Solvent Particles Research Articles

How Do Deep Eutectic Solvents Form Porous Liquids? The Example of Methyltriphenylphosphonium Bromide: Glycerol and ZIF-8.

Porous liquids are new materials that provide permanent porosity in the liquid phase through the dispersion of nanoporous solid particles in a bulky solvent. Herein, we aim at understanding how new sustainable solvents such as deep eutectic solvent (DES) can be used to form porous stable suspensions for the capture of gases of interest for sustainable chemistry. The properties of an ionic DES, methyltriphenylphosphonium bromide/glycerol in a 1:3 molar composition, and its behavior at the interface with a metal-organic framework (MOF), ZIF-8, are here investigated by polarizable molecular dynamics simulations. The structural and dynamic properties of the DES are analyzed in the bulk liquid and in the interfacial regions with the MOF, namely, in the accessible cavities exposed at the surface. The porosity of the suspension is maintained, and it is caused not only by the Coulomb cohesive energy between cations and anions, which prevents the small anions from entering the pores, but also by the glycerol molecules not penetrating the small aperture of the ZIF-8 structure. This was further verified by simulating a system composed of glycerol and ZIF-8. Simulations with CO2 show its partition between the DES and the MOF, with higher concentrations registered in the MOF cavities.

Amino acid chiral amplification using Monte Carlo dynamic.

This study investigates the stability of chiral-molecule solution phases, with a specific focus on amino acids. The model framework is based on a two-dimensional square lattice model, where individual sites may be occupied by oriented chiral molecules or structureless solvent particles. Utilizing the Glauber dynamics and statistical mechanical formalism, as previously introduced and examined by Lombardo et al., we explore the influence of temperature, amino acid concentration, enantiomeric excess, and homochiral interaction strength on nucleation mechanisms, equilibrium phase behavior, and crystal composition. Our findings offer thermodynamic insights into the chiral amplification process of amino acids, contributing to a deeper understanding of the underlying processes.

The Effect of Polymer-Solvent Interaction on the Swelling of Polymer Matrix Tablets: A Magnetic Resonance Microscopy Study Complemented by Bond Fluctuation Model Simulations.

Polymer matrix tablets are an important drug-delivery system widely used for oral drug administration. Understanding the tablet hydration process, both experimentally and theoretically, is, thus, very important for the development of drug delivery systems that exhibit high drug loading capacity and controlled release potential. In this study, we used magnetic resonance microscopy (MRM) to nondestructively and dynamically analyze the water hydration process of xanthan-based tablets. The swelling process was characterized by well-resolved fronts of erosion, swelling, and penetration. The experimental results were complemented by numerical simulations of the polymer matrix hydration process. In the simulations, the polymer tablet matrix was modeled as an assembly of interacting chains with embedded drug particles, while its hydration process was mediated by interaction with solvent particles. The swelling dynamics were modeled within a Monte Carlo-based bond fluctuation model (BFM) that elegantly accounted for steric and nearest-neighbor interactions. This study provides an efficient experimental-theoretical approach for the study of polymer matrix swelling processes.

Phonon thermophoresis of crystalline nanoparticles in liquids.

Our nonequilibrium thermodynamic model of thermodiffusion in molecular liquid systems is used to examine the role of thermal phonons in the thermophoresis of liquid suspensions of crystalline nanoparticles, which tend to have high thermal conductivity. The Soret coefficient used to characterize stationary thermodiffusion is related to differences in entropy between a particle and the body of liquid that it displaces. Calculated phonon Soret coefficients for graphite and diamond nanoparticles in three polar solvents are used to establish parameters where the phonon mechanism is expected to dominate particle thermophoresis compared to slip-flow caused by forces induced in the surface layer by the temperature gradient. Because the active mode of thermal conductivity in crystals varies with particle size, phonon thermophoresis is expected to dominate within a specific range of particle size, which varies with the properties of the particle and suspending liquid. For graphite and diamond particles in polar solvents the model estimates a size range of around 10-100 nm. Finally, thermophoretic particle accumulation is ultimately limited by the increasing concentration of particles having high thermal conductivity because the zone of particle concentration decreases the local temperature gradient that drives thermophoresis. The respective nonperturbing concentration is evaluated as the function of the size of a given material.

Impacts of the reactants on the synthesis of ZnO particles in glycerol-based solvents

Glycerol/additive solvents allow unusual mechanistic routes to form ZnO. Balance between stoichiometry and temperature provides distinct zinc hydroxide forms and zinc oxide particles.

One-pot facile synthesis of rod-like Bi2S3 particles in deep eutectic solvent and their ppb-level selective H2S gas detection.

Bismuth sulfide, Bi2S3, was prepared by a one-pot reaction using various choline chloride-based deep eutectic solvents (DESs) as the reaction field. Rod-like particles obtained with acetamide-thioacetamide-based DESs were found to exhibit specifically dominant detection properties for H2S gas, and the gas detection mechanism was discussed by adsorption reaction.

Extraction and Characterization of Natural Coagulant Made from Banana Plant Stems (Musa acuminate) for the Removal of Turbidity from Wastewater

Wastewater treatment with chemical coagulants has a variety of drawbacks, including sludge management, cost, concerns for human health, and environmental pollution. In light of this, a study was conducted to determine whether banana plant stem (Musa acuminate) made coagulant can effectively reduce turbidity (NTU) of wastewater. In this study, conventional extraction method was used to extract the coagulant from the banana plant stem by using NaCl (0.1, 0.5, 1 M) solvent. After extraction, the coagulation efficiency of each produced coagulant was computed in terms of their turbidity removal efficiency (%) from sampled wastewater. The sampled wastewater had an average turbidity value of 893 NTU. Response surface methodology (RSM) and central composite design (CCD) were used to study the effects of NaCl solvent concentration (M), extraction time (min), and particle size (mm) on the coagulation efficiency (%) of the extracted coagulant. In addition, the coagulant was characterized such as FTIR analysis, point of zero charge value determination, and inulin compound presence analysis. From all prepared coagulants, the maximum coagulation efficiency obtained was 86.3% at the optimum conditions, such as 0.55 M (NaCl) of solvent concentration, 1.25 mm particle size, and 20 min of extraction time. The characterized coagulant had 6.2 points of zero charge value and also had various types of functional groups. Based on the findings of this study, it can be said that the coagulant prepared from banana stems (Musa acuminate) was an efficient natural coagulant that could be applied to treat wastewater.

Coarse-Graining Waters: Unveiling The Effective Hydrophilicity/Hydrophobicity of Individual Protein Atoms and The Roles of Waters' Hydrogens.

There have been many coarse-graining methods developed that aim to reduce the sizes of simulated systems and their computational costs. In this work, we develop a new coarse-graining method, called coarse-graining-delta (or δ-CG in short), that reduces the degrees of freedom of the potential energy surface by coarse-graining relative locations of atoms from their unit centers. Our method extends and generalizes the methods used in the coarse-grained normal mode analysis and enables us to study the roles of the individual removed atoms in a system, which have been difficult to study in molecular dynamics simulations. By applying δ-CG to coarse-grain three-point water molecules into single-point solvent particles, we successfully identify the effective hydrophilicity and hydrophobicity of all the individual protein atom types, which collectively correlate well with the known hydrophilic, hydrophobic, and amphipathic characteristics of amino acids. Moreover, our investigation shows that water's hydrogens have two roles in interacting with protein atoms. First, water molecules adjust their poses around different amino acids and their atoms, and the statistical preferences of the hydrogen poses near the atoms determine the effective hydrophilicity and hydrophobicity of the atoms, which have not been successfully addressed before. Second, the collective dynamics of the hydrogens assist the water molecules in escaping from the potential energy wells of the hydrophilic atoms. Our method also shows that coarse-graining a system mathematically leads to breaking antisymmetry of the nonbonded interactions; as a result, two interacting coarse-grained units exert different forces on each other. Our study indicates that the accuracy of coarse-grained force fields, such as the MARTINI force field and the UNRES force field, can be improved in two ways: (i) refining their potential energy functions and coefficients by analyzing the coarse-grained potential energy surface using δ-CG, and (ii) introducing non-antisymmetric interactions.

Development of a novel machine learning approach to optimize important parameters for improving the solubility of an anti-cancer drug within green chemistry solvent

Understanding the solubility of drug particles in solvents has remained a big challenge in different fields. Development of advanced computational methods to predict the solubility of drugs is an important necessity due to the difficulty and time-consuming characteristics of experimental measurements. This study used hybrid machine learning (ML) models utilizing two inputs, including Pressure (X1) and Temperature (X2), to investigate the current data, and correlate the solubility of drug particles in supercritical solvent. The methods of Random Forest (RF), Extra Trees (ET), and Gradient Boosting (GB) regression models were used to build the models on the available data. RF, ET, and GB have R-squared of 0.857, 0.998, and 0.992, based on the analysis results. Additionally, in terms of MAE, they illustrated error value 2.90E-06, 1.98E-06, and 1.10E-06, respectively. One more metric to consider is MAPE, in which the error rates for the three regions were 3.15E-01, 2.27E-01, and 1.16E-01, respectively. The DT method was chosen as the best method, and can be used to find optimal amounts, which is summarized as a vector: (×1 = 383, X2 = 333.15, Y = 6.004e-05).

Optimization of Papaya Seed Oil Production Process (Carica papaya L.) with Soxhlation Extraction Method using Factorial Design

This study aims to optimize the extraction of papaya seed oil (Carica papaya L.) using a factorial design level 2. Papaya seeds are a significant component of the fruit, comprising approximately 14.3% of the total fruit weight. These seeds contain about 25% vegetable oil, predominantly composed of unsaturated fatty acids, which have the potential to be processed into consumable oil. The extraction method employed is Soxhlet extraction using a non-polar solvent, n-hexane. A factorial design level 23 was utilized to determine the most influential process variables. The variables were considered to the ratio of papaya seed mass to solvent volume (1:7 and 1:11), particle size (10 and 30 mesh), and extraction time (170 and 190 min). Optimization was conducted using the quicker method calculation, where the determination of the largest effect and the largest main effect played a crucial role. The analysis revealed that the ratio of papaya seed mass to solvent volume had the most significant main effect, with an effect value of 0.1217. From the analysis, it was found that the 1:7 ratio produced the lowest level of Free Fatty Acids (FFA) in the oil, at 0.5076%, which aligns with the Indonesian National Standard (SNI) requirement of 0.36-0.82% FFA content. Furthermore, an analysis of density, viscosity, and moisture content was conducted on the 1:7 ratio. The test results showed that the 1:7 ratio resulted in an oil density of 0.924 g/mL, moisture content of 0.07127%, and FFA content of 0.5076%. However, based on theoretical knowledge, an increase in FFA content leads to a decrease in oil quality. Additionally, higher ratios corresponded to increased moisture content and density. In conclusion, the papaya seed oil produced in this study complies with the Indonesian National Standard (SNI, 01-3555-1998) regarding FFA content (0.36-0.82%), moisture content (maximum 0.15%), and density (0.924-0.929 g/mL).

A Consistent Thermodynamic Characterization of the Adsorption Process through the Calculation of Free Energy Contributions.

We apply in this study different methodologies based on thermodynamic integration (TI), free energy perturbation (FEP), and potential of mean force (PMF) to address the challenging issue of the calculation of the free energy of adsorption. A model system composed of a solid substrate, an adsorbate, and solvent particles is specifically designed to reduce the dependence of our free energy results on the sampling of the phase space and the choice of the pathway. The reliability and efficiency of these alchemical free energy simulations are established through the closure of a thermodynamic cycle describing the adsorption process in solution and in a vacuum. We complete this study by the calculation of free energy contributions related to phenomena of desorption of solvent molecules and desolvation of the adsorbate upon adsorption. This calculation relies on the work of adhesion, the interfacial tension of the liquid-vapor of the solvent, and the free energy of solvation of the substrate. The different ways of calculating the free energy of adsorption are in excellent agreement and could complete experiments in the field of adsorption by giving quantitative data on the different energy contributions involved in the process.

Effective charge of PNIPAM microgels determined by conductivity measurements

AbstractUnderstanding the effective charge of colloidal particles is crucial to control the stability and performance of a colloidal system. In particular, the electrostatic interaction potential between the particles determines the stability and thermodynamic properties of electrostatically charged colloidal dispersions. In the case of thermosensitive microgels, which are solvent and ions permeable particles, it is expected that the microgel's size and the number of ions within it are affected by temperature changes. This temperature‐dependent microgel‐solvent ion interchange regulates the microgel net charge and, consequently, the interaction potential. Here, a straightforward experimental method based on conductivity measurements is presented to determine the temperature dependence of the effective net charge of poly‐N‐isopropylacrylamide, PNIPAM, microgels under different salinity conditions. Our results show that the net charge of the microgel decreases with increasing temperature. Specifically, microgels reduce their net charge by around 40%, when the temperature is changed from 25 to 40 °C. This scenario could be explained by the entrance of counterions into the microgel after its collapse to partially neutralize the increase of the electrostatic repulsion due to the closer proximity among the charged groups present in the polymer particle.

Block copolymer particles with tunable and robust internal nanostructures by combining hydrogen-bonding and crosslinking

Nanostructured block copolymer (BCP) particles are attractive due to their ordered internal structures, unique shape and surface patterns; however, their structural integrity can be easily lost because of weak intermolecular interactions, which limits their practical applications. In this study, we present a simple and reliable method to fabricate nanostructured particles of polystyrene-block-poly(4-vinylpyridine) with tunable and robust nanostructures by employing hydrogen-bonding and cross-linking strategies. The key feature of poly(4-vinylpyridine) is the presence of reactive pyridyl moieties, which allow precise regulation of internal nanostructures via hydrogen bonds and locking of the structural integrity via quaternarization by feeding hydrogen bond donors and cross-linkers, respectively. The solvent resistance is well proven by immersing the particles in either selective solvents of the continuous phase or good solvent of the BCP. Furthermore, mesoporous BCP particles derived from the cross-linked particles are obtained simply by a swelling/deswelling treatment. This study provides a way to improve the structural robustness of BCP particles and could be a key step that advances the functionalization and subsequent applications of such nanostructured BCP colloidal particles.

Dapsone-Loaded Mixed Micellar Gel for Treatment OF Acne Vulgaris

Mixed polymeric micelles are potential nanocarriers for topical drug delivery. Dapsone (DAP) is an antibacterial used as anti-acne agent, but challenged by low water solubility and poor skin permeability. In the present study, DAP-loaded mixed micellar gel was developed comprising Pluronics F-68 and F-127. Micelles were prepared by solvent evaporation method and particle size, ex vivo permeation, drug loading, and entrapment efficiency were determined. Central Composite Design was used to optimize formulation. Independent variables were concentration of Pluronics at three levels while micelle size and drug loading capacities were dependent variables. Droplet size ranged from 400 to 500 nm. Transmission electron microscopy revealed spherical morphology of micelles. Optimized micelles were incorporated into gel base using HPMC K100M, Sodium CMC, and Carbopol 980 as gelling agents. Gels were evaluated for pH, drug content, spreadability, rheology, syneresis, ex vivo permeation, and subacute dermal toxicity. Compared with solubility of free DAP (0.24+0.056 µg/ml), solubility in mixed micelles was 18.42±3.4 µg/ml in water at room temperature. Order of spreadability of gels was Na CMC < HPMC < Carbopol 980. Carbopol gels displayed thixotropy with index of 3.17. Syneresis for all gels from day 0 to day 30 was found to be in range of 4.2 to 15.6% w/w. Subacute dermal toxicity studies showed no signs of erythema and edema on rat skin until 21 days. These results suggest that mixed micelles can significantly increase solubility and permeability and sustain release of DAP and are suitable carriers for topical DAP delivery in anti-acne therapies.

A comparative assessment for efficient oleuropein extraction from olive leaf (Olea europaea L. folium)

Since oleuropein has long been known in the health sector and is abundant directly in our country as the fourth largest olive producer, oleuropein, the predominant phenolic ingredient in olive leaves, was recovered in this study using Soxhlet extraction. The effects of different solvent types (acetonitrile, ethanol, methanol, and water), extraction period (4 cycles, 4 h, and 8 h), particle size (250-500 µm and 900-2000 µm), and pretreatment of olive leaves on the yield of oleuropein were examined to determine the maximum yield. A greater oleuropein yield was obtained when the particle size of olive leaves utilized for extraction was lowered. Furthermore, aqueous solvents revealed a higher yield of oleuropein than pure solvents and prolonging the extraction duration resulted in a significant increase in the amount of oleuropein extracted. On the other hand, pretreatment of olive leaves resulted in a reduction in oleuropein output. As a result, with 36% extraction efficiency in terms of olive leaf conversion, the highest oleuropein extraction yield was obtained as 13.35 mg g-1 dry leaf for 8 h of extraction time using olive leaves with a particle size of 250-500 µm and an 80% methanol solution as solvent.

Machine learning of an implicit solvent for dynamic Monte Carlo simulations.

The Bond Fluctuation Model (BFM) is a highly efficient and versatile method for simulating polymers, membranes, and soft matter. Due to its coarse-grained nature, the BFM is employed to understand the universal properties of polymers. Solvent effects are often mediated by explicit solvent particles, while implicit solvent models have had limited use as they may lead to frozen states and, thus, ergodicity-related problems. In simulation setups, such as coagulated multiple homopolymers chains, explicit solvent models are computationally expensive because the region of interest can be localized in a small space compared to the dimension of the periodic box. We introduce an implicit solvent model based on an artificial neural network (NN) that was trained with BFM simulation data for single homopolymers in an explicit solvent. We demonstrate that NN-based simulations that take into account only the information of the local environment of monomers reproduce the expected universal macroscopic properties of the polymer under varying solvent conditions. The homopolymer chains simulated using the NN reproduce the coil-globule transition, the static and dynamic bond autocorrelation, and the mean square displacement of chain monomers. We show that the learned parameters from a single chain system can be transferred to a system containing multiple homopolymers, indicating that the learned parameters are transferable to considerably different systems.

Arrested coarsening and large density fluctuations in driven particle mixtures in two dimensions

Using molecular dynamics simulations, we study a driven, nonadditive binary mixture of spherical particles confined to move in two dimensions and immersed in an explicit solvent consisting of point particles with purely repulsive interactions. We show that, without a drive, the mixture of spherical particles phase separates and coarsens with kinetics consistent with an Ising-like conserved dynamics. Conversely, when the drive is applied, the coarsening is arrested and the system develops large density fluctuations. We show that the drive creates domains of a characteristic size which decreases with an increasing force. Furthermore, we find that these domains are anisotropic and can be oriented either parallel or perpendicular to the drive direction. Finally, we connect our findings to existing theories of strongly-driven systems, pointing out the importance of introducing the explicit solvent particles to break the Galilean invariance of the system.

Unexpected Solvent Effect Leading to Interface Segregation of Single-Chain Nanoparticles in All-Polymer Nanocomposite Films upon Solvent Evaporation

In athermal all-polymer nanocomposites (all-PNCs), single-chain nanoparticles (SCNPs) are often considered to be well miscible with polymer matrixes due to their similarity in chemical compositions. However, internal cross-linking units of SCNPs must have different chemistries from the backbone monomers and, therefore, also from matrix chains. Here, we use large-scale molecular dynamics simulations to study the influence of solvent selectivity, particularly to internal cross-linkers in SCNPs, on dispersion state of SCNPs in all-PNC films upon solvent evaporation. Surprisingly, we find distinct dispersion states of SCNPs in drying films with different solvent selectivities. When the solvent is both good for cross-linkers and backbone/matrix monomers, SCNPs can be uniformly dispersed. However, when the backbone/matrix monomers have better solvophilicity than the cross-linkers and the solvophilicity of the latter is weak enough, we find segregation of SCNPs in surface regions. Such phenomena can be attributed to the intrinsic difference in the solvent density at an interface region from that in the bulk, which eventually results in the aggregation of SCNPs at the interface region where the solvent particles are much less than in the bulk. At the interface region, cross-linkers in the SCNPs will have less contact with the solvent and, therefore, less enthalpy penalty than being located in the bulk region of the film. The results demonstrate that solvent selectivity has a non-negligible effect on the structure of the composite film, which will inevitably have impacts on macroscopic properties of the film.

A Review of 3D Polymeric Scaffolds for Bone Tissue Engineering: Principles, Fabrication Techniques, Immunomodulatory Roles, and Challenges.

Over the last few years, biopolymers have attracted great interest in tissue engineering and regenerative medicine due to the great diversity of their chemical, mechanical, and physical properties for the fabrication of 3D scaffolds. This review is devoted to recent advances in synthetic and natural polymeric 3D scaffolds for bone tissue engineering (BTE) and regenerative therapies. The review comprehensively discusses the implications of biological macromolecules, structure, and composition of polymeric scaffolds used in BTE. Various approaches to fabricating 3D BTE scaffolds are discussed, including solvent casting and particle leaching, freeze-drying, thermally induced phase separation, gas foaming, electrospinning, and sol-gel techniques. Rapid prototyping technologies such as stereolithography, fused deposition modeling, selective laser sintering, and 3D bioprinting are also covered. The immunomodulatory roles of polymeric scaffolds utilized for BTE applications are discussed. In addition, the features and challenges of 3D polymer scaffolds fabricated using advanced additive manufacturing technologies (rapid prototyping) are addressed and compared to conventional subtractive manufacturing techniques. Finally, the challenges of applying scaffold-based BTE treatments in practice are discussed in-depth.

Active nematic liquid crystals simulated by particle-based mesoscopic methods.

Two Multi-particle collision dynamics algorithms that simulate nematic liquid crystals are generalised to reproduce active behaviour. One of the algorithms is due to Shendruk and Yeomans and is based on particles that carry an orientation vector ordered by a mean-field energy [T. N. Shendruk and J. M. Yeomans, Soft Matter, 2015, 11, 5101]. In the other algorithm, due to Mandal and Mazza, particles possess an order parameter tensor which evolves according to the Qian-Sheng model of nematohydrodynamics [S. Mandal and M. G. Mazza, Phys. Rev. E, 2019, 99, 063319]. For both methods activity is incorporated through a force proportional to the divergence of the local average order parameter tensor. Both implementations produce disclination curves in the nematic fluid that undergo nucleation and self-annihilation dynamics. Topological defects are found to be consistent with those observed in recent experiments of three-dimensional active nematics. Results permit to compare the length-scales over which the different nematic Multi-particle collision dynamics methods operate. The structure and dynamics of the orientation and flow fields agree with those obtained recently in numerical studies of continuum three-dimensional active nematics. Overall, our results open the opportunity to use mesoscopic particle-based approaches to study active liquid crystals in situations such as nonequilibrium states driven by flow or colloidal particles in active anisotropic solvents.