Asymmetric block copolymer membrane fabrication mechanism through self-assembly and non-solvent induced phase separation (SNIPS) process

In this paper, the concept of the functional mechanism of copolymer membrane formation is explained and analyzed from the theoretical and experimental points of view. To understand the phase inversion process and control the final membrane morphology, styrene-acrylonitrile copolymer (SAN) membrane morphology through the self-assembly phenomena is investigated. Since the analysis of the membrane morphology requires the study of both thermodynamic and kinetic parameters, the effect of different membrane formation conditions is investigated experimentally; In order to perceive the formation mechanism of the extraordinary structure membrane, a thermodynamic hypothesis is also developed based on the hydrophilic coil migration to the membrane surface. This hypothesis is analyzed according to Hansen Solubility Parameters and proved using EDX, SAXS, and contact angle analysis of SAN25. Moreover, the SAN30 membrane is fabricated under different operating conditions to evaluate the possibility of morphological prediction based on the developed hypothesis.

Solvent-Resistant UV-Cured Polysulfone Support Membranes Using a Green Solvent

Solvent-resistant UV-cured supports consisting of a semi-interpenetrating network of polysulfone (PSf) and cross-linked poly-acrylate were successfully synthesized for the first time using an alternative, non-reprotoxic, and biodegradable solvent. Tamisolve® NxG is a high-boiling, dipolar aprotic solvent with solubility parameters similar to those of dimethylformamide (DMF) and N-methyl-2-pyrrolidone (NMP), making it an eco-friendly alternative. The support membranes, prepared via UV-curing followed by non-solvent-induced phase inversion, can serve as a universal solvent-resistant support for the synthesis of a broad set of membranes, for which the selective layer can be deposited from any solvent. Parameters such as UV irradiation time and intensity, as well as the concentrations of PSf, penta-acrylate, and photo-initiator in the casting solution were varied to obtain such supports. The characteristics of the resulting supports were investigated in terms of separation performance, hydrophobicity, porosity, degree of acrylate conversion, and pure water flux. The resulting membranes showed improved chemical resistance in solvents such as ethyl acetate, NMP, tetrahydrofuran (THF), and toluene. Solvent-resistant supports with different pore sizes were synthesized and used for the preparation of thin film composite (TFC) membranes to demonstrate their potential. Promising separation performances with Rose Bengal (RB) rejections up to 98% and water permeances up to 1.5 L m−2 h−1 bar−1 were reached with these TFC-membranes carrying a polyamide top layer synthesized via interfacial polymerization.

Atomistic Descriptors for Machine Learning Models of Solubility Parameters for Small Molecules and Polymers

Descriptors derived from atomic structure and quantum chemical calculations for small molecules representing polymer repeat elements were evaluated for machine learning models to predict the Hildebrand solubility parameters of the corresponding polymers. Since reliable cohesive energy density data and solubility parameters for polymers are difficult to obtain, the experimental heat of vaporization ΔHvap of a set of small molecules was used as a proxy property to evaluate the descriptors. Using the atomistic descriptors, the multilinear regression model showed good accuracy in predicting ΔHvap of the small-molecule set, with a mean absolute error of 2.63 kJ/mol for training and 3.61 kJ/mol for cross-validation. Kernel ridge regression showed similar performance for the small-molecule training set but slightly worse accuracy for the prediction of ΔHvap of molecules representing repeating polymer elements. The Hildebrand solubility parameters of the polymers derived from the atomistic descriptors of the repeating polymer elements showed good correlation with values from the CROW polymer database.

Polymer Concentration Maximizes Encapsulation Efficiency in Electrohydrodynamic Mixing Nanoprecipitation

Encapsulation in self-assembled block copolymer (BCP) based nanoparticles (NPs) is a common approach to enhance hydrophobic drug solubility, and nanoprecipitation processes in particular can yield high encapsulation efficiency (EE). However, guiding principles for optimizing polymer, drug, and solvent selection are critically needed to facilitate rapid design of drug nanocarriers. Here, we evaluated the relationship between drug-polymer compatibility and concentration ratios on EE and nanocarrier size. Our studies employed a panel of four drugs with differing molecular structures (i.e., coumarin 6, dexamethasone, vorinostat/SAHA, and lutein) and two BCPs [poly(caprolactone)-b-poly(ethylene oxide) (PCL-b-PEO) and poly(styrene)-b-poly(ethylene oxide) (PS-b-PEO)] synthesized using three nanoprecipitation processes [i.e., batch sonication, continuous flow flash nanoprecipitation (FNP), and electrohydrodynamic mixing-mediated nanoprecipitation (EM-NP)]. Continuous FNP and EM-NP processes demonstrated up to 50% higher EE than batch sonication methods, particularly for aliphatic compounds. Drug-polymer compatibilities were assessed using Hansen solubility parameters, Hansen interaction spheres, and Flory Huggins interaction parameters, but few correlations were EE observed. Although some Hansen solubility (i.e., hydrogen bonding and total) and Flory Huggins interaction parameters were predictive of drug-polymer preferences, no parameter was predictive of EE trends among drugs. Next, the relationship between polymer: drug molar ratio and EE was assessed using coumarin 6 as a model drug. As polymer:drug ratio increased from <1 to 3–6, EE approached a maximum (i.e., ∼51% for PCL BCPs vs. ∼44% PS BCPs) with Langmuir adsorption behavior. Langmuir behavior likely reflects a formation mechanism in which drug aggregate growth is controlled by BCP adsorption. These data suggest polymer:drug ratio is a better predictor of EE than solubility parameters and should serve as a first point of optimization.

Molecular Dynamics Simulation of Polysulfone and Polystyrene-co-maleic Anhydride Blends Compatibility: A mesoscopic, Ewald Approach and Experimental Comparison

This work aims to use molecular modeling to envisage the compatibility of Polysulfone (PSF) and Poly (styrene-co-maleic anhydride) (PSMA) polymers blend. A blend-module was developed based on the molecular dynamics (MD) technique compared to an experimental study. Molecular dynamics simulations were achieved using the condensed phase-optimized molecular-potentials for atomistic simulation studies (COMPASS) force field with atomic-based electrostatic. The PSF/PSMA blend compatibility facets and thermodynamic Gibb’s free energy across ranges of PSF/PSMA blend compositions were calculated. In doing so, the Flory Huggins chi interaction parameter of mixing (χ) and solubility parameters (δ) were computed from 298K and on increasing temperature to predict the miscibility of the polymers blend in the amorphous cell model by atomistic simulations. It was found that the blend-system is miscible using the interaction chi parameter of Florry Huggins at a temperature above 400K. At higher time-step, mesoscopic simulations for PSF/PSMA reached equilibrium and computed free energy. Mixing energy indicated the stability of the PSF/PSMA polymer blend. The results of this work narrate to the Flory Huggins theory enthalpy of mixing for binary blend polymers at 40 and 60 % PSMA.Additionally, the kinetic phase of the miscibility/immiscibility of the PSF/PSMA blend system's miscibility/immiscibility was examined using Differential Scanning Calorimetry (DSC). The result confirms the good interaction between the two polymers through the shift of glass transition temperature (Tg) values within individual polymers Tg. It is crucial to investigate the miscibility of two different polymers for a variety of polymer applications. The MD simulation provides a powerful, accurate computational tool in the estimation of polymer compatibilities.

Mixed Solvents in Multi-Layer Ceramic Capacitors (MLCC) Elec-Tronic Paste and Their Effects on the Properties of Organic Vehicle

The copper end paste used in multilayer ceramic capacitors sintered in nitrogen atmosphere will lead to carbon residue of organic vehicle, which will lead to the reduction of electrode conduc-tivity and high scrap rate. With an attempt to leave no residue in the sintering, the compatibility of solvents and thickeners should be improved because it has an important influence on the hi-erarchical volatilization and carbon residue of organic vehicles. In this work, the volatility of different solvents was compared and several solvents were mixed in a definite proportion to prepare an organic vehicle with polyacrylate resins. The hierarchical volatility and solubility parameters of mixed solvents were adjusted effectively by changing proportions of different components, the thermogravimetric curves of resins and organic vehicles were measured by thermogravimetric analyzer, the effect of solubility parameter on the dissolvability of resins in the solvent and the residual of organic vehicles were studied. Results showed that the hierar-chical volatilization of solvents can be obtained by mixing different solvents; the intrinsic vis-cosity of the organic vehicle is higher and the thermal decomposition residue of polyacrylate resins is lower when the solubility parameters of mixed solvents and polyacrylate resins are closer. The low residual sintering of organic vehicles can be achieved by using the mixed solvent with hierarchical volatility and approximate solubility parameters as resins.

Cellulose Diacetate/Organoclay Nanocomposites as Controlled Release Matrices for Pest Control Applications

This study aimed to develop cellulose-based polymer matrices as controlled release devices for plant-based insect repellents and attractants, with the aim of finding sustainable and environmentally friendly pest control methods for agricultural applications. Citronellol, terpineol and methyl salicylate were the selected active compounds for this study. Their compatibility with cellulose diacetate was predicted using Hansen Solubility Parameters, which predicted terpineol as the most compatible with cellulose diacetate, followed by methyl salicylate and citronellol. This was consistent with the plasticization efficiency trend from DMA results of solvent cast cellulose diacetate films containing the active compounds. The chemical identity of the films and cellulose diacetate-active compound intermolecular interactions were verified by FTIR. TGA demonstrated the thermal stability of cellulose diacetate/active compound/clay formulations at temperatures not exceeding 170 °C. Cellulose diacetate/organoclay nanocomposite matrices containing the active compounds at 35 wt-% were prepared by twin screw extrusion compounding, with the active compounds also functioning as plasticizers. The amount of active compound in the strands was determined by solvent extraction and TGA. Both methods showed that small amounts of active compound were lost during the compounding process. SEM demonstrated the effect of organoclay on the internal morphology of the matrix, whereas TEM showed clay dispersion and intercalation within the matrix. The matrix served as a reservoir for the active compounds while simultaneously controlling their release into the environment. Release profiles, obtained through oven ageing at 40 °C for 70 days, were fitted to existing Log-logistic and Weibull models, and novel Diffusion and Modified Weibull release models. Citronellol was released the fastest, followed by methyl salicylate and terpineol. The findings suggest that cellulose diacetate/organoclay strands are promising controlled-release matrices for pest control purposes.