This work applied molecular dynamics (MD) simulation to calculate densities of natural gas mixtures at extremely high pressure (>138 MPa) and high temperature (>200 ℃) conditions (xHPHT) to bridge the knowledge and technical gaps between experiments and classical theories. The experimental data are scarce at these conditions which are also out of assumptions for classical predictive correlations, such as the Dranchuk & Abou-Kassem (DAK) equation of state (EOS). Force fields of natural gas components were carefully chosen from literatures and the simulation results are validated with experimental data. The largest relative error is 2.67% for pure hydrocarbons, 2.99% for C1/C3 mixture, 7.85% for C1/C4 mixture, and 8.47% for pure H₂S. These satisfactory predictions demonstrate that the MD simulation approach is reliable to predict natural- and acid-gases thermodynamic properties. The validated model is further used to generate data for the study of the EOS with pressure up to 276 MPa and temperature up to 573 K. Our results also reveal that the Dranchuk & Abou-Kassem (DAK) EOS is capable of predicting natural gas compressibility to a satisfactory accuracy at xHPHT conditions, which extends the confidence range of the DAK EOS.

It is important to study the solvent effect on keto-enol tautomerism that has applications in many areas of chemical engineering. In this work, we use a multiscale reaction density functional theory (RxDFT) to study the keto-enol tautomerism and isomerization of pyruvic acid. The results show that both effects of solvation and water assistance could reduce the reaction barriers. The water molecule participates the reaction as a catalyst to accept/give the protons with forming a hexagonal ring in the transition state. As a result of this temporary and intermediate hexagonal ring, the solute configuration undergoes a small variation during the reaction, giving a diminished contribution to the intrinsic reaction free energy. The solvent distribution shows a local ordering behavior near the solute that also reduces the contribution of solvation effect to the reaction barrier. Water assistance plays a major role in both pre-reaction and post-reaction process. In terms of the driving force for the reaction, the effects of both solvation and water assistance are important.

The prime objective of the present communication is to examine the entropy-optimized second order velocity slip Darcy–Forchheimer hybrid nanofluid flow of viscous material between two rotating disks. Electrical conducting flow is considered and saturated through Darcy–Forchheimer relation. Both the disks are rotating with different angular frequencies and stretches with different rates. Here graphene oxide and titanium dioxide are considered for hybrid nanoparticles and water as a continuous phase liquid. Joule heating, heat generation/absorption and viscous dissipation effects are incorporated in the mathematical modeling of energy expression. Furthermore, binary chemical reaction with activation energy is considered. The total entropy rate is calculated in the presence of heat transfer irreversibility, fluid friction irreversibility, Joule heating irreversibility, porosity irreversibility and chemical reaction irreversibility through thermodynamics second law. The nonlinear governing equations are first converted into ordinary differential equations through implementation of appropriate similarity transformations and then numerical solutions are calculated through Built-in-Shooting method. Characteristics of sundry flow variables on the entropy generation rate, velocity, concentration, Bejan number, temperature are discussed graphically for both graphene oxide and titanium dioxide hybrid nanoparticles. The engineering interest like skin friction coefficient and Nusselt number are computed numerically and presented through tables. It is noticed from the obtained results that entropy generation rate and Bejan number have similar effects versus diffusion parameter. Also entropy generation rate is more against the higher Brinkman number.

The gas-containing nanobubbles have attracted extensive attention due to their remarkable properties and extensive application potential. However, a number of fundamental aspects of nanobubbles, including thermodynamic states for the confined gas, remain still unclear. Here we theoretically demonstrate that the van der Waals (vdW) gases confined in nanobubbles exhibit a unique thermodynamic state of remarkably deviating from the bulk gas phase, and the state transition behavior due to the size-dependent Laplace pressure. In general, the vdW gas inside nanobubbles present multiple stable or transient states, where 0–2 states are for supercritical gas and 0–4 for subcritical gas. Our further analysis based on Rayleigh–Plesset equation and free energy determination indicates that the gas states in nanobubbles exhibits different levels of stability, from which the coexistence of multiple bubble states and microphase equilibrium between droplets and bubbles are predicted. This work provides insight to understand the thermodynamic states appeared for gas in nanobubbles.

Understanding the electrokinetic conversion efficiency in a nanochannel is vital for designing energy storage and conversion devices. In this paper, an analytical electrokinetic energy conversion efficiency in a nanochannel is obtained based on the linear electrokinetic response. The analytical result shows that the conversion efficiency has a maximum with the increasing of the nanochannel pore radius. Numerical solutions based on the Poisson-Nernst-Planck (PNP) and Navier-Stokes (NS) equations are used to confirm the analytical expressions. Besides, the influences of the pore radius and surface roughness on the conversion efficiency in nanochannels are also studied by the numerical calculations. In particular, the influences of the surface roughness on the fluid flow, streaming current and streaming potential are examined. The results show that the large bumps and grooves representing the roughness can hinder the fluid flows and ion transports in the nanochannels. The maximum efficiency in a smooth nanochannel is higher than that in a rough channel. However, the small bumps and grooves can increase the surface area of the channel, which is beneficial to improving the conversion efficiency in some cases. This research can provide theoretical guidance to design electrokinetic energy conversion devices.

How to completely remove the water from ionic liquids (ILs) is difficult for researchers because of the hygroscopicity of ILs. In order to study the hygroscopicity of ILs, two kinds of ILs, 1-Butyl-3-methylimidazolium hexafluorophosphate ([Bmim][PF₆]) and 1-Butyl-3-methylimidazolium Bis(trifluoromethanesulfonyl) ([Bmim][NTf₂]) were investigated by molecular dynamics simulations. Although [Bmim][PF₆] and [Bmim][NTf₂] are hydrophobic, both of the ILs could absorb water molecules from the vapor. In this work, the process of absorbing water from the vapor phase was studied, and the water molecules could disperse into the IL. Aggregation was observed with increasing the water concentration. Although the absorbed water increases obviously, the amount of free water and small cluster in the ILs does not change significantly and always stays at a certain level. The amount of free water and small cluster in [Bmim][PF₆] is more than that in [Bmim][NTf₂], which is consistent with their hydrophobicity. In addition, the liquid-vacuum and liquid–liquid interfaces of the ILs were simulated and analyzed in detail. The number density distribution and angle distribution indicated that [Bmim]⁺ cations arrangement regularly at the IL-vacuum interface. The butyl chain point to the vacuum, while the imidazlium ring is close to the IL phase region and perpendicular to the interface. While at the IL-water interface, the cations and anions are disordered.

The increasing concentration of CO₂ in atmosphere is deemed the main reason of global warming. Therefore, efficiently capturing CO₂ from various sources with energy conservation is of great significance. Herein, a series of experiments were carried out to successfully test the slurry-based ab-adsorption method for continuously capturing CO₂ in the large-scale cycled separation unit with cost-effect taking into account the scale-up criteria. A bubble column (with height 4900 mm and inner diameter 376 mm) and a desorption tank (with volume 310 L) are the essential components of the separation unit. The novel slurry used in this study was formed with zeolitic imidazolate framework-8 and 2-methylimidazole-water solution. The influence of operation conditions was investigated systematically. The results show that increasing sorption pressure and slurry height level, decreasing gas volume flow and sorption temperature are beneficial for separation processes. The volume fraction of CO₂ in the feed gas was also studied. Although the scale-up effect had been observed and it was found that it exerted a negative effect on CO₂ capture, depending on experimental conditions, CO₂ removal efficiency could still reach 85%-95% and the maximum CO₂ loading in the recycled slurry could be up to 0.007 mol·L^-1·kPa^-1. Furthermore, the slurry-based method could be operated well even under very moderate regeneration conditions (333 K and 0.05 MPa), which means that the novel approach shows greater energy conservation than traditional amine absorption methods.

The interaction of water with TiO₂ surfaces is of enduring interest because of wide applications of the TiO₂ materials in aqueous environments. The structure and dynamic properties of water molecules in TiO₂ nanopores are crucial as increasingly TiO₂ materials are synthesized into nanoporous structures. In this work, the structural and dynamic properties of water molecules in nanoscale slit pores of TiO₂ are investigated, by using three sets of force field models for the water- TiO₂ interaction, as well as four TiO₂ slit pore widths. It is concluded that the water- TiO₂ interaction dominates the interfacial structure of water molecules, while the dynamic properties of water molecules are primarily influenced by the slit width in both interfacial and central regions. These findings indicate that both of the fluid properties and the interactions of fluids with pore wall will determine the transport properties of fluid in nanopores. If the pore size is large enough, e.g. 1.0 nm or larger in this work, the transport properties will be determined most by the fluids themselves. For the cases of pores whose sizes are in the range of interfacial region, the influences of pore size and interfacial interaction will interfere each other.

Electrochemical reduction of CO₂ is a novel research field towards a CO₂-neutral global economy and combating fast accelerating and disastrous climate changes while finding new solutions to store renewable energy in value-added chemicals and fuels. Ionic liquids (ILs), as medium and catalysts (or supporting part of catalysts) have been given wide attention in the electrochemical CO₂ reduction reaction (CO₂RR) due to their unique advantages in lowering overpotential and improving the product selectivity, as well as their designable and tunable properties. In this review, we have summarized the recent progress of CO₂ electro-reduction in IL-based electrolytes to produce higher-value chemicals. We then have highlighted the unique enhancing effect of ILs on CO₂RR as templates, precursors, and surface functional moieties of electrocatalytic materials. Finally, computational chemistry tools utilized to understand how the ILs facilitate the CO₂RR or to propose the reaction mechanisms, generated intermediates and products have been discussed.

Styrene-butadiene rubber (SBR) is widely used in tires in the automotive segment and vulcanization using sulfur is a common process to enhance its mechanical properties. However, the addition of sulfur as the cross-linking agent usually results in impurities in pyrolysis products during rubber recycling, and thus the desulfurization during tire pyrolysis attracts much attention. In this work, the pyrolysis of vulcanized SBR is studied in detail with the help of ReaxFF molecular dynamics simulation. A series of crosslinked SBR models were built with different sulfur contents and densities. The following ReaxFF MD simulations were performed to show products distributions at different pyrolysis conditions. The simulation results show that sulfur products distribution is mainly controlled by sulfur contents and temperatures. The reaction mechanism is proposed based on the analysis of sulfur products conversion pathway, where most sulfur atoms are bonded with hydrocarbon radicals and the rest transfer to H₂S. High sulfur contents tend to the formation of elemental sulfur intermediate, and temperature increase facilitates the release of H₂S.

To improve the stability of nanoparticles in aqueous solution, polymer or surfactant, etc. are often added in solutions during the preparation process of nanoparticles, which can induce new interfaces that influence the solubility of nanoparticles. In this work, a novel interfacial thermodynamic model for describing the Gibbs energy of the nanoparticles coated by stabilizers was proposed to predict the solubility of nanoparticles. Within the developed model, the activity coefficient of nano metal system was determined by Davies model and that of nano drug system by Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT). The Gibbs energy of the interface was established as a function of molecular parameters via the application for nano metal system. Furthermore, the model was further used to predict the solubility of nano drugs itraconazole, fenofibrate, and griseofulvin. It was found that the Gibbs energy of the interface plays an important role especially when the radius of nano metal is less than 40 nm, and the developed model can predict the solubility of nano drug with high accuracy in comparison with the experimental data as well as predict the changing trend of solubility of nano drugs that increases as the particle size decreases. Meanwhile, the stabilization mechanism of stabilizers on nano drugs was studied which provided theoretical guidance for the selection of polymer or surfactant stabilizer. These findings showed that the developed model can provide a reliable prediction of the solubility of nanoparticles and help to comprehend the stabilization mechanism of the stabilizers on nano drugs with different particle sizes, which is expected to provide important information for the design of nano drugs formulations.

The increased concentration of CO₂ due to continuous breathing and no discharge of human beings in the manned closed space, like spacecraft and submarines, can be a threat to health and safety. Effective removal of low concentration CO₂ from the manned closed space is essential to meet the requirements of long-term space or deep-sea exploration, which is an international frontier and trend. Ionic liquids (ILs), as a widespread and green solvent, already showed its excellent performance on CO₂ capture and absorption, indicating its potential application in low concentration CO₂ capture. In this review, we first summarized the current methods and strategies for direct capture from low concentration CO₂ in both the atmosphere and manned closed spaces. Then, the multi-scale simulation methods of CO₂ capture by ionic liquids are described in detail, including screening ionic liquids by COSMO-RS methods, capture mechanism by density functional theory and molecular dynamics simulation, and absorption process by computational fluid dynamics simulation. Lastly, some typical IL-based green technologies for low concentration CO₂ capture, such as functionalized ILs, co-solvent systems with ILs, and supported materials based on ILs, are introduced, and analyzed the subtle possibility in manned closed spaces. Finally, we look forward to the technology and development of low concentration CO₂ capture, which can meet the needs of human survival in closed space and proposed that supported materials with ionic liquids have great advantages and infinite possibilities in the vital area.

The choice of support is one of the most significant components in the direct synthesis of H₂O₂. Aiming to improvement of activity and selectivity of H₂O₂ on Pd/TiO₂ surface, we systematically investigated the important elementary steps on Pd/TiO₂-Vo@C, Pd/TiO₂-Vo, Pd/TiO₂-2Vo, Pd/TiO₂, and Pd/C using the first-principles calculations. The Bader charge analysis and charge density difference of O2 adsorption elucidate the relationship between the electronic distribution and chemisorption energy. The effective barrier analysis further enables to quantitatively estimate the reactivity of H₂O₂ and H₂O. We demonstrate unambiguously that the selectivity of H₂O formation is boosted as the oxygen vacancy concentration raised. Moreover, the introduction of C into a TiO₂ with appropriate oxygen vacancies can slightly reduce the effective barrier for H₂O₂ formation and increase the effective barrier for H₂O formation leading to a higher activity and selectivity of H₂O₂ formation. Our finding suggests that carbon-doped oxygen vacancy TiO₂ supported Pd is potential alternative catalyst compared with the Pd/TiO₂.

Ethylene oxide (EO) is an important raw material for producing ethylene carbonate (EC). However, the traditional method for the separation of EO from mixture gas by water in the refining process is high energy consumption. In this paper, two processes of manufacturing EC from EO mixture gas were studied by process simulation. Two processes for producing EC from EO mixture as raw materials without EO purification, called the OSAC process and the Modified OSAC process, were developed and assessed systematically. Both processes use EC as the absorbent to capture EO, avoiding the separation process of EO from solution. For comparisons, the EC producing process containing EO absorption by water, EO refinement and carbonylation process were also modeled, which was called the ERC process. Three schemes were designed for the EO absorber using EC as absorbent. Compared with the initial absorber scheme, the optimal liquid–vapor ratio is reduced from 1.66 to 1.45 (mass). Moreover, the mass distribution analysis for the three processes were carried out in the form of the material chain. It was found that, compared with the ERC process, the energy consumption of the OSAC and the Modified OSAC process is reduced by 56.89% and 30.03%, respectively. This work will provide helpful information for the industrialization of the OSAC process.

Understanding the microscopic structure and thermodynamic properties of electrode/electrolyte interfaces is central to the rational design of electric-double-layer capacitors (EDLCs). Whereas practical applications often entail electrodes with complicated pore structures, theoretical studies are mostly restricted to EDLCs of simple geometry such as planar or slit pores ignoring the curvature effects of the electrode surface. Significant gaps exist regarding the EDLC performance and the interfacial structure. Herein the classical density functional theory (CDFT) is used to study the capacitance and interfacial behavior of spherical electric double layers within a coarse-grained model. The capacitive performance is associated with electrode curvature, surface potential, and electrolyte concentration and can be correlated with a regression-tree (RT) model. The combination of CDFT with machine-learning methods provides a promising quantitative framework useful for the computational screening of porous electrodes and novel electrolytes.

The research on the adsorption equilibria, kinetics, and increase in process temperature of the volatile organic compound (VOC) adsorption in porous materials ensures safe production, thereby reducing production costs and improving separation efficiency. Therefore, it is critical in predicting the entire adsorption process based on minimal or no experimental input of the adsorbate and adsorbent. We discuss, in this review, the factors that affect the adsorption performance of VOCs in activated carbons, including the adsorption equilibrium, adsorption kinetics, and exotherm during adsorption. Subsequently, the existing prediction models are summarized and compared concerning the adsorption equilibrium, adsorption kinetics, and exothermic process of adsorption. We then propose a new prediction model based on intermolecular interaction and provide an outlook toward the design and manipulation of efficient adsorbents for the VOC system.

The solubility, metastable zone width (MSZW), and induction time of thiourea for cooling crystallization were experimentally determined in the temperature range of 283–323 K. The solubility data could be well described by the Apelblat equation model as lnx = -99.55 + 1071.66/T + 16.27lnT. The determinations of the effects of various stirring and cooling rates indicated that the MSZW increased with increasing and decreasing cooling and stirring rates, respectively. Furthermore, the induction times at various temperatures and supersaturation ratios were also measured. The results indicated that homogeneous nucleation could occur at high supersaturation, whereas heterogeneous nucleation was more likely to occur at low supersaturation. Based on the classical nucleation theory and induction period data, the calculated solid–liquid interfacial tensions of thiourea in deionized water at 302.46 and 312.58 K were 2.86 and 2.94 mJ·m^-2, respectively.

The heat capacity of ionic liquids is an important physical property, and experimental measuring is usually used as a common method to obtain them. Owing to the huge number of ionic liquids that can be potentially synthesized, it is desirable to acquire theoretical predictions. In this work, the Conductor-like Screening Model for Real Solvents (COSMO-RS) was used to predict the heat capacity of pure ionic liquids, and an intensive literature survey was conducted for providing a database to verify the prediction of COSMO-RS. The survey shows that the heat capacity is available for 117 ionic liquids at temperatures ranging 77.66–520 K since 2004, and the 4025 data points in total with the values from 76.37 to 1484 J·mol^-1·K^-1 have been reported. The prediction of heat capacity with COSMO-RS can only be conducted at two temperatures (298 and 323 K). The comparison with the experimental data proves the prediction reliability of COSMO-RS, and the average relative deviation (ARD) is 8.54%. Based on the predictions at two temperatures, a linear equation was obtained for each ionic liquid, and the heat capacities at other temperatures were then estimated via interpolation and extrapolation. The acquired heat capacities at other temperatures were then compared with the experimental data, and the ARD is only 9.50%. This evidences that the heat capacity of a pure ionic liquid follows a linear equation within the temperature range of study, and COSMO-RS can be used to predict the heat capacity of ionic liquids reliably.

The dehydration of water by dimethyl carbonate (DMC) is of great significance for its application in electrochemistry and oil industry. With the rapid development of nanomaterial, one-dimensional (e.g. carbon nanotube (CNT)) and two-dimensional (e.g. lamellar graphene) materials have been widely used for molecular sieving. In this work, the molecular behavior of dimethyl carbonate/water mixture confined in CNT with varying diameters was studied based on molecular dynamics simulation. Due to different van der Waals interactions for the components in the mixtures with the solid surface, DMC molecules are preferentially adsorbed on the inner surface of the pore wall and formed an adsorption layer. Comparing with the pure water molecules confined in CNT, the adsorption DMC layer shows notable effect on the local compositions and microstructures of water molecules under nanoconfinement, which may result in different water mobility. Our analysis shows that the surface-induced DMC molecules can destroy the hydrogen bonding network of water molecules and result in an uniform and dispersed distribution of water molecules in the tube. These clear molecular understandings can be useful in material design for membrane separation.

The Hansen solubility parameters (HSP) are frequently used for solvent selection and characterization of polymers, and are directly related to the suspension behavior of pigments in solvent mixtures. The performance of currently available group contribution (GC) methods for HSP were evaluated and found to be insufficient for computer-aided product design (CAPD) of paints and coatings. A revised and, for this purpose, improved GC method is presented for estimating HSP of organic compounds, intended for organic pigments. Due to the significant limitations of GC methods, an uncertainty analysis and parameter confidence intervals are provided in order to better quantify the estimation accuracy of the proposed approach. Compared to other applicable GC methods, the prediction error is reduced significantly with average absolute errors of 0.45 MPa^1/2, 1.35 MPa^1/2, and 1.09 MPa^1/2 for the partial dispersion (δ_D), polar (δ_P) and hydrogen-bonding (δ_H) solubility parameters respectively for a database of 1106 compounds. The performance for organic pigments is comparable to the overall method performance, with higher average errors for δ_D and lower average errors for δ_P and δ_H.

Abnormal melting point depression of metal nanoparticles often occurs in heterogeneous catalytic reactions, which leads to a reduction in the stability of reactive nanoclusters. To study this abnormal phenomenon, the original and surface-energy modified Gibbs–Thomson equations were analyzed in this work and further modified by considering the effect of the substrate. The results revealed that the original Gibbs–Thomson equation was not suitable for the particles with radii smaller than 10 nm. Moreover, the performance of the surface-energy modified Gibbs–Thomson equation was improved, and the deviation was reduced to (-350-100) K, although further modification of the equation by considering the interfacial effect was necessary for the small particles (r < 5 nm). The new model with the interfacial effect improved the model performance with a deviation of approximately -50 to 20 K, where the interfacial effect can be predicted quantitatively from the thermodynamic properties of the metal and substrate. Additionally, the micro-wetting parameter α_w can be used to qualitatively study the overall impact of the substrate on the melting point depression.

Molecular simulation plays an increasingly important role in studying the properties of complex fluid systems containing charges, such as ions, piezoelectric materials, ionic liquids, ionic surfactants, polyelectrolytes, zwitterionic materials, nucleic acids, proteins, biomembranes and etc., where the electrostatic interactions are of special significance. Several methods have been available for treating the electrostatic interactions in explicit and implicit solvent models. Accurate and efficient treatment of such interactions has therefore always been one of the most challenging issues in classical molecular dynamics simulations due to their inhomogeneity and long-range characteristics. Currently, two major challenges remain in the application field of electrostatic interactions in molecular simulations; (i) improving the representation of electrostatic interactions while reducing the computational costs in molecular simulations; (ii) revealing the role of electrostatic interactions in regulating the specific properties of complex fluids. In this review, the calculation methods of electrostatic interactions, including basic principles, applicable conditions, advantages and disadvantages are summarized and compared. Subsequently, the specific role of electrostatic interactions in governing the properties and behaviors of different complex fluids is emphasized and explained. Finally, challenges and perspective on the computational study of charged systems are given.

Thermodynamic properties of complex systems play an essential role in developing chemical engineering processes. It remains a challenge to predict the thermodynamic properties of complex systems in a wide range and describe the behavior of ions and molecules in complex systems. Machine learning emerges as a powerful tool to resolve this issue because it can describe complex relationships beyond the capacity of traditional mathematical functions. This minireview will summarize some fundamental concepts of machine learning methods and their applications in three aspects of the molecular thermodynamics using several examples. The first aspect is to apply machine learning methods to predict the thermodynamic properties of a broad spectrum of systems based on known data. The second aspect is to integer machine learning and molecular simulations to accelerate the discovery of materials. The third aspect is to develop machine learning force field that can eliminate the barrier between quantum mechanics and all-atom molecular dynamics simulations. The applications in these three aspects illustrate the potential of machine learning in molecular thermodynamics of chemical engineering. We will also discuss the perspective of the broad applications of machine learning in chemical engineering.