Thermodynamic analysis and molecular dynamic simulation of the solubility of vortioxetine hydrobromide in three binary solvent mixtures

Molecular dynamics simulations of the solubility and conformation change of chitosan grafted polyacrylamide: Impact of grafting rate

Graft modification is an effective approach to improve the water solubility and molecular weight of chitosan. This work investigated the effect of grafting rate on water solubility of chitosan-grafted polyacrylamide (Chi-g-PAM) using molecular dynamics simulations. The intramolecular and intermolecular interaction between Chi-g-PAM with the grafting rate of 100%-250% and water together with the conformation change were analyzed by radial distribution function (RDF), radius of gyration, solvation free energy (ΔGSFE), mean square displacement, diffusion coefficient and shear viscosity. The results showed that the intramolecular hydrogen bonding of Chi-g-PAM was the dominant factor affecting its water solubility. While the grafting rate of Chi-g-PAM increased from 100% to 250%, the RDF of Chi-g-PAM decreased from 5.39 to 3.57 between O-H at 2.0 Å and 2.60 to 1.30 between N-H at 2.1 Å. The interaction between Chi-g-PAM and water increased with grafting rate as the absolute value of ΔGSFE for Chi-g-PAM increased from 432.917 kcal/mol to 858.749 kcal/mol. The solubility of Chi-g-PAM in acidic solution was much better than that of Chi-g-PAM in aqueous solution. Our work on the fundamental insights into the effect of grafted molecular structure of chitosan-based copolymer on its solubility will benefit the development of environmentally friendly chitosan-based flocculants.

Formulation Graphs for Mapping Structure-Composition of Battery Electrolytes to Device Performance

Advanced computational methods are being actively sought to address the challenges associated with the discovery and development of new combinatorial materials, such as formulations. A widely adopted approach involves domain-informed high-throughput screening of individual components that can be combined together to form a formulation. This manages to accelerate the discovery of new compounds for a target application but still leaves the process of identifying the right "formulation" from the shortlisted chemical space largely a laboratory experiment-driven process. We report a deep learning model, the Formulation Graph Convolution Network (F-GCN), that can map the structure-composition relationship of the formulation constituents to the property of liquid formulation as a whole. Multiple GCNs are assembled in parallel that featurize formulation constituents domain-intuitively on the fly. The resulting molecular descriptors are scaled based on the respective constituent's molar percentage in the formulation, followed by integration into a combined formulation descriptor that represents the complete formulation to an external learning architecture. The use case of the proposed formulation learning model is demonstrated for battery electrolytes by training and testing it on two exemplary data sets representing electrolyte formulations vs battery performance: one data set is sourced from the literature about Li/Cu half-cells, while the other is obtained by lab experiments related to lithium-iodide full-cell chemistry. The model is shown to predict performance metrics such as Coulombic efficiency (CE) and specific capacity of new electrolyte formulations with the lowest reported errors. The best-performing F-GCN model uses molecular descriptors derived from molecular graphs (GCNs) that are informed with HOMO-LUMO and electric moment properties of the molecules using a knowledge transfer technique.

New insight into desorption behavior and mechanism of oil from aged oil-contaminated soil in microemulsion

The intractable nature of oil-contaminated soil (OS) constitutes the chief limiting factor for its remediation. Herein, the aging effect (i.e., oil-soil interactions and pore-scale effect) was investigated by analyzing the properties of aged OS and further demonstrated by investigating the desorption behavior of the oil from the OS. XPS was performed to detect the chemical environment of N, O, and Al, indicating the coordination adsorption of carbonyl groups (oil) on the soil surface. Alterations in the functional groups of the OS were detected using FT-IR, indicating that the oil-soil interactions were enhanced via wind-thermal aging. SEM and BET were used to analyze the structural morphology and pore-scale of the OS. The analysis revealed that aging promoted the development of the pore-scale effect in the OS. Moreover, the desorption behavior of oil molecules from the aged OS was investigated via desorption thermodynamics and kinetics. The desorption mechanism of the OS was elucidated via intraparticle diffusion kinetics. The desorption process of oil molecules underwent three stages: film diffusion, intraparticle diffusion, and surface desorption. Owing to the aging effect, the latter two stages constituted the major steps for controlling oil desorption. This mechanism provided theoretical guidance to apply microemulsion elution for remedying industrial OS.

Supramolecular glasses with color-tunable circularly polarized afterglow through evaporation-induced self-assembly of chiral metal-organic complexes

The fabrication of chiral molecules into macroscopic systems has many valuable applications, especially in the fields of optical displays, data encryption, information storage, and so on. Here, we design and prepare a serious of supramolecular glasses (SGs) based on Zn-L-Histidine complexes, via an evaporation-induced self-assembly (EISA) strategy. Metal-ligand interactions between the zinc(II) ion and chiral L-Histidine endow the SGs with interesting circularly polarized afterglow (CPA). Multicolored CPA emissions from blue to red with dissymmetry factor as high as 9.5 × 10^-3 and excited-state lifetime up to 356.7 ms are achieved under ambient conditions. Therefore, this work not only communicates the bulk SGs with wide-tunable afterglow and large circular polarization, but also provides an EISA method for the macroscopic self-assembly of chiral metal-organic hybrids toward photonic applications.

Systematic thermodynamic analysis of apremilast polymorphs via solubility measurement with modeling: Mechanism evaluation through molecular simulation

The polymorphism of apremilast has been investigated. Two polymorphs have been identified and characterized by differential scanning calorimeter, fourier transform infrared spectroscopy, and powder X-ray diffractometer. Solubilities of apremilast forms B and E in three binary solvents of methanol-water, acetonitrile-water, and acetonitrile-methanol have been measured using the static method at a temperature ranging from 288.15 K to 328.15 K under standard atmospheric pressure. Subsequently, the solubility data have been analyzed using the Wilson, NRTL, and UNIQUAC thermodynamic models, respectively. Furthermore, the Gibbs energy of solution and the radial distribution function have been calculated using the molecular simulation method to evaluate the dissolution mechanism. The Gibbs energy of solution reveals that the rank of solute-solvent interaction correlated well with solubility order in binary solvent mixtures, and the radial distribution function indicates that weakening of solvent-solvent interaction led to an increase in solubility.

Enhancing continuous reactive crystallization of lithium carbonate in multistage mixed suspension mixed product removal crystallizers with pulsed ultrasound

In this work, pulsed ultrasound was used to facilitate steady-state reactive crystallization and increase the final yield and productivity of lithium carbonate in continuously operated single and multistage mixed suspension mixed product removal (MSMPR) crystallizers. Experimental analyses of the stirred tank MSMPR cascade were performed to investigate the effects of ultrasound field, residence time and temperature which contributed to the steady-state yield, crystal size distribution and crystal morphology. The results show that pulsed ultrasound can not only significantly enhance the reaction rate, but also help to improve the particle size distribution and the crystal habit. Subsequently, a population balance model was developed and applied to estimate the final yield of the continuous process of the lithium bicarbonate thermal decomposition reaction coupling lithium carbonate crystallization. The consistency of the final yield between the experiments and the simulations proved the reliability of the established model. Through the experimental and simulation analyses, it is demonstrated that the use of pulsed ultrasound, higher final stage temperature, MSMPR cascade design and appropriate residence time help to achieve higher yield and productivity. Furtherly, based on the conclusion drawn, pulsed ultrasound enhanced three-stage MSMPR cascaded lithium carbonate continuous crystallization processes were designed, and the maximum productivity of 44.0 g/h was obtained experimentally.

Experimental and Molecular Simulation Studies of the Attachment Behavior of Photoinitiator XBPO Crystals in Different Solvents

The aggregation of crystals is a common phenomenon during the crystallization process. However, the formation mechanism of the aggregates remains elusive. In this work, we combine experiments with molecular simulations to investigate the attachment behavior of an organic compound photoinitiator bis(2,4,6-trimethylbenzoyl)phenylphosphine oxide (XBPO) in different solvents. The simulation results were highly in line with the experimental results. The results indicate that the aggregation behavior occurs on the high-energy surface (1 0 0) and the attachment angle is 0° during the solvothermal process. Meanwhile, solvents play the critical role in the formation of aggregated particles. It was found that the solvents with high Kamlet-Taft dipolarity/polarizability can promote the aggregation behavior of photoinitiator XBPO crystals. Furthermore, a solvent-mediated growth mechanism assisted by "oriented attachment"-like and Ostwald ripening mechanisms was proposed to elucidate the growth and aggregation of particles. We anticipate that this study will provide a comprehensive understanding of the attachment behavior and be helpful to control the aggregation of crystals.