Solvent Molecular Weight Research Articles

Bio‐polyols synthesized by liquefaction of cellulose: Influence of liquefaction solvent molecular weight

AbstractCurrently, the plastics industry including polyurethanes is based on the use of petrochemicals. For this reason, scientists are looking for new types of renewable resources for the substitution of petrochemical substances. This work aims to evaluate the effect of polyethylene glycols (PEG) with different molecular mass impact on properties of bio‐based polyols synthesized via biomass liquefaction of cellulose. To date, research has mostly focused on the use of different biomass sources, but the area of bio‐polyols synthesis with PEG with various molecular weights has not been explored in depth. For this reason, polyols were synthesized using PEG with a molecular weight in the range of 200–600 g/mol. Depending on the type of liquefaction solvent, the bio‐polyols showed a hydroxyl value of 519–652 mgKOH/g, a viscosity of 0.736–1.415 Pa∙s, and a water content below 1%. Observed difference may be related to change of reactivity of the PEG chains caused by steric hindrance of longer chains and the difference in the amount of reactive OH groups. These findings add substantially to understanding of the influence of liquefaction solvent molecular mass on the properties of new bio‐polyols and those of polyurethane materials.

Thermodynamic modeling of determined the optimal condition of the gas antisolvent process with different solvent

This study investigated the liquid-phase volume expansion to optimize the gas antisolvent (GAS) process condition. During the GAS process, particle precipitation does not take place in any operational conditions. Therefore, thermodynamic models are required to select the appropriate conditions and understand the precipitation mechanism. The Peng–Robinson equation of state with van-der-Waals (vdW2) mixing rules was used for the evaluation of the proper operational conditions at the temperature ranges of 308–338 K. The volume expansion of the system was studied at different process conditions for the binary (carbon dioxide-solvent) and ternary (carbon dioxide-solvent-rosuvastatin) systems. For this purpose, rosuvastatin (ROS) and carbon dioxides were solute and antisolvent, respectively. Dimethyl sulfoxide, ethanol, propanol, butanol, and pentanol were chosen as organic solvents. The minimum pressure for the ternary (carbon dioxide-dimethyl sulfoxide-rosuvastatin) system at 308, 318, 328, and 338 K was 7.80, 8.58, 9.79, and 11.1 MPa, respectively. The effect of solvent on volume expansion and minimum pressure was investigated. The calculated Pmin was 80, 82.4, 85.4, and 89.4 bar for ethanol, butanol propanol, and pentanol at 318 K respectively. According to modeling results, there was a direct relationship between the molecular weight of solvent with the same structure and minimum pressure.

Data-driven modeling of H2 solubility in hydrocarbons using white-box approaches

As a result of technological advancements, reliable calculation of hydrogen (H2) solubility in diverse hydrocarbons is now required for the design and efficient operation of processes in chemical and petroleum processing facilities. The accuracy of equations of state (EOSs) in estimating H2 solubility is restricted, particularly in high-pressure or/and high-temperature conditions, which could result in energy loss and/or potential safety and environmental problem. Two strong machine learning techniques for building advanced correlation were used to evaluate H2 solubility in hydrocarbons in this study which were Group method of data handling (GMDH) and genetic programming (GP). For that purpose, 1332 datasets from experimental results of H2 solubility in 32 distinct hydrocarbons were collected from 68 various systems throughout a wide range of operating temperatures from 98 K to 701 K and pressures from 0.101325 MPa to 78.45 MPa. Hydrocarbons from two distinct classes include alkane, alkene, cycloalkane, aromatic, polycyclic aromatic, and terpene. Hydrocarbons have a molecular mass range of 28.054–647.2 g/mol, which corresponds to a carbon number of 2–46. Solvent molecular weight, critical pressure, and critical temperature, as well as pressure and temperature operational parameters, were used to create the features. With a regression coefficient (R2) which was equal to 0.986 and root mean square error (RMSE) which was 0.0132, the GP modeling approach estimated experimental solubility data more accurately than the GMDH approach. Operating pressure, followed by molecular weight of hydrocarbon solvents and temperature, had the greatest influence on estimation H2 solubility, according to sensitivity analysis. The GP model shown in this paper is a reliable development that may be used in the chemical and petroleum sectors as a reliable and effective estimator for H2 solubility in diverse hydrocarbons.

Recovery of paraffin from the filter cake used for paraffin decoloration in the Fischer-Tropsch synthetic process

The Fischer-Tropsch synthetic paraffin residue are mainly treated by combustion or landfill. In this study, an innovative process has been developed for the grading utilization of the Fischer-Tropsch synthetic paraffin residue by extraction and pyrolysis. Firstly, the Fischer-Tropsch synthetic paraffin residue was respectively extracted by n-pentane, n-hexane, n-heptane, cyclohexane and dichloromethane. The yield of extracted paraffin was related to solvent molecular weight and polarity, light alkanes were extracted more easily in non-polar solvents with relatively larger molecular weight. N-heptane showed the highest extraction yield of 57.86%, the extracted paraffin was similar to the paraffin product from Fischer-Tropsch and had more light components, less alkenes and oxygenated components. Afterwards, the solid residues after extraction were pyrolyzed at optimum conditions with 10 ℃/min and 500 ℃. The maximum yield of paraffin was up to 61.75% with the solvent of n-heptane in the grading utilization process, which accounted for 94.33% of the organic components in the Fischer-Tropsch synthetic paraffin residue. The recovered paraffin had higher saturation and less impurity than the Fischer-Tropsch paraffin. The solid product after pyrolysis had high specific surface area and could be processed into adsorbent and catalyst carrier. The grading technology could provide a rationalizing industrial scheme for handling the Fischer-Tropsch synthetic paraffin residue from the Shanxi Lu′an group corporation coal to oil plant of 1.0 million tons/a, 1852.5 tons of high-quality paraffin can be recovered each year.

Derivation of limiting ion mobility equation based on the application of solvation effect-incorporated Poisson-Boltzmann equation

Interaction potential energy between ion and solvent molecular dipole moments in solvation shell around ion was derived on basis of the application of the solution of linear SEI-PB (Solvation Effects-Incorporated Poisson-Boltzmann) equation. Based on application of the solution of linear SEI-PB equation, distribution of solvent molecules in solvation shell around ion in electrolyte solution at thermodynamic equilibrium was derived. In case approaching to limit of infinite dilution, analytical expression for evaluating limiting ion mobility is derived from the boundary condition that the average number of solvent molecules accompanying with translational motion of ion is equal to the mean solvation number of ion. The derived limiting ion mobility formula is different from the Stokes–Einstein relation and lies in relation to direct proportion with the cube of dynamic size of ion in solution, depending not only on the viscous coefficient, dielectric constant, the density and molecular weight of solvent but also on temperature.By virtue of the equation, it was possible to estimate dynamic sizes of ions in solution. It was found the estimated dynamic sizes of ions in aqueous solution to be compatible with the average ion–water distances, and to be always greater than crystallographic ionic radii in size.A new relation between the limiting ion mobility and the solvent molecular dipole moment in solvation shell was established based on the interaction potential energy between ion and solvent molecular dipole moments in solvation shell around ion. By virtue of the proposed relation, we could find out the average water molecular dipole moment in hydration shell to be different more or less in size from that in bulk solution according to ionic species in aqueous solution.

The role of solvent molecular weight in shear thickening and shear jamming.

The application of stress can drive a dense suspension into a regime of highly non-Newtonian response, characterized by discontinuous shear thickening (DST) and potentially shear jamming (SJ), due to the formation of a frictionally stabilized contact network. Investigating how the molecular weight of the suspending solvent affects the frictional particle-particle interactions, we report on experiments with suspensions of fumed silica particles in polyethylene glycol (PEG). Focusing on the monomer-to-oligomer limit, with n = 1 to 8 ethylene oxide repeat units, we find that increasing n enhances shear thickening under steady-state shear and even elicits rapidly propagating shear jamming fronts, as assessed by high-speed ultrasound imaging of impact experiments. We associate this behavior with a weakening of the solvation layers surrounding the particles as n is increased, which thereby facilitates the formation of frictional contacts. We argue that for n larger than the monomer-to-oligomer limit the trend reverses and frictional interactions are diminished, as observed in prior experiments. This reversal occurs because the polymeric solvent transitions from being enthalpically bound to entropically bound to the particle surfaces, which strengthens solvation layers.

A new engineering process of biodegradable polymeric solid implants for ultra-long-acting drug delivery

We present a long-acting (LA) biodegradable polymeric solid implant (PSI) fabricated using a new process combining in-situ phase inversion and compression. This robust process allows fabrication of solid implants that can have different shapes and sizes, accommodate high drug payloads, and provide sustained drug release over several months. Herein the integrase inhibitor dolutegravir (DTG) was used to develop PSIs for HIV prevention. PSIs were fabricated using a three-step process by (a) phase inversion of DTG-loaded polymer solution to form an initial in-situ forming implant in an aqueous solution, (b) micronization of dried DTG-loaded solid implants, and (c) compression of the micronized DTG-loaded solid implants to form the PSI. High drug loading (up to 85 wt%) was achieved in the PSIs. DTG exhibited minimum burst release in the first 24 h (<6%) and sustained release kinetics over 6 months. The release kinetics of DTG can be fine-tuned by varying drug-loading concentration, the ratio of polymer (poly(lactic-co-glycolic acid), PLGA) to solvent (N-methyl-2-pyrrolidone, NMP) and polymer (PLGA) molecular weight in the precursor solution. The physical/chemical properties of DTG were retained post-storage under accelerated storage conditions (40 °C/75% relative humidity) for 6 months. The versatility of this technology makes it an attractive drug delivery platform for HIV prevention applications.

Experimental investigation on CO2 absorption and physicochemical characteristics of different carbon-loaded aqueous solvents.

The anthropogenic carbon dioxide (CO2) denseness in the earth's atmosphere is increasing day-to-day by combusting fossil fuels for power generation. And, it is the most important greenhouse gas (GHG) responsible for 64% of global warming. Solvent-based carbon capture gained more attention towards researchers because of its easiness to integrate with the coal-fired power plant without significant modifications. During CO2 absorption, the physical property of the solvent gets changed. A change in the solvent's physicochemical property affects further CO2 absorption, thereby increasing the carbon-capture energy demand. The present experimental study encompasses CO2 absorption studies using 30 wt% aqueous monoethanolamine (MEA), 2-amino-2-methyl-1-propanol (AMP) and piperazine (PZ) followed by the detailed analysis of physicochemical properties (pH, carbon loading (α), viscosity (μ), density (ρ) and surface tension (σ)) of various CO2-loaded solutions. The results revealed that these properties are exhibiting interdependent eccentrics. Furthermore, an empirical model was developed to predict the carbon loading of the tested solvents. This model includes the tested physicochemical properties, reaction mixture temperature, diffusivity and change in the mass of solvent during carbon loading. In addition, an empirical model for viscosity as a function of temperature, carbon loading and molecular weight of solvents was developed. These models appear to predict the carbon loading and the viscosity well with greater accuracy. Graphical abstract.

Pattern-Directed Phase Transitions and VOC Sensing of Liquid Crystal Films

Solvent vapor exposure could transform a crystalline or smectic liquid crystal (LC) film into nematic and isotropic phases under ambient conditions. The average time for such phase transitions is found to linearly reduce with an increase in vapor pressure and reduction in the molecular weight of solvents. Such responses of solvent vapor-annealed phase transitions of a nanoparticle-loaded LC droplet were then converted into an electrical signal, wherein the electrical resistance reduced (increased) with time upon destruction (restoration) of the orientational order of the LC matrix. Variation in the electrical response was used to identify the volatile organic vapors, phase transition of LCs, rate of diffusion–absorption of solvent into LCs, and rate of desorption–evaporation of solvent from LCs. Pattern-directed phase transitions on physically heterogeneous surfaces showed a faster (slower) kinetics on thinner (thicker) patterns. However, for chemically heterogeneous surfaces, weaker (stronger) anchoring of LCs on hydrophobic (hydrophilic) patches ensured a faster (slower) transition.

Investigation of the role of polyol molecular weight in the polyol synthesis of silver nanoparticles

The polyol synthesis method is a popular approach for fabricating long silver nanowires. Additionally, the polyol method has been claimed to produce various shapes and sizes of nanoparticles by altering certain parameters of the reaction, such as the molecular weight of the solvent. Yet the effect of varying the molecular weight of the polyol solvent on the synthesis product is not well understood, since studies that report an effect that the solvent use substantially different procedures. Here, we analyze the effect of changing the polyol solvent, from ethylene glycol to poly(ethylene glycol) with different molecular weights, on the shape and size of silver nanoparticles using the same procedure. Using ethylene glycol, silver nanowires (up to 2 μm in length) are synthesized, similar to what has been widely reported. Under the same conditions, poly(ethylene glycol) of any molecular weight yields shorter nanoparticles (<500 nm) with different shapes. Additionally, the impacts that synthesis variables have differ with polyol molecular weight. Using ethylene glycol, chloride ions are required to obtain nanowires; the length of which can be shortened by adjusting the reaction time or the concentration of capping agent. Using poly(ethylene glycol), these synthesis variables have different outcomes: chloride ions do not affect the yield of anisotropic nanoparticles; neither does the concentration of the capping agent.

Effect of kinematic viscosity on the staining performance of caries detector dyes

The relationship between performance of caries detector dyes and solvent molecular weight has been reported, but viscosity has not yet been investigated. Therefore, using extracted human teeth, we compared 6 experimental caries detector dyes with different viscosities to clarify the relationship between dye viscosity and staining performance in sclerotic dentin. Carious dentin started showing dentin staining when stained with caries detector dyes with kinematic viscosity≥263 mm2/s, showed no immunoreactivity for Streptococcus mutans on immunohistochemistry, and contained dentinal tubules free of debris on scanning electron microscopy. Samples stained using a caries detector dye with kinematic viscosity of 332 mm2/s contained calcification product-like debris in the dentinal tubules. These findings suggest that the caries detector dye has a threshold kinematic viscosity between 263 and 332 mm2/s at which sclerotic dentin and tissues beyond are not stained. The caries detector dye appears to control tooth dyeability based on solvent viscosity.

The Prediction of Cloud Point Temperature in Wax and Pure Paraffin Depositions by using a PSO based ANN Approach

Objectives: Predicting the Cloud Point Temperatures in Wax and Pure Paraffin Depositions which can help oil experts make substantial decisions to have less heavy material deposition in crude (oil). Methods/Statistical Analysis: In this paper, we use a PSO based ANN approach to predict the cloud point temperature of depositions, which has been designed based on the most important parameters that are related to cloud point temperature. Solvent molecular weights, solute molecular weights, and solute weight fraction are the main parameters that have been considered, while observing the cloud point temperature amounts. Findings: By predicting factors that make sediment happen, we eliminate or reduce the deposition of action. The modeled results show 99% for test dataset in both used depositions. Application/Improvements: The proposed method improves the results to achieve more precision results compared to the previous related works. Keyword: ANN, Cloud Point Temperature, Paraffin Deposition, Wax Deposition, PSO

Reverse osmosis separation of particular organic solvent mixtures by a perfluorodioxole copolymer membrane

Reverse osmosis (RO) separation of organic solvent mixtures where solvent molecular weights are < 100 Da is challenging especially for powerful solvents that swell most uncrosslinked polymers. To avoid polymer swelling by solvents, a particular perfluoropolymer, perfluoro-2,2-dimethyl-1,3-dioxole copolymerized with tetrafluoroethylene, (PDD-TFE), designated CMS-7, was studied. This amorphous glassy extremely hydrophobic copolymer has a very high free volume (FV) fraction. The maximum dimension of FV regions is less than ~ 0.65 nm allowing only single solvent molecule permeation. Further, interactions between polarity, dimensions and shapes of solvent molecules with those of polymer FV elements can lead to extraordinarily selective permeation. RO separation of the following binary systems through a thin 1.67 µm film of this polymer supported on an e-PTFE support was studied over 1000–3500 kPa feed pressure: N-Methyl-2-pyrrolidone (NMP)-toluene; dimethylformamide (DMF)-toluene; dimethylsulfoxide (DMSO)-toluene; NMP-methanol; n-butanol-ethanol. Pure toluene appeared as permeate for three polar aprotic-aromatic systems from highly toluene-rich feeds; the membrane rejected polar molecules having dimensions similar to those of toluene. High osmotic pressure of the feed mixtures employed vis-à-vis feed pressures used reduced toluene permeation flux and the range of separable feed mixtures. Pure methanol permeate was obtained from particular polar aprotic-polar protic NMP-methanol mixtures due to significantly smaller methanol dimensions. Pure ethanol permeate was also similarly obtained from a particular mixture with n-butanol, a case of polar protic1-polar protic2 system where ethanol molecules were smaller. Such novel and clean-cut pressure-driven separations may be due to various combinations of the dimensions of the solvent molecules and the polymer FV regions, high polymer hydrophobicity, polarity of the aprotic/protic solvents and very low swelling of the polymer. Solvent sorption studies of dense polymers provide an insight into swelling of the polymer by the solvent and potential solvent-specific interactions. Sorption studies using 25 µm polymer samples for polar aprotic solvents, NMP, DMF, DMSO, yielded very low levels of sorption, 0.4–0.9 wt%; those for toluene and methanol were already known to be only 1.34 and 1.2 wt% respectively. Permeation behaviors of other solvent mixtures, toluene-n-heptane, NMP-tetrahydrofuran, methanol-water, ethanol-water as well as individual phases of the immiscible mixture of NMP and the nonpolar solvent n-heptane were also studied. To improve understanding, permeation of pure water in reverse osmosis mode was also investigated.

Quantitative structure-property relationship (QSPR) for prediction of CO2 Henry’s law constant in some physical solvents with consideration of temperature effects

Different types of physical solvents have been utilized for CO2 removal from natural gas in the sweetening process. In this work, quantitative structure-property relationship (QSPR) method is suggested to build powerful models to predict Henry’s law constant (HLC) for CO2 in physical solvents. Modeling the HLC for CO2 as a function of molecular descriptors was achieved by multiple linear regression and descriptor selection was by genetic algorithm. The main proposed model has two simple descriptors, including the number of hydroxyl groups and molecular weight of solvents at fixed temperature. Also, the effect of temperature was studied, and this operational variable was added to the mentioned simple descriptors. In this case, the data set is comprised of 77 HLC for CO2 in solvents and at different temperatures. Several internal and external validation methods demonstrated the excellent ability for prediction, and the average relative deviation of main model was 6.48.

Direct observation of DNA dynamics in semidilute solutions in extensional flow

The dynamic behavior of semidilute polymer solutions is governed by an interplay between solvent quality, concentration, molecular weight, and flow type. Semidilute solutions are characterized by large fluctuations in polymer concentration, wherein polymer coils interpenetrate but may not be topologically entangled at equilibrium. In nonequilibrium flows, it is generally thought that polymer chains can “self-entangle” in semidilute solutions, thereby leading to entanglements in solutions that are nominally unentangled at equilibrium. Despite recent progress in the field, we still lack a complete molecular-level understanding of the dynamics of polymer chains in semidilute solutions. In this work, we use single molecule techniques to investigate the dynamics of dilute and semidilute solutions of λ-phage deoxyribonucleic acid in planar extensional flow, including polymer relaxation from high stretch, transient stretching dynamics in step-strain experiments, and steady-state stretching in flow. Our results are consistent with a power-law scaling of the longest polymer relaxation time τ∼(c/c*)0.48 in semidilute solutions, where c is the polymer concentration and c* is the overlap concentration. Based on these results, an effective excluded volume exponent ν ≈ 0.56 was found, which is in good agreement with recent bulk rheological experiments. We further studied the nonequilibrium stretching dynamics of semidilute polymer solutions, including transient (1 c*) and steady-state (0.2 c* and 1 c*) stretching dynamics in planar extensional flow using an automated microfluidic trap. Our results show that polymer stretching dynamics in semidilute solutions is a strong function of concentration. In particular, a decrease in transient polymer stretch in semidilute solutions at moderate Weissenberg number (Wi) compared to dilute solutions is observed. Moreover, our experiments reveal a milder coil-to-stretch transition for semidilute polymer solutions at 0.2 c* and 1 c* compared to dilute solutions. Interestingly, a unique set of molecular conformations during the transient stretching process for single polymers in semidilute solutions is observed, which suggests transient stretching pathways for polymer chains in semidilute solutions are qualitatively different compared to dilute solutions due to intermolecular interactions. Taken together, this work provides a molecular framework for understanding the nonequilibrium stretching dynamics of semidilute solutions in strong flows.

Fischer-Tropsch synthesis: Effect of solvent on the H2–D2 isotopic exchange rate over an activated nickel catalyst

The effect of solvent on the hydrogen-deuterium isotopic homomolecular exchange rate over a 26.4% Ni/Al2O3 catalyst was investigated using a plug flow reactor at room temperature (23°C) and at atmospheric pressure. In this study, two different molecular weight solvents were tested: n-pentane (MW¯(average molecular weight)=72), and n-hexadecane (MW¯=226). At dry (without addition of solvent) and n-pentane solvent addition conditions, similar amounts of H2 and D2 are consumed and the concentration of the HD produced is two times the consumption of H2 or D2. Thus, these conditions exhibited around 100% exchange with the formation of H2:HD:D2 having a 1:2:1 ratio. With n-hexadecane solvent, the initial exchange rate was approximately 45%, but the exchange rate decreased with time and reached a steady state rate after 60min on-stream. The lower exchange rate of the n-hexadecane solvent might be due to the limited mobility of reactant molecules in the liquid-filled pores of the catalyst. The exchange rate of the catalyst is decreased with increasing molecular weight and density of the solvent. An isotopic partitioning preference was not observed for the nickel catalyst under various co-fed solvents, and similar findings were observed in our previous work (Catalysis Letters 143 (2013) 1368–1373).

Estimation of asphaltene precipitation in light, medium and heavy oils: experimental study and neural network modeling

Asphaltene can precipitate in oil reservoirs as a result of natural depletion and/or gas injection crippling the oil production performance. Most of the conventional models for asphaltene precipitation cannot precisely capture the asphaltene precipitation at a wide pressure range and for different oil types. To have a precise model that can be used for various oil types at a wide range of pressure conditions, a comprehensive artificial neural network (ANN) model was proposed to estimate the weight percent of precipitated asphaltene in different oil types (three oil types, namely light, medium and heavy). The dilution ratio, pressure, molecular weight of solvent, API gravity and resin-to-asphaltene ratio were considered as the model input parameters. The oil samples were thus categorized based on the differences in their API gravity and resin-to-asphaltene ratio. Five hundred and fifty experimental precipitation datapoints were obtained from our experimental apparatus in a wide range of pressure, dilution ratio and injected fluid molecular weight, and used to make a comprehensive databank for model calibration and verification. At the test stage, the coefficient of correlation (R2) was higher than 0.98 and mean square error was less than 0.04 indicating the good performance of the proposed model. Furthermore, a comparison between the prediction of ANN model and two types of alternative approaches, namely the thermodynamic and the fractal/aggregation approaches, was performed. For this purpose, the prediction of two of the widely used solubility models, Flory---Huggins and Modified Flory---Huggins and also a polydisperse thermodynamic model was compared to the prediction of the proposed ANN model. In addition to those, as a fractal/aggregation model, a scaling model was also selected and employed to compare its performance against that of the proposed ANN model. The ANN model showed a better performance as compared to the other conventional models. The results demonstrated that the proposed model provides acceptable prediction for different oil types over a wide range of pressure which is a difficult task for most of the conventional techniques.

Robust method based on optimized support vector regression for modeling of asphaltene precipitation

Abstract Precipitation of asphaltene largely affects the production rate of crude oil owing to the clogging of transportation pipeline as well as formation damage. Therefore, it is imperative to search for a robust method for the modeling of asphaltene precipitation. This paper aims to propose a new mathematical model for computing asphaltene precipitation as a function of titration data including dilution ratio, temperature, and molecular weight of solvent. This model is constructed based on integrating the support vector regression with the imperialist competitive algorithm. Optimization increases the performance of support vector regression by virtue of determining the optimal values of their parameters. The constructed model is applied to experimental data and its performance is compared with scaling equation which is traditionally employed for modeling of asphaltene precipitation. The results of this study show that the integration of imperialist competitive algorithm and support vector regression has a better performance than the scaling equation. This paper offers that the support vector regression optimized by virtue of the imperialist competitive algorithm is a reliable model for modeling asphaltene precipitation.

Application of Artificial Neural Network-Particle Swarm Optimization Algorithm for Prediction of Asphaltene Precipitation During Gas Injection Process and Comparison With Gaussian Process Algorithm

Asphaltene precipitation is a major problem in the oil production and transportation of oil. Changes in pressure, temperature, and composition of oil can lead to asphaltene precipitation. In the case of gas injection into oil reservoirs, the injected gas causes a change in oil composition and may lead to asphaltene precipitation. Accurate determination and prediction of the precipitated amount are vital, for this purpose there are several approaches such as experimental method, scaling equation, thermodynamics models, and neural network as the most recent ones. In this paper, we propose a new artificial neural network (ANN) optimized by particle swarm optimization (PSO) to predict the amount of asphaltene precipitation. This is conducted during the process of gas injection into oil reservoirs for enhanced oil recovery purposes. In the developed models, (1) oil composition, (2) temperature, (3) pressure, (4) oil specific gravity, (5) solvent mole percent, (6) solvent molecular weight, and (7) asphaltene content are considered as input parameters to the neural network. The weight of asphaltene and asphaltene content are considered as input parameters to the neural network and the weight of asphaltene precipitation as an output parameter. A comparison between the results of the proposed new model with Gaussian Process algorithm and previous research shows that the predictive model is more accurate.

Uklady polimerowe formowane in situ do zastosowan biomedycznych. Cz. I. Implanty wstrzykiwalne

The paper is a literature review with 111 references on the polymeric implants forming in the site of incorporation into organism. This kind of materials may have only a structural function, but they can also serve as carriers of bioactive compounds in the treated site. In situ forming implants (ISFI) can be obtained by reaction of functional groups contained in the system components or as a result of physical processes. ISFI serving as injectable scaffolds intended for tissue regeneration and the requirements that should be fulfilled by these materials are presented. Also, various ideas for using ISFI as controlled drug delivery systems, in particular clinically used materials, are described. The attention is focused on the systems solidifying by solid phase separation, based on aliphatic polyesters accepted for biomedical applications. The composition of these systems and the influence of solvent and polymer molecular weight on the rate of implant formation as well as kinetics of bioactive substance release are discussed.