitable for tracking plasma membranes for a long time due to their limited retention time. Herein, Mem580-F-Sulfo is designed to target and anchor cell membranes and therefore track cell membranes for a longer time. This tracker is composed of a lipophilic boron-dipyrromethene (BODIPY) derivative and a hydrophilic zwitterion to form an amphiphilic structure, which enables its targeting ability toward cell membranes. Moreover, a reactive ester group is included to bind with proteins through covalent bonds in cell membranes non-specifically, which extends retention time in cell membranes. Mem580-F-Sulfo shows intense brightness (94600), with a high molar absorption coefficient of up to about 100000 L·mol^-1·cm^-1 and a fluorescence quantum yield of up to 0.97. It shows fast cell membrane targeting ability and long retention up to 90 min. In brief, this work has not only developed a tracker with good cell membrane targetability but also provided a new strategy for improving the targeting stability of cell membranes.

Circulating fluidized bed flue gas desulfurization (CFB-FGD) process has been widely applied in recent years. However, high cost caused by the use of high-quality slaked lime and difficult operation due to the complex flow field are two issues which have received great attention. Accordingly, a laboratory-scale fluidized bed reactor was constructed to investigate the effects of physical properties and external conditions on desulfurization performance of slaked lime, and the conclusions were tried out in an industrial-scale CFB-FGD tower. After that, a numerical model of the tower was established based on computational particle fluid dynamics (CPFD) and two-film theory. After comparison and validation with actual operation data, the effects of operating parameters on gas-solid distribution and desulfurization characteristics were investigated. The results of experiments and industrial trials showed that the use of slaked lime with a calcium hydroxide content of approximately 80% and particle size greater than 40 μm could significantly reduce the cost of desulfurizer. Simulation results showed that the flow field in the desulfurization tower was skewed under the influence of circulating ash. We obtained optimal operating conditions of 7.5 kg·s^-1 for the atomized water flow, 70 kg·s^-1 for circulating ash flow, and 0.56 kg·s^-1 for slaked lime flow, with desulfurization efficiency reaching 98.19% and the exit flue gas meeting the ultraclean emission and safety requirements. All parameters selected in the simulation were based on engineering examples and had certain application reference significance.

The removal of organic sulfur through catalytic hydrolysis is a significant area of research in the field of desulfurization. This review provides an overview of recent advancements in catalytic hydrolysis technology of organic sulfur, including the activity, stability, and atmosphere effects of hydrolysis catalysts. The emphasis is on strategies for enhancing hydrolysis activity and anti-oxygen poisoning property of catalysts. Surface modification, metal doping and nitrogen doping have been found to improve the activity of catalysts. Alkaline components modification is the most commonly used method, the formation of oxygen vacancies through metal doping and creation of nitrogen basic sites through nitrogen doping also contribute to the hydrolysis of organic sulfur. The strategies for anti-oxygen poisoning are discussed in a systematic manner. The structural regulation of catalysts is beneficial for the desorption and diffusion of hydrogen sulfide (H₂S), thereby effectively inhibiting its oxidation. Nitrogen doping and the addition of electronic promoters such as transition metals can protect active sites and decrease the number of active oxygen species. These methods have been proven to enhance the anti-poisoning performance of catalysts. Additionally, this article summarizes how different atmospheres affect the activity of hydrolysis catalysts. The objective of this review is to pave the way for the development of efficient, stable and widely used catalysts for organic sulfur hydrolysis.

The gasoline inline blending process has widely used real-time optimization techniques to achieve optimization objectives, such as minimizing the cost of production. However, the effectiveness of real-time optimization in gasoline blending relies on accurate blending models and is challenged by stochastic disturbances. Thus, we propose a real-time optimization algorithm based on the soft actor-critic (SAC) deep reinforcement learning strategy to optimize gasoline blending without relying on a single blending model and to be robust against disturbances. Our approach constructs the environment using nonlinear blending models and feedstocks with disturbances. The algorithm incorporates the Lagrange multiplier and path constraints in reward design to manage sparse product constraints. Carefully abstracted states facilitate algorithm convergence, and the normalized action vector in each optimization period allows the agent to generalize to some extent across different target production scenarios. Through these well-designed components, the algorithm based on the SAC outperforms real-time optimization methods based on either nonlinear or linear programming. It even demonstrates comparable performance with the time-horizon based real-time optimization method, which requires knowledge of uncertainty models, confirming its capability to handle uncertainty without accurate models. Our simulation illustrates a promising approach to free real-time optimization of the gasoline blending process from uncertainty models that are difficult to acquire in practice.