Density Of Polystyrene Research Articles

All-organic polymer dielectrics prepared via optimization of sequential structure of polystyrene-based copolymers

It is a great challenge to improve simultaneously the permittivity (εr) and breakdown strength of polymer dielectrics. The linear polystyrene (PS) has the advantages of low cost, easy processing and high charge-discharge efficiency (η). However, the low εr and low breakdown strength result in the low discharge energy density (Ue) of PS. For polar liquid crystalline polymer poly[11-((4′-cyano-[1,1′-biphenyl]-4-yl)oxy)undecyl methacrylate] (PCBMA), it shows the merit of high εr, low band gap width and good film-forming property. In this paper, random copolymers P(St-co-CBMA) and block copolymers PS-b-PCBMA were synthesized by radical polymerization and reversible addition-breaking chain transfer polymerization, respectively. The effect of sequential structure on the dielectric behaviors and energy storage properties of polystyrene copolymers is investigated in detail. The experimental results indicate that a high εr value of 5.2 (±0.049), an outstanding Ue of 8.94 J/cm3 and high η of 87.4% at 476 MV/m are achieved in random copolymer P(St-co-CBMA) with the 92 mol% content of CBMA unit because of the strong orientation polarization, deep traps and good film-forming property. This work demonstrates that it is a feasible strategy to obtain high performance polystyrene copolymer dielectrics via tailoring sequential structure between functional monomer and styrene monomer.

Selective Laser Sintering of Polystyrene: Preserving Mechanical Properties without Post-processing

This study investigated the possibility of improving strength and density of polystyrene (PS) parts produced by selective laser sintering (SLS) without additives or post-processing. Post-processing methods are used by researchers to achieve optimal mechanical properties. An efficient method was proposed to systematically evaluate the PS powders and optimize the SLS process, in order to overcome the challenges of sintering the PS parts. The tailored SLS powder was produced from PS granule, and its properties including particle size and particle morphology, powder bed density and Hausner ratio (HR) were analyzed in order to evaluate powder quality. The FT-IR test was also utilized to investigate the possible effects of cryogenic milling and SLS processes on the material’s chemical compounds. Then, the effects of input parameters, including powder bed temperature as well as power and speed of the laser on the parts’ mechanical properties, were investigated. The sample’s maximum tensile strength and elongation were, respectively, 17.06 ± 0.9 MPa and 2.75% ± 0.55. The results revealed that it is possible to strengthen PS samples without additives and post-processing. However, due to the powder particle burning and confinement in the molten pool, the increase in energy density beyond the optimum level created spherical pores in the structure that weakened the sample’s strength. It is indicated that the energy density of the laser can be increased to achieve higher strength of specimens and dimensional accuracy can be controlled. TGA analysis of the SLS samples demonstrates when the energy density exceeds 0.4 J/mm2, degradation and decomposition take place in the specimens.

Development of Mathematical Model Based on Artificial Neural Network to Predict Density in Polymerization Process of Styrene

In the chemical industry is important to control the process in order to guarantee the quality and repeatability of the final product. Using sensors in the industrial plant allows a large volume of data to be captured regarding the process. These data can be used for modelling to better understanding and predict the properties of the product in the process. In this work, two types of Artificial Neural Networks (ANN) and the hybrid model Adaptive Neuro Fuzzy Inference System (ANFIS) were used to predict the density of polystyrene along the styrene polymerization process. The dataset used was extracted from the batch of polymerization reactions performed in open-loop, manual control and closed-loop and monitored in each 5 seconds. The Feedforward and Elman ANN has coefficient of correlation (R) equal 94.2%. However, the best topology obtained to Feedforward ANN presents 2 hidden layers and error index RMSE (Root Mean Squared Error) equal to 2.69x10-2. The Elman ANN presents only 1 hidden layer and RMSE of 3.39x10-2. The ANFIS model, in turn, presented R equal to 91% and RMSE of 0.2123. Therefore, ANFIS model did not prove to be the most adequate for the prediction of the polystyrene density in the studied process.Polymerization process pose significant challenges to the industrial community as it is difficult to control with high nonlinearity behaviour and fast dynamic response. The monitoring and control of polymer processes guarantee to the final product the qualities required by the market. Muhammad and Aziz (2017), for instance, studied the production of low density polyethylene (LDPE) and presented a review of the control strategies developed for the LDPE process. The strategies presented were developed in tubular and autoclave reactors and highlights the importance of nonlinear control in polymerization process.The use of sensors to monitor production allows a large volume of process data to be collected. Therefore, it is necessary to construct mathematical models of prediction to interpret and correlate significant patterns, indispensable to assist in the management of decisions and risk analysis.The development of phenomenological models for polymerization is complex and requires deep knowledge about the processes involved in each step. Modelling using artificial intelligence is a strategy that can provide valuable information about the process and allows the construction of an intelligent model capable of predicting process response based on parameters provided. ANN and ANFIS are artificial intelligence tools that can be used to build predictive models. In supervised learning, the data are presented to the network and its main objective is to provide a model that correctly correlates the pairs inputs - outputs of the problems. The use of ANN and ANFIS to predict the density of the polystyrene produced in the process becomes attractive since it is a type of non-linear modelling.Jumari and Mohd-Yusof (2017) presents models to measure melt flow index (MFI) in industrial polypropylene loop reactors using first principle (FP) model and ANN model. The authors state that the prediction of the ANN model is more accurate compare to the MFI calculated by the FP model. Furthermore, the CPU time recorded that ANN model is much faster than FP model.This work aims to develop direct and recursive ANN and ANFIS models from a set of experimental data from a controlled styrene polymerization plant capable of predicting the density of the product satisfactorily.

Probing the Density Variation of Confined Polymer Thin Films via Simple Model-Independent Nanoparticle Adsorption

After more than 2 decades of intense research, the density variation in confined polymer films still remains a puzzling problem subject to controversy as the methods utilized to determine the density are often model dependent. Here, we propose a direct and model independent method to detect the density/refractive index variations in polymer thin films through the adsorption of ceria nanoparticles (NPs) onto their surface. The amount of adsorbed NP scales with the polymer film refractive index; hence, any increase/decrease in the NP surface coverage directly indicates an increase/decrease in the film refractive index and density. Experimenting our proposed novel approach on two well-studied polymers, we found that the density of polystyrene (PS) thin films deposited on oxide-free Si substrate increases with a reduction of the film thickness. On the contrary, poly(methyl methacrylate) (PMMA) films deposited on wafers with native silicon oxide show a decrease of their density when the film thickness is reduced.

Simultaneous Determination of the Surface Tension and Density of Polystyrene in Supercritical Nitrogen

In this paper we present a simple procedure for calculating the mass density of polymers at high temperature and pressure conditions. The proposed method entails the integration of a pendant drop volume from an axisymmetric drop image profile; this same pendant drop profile can be used to determine the surface tension using axisymmetric drop shape analysis (ADSA). Our approach yields both density and surface tension data simultaneously and is advantageous since it does not require any additional procedure or module to calculate the density of polymers in a fluid. This integration method provides a set of density data for the sample polymer, polystyrene, in supercritical fluid nitrogen, which is similar to the data derived from the empirical Tait equation and the semiempirical Sanchez−Lacombe equation of state when the temperature is above the polymer glass transition point. The results corroborate the use of all three approaches in determining the mass density of polymers at high temperatures. The comparable surface tension data are obtained at temperatures above the glass transition temperature of polymer with the densities generated by the three density determination approaches. We expect that the approach based on ADSA in conjunction with the mass density determination by the current integration method can be applied to the surface tension measurements of many other polymer melts in various fluid environments.

Experiments on Solid-state Cell Nucleation in Polystyrene and Polycarbonate as a Function of Foaming Temperature and Foaming Time

In this paper, the equivalency between the foaming time and foaming temperature of the cell density, the number of cells per unit volume remaining in the foamed plastics, will be discussed. The foaming was carried out by the following method. The blowing agent was soaked into the solid resin at high pressure under temperature lower than the glass transition temperature of the resin. After the blowing agent reached its saturation state, cell nucleation and cell growth were induced by heating various foaming temperatures higher than glass transition temperature and various foaming times after decompression. Finally, cell growth was halted by cooling. Concretely, using a device that can accurately control temperature and the decompression rate, polystyrene (PS) and polycarbonate (PC) resins which are amorphous resins were foamed under various the foaming temperatures and the foaming times by the above-mentioned method. The following results were obtained. (1) Cell density of foamed PS and PC plastics shows time and temperature dependence as the cell density becomes large when foaming temperature is low and foaming time is short. (2) Equivalency is maintained between the foaming time and foaming temperature dependence of the cell density of PS and PC foamed plastics, and they can be expressed with one master curve respectively. That is, the time-temperature equivalent law is held about cell density. (3) These results seem to become one technique to select the foaming condition of foamed plastics having required cell densities.

Effect of Low Density Polyethylene on Polystyrene Foam

This work examines the foam density of polystyrene (PS) blended with low density polyethylene (LDPE) at various ratios, and the thermal conductivity of vacuum insulation panels (VIPs) using PS/PE with filler foam as core materials. The experimental results indicate that LDPE strongly influences the foam density of PS/PE foam and the content of open-cells in PS/PE with filler foam. A higher content of open-cells in PS/PE with filler foam can lead to a lower thermal conductivity of VIP.

The influence of pressure-dependent variation of the elastic constants on tunnelling systems in amorphous solids

We have measured the dielectric response ε( ω) and the thermal conductivity κ of polystyrene (PS) and of polycarbonate (PC) under high hydrostatic pressure (0.1 MPa<p<650 MPa ) and at low temperatures ( 50 mK<T<100 K ). The investigations show a pressure influence on the minimum temperature of Δ ε′/ ε′ and on κ. With the pressure dependence of the density and sound velocity of PC and PS the influence of pressure on the tunnelling constant C i can be determined. These results show that the product P ̄ γ l,t 2 of the standard tunnelling model (STM) scales with the pressure-dependent elastic constants c 11 and c 44.

Response of Adsorbed Polystyrene Layers to Desorption Conditions

Response of Adsorbed Polystyrene Layers to Desorption Conditions

The Volume Fraction Profile of Terminally Adsorbed Polymers

AbstractWe have used neutron reflectivity to measure the concentration profile of carboxylic acid-terminated polystyrene at the liquid/solid interface. Two isotopic systems were studied: (1) deuterated polystyrene (DPS) in cyclohexane and (2) polystyrene (PS) in deuterated cyclohexane. Although measured at 24°C (a poor solvent condition), the high grafting density of PS tethered chains causes the chains to weakly stretch to 3-5 times its unperturbed dimension. Although of similar molecular weight, the height of the DPS layer is about 50% higher than that of the PS. In both systems, the volume fraction of polymer near the wall is ∼ 0.60. For the DPS system, reflectivity profiles can be simulated using a parabolic profile with a depletion layer at the silicon-liquid interface. However, in the PS system, no depletion is observed. Here, the shape. of the PS concentration profile is parabolic with a rounded tail.

Density of polystyrene in diethyl malonate in the one-phase and two-phase regions near the critical solution point

Density of polystyrene in diethyl malonate in the one-phase and two-phase regions near the critical solution point

Effect of cooling rate and pressure at vitrification on the density of polystyrene

Abstract The effects of solidification pressure and cooling rate on the as-prepared density of polystyrene have been determined simultaneously. In general, the dependence of density individually on vitrification pressure and cooling rate is as previously reported; i.e., density decreases with increasing cooling rate and increases in a logarithmic fashion with pressure. However, we observe that the variation of density with vitrification pressure (∂p ρ/∂Pv) is independent of cooling rate; that the variation of density with vitrification cooling rate (∂ρ/∂Rv) is independent of pressure; and that the as-prepared density varies linearly with log(vitrification cooling rate).

Density changes in stretched polymers

Data are presented on the relation between the density of polystyrene and polyvinyl alcohol specimens and the relative elongation. The change in density observed during the stretching of polyvinyl alcohol specimens is associated with changes in the optical density of the 1146 cm−1 band and the crystalline phase content of the polymer.

Influence of solvent on measurement of cohesive energy density of polystyrene

The solubility parameter (δ2) of polystyrene was measured by the maximum [δ] method in four series of solvents which were structurally different. In each case δ2 varied with the solvent series used, from 8·75 to 9·25 (cal/ml)1/2 The enthalpy parameter (XH), which was calculated for polystyrene dissolved in at least one member of each series, was then used to derive δ2, and little or no variation in δ2, with solvent was observed. The average value was δ2 = 9·16 ± 0·1 (cal/ml)1/2 It has been shown that determination of δ2, from [η]max can be solvent-dependent because of the influence of the entropy term Xs. It was concluded that if reliable values of δ2 are to be obtained, they should be estimated from XH.

Cohesive Energy Density of Polystyrene

Bristow and Watson1 have recently described the determination of the cohesive energy densities of polymers by swelling and viscosity measurements. This communication summarizes the results of viscosity measurements on polystyrene solutions directed towards a similar end. The measurements cover a slightly different range of solvents from that of Bristow and Watson, and in some solvents a range of molecular weights has been investigated.

Density of polystyrene and polyvinyltoluene latex particles

The accurate determination of particle diameters from light scattering by means of functions derived from the Mie theory requires that the density of the particles be known very accurately since it enters the evaluation of both refractometric and scattering data. For this reason the densities of a series of monodisperse polystyrene and polyvinyltoluene latices were determined by using differential pycnometry introducing a few new features into this technique. It is shown that the technique, as used, should be capable of giving, with suitable systems, seven significant figures for the particle density. Such a high accuracy could not be aimed for in the three-component system used nor was it needed, the actual uncertainty occurring in the fifth figure. The data, apart from satisfying the purpose stated, showed that the density varies only a little with the particle diameter within the colloidal range.