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Polymers Physics: From Theory to Experimental Applications

A special issue of Polymers (ISSN 2073-4360). This special issue belongs to the section "Polymer Physics and Theory".

Deadline for manuscript submissions: closed (15 September 2024) | Viewed by 35676

Special Issue Editors

Special Issue Information

Dear Colleagues,

Polymer processing techniques are of paramount importance in the manufacture of plastic parts. The main concern is producing parts with the desired quality, which usually refers to mechanical performance, dimensional accuracy, and appearance. To maximize the overall efficiency of polymer processing techniques, new constitutive models and advanced modeling codes are needed along with experimental measurements to simulate, compare, and optimize processes. This is a complex task involving understanding the molecular theory behind such complex deformations, solving the problem numerically for small scales, transferring the molecular theory to a continuum medium, solving the resulting differential equations numerically, performing numerical experiments, and comparing the numerical and experimental results.

Thus, this Special Issue will welcome contributions which develop theories for new rheological constitutive equations and implementation of efficient algorithms to describe polymer physics. In addition, experimental studies for the preparation and characterization of new polymeric materials are also welcomed. Topics include but are not limited to the following:

  • Viscoelastic flow modeling;
  • Molecular simulation;
  • Heat transfer problems;
  • Machine learning techniques;
  • New materials, additives, and fillers;
  • Additive manufacturing and 3D printing;
  • Polymer rheology and mechanical properties.

Dr. Célio Pinto Fernandes
Dr. Luís Lima Ferrás
Dr. Alexandre M. Afonso
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Polymers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

 

Keywords

  • multiphase flows
  • suspensions
  • viscoelasticity
  • heat transfer
  • machine learning
  • additive manufacturing
  • 3D printing
  • polymer rheology and mechanical properties

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Published Papers (18 papers)

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Editorial

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4 pages, 177 KiB  
Editorial
Polymer Physics: From Theory to Experimental Applications
by Célio Fernandes, Luís L. Ferrás and Alexandre M. Afonso
Polymers 2024, 16(6), 768; https://doi.org/10.3390/polym16060768 - 11 Mar 2024
Viewed by 1552
Abstract
The significance of polymer processing techniques cannot be overstated in the production of polymer components [...] Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)

Research

Jump to: Editorial, Review

22 pages, 4076 KiB  
Article
Simulation and Analysis of the Loading, Relaxation, and Recovery Behavior of Polyethylene and Its Pipes
by Furui Shi and P.-Y. Ben Jar
Polymers 2024, 16(22), 3153; https://doi.org/10.3390/polym16223153 - 12 Nov 2024
Viewed by 700
Abstract
Spring–dashpot models have long been used to simulate the mechanical behavior of polymers, but their usefulness is limited because multiple model parameter values can reproduce the experimental data. In view of this limitation, this study explores the possibility of improving uniqueness of parameter [...] Read more.
Spring–dashpot models have long been used to simulate the mechanical behavior of polymers, but their usefulness is limited because multiple model parameter values can reproduce the experimental data. In view of this limitation, this study explores the possibility of improving uniqueness of parameter values so that the parameters can be used to establish the relationship between deformation and microstructural changes. An approach was developed based on stress during the loading, relaxation, and recovery of polyethylene. In total, 1000 sets of parameter values were determined for fitting the data from the relaxation stages with a discrepancy within 0.08 MPa. Despite a small discrepancy, the 1000 sets showed a wide range of variation, but one model parameter, σv,L0, followed two distinct paths rather than random distribution. The five selected sets of parameter values with discrepancies below 0.04 MPa were found to be highly consistent, except for the characteristic relaxation time. Therefore, this study concludes that the uniqueness of model parameter values can be improved to characterize the mechanical behavior of polyethylene. This approach then determined the quasi-static stress of four polyethylene pipes, which showed that these pipes had very close quasi-static stress. This indicates that the uniqueness of the parameter values can be improved for the spring–dashpot model, enabling further study using spring–dashpot models to characterize polyethylene’s microstructural changes during deformation. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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Figure 1

Figure 1
<p>Specimens used in the RR tests: (<b>a</b>) dimensions of cylindrical specimen, (<b>b</b>) cylindrical specimen, (<b>c</b>) dimensions of NPR specimen (PE-Xa pipe as an example), and (<b>d</b>) NPR specimen. All units are in millimeters.</p>
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<p>Three-branch spring–dashpot model used in this study.</p>
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<p>Procedure for the determination of fitting parameters in the relaxation, recovery, and loading stages of RR tests.</p>
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<p>The 1000 sets of parameter values for simulation at the relaxation stages of different deformation levels in one RR test of HDPE-b: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>v</mi> <mo>,</mo> <mi>L</mi> </mrow> </msub> <mo>(</mo> <mn>0</mn> <mo>)</mo> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>v</mi> <mo>,</mo> <mi>S</mi> </mrow> </msub> <mo>(</mo> <mn>0</mn> <mo>)</mo> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mn>0</mn> <mo>,</mo> <mi>L</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mn>0</mn> <mo>,</mo> <mi>S</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>e</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>τ</mi> </mrow> <mrow> <mi>v</mi> <mo>,</mo> <mi>L</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>τ</mi> </mrow> <mrow> <mi>v</mi> <mo>,</mo> <mi>S</mi> </mrow> </msub> </mrow> </semantics></math>, and (<b>g</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>q</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math>. Different colors at one stroke are used to indicate the 1000 sets of parameter values.</p>
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<p>A two-path pattern of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>v</mi> <mo>,</mo> <mi>L</mi> </mrow> </msub> <mo>(</mo> <mn>0</mn> <mo>)</mo> </mrow> </semantics></math> as a function of stroke for NPR specimens based on 1000 sets of parameter values: (<b>a</b>) PE-Xa, (<b>b</b>) PE2708, (<b>c</b>) PE4710-yellow, and (<b>d</b>) PE4710-black pipes. Different colors at one stroke are used to indicate the 1000 sets of parameter values.</p>
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<p>Best five sets of parameter values (in open red circles) selected from 1000 sets for the simulation of stress variation at the relaxation stages of HDPE-b and the corresponding <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>q</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math>: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>v</mi> <mo>,</mo> <mi>L</mi> </mrow> </msub> <mo>(</mo> <mn>0</mn> <mo>)</mo> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>v</mi> <mo>,</mo> <mi>S</mi> </mrow> </msub> <mo>(</mo> <mn>0</mn> <mo>)</mo> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mn>0</mn> <mo>,</mo> <mi>L</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mn>0</mn> <mo>,</mo> <mi>S</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>e</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>τ</mi> </mrow> <mrow> <mi>v</mi> <mo>,</mo> <mi>L</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>τ</mi> </mrow> <mrow> <mi>v</mi> <mo>,</mo> <mi>S</mi> </mrow> </msub> </mrow> </semantics></math>, and (<b>g</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>q</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math>. Different colors at one stroke are used to indicate the five best sets of parameter values.</p>
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<p>Simulation of stress change at relaxation stages of different strokes for HDPE-b using the fitting parameter values in <a href="#polymers-16-03153-f006" class="html-fig">Figure 6</a>.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>K</mi> </mrow> <mrow> <mi>v</mi> <mo>,</mo> <mi>L</mi> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>K</mi> </mrow> <mrow> <mi>v</mi> <mo>,</mo> <mi>S</mi> </mrow> </msub> </mrow> </semantics></math> as a function of stroke of HDPE-b.</p>
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<p>Summary RR test results for NPR specimens: (<b>a</b>) applied stress at the onset of relaxation,<math display="inline"><semantics> <mrow> <mo> </mo> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>A</mi> </mrow> </msub> </mrow> </semantics></math>(0), and (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>σ</mi> </mrow> <mrow> <mi>q</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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16 pages, 4616 KiB  
Article
Analyzing Homogeneity of Highly Viscous Polymer Suspensions in Change Can Mixers
by Michael Roland Larsen, Erik Tomas Holmen Olofsson and Jon Spangenberg
Polymers 2024, 16(18), 2675; https://doi.org/10.3390/polym16182675 - 23 Sep 2024
Viewed by 553
Abstract
The mixing of highly viscous non-Newtonian suspensions is a critical process in various industrial applications. This computational fluid dynamics (CFD) study presents an in-depth analysis of non-isothermal mixing performance in change can mixers. The aim of the study was to identify parameters that [...] Read more.
The mixing of highly viscous non-Newtonian suspensions is a critical process in various industrial applications. This computational fluid dynamics (CFD) study presents an in-depth analysis of non-isothermal mixing performance in change can mixers. The aim of the study was to identify parameters that significantly influence both distributive and dispersive mixing in these mixers, which are essential for optimizing industrial mixing processes. The study employed a numerical design of experiments (DOE) approach to identify the parameters that most significantly influence both distributive and dispersive mixing, as measured by the Kramer mixing index (MKramer) and the Ica Manas-Zloczower mixing index λMZ¯. The investigated parameters included mixing time, number of arms, arm size ratio, revolutions per minute (RPM), z-axis rotation, z-axis movement, and initial and mixing temperatures. The methodology involved employing the bootstrap forest algorithm for predicting the mixing indices, achieving an R2 of 0.949 for MKramer and an R2 of 0.836 for λMZ¯. The results indicate that the z-axis rotation has the greatest impact on both distributive and dispersive mixing. An increased number of arms negatively impacted λMZ, but had a small positive effect on MKramer. Surprisingly, in this study, neither the initial temperature of the material nor the mixing temperature significantly impacted the mixing performance. These findings highlight the relative importance of operational parameters over traditional temperature factors and provide a new perspective on mixing science. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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Figure 1

Figure 1
<p>Illustration of the change can mixer (<b>left</b>) and mixing arm (<b>right</b>).</p>
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<p>CFD model at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>. The blue/turquoise mass represents the fluid, while the red mass represents the powder.</p>
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<p>The model plotted to measurements at 80 and 100 °C.</p>
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<p>Velocity profiles at 60 s for (<b>a</b>) Sim. No. 7 and (<b>b</b>) Sim. No. 35. The velocity values are in m/s.</p>
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<p>Average fluid temperature for Sim. No. 7 and Sim. No. 35 as a function of time.</p>
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<p>Dispersive mixing index for Sim. No. 7 and 35 as a function of time.</p>
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<p>Distributive mixing index for Sim. No. 7 and Sim. No. 35 compared to time.</p>
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<p>Predictor screening analysis of the influence of each parameter on dispersive mixing. Note the significance line at 5%.</p>
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<p>(<b>a</b>) Influence of each parameter on dispersive mixing, and (<b>b</b>) comparison between predicted and simulation values. Note the significance line at 5% in (<b>a</b>).</p>
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<p><math display="inline"><semantics> <mrow> <mover accent="true"> <mrow> <msub> <mrow> <mi>λ</mi> </mrow> <mrow> <mi>M</mi> <mi>Z</mi> </mrow> </msub> </mrow> <mo>¯</mo> </mover> </mrow> </semantics></math> values for Batch 12 with predicted and simulation values.</p>
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<p>Vorticity comparison for three simulations with varying numbers of arms.</p>
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<p>Screening of each parameter to <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>10</mn> <mi> </mi> <mi mathvariant="normal">s</mi> </mrow> </semantics></math> and then <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>30</mn> <mi> </mi> <mi mathvariant="normal">s</mi> </mrow> </semantics></math> and then every <math display="inline"><semantics> <mrow> <mn>30</mn> <mi> </mi> <mi mathvariant="normal">s</mi> </mrow> </semantics></math>. Note the significance line at 5%. Positive and negative indicate the way in which the parameter affects the mixing when increased.</p>
Full article ">Figure 13
<p>(<b>a</b>) Contribution for each parameter, and (<b>b</b>) the predicted vs the simulated values. Note the significance line at 5% in (<b>a</b>).</p>
Full article ">
18 pages, 6477 KiB  
Article
Development of a Cure Model for Unsaturated Polyester Resin Systems Based on Processing Conditions
by Abdallah Barakat, Marc Al Ghazal, Romeo Sephyrin Fono Tamo, Akash Phadatare, John Unser, Joshua Hagan and Uday Vaidya
Polymers 2024, 16(17), 2391; https://doi.org/10.3390/polym16172391 - 23 Aug 2024
Cited by 1 | Viewed by 1049
Abstract
Unsaturated polyester resin (UPR) systems are extensively used in composite materials for applications in the transportation, marine, and infrastructure sectors. There are continually evolving formulations of UPRs that need to be evaluated and optimized for processing. Differential Scanning Calorimetry (DSC) provides valuable insight [...] Read more.
Unsaturated polyester resin (UPR) systems are extensively used in composite materials for applications in the transportation, marine, and infrastructure sectors. There are continually evolving formulations of UPRs that need to be evaluated and optimized for processing. Differential Scanning Calorimetry (DSC) provides valuable insight into the non-isothermal and isothermal behavior of UPRs within a prescribed temperature range. In the present work, non-isothermal DSC tests were carried out between temperatures of 0.0 °C and 250 °C, through different heating and cooling ramp rates. The isothermal DSC tests were carried out between 0.0 and 170 °C. The instantaneous rate of cure of the tested temperatures were measured. The application of an autocatalytic model in a calculator was used to simulate curing behaviors under different processing conditions. As the temperature increased from 10 °C up to 170 °C, the rate of cure reduced, and the heat of reaction increased. The simulated cure behavior from the DSC data showed that the degree of cure (α) maximum value of 71.25% was achieved at the highest heating temperature of 85 °C. For the low heating temperature, i.e., 5 °C, the maximum degree of cure (α) did not exceed 12% because there was not enough heat to activate the catalyst to crosslink further. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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Figure 1

Figure 1
<p>A flow diagram illustrates the simulation process of the cure behavior. The autocatalytic model utilizes the heat of reaction of the resin system and yields the rate of cure and conversion rate. These values vary based on the input processing temperature, which in turn influences the heat of reaction.</p>
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<p>Gel test results for Resin 1 and Resin 2. The test was conducted for a sufficient period until the peak temperature was achieved and no further heat release was recorded. Resin 2, as a fast-cure system, exhibits a higher release rate and provides a greater exothermic heat.</p>
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<p>TGA results for Resin 1 and Resin 2. Both resin systems exhibited similar trends; however, COR61-AA-248S begins to lose weight more rapidly than COR61-AA-270LF. The decomposition of Resin 1 and Resin 2 at <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>5</mn> </mrow> </msub> </mrow> </semantics></math> occurs at 243 °C and 296 °C, respectively.</p>
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<p>Heat flow of resin systems corresponding to three heating ramp rates, 5, 10, and 20 °C. (<b>a</b>) Non-isothermal DSC runs for Resin 1 and (<b>b</b>) non-isothermal DSC runs for Resin 2.</p>
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<p>Heat flow of resin systems corresponding to temperature range from 10 °C to 50 °C without initiator. (<b>a</b>) Isothermal DSC runs for Resin 1 and (<b>b</b>) isothermal DSC runs for Resin 2.</p>
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<p>Heat flow of resin systems corresponding to temperature range from 60 °C to 170 °C with initiator. (<b>a</b>) Isothermal DSC runs for Resin 1 and (<b>b</b>) isothermal DSC runs for Resin 2.</p>
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<p>Fourier-transform infrared (FTIR) spectrum of the cured UPRs for both resin systems. (<b>a</b>) Resin 1 and (<b>b</b>) Resin 2.</p>
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<p>An example of the cure kinetics behavior of Resin system 1 simulated by the MATLAB GUI using constant processing temperatures of 15 °C, 25 °C, 35 °C, 45 °C, 55 °C, 65 °C, 75 °C, and 85 °C. (<b>a</b>) Instantaneous rate of cure corresponding to reaction time. (<b>b</b>) Degree of cure over time.</p>
Full article ">Figure 9
<p>Examples of cure kinetics behaviors of Resin system 1 simulated by MATLAB GUI using variable heating temperature. (<b>a</b>) Corresponding instantaneous rate of cure. (<b>b</b>) Degree of cure for a variable processing temperature, including heating up with a ramp rate, dwell time at a constant temperature, and cooling down with a ramp rate.</p>
Full article ">
21 pages, 6156 KiB  
Article
Investigations of the Laser Ablation Mechanism of PMMA Microchannels Using Single-Pass and Multi-Pass Laser Scans
by Xiao Li, Rujun Tang, Ding Li, Fengping Li, Leiqing Chen, Dehua Zhu, Guang Feng, Kunpeng Zhang and Bing Han
Polymers 2024, 16(16), 2361; https://doi.org/10.3390/polym16162361 - 21 Aug 2024
Viewed by 921
Abstract
CO2 laser machining is a cost effective and time saving solution for fabricating microchannels on polymethylmethacrylate (PMMA). Due to the lack of research on the incubation effect and ablation behavior of PMMA under high-power laser irradiation, predictions of the microchannel profile are [...] Read more.
CO2 laser machining is a cost effective and time saving solution for fabricating microchannels on polymethylmethacrylate (PMMA). Due to the lack of research on the incubation effect and ablation behavior of PMMA under high-power laser irradiation, predictions of the microchannel profile are limited. In this study, the ablation process and mechanism of a continuous CO2 laser machining process on microchannel production in PMMA in single-pass and multi-pass laser scan modes are investigated. It is found that a higher laser energy density of a single pass causes a lower ablation threshold. The ablated surface can be divided into three regions: the ablation zone, the incubation zone, and the virgin zone. The PMMA ablation process is mainly attributed to the thermal decomposition reactions and the splashing of molten polymer. The depth, width, aspect ratio, volume ablation rate, and mass ablation rate of the channel increase as the laser scanning speed decreases and the number of laser scans increases. The differences in ablation results obtained under the same total laser energy density using different scan modes are attributed to the incubation effect, which is caused by the thermal deposition of laser energy in the polymer. Finally, an optimized simulation model that is used to solve the problem of a channel width greater than spot diameter is proposed. The error percentage between the experimental and simulation results varies from 0.44% to 5.9%. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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Figure 1

Figure 1
<p>Schematic diagram of the experimental set-up: (<b>a</b>) CO<sub>2</sub> laser source; (<b>b</b>) beam expander; (<b>c</b>) galvanometer systems; (<b>d</b>) telecentric f-theta lens; (<b>e</b>) adjustable platform; (<b>f</b>) PMMA sample.</p>
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<p>Measurement method of the channel profile using LSCM: (<b>a</b>) width and depth; (<b>b</b>) cross-sectional area.</p>
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<p>Ablation morphology on the surface of PMMA obtained with a single-pass laser scan with the following scanning speeds and laser energy densities: (<b>a</b>) 2700 mm/s, 2.06 J/cm<sup>2</sup>; (<b>b</b>) 2600 mm/s, 2.14 J/cm<sup>2</sup>; (<b>c</b>) 1800 mm/s, 3.10 J/cm<sup>2</sup>.</p>
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<p>Ablation morphology on the surface of PMMA obtained with a multi-pass laser scanning system with the following scanning speeds, scanning numbers, and total laser energy density: (<b>a</b>) 3000 mm/s, 1 pass, 1.86 J/cm<sup>2</sup>; (<b>b</b>) 3000 mm/s, 2 pass, 3.71 J/cm<sup>2</sup>; (<b>c</b>) 3000 mm/s, 3 pass, 5.57 J/cm<sup>2</sup>; (<b>d</b>) 6000 mm/s, 5 pass, 4.64 J/cm<sup>2</sup>; (<b>e</b>) 6000 mm/s, 6 pass, 5.57 J/cm<sup>2</sup>; (<b>f</b>) 6000 mm/s, 7 pass, 6.50 J/cm<sup>2</sup>.</p>
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<p>Ablation morphology images obtained using LSCM and SEM: (1) Scanning speed of 3000 mm/s for 2 passes: (<b>a</b>) LSCM, 20×; (<b>b</b>) SEM, 250X; (<b>c</b>) SEM, 1000×; (2) Scanning speed of 3000 mm/s for 4 passes: (<b>d</b>) LSCM, 20×; (<b>e</b>) SEM, 250×; (<b>f</b>) SEM, 500×; (3) Scanning speed of 3000 mm/s for 12 passes: (<b>g</b>) LSCM, 20×; (<b>h</b>) SEM, 250×; (<b>i</b>) SEM, 1500×.</p>
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<p>The cross-sectional profile of the channel obtained in single-pass mode at a scanning speed of 250 mm/s to 1000 mm/s.</p>
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<p>The cross-sectional profile of the channel obtained in multi-pass mode at a scanning speed of 3000 mm/s from 5 passes to 16 passes.</p>
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<p>Channel width dependence on the total laser energy density of different laser scan modes.</p>
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<p>Channel depth dependence on the total laser energy density of different laser scan modes.</p>
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<p>Cross-sectional area dependence on the laser scanning speed in single-pass mode.</p>
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<p>Volume ablation rate dependence on the laser scanning speed in single-pass mode.</p>
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<p>Cross-sectional area dependence on the number of laser scans in multi-pass mode.</p>
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<p>Volume ablation rate dependence on the number of laser scans in multi-pass mode.</p>
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<p>Mass loss dependence on the laser scanning speed in single-pass mode.</p>
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<p>Mass ablation rate dependence on the laser scanning speed in single-pass mode.</p>
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<p>Mass loss dependence on the number of scans in multi-pass mode.</p>
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<p>Mass ablation rate dependence on the number of scans in multi-pass mode.</p>
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<p>Dependence of channel depth of the experimental values and the simulation calculation values on laser scanning speed in single-pass mode.</p>
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<p>Dependence of channel width of the experimental values and the simulation calculation values on laser scanning speed in single-pass mode.</p>
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<p>The cross-sectional profile of the channels obtained by using different laser scanning speeds: (<b>a</b>) 150 mm/s; (<b>b</b>) 250 mm/s; (<b>c</b>) 350 mm/s; (<b>d</b>) 600 mm/s.</p>
Full article ">
33 pages, 514 KiB  
Article
General Relations between Stress Fluctuations and Viscoelasticity in Amorphous Polymer and Glass-Forming Systems
by Alexander Semenov and Jörg Baschnagel
Polymers 2024, 16(16), 2336; https://doi.org/10.3390/polym16162336 - 18 Aug 2024
Viewed by 851
Abstract
Mechanical stress governs the dynamics of viscoelastic polymer systems and supercooled glass-forming fluids. It was recently established that liquids with long terminal relaxation times are characterized by transiently frozen stress fields, which, moreover, exhibit long-range correlations contributing to the dynamically heterogeneous nature of [...] Read more.
Mechanical stress governs the dynamics of viscoelastic polymer systems and supercooled glass-forming fluids. It was recently established that liquids with long terminal relaxation times are characterized by transiently frozen stress fields, which, moreover, exhibit long-range correlations contributing to the dynamically heterogeneous nature of such systems. Recent studies show that stress correlations and relaxation elastic moduli are intimately related in isotropic viscoelastic systems. However, the origin of these relations (involving spatially resolved material relaxation functions) is non-trivial: some relations are based on the fluctuation-dissipation theorem (FDT), while others involve approximations. Generalizing our recent results on 2D systems, we here rigorously derive three exact FDT relations (already established in our recent investigations and, partially, in classical studies) between spatio-temporal stress correlations and generalized relaxation moduli, and a couple of new exact relations. We also derive several new approximate relations valid in the hydrodynamic regime, taking into account the effects of thermal conductivity and composition fluctuations for arbitrary space dimension. One approximate relation was heuristically obtained in our previous studies and verified using our extended simulation data on two-dimensional (2D) glass-forming systems. As a result, we provide the means to obtain, in any spatial dimension, all stress-correlation functions in terms of relaxation moduli and vice versa. The new approximate relations are tested using simulation data on 2D systems of polydisperse Lennard–Jones particles. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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Figure 1
<p>The wave-number (<span class="html-italic">q</span>) dependence of the instantaneous (adiabatic) elastic modulus <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>(</mo> <mi>q</mi> <mo>)</mo> <mo>≡</mo> <mi>N</mi> <mo>(</mo> <mi>q</mi> <mo>,</mo> <mi>t</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>), black curve, and its three approximations based on the shear <math display="inline"><semantics> <mrow> <mo>(</mo> <mi>G</mi> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> </semantics></math>), longitudinal <math display="inline"><semantics> <mrow> <mo>(</mo> <mi>L</mi> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> </semantics></math>) and transverse <math display="inline"><semantics> <mrow> <mo>(</mo> <mi>M</mi> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> </semantics></math>) elastic moduli: <math display="inline"><semantics> <mrow> <msub> <mi>N</mi> <mrow> <mi>a</mi> <mn>0</mn> </mrow> </msub> <mrow> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>, Equation (<a href="#FD122-polymers-16-02336" class="html-disp-formula">122</a>) (red curve), <math display="inline"><semantics> <mrow> <msub> <mi>N</mi> <mrow> <mi>a</mi> <mn>1</mn> </mrow> </msub> <mrow> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>, Equation (<a href="#FD127-polymers-16-02336" class="html-disp-formula">127</a>) (blue curve), and <math display="inline"><semantics> <mrow> <msub> <mi>N</mi> <mrow> <mi>a</mi> <mn>2</mn> </mrow> </msub> <mrow> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>, Equation (<a href="#FD130-polymers-16-02336" class="html-disp-formula">130</a>) (green curve). All the moduli <math display="inline"><semantics> <mrow> <mo>(</mo> <mi>N</mi> </mrow> </semantics></math>, <span class="html-italic">G</span>, <span class="html-italic">L</span>, <span class="html-italic">M</span>) are based on the stress correlation functions <math display="inline"><semantics> <mrow> <msub> <mi>C</mi> <mi>N</mi> </msub> <mrow> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>C</mi> <mi>G</mi> </msub> <mrow> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>, …obtained by MD simulations for a polydisperse system of LJ particles [<a href="#B32-polymers-16-02336" class="html-bibr">32</a>,<a href="#B58-polymers-16-02336" class="html-bibr">58</a>,<a href="#B60-polymers-16-02336" class="html-bibr">60</a>,<a href="#B66-polymers-16-02336" class="html-bibr">66</a>]. Panel (<b>a</b>) highlights the range <math display="inline"><semantics> <mrow> <mn>0</mn> <mo>&lt;</mo> <mi>q</mi> <mo>&lt;</mo> <mn>5</mn> </mrow> </semantics></math>, while panel (<b>b</b>) shows a wider range, <math display="inline"><semantics> <mrow> <mn>0</mn> <mo>&lt;</mo> <mi>q</mi> <mo>&lt;</mo> <mn>10</mn> </mrow> </semantics></math>, including the main structural peak at <math display="inline"><semantics> <mrow> <mi>q</mi> <mo>≈</mo> <mn>6.3</mn> </mrow> </semantics></math>. Temperature <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math> (in LJ energy units) and the mean particle size <math display="inline"><semantics> <mrow> <mi>b</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>.</p>
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32 pages, 9182 KiB  
Article
Improved Approach for ab Initio Calculations of Rate Coefficients for Secondary Reactions in Acrylate Free-Radical Polymerization
by Fernando A. Lugo, Mariya Edeleva, Paul H. M. Van Steenberge and Maarten K. Sabbe
Polymers 2024, 16(7), 872; https://doi.org/10.3390/polym16070872 - 22 Mar 2024
Cited by 1 | Viewed by 1200
Abstract
Secondary reactions in radical polymerization pose a challenge when creating kinetic models for predicting polymer structures. Despite the high impact of these reactions in the polymer structure, their effects are difficult to isolate and measure to produce kinetic data. To this end, we [...] Read more.
Secondary reactions in radical polymerization pose a challenge when creating kinetic models for predicting polymer structures. Despite the high impact of these reactions in the polymer structure, their effects are difficult to isolate and measure to produce kinetic data. To this end, we used solvation-corrected M06-2X/6-311+G(d,p) ab initio calculations to predict a complete and consistent data set of intrinsic rate coefficients of the secondary reactions in acrylate radical polymerization, including backbiting, β-scission, radical migration, macromonomer propagation, mid-chain radical propagation, chain transfer to monomer and chain transfer to polymer. Two new approaches towards computationally predicting rate coefficients for secondary reactions are proposed: (i) explicit accounting for all possible enantiomers for reactions involving optically active centers; (ii) imposing reduced flexibility if the reaction center is in the middle of the polymer chain. The accuracy and reliability of the ab initio predictions were benchmarked against experimental data via kinetic Monte Carlo simulations under three sufficiently different experimental conditions: a high-frequency modulated polymerization process in the transient regime, a low-frequency modulated process in the sliding regime at both low and high temperatures and a degradation process in the absence of free monomers. The complete and consistent ab initio data set compiled in this work predicts a good agreement when benchmarked via kMC simulations against experimental data, which is a technique never used before for computational chemistry. The simulation results show that these two newly proposed approaches are promising for bridging the gap between experimental and computational chemistry methods in polymer reaction engineering. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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<p>Most relevant secondary reactions in free-radical polymerization of acrylates.</p>
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<p>Backbiting reaction of the methyl acrylate pentamer: minimum-energy optical isomer (RSRS/SRSR).</p>
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<p>ECR propagation scheme showing identical-chirality (IC) propagation, producing a <span class="html-italic">meso</span> dyad, and alternating-chirality (AC) propagation, producing a <span class="html-italic">racemo</span> dyad.</p>
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<p>Comparison of the rate coefficients in this work with the literature values for the backbiting reaction. The colored sections represent the area between the 25% and 75% percentiles within a group of data: <span class="html-fig-inline" id="polymers-16-00872-i001"><img alt="Polymers 16 00872 i001" src="/polymers/polymers-16-00872/article_deploy/html/images/polymers-16-00872-i001.png"/></span> this work’s prediction; <span class="html-fig-inline" id="polymers-16-00872-i002"><img alt="Polymers 16 00872 i002" src="/polymers/polymers-16-00872/article_deploy/html/images/polymers-16-00872-i002.png"/></span> <span class="html-fig-inline" id="polymers-16-00872-i003"><img alt="Polymers 16 00872 i003" src="/polymers/polymers-16-00872/article_deploy/html/images/polymers-16-00872-i003.png"/></span> experimental median; <span class="html-fig-inline" id="polymers-16-00872-i004"><img alt="Polymers 16 00872 i004" src="/polymers/polymers-16-00872/article_deploy/html/images/polymers-16-00872-i004.png"/></span> ab initio median; <span class="html-fig-inline" id="polymers-16-00872-i005"><img alt="Polymers 16 00872 i005" src="/polymers/polymers-16-00872/article_deploy/html/images/polymers-16-00872-i005.png"/></span> 25–75% ab initio percentile area [<a href="#B34-polymers-16-00872" class="html-bibr">34</a>,<a href="#B35-polymers-16-00872" class="html-bibr">35</a>,<a href="#B56-polymers-16-00872" class="html-bibr">56</a>,<a href="#B62-polymers-16-00872" class="html-bibr">62</a>]; <span class="html-fig-inline" id="polymers-16-00872-i006"><img alt="Polymers 16 00872 i006" src="/polymers/polymers-16-00872/article_deploy/html/images/polymers-16-00872-i006.png"/></span> 25–75% experimental percentile area [<a href="#B28-polymers-16-00872" class="html-bibr">28</a>,<a href="#B32-polymers-16-00872" class="html-bibr">32</a>,<a href="#B50-polymers-16-00872" class="html-bibr">50</a>,<a href="#B57-polymers-16-00872" class="html-bibr">57</a>,<a href="#B58-polymers-16-00872" class="html-bibr">58</a>,<a href="#B59-polymers-16-00872" class="html-bibr">59</a>,<a href="#B60-polymers-16-00872" class="html-bibr">60</a>,<a href="#B61-polymers-16-00872" class="html-bibr">61</a>].</p>
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<p>β-scission molecular model representing a left β-scission reaction.</p>
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<p>Reduced-flexibility effect on each structure involved in the reaction. The black circle (<span class="html-fig-inline" id="polymers-16-00872-i007"><img alt="Polymers 16 00872 i007" src="/polymers/polymers-16-00872/article_deploy/html/images/polymers-16-00872-i007.png"/></span>) represent the Gibbs energy of a reactant structure with a certain elongation, relative to the non-elongated reactant molecular model. The red circle (<span class="html-fig-inline" id="polymers-16-00872-i008"><img alt="Polymers 16 00872 i008" src="/polymers/polymers-16-00872/article_deploy/html/images/polymers-16-00872-i008.png"/></span>) represents the Gibbs energy of the transition-state structure with a certain elongation, relative to the non-elongated transition-state molecular model. The blue circle (<span class="html-fig-inline" id="polymers-16-00872-i009"><img alt="Polymers 16 00872 i009" src="/polymers/polymers-16-00872/article_deploy/html/images/polymers-16-00872-i009.png"/></span>) represents the Gibbs reaction barrier at a certain elongation.</p>
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<p>General methyl acrylate pentamer structure with the mid-chain radical on position 4, as used for the migration reaction model.</p>
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<p>Δ<sup>‡</sup>G (<span class="html-fig-inline" id="polymers-16-00872-i010"><img alt="Polymers 16 00872 i010" src="/polymers/polymers-16-00872/article_deploy/html/images/polymers-16-00872-i010.png"/></span>) vs. elongation of the radical migration reaction barrier applying the reduced-flexibility approach.</p>
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<p>Macromonomer propagation model: unimer radical propagating to a tetramer macromonomer.</p>
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<p>Mid-chain radical propagation model. A trimer structure with an MCR in the middle unit propagating to an MA monomer.</p>
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<p>Carbons atoms possessing abstractable hydrogens in the CTM model of a butyl acrylate monomer molecule.</p>
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<p>Chain-transfer-to-polymer model. An ECR monomer abstracting a hydrogen from the methyl acrylate trimer in the middle unit.</p>
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<p>Experiment (1): PLP-SEC trace experiment of n-butyl acrylate at 306 K, in bulk, at laser frequency of 500 Hz. Comparison between experiment [<a href="#B49-polymers-16-00872" class="html-bibr">49</a>], <span class="html-italic">k</span>MC-simulated SEC trace with parameters derived from [<a href="#B50-polymers-16-00872" class="html-bibr">50</a>] and this work’s predicted rate coefficients via different methods.</p>
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<p>Experiment (2): PLP-SEC trace experiment of n-butyl acrylate at 306 K, a solvent fraction of 0.75 and a laser frequency of 50 Hz. Comparison between experiment [<a href="#B75-polymers-16-00872" class="html-bibr">75</a>] and <span class="html-italic">k</span>MC-simulated SEC trace with parameters derived from Vir et al. [<a href="#B50-polymers-16-00872" class="html-bibr">50</a>] (reference set) and this work’s predicted rate coefficients via different methods (data 2, 3 and 4).</p>
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<p>Experiment (3): PLP-SEC trace experiment of n-butyl acrylate at 413 K, in bulk, at laser frequency 10 Hz. Comparison between experiment [<a href="#B50-polymers-16-00872" class="html-bibr">50</a>] and <span class="html-italic">k</span>MC-simulated SEC trace with parameters derived from Vir et al. [<a href="#B50-polymers-16-00872" class="html-bibr">50</a>] (reference set) and this work’s predicted rate coefficients via different methods (data 2, 3 and 4).</p>
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<p>Simulated (full lines) and experimental (points) mass fractions corresponding to the main ESI-MS signals of the synthesis of macromonomers (MMs) via the activation of bromine-capped poly(<span class="html-italic">n</span>-butyl acrylate) in Van Steenberge et al. [<a href="#B54-polymers-16-00872" class="html-bibr">54</a>], top left, red; dead-polymer product of CTP, top right, blue; dormant Br-capped p-(n-BA) including the fraction of activated ECRs and MCRs, bottom left, yellow; MM product of right β-scission, bottom right, green; MM product of left β-scission.</p>
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16 pages, 373 KiB  
Article
Analytical Solutions to the Unsteady Poiseuille Flow of a Second Grade Fluid with Slip Boundary Conditions
by Evgenii S. Baranovskii
Polymers 2024, 16(2), 179; https://doi.org/10.3390/polym16020179 - 7 Jan 2024
Cited by 5 | Viewed by 1546
Abstract
This paper deals with an initial-boundary value problem modeling the unidirectional pressure-driven flow of a second grade fluid in a plane channel with impermeable solid walls. On the channel walls, Navier-type slip boundary conditions are stated. Our aim is to investigate the well-posedness [...] Read more.
This paper deals with an initial-boundary value problem modeling the unidirectional pressure-driven flow of a second grade fluid in a plane channel with impermeable solid walls. On the channel walls, Navier-type slip boundary conditions are stated. Our aim is to investigate the well-posedness of this problem and obtain its analytical solution under weak regularity requirements on a function describing the velocity distribution at initial time. In order to overcome difficulties related to finding classical solutions, we propose the concept of a generalized solution that is defined as the limit of a uniformly convergent sequence of classical solutions with vanishing perturbations in the initial data. We prove the unique solvability of the problem under consideration in the class of generalized solutions. The main ingredients of our proof are a generalized Abel criterion for uniform convergence of function series and the use of an orthonormal basis consisting of eigenfunctions of the related Sturm–Liouville problem. As a result, explicit expressions for the flow velocity and the pressure in the channel are established. The constructed analytical solutions favor a better understanding of the qualitative features of time-dependent flows of polymer fluids and can be applied to the verification of relevant numerical, asymptotic, and approximate analytical methods. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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<p>Sketch of the plane Poiseuille flow.</p>
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<p>Velocity profiles for the plane Poiseuille flow with <math display="inline"> <semantics> <mrow> <mi>h</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics> </math>, <math display="inline"> <semantics> <mrow> <mi>μ</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics> </math>, <math display="inline"> <semantics> <mrow> <mi>ξ</mi> <mo>=</mo> <mn>3</mn> </mrow> </semantics> </math>, <math display="inline"> <semantics> <mrow> <mi>k</mi> <mo>=</mo> <mn>5</mn> </mrow> </semantics> </math>, <math display="inline"> <semantics> <mrow> <msub> <mi>u</mi> <mn>0</mn> </msub> <mo>≡</mo> <mn>0</mn> </mrow> </semantics> </math>, <math display="inline"> <semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.2</mn></mrow> </semantics> </math> (second grade fluid), <math display="inline"> <semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics> </math> (Newtonian fluid) at time <math display="inline"> <semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>0.2</mn></mrow> </semantics> </math>.</p>
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18 pages, 2345 KiB  
Article
Knot Formation on DNA Pushed Inside Chiral Nanochannels
by Renáta Rusková and Dušan Račko
Polymers 2023, 15(20), 4185; https://doi.org/10.3390/polym15204185 - 22 Oct 2023
Cited by 3 | Viewed by 8898
Abstract
We performed coarse-grained molecular dynamics simulations of DNA polymers pushed inside infinite open chiral and achiral channels. We investigated the behavior of the polymer metrics in terms of span, monomer distributions and changes of topological state of the polymer in the channels. We [...] Read more.
We performed coarse-grained molecular dynamics simulations of DNA polymers pushed inside infinite open chiral and achiral channels. We investigated the behavior of the polymer metrics in terms of span, monomer distributions and changes of topological state of the polymer in the channels. We also compared the regime of pushing a polymer inside the infinite channel to the case of polymer compression in finite channels of knot factories investigated in earlier works. We observed that the compression in the open channels affects the polymer metrics to different extents in chiral and achiral channels. We also observed that the chiral channels give rise to the formation of equichiral knots with the same handedness as the handedness of the chiral channels. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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<p>Polymer metrics in terms of the molecule’s span during pushing of DNA molecule inside channels as a function of pushing speed and confinement strength expressed as <span class="html-italic">D</span>/<span class="html-italic">P</span>. (<b>a</b>) The panel compares the polymer span in units of <span class="html-italic">σ</span>/ℓ pushed with different velocities of the piston <span class="html-italic">v</span> in units of 1000 <span class="html-italic">σ</span>/<span class="html-italic">τ</span>. The black lines indicate the span of a polymer pushed in helical channels, and red lines correspond to the simulations in a cylindrical channel. The areas in shades of purple show differences with the respective cases and a given confinement strength. The inset shows the velocities of the piston obtained for the external force employed on the piston. (<b>b</b>) The panel shows the span of polymer pushed in open infinite helical channels and compares the data with a previously investigated case of a polymer compressed in a blinded channel [<a href="#B36-polymers-15-04185" class="html-bibr">36</a>]. (<b>c</b>) The panel shows a comparison of the polymer’s span in open infinite channels versus blinded channels with cylindrical geometry and as a function of force in the units of <span class="html-italic">Fσ/ε</span><sub>0</sub> and confinement strength expressed in terms of <span class="html-italic">D</span>/<span class="html-italic">P</span>. The insets show rendered snapshots obtained for <span class="html-italic">D</span>/<span class="html-italic">P</span> = 0.5 and <span class="html-italic">F</span> = 5<span class="html-italic">ε</span><sub>0</sub>/<span class="html-italic">σ</span>, where the polymer is shown in a rainbow color scheme, with one end of the polymer shown in blue and the other in red.</p>
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<p>Monomer distributions of DNA polymer pushed inside channels with cylindrical and helical geometry. The panels show the distributions obtained in cylindrical (<b>a</b>–<b>c</b>) and helical channels (<b>d</b>–<b>f</b>). The distributions are also shown for different confinement strengths in terms of the <span class="html-italic">D</span>/<span class="html-italic">P</span> ratio, equal to 0.5 (<b>a</b>,<b>d</b>); <span class="html-italic">D</span>/<span class="html-italic">P</span> = 1 (<b>b</b>,<b>e</b>); and <span class="html-italic">D</span>/<span class="html-italic">P</span> = 2 in panels (<b>c</b>,<b>f</b>). The very left of each panel shows heatmaps of the monomer distributions with a color gradient ranging from blue to red, where the distribution’s peak is indicated by red and zero occurrences are denoted by blue. The left graph in every panel shows monomer distribution along the channel from the position (in units of <span class="html-italic">σ</span>/ℓ) of the piston as a function of piston velocity, taking into regard also direction of pushing in the simulations. The insets of this graph also show index-to-bead projections of axial monomer distributions obtained for <span class="html-italic">F</span> = 0.1<span class="html-italic">ε</span><sub>0</sub>/<span class="html-italic">σ</span> and <span class="html-italic">F</span> = 5<span class="html-italic">ε</span><sub>0</sub>/<span class="html-italic">σ</span>. The graphs to the right in the pair in every panel show radial distribution functions of monomers from the geometric center of the channel in units of <span class="html-italic">σ</span>/ℓ, in simulations represented by the <span class="html-italic">x</span> = 0 axis. The arrows indicate the direction of increasing or decreasing velocity. Each panel also shows a snapshot obtained for the particular geometry of the channel, confinement strength <span class="html-italic">D</span>/<span class="html-italic">P</span>, and force = 1 <span class="html-italic">ε</span><sub>0</sub>/<span class="html-italic">σ</span>. The polymer is depicted in rainbow coloring, with the first bead in blue and the last bead in the chain in red.</p>
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<p>Knotting probabilities. (<b>a</b>) The first two columns compare knotting probabilities in terms of crossing numbers, distinguished by a thermometer scale, obtained for DNA polymer pushed inside infinite open channels with cylindrical and helical geometries. The rows correspond to different confinement strength in terms of <span class="html-italic">D</span>/<span class="html-italic">P</span>. In the case of helical channels, the knot types are evaluated in terms of the frequencies of amphichiral (Am.), torus (Tor.), twist knots (Tw.), unknots (Un.), and undefined knots (“?”). The last column shows a comparison of equichiral and antichiral knots, i.e., the knots with the same handedness as or the opposite handedness to that of the chiral helical channel. (<b>b</b>) Average writhe of the DNA chains in helical channels as a function of increasing pushing velocities and strength of confinement in terms of the <span class="html-italic">D</span>/<span class="html-italic">P</span> ratio. The <span class="html-italic">ω</span>+ and <span class="html-italic">ω</span>− indicate handedness of the channels (see <a href="#sec2dot2-polymers-15-04185" class="html-sec">Section 2.2</a>). The computed pushing velocities are shown in the inset of <a href="#polymers-15-04185-f001" class="html-fig">Figure 1</a>a. (<b>c</b>) A proposed mechanism for how the helical channels control handedness of compression–confinement-induced knotting.</p>
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13 pages, 3238 KiB  
Article
Effectiveness of the Use of Polymers in High-Performance Concrete Containing Silica Fume
by Alya Harichane, Nadhir Toubal Seghir, Paweł Niewiadomski, Łukasz Sadowski and Michał Cisiński
Polymers 2023, 15(18), 3730; https://doi.org/10.3390/polym15183730 - 11 Sep 2023
Cited by 2 | Viewed by 1377
Abstract
The incorporation of polycarboxylate ether superplasticizer (PCE)-type polymers and silica fume (SF) in high-performance concretes (HPC) leads to remarkable rheological and mechanical improvements. In the fresh state, PCEs are adsorbed on cement particles and dispersants, promoting the workability of the concrete. Silica fume [...] Read more.
The incorporation of polycarboxylate ether superplasticizer (PCE)-type polymers and silica fume (SF) in high-performance concretes (HPC) leads to remarkable rheological and mechanical improvements. In the fresh state, PCEs are adsorbed on cement particles and dispersants, promoting the workability of the concrete. Silica fume enables very well-compacted concrete to be obtained, which is characterized by high mechanical parameters in its hardened state. Some PCEs are incompatible with silica fume, which can result in slump loss and poor rheological behavior. The main objective of this research is to study the influence of three types of PCEs, which all have different molecular architectures, on the rheological and mechanical behavior of high-performance concretes containing 10% SF as a partial replacement of cement. The results show that the carboxylic density of PCE has an influence on its compatibility with SF. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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<p>Particle size distribution curves of the PC and SF.</p>
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<p>Particle size distribution curves of the used aggregates.</p>
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<p>Chromatogram of polymers: (<b>a</b>) PCE1, (<b>b</b>) PCE2, and (<b>c</b>) PCE3.</p>
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<p>Chromatogram of polymers: (<b>a</b>) PCE1, (<b>b</b>) PCE2, and (<b>c</b>) PCE3.</p>
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<p>Slump values of the HPC.</p>
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<p>Plastic viscosity as a function of the shear rate of the cement paste: (<b>a</b>) PCE1, (<b>b</b>) PCE2, (<b>c</b>) PCE3; w/b = 0.35.</p>
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<p>Plastic viscosity as a function of the shear rate of the cement paste: (<b>a</b>) PCE1, (<b>b</b>) PCE2, (<b>c</b>) PCE3; w/b = 0.35.</p>
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<p>Shear stress as a function of the shear rate of the cement paste: (<b>a</b>) PCE1, (<b>b</b>) PCE2, (<b>c</b>) PCE3; w/b = 0.35.</p>
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<p>Shear stress as a function of the shear rate of the cement paste: (<b>a</b>) PCE1, (<b>b</b>) PCE2, (<b>c</b>) PCE3; w/b = 0.35.</p>
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<p>Zeta potential of the cement paste as a function of the PCE type.</p>
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<p>Compressive strengths of the HPC (containing superplasticizers PCE1, 2, and 3) after different times of hydration.</p>
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19 pages, 1379 KiB  
Article
Numerical Simulation of Three-Dimensional Free Surface Flows Using the K–BKZ–PSM Integral Constitutive Equation
by Juliana Bertoco, Antonio Castelo, Luís L. Ferrás and Célio Fernandes
Polymers 2023, 15(18), 3705; https://doi.org/10.3390/polym15183705 - 8 Sep 2023
Cited by 3 | Viewed by 1180
Abstract
This work introduces a novel numerical method designed to address three-dimensional unsteady free surface flows incorporating integral viscoelastic constitutive equations, specifically the K–BKZ–PSM (Kaye–Bernstein, Kearsley, Zapas–Papanastasiou, Scriven, Macosko) model. The new proposed methodology employs a second-order finite difference approach along with the deformation [...] Read more.
This work introduces a novel numerical method designed to address three-dimensional unsteady free surface flows incorporating integral viscoelastic constitutive equations, specifically the K–BKZ–PSM (Kaye–Bernstein, Kearsley, Zapas–Papanastasiou, Scriven, Macosko) model. The new proposed methodology employs a second-order finite difference approach along with the deformation fields method to solve the integral constitutive equation and the marker particle method (known as marker-and-cell) to accurately capture the evolution of the fluid’s free surface. The newly developed numerical method has proven its effectiveness in handling complex fluid flow scenarios, including confined flows and extrudate swell simulations of Boger fluids. Furthermore, a new semi-analytical solution for velocity and stress fields is derived, considering fully developed flows of a K–BKZ–PSM fluid in a pipe. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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<p>(<b>a</b>) Typical three-dimensional staggered cell and (<b>b</b>) illustration of cell type classification used.</p>
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<p>Representation of the pipe and a section in the <math display="inline"><semantics> <mrow> <mi>r</mi> <mi>z</mi> </mrow> </semantics></math> plane.</p>
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<p>Velocity components <span class="html-italic">u</span> and <span class="html-italic">w</span> of <math display="inline"><semantics> <mrow> <mi mathvariant="bold">v</mi> <mo>(</mo> <mi>u</mi> <mo>,</mo> <mi>v</mi> <mo>,</mo> <mi>w</mi> <mo>)</mo> </mrow> </semantics></math> along the plane <math display="inline"><semantics> <mrow> <mi>x</mi> <mi>z</mi> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <mi>y</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>) at <math display="inline"><semantics> <mrow> <mover> <mi>t</mi> <mo>¯</mo> </mover> <mo>=</mo> <mn>20</mn> <mspace width="3.33333pt"/> <mi mathvariant="normal">s</mi> </mrow> </semantics></math>. (<b>a</b>) Visualization of the velocity profile <span class="html-italic">w</span>. (<b>b</b>) Visualization of the velocity profile <span class="html-italic">u</span>.</p>
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<p>Pressure and <math display="inline"><semantics> <msup> <mi>τ</mi> <mrow> <mi>x</mi> <mi>z</mi> </mrow> </msup> </semantics></math> distribution along the <math display="inline"><semantics> <mrow> <mi>x</mi> <mi>z</mi> </mrow> </semantics></math> plane (<math display="inline"><semantics> <mrow> <mi>y</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>). (<b>a</b>) Visualization of the pressure <span class="html-italic">p</span>. (<b>b</b>) Visualization of the <math display="inline"><semantics> <msup> <mi>τ</mi> <mrow> <mi>x</mi> <mi>z</mi> </mrow> </msup> </semantics></math> tensor component.</p>
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<p>Comparison between the analytical and numerical solutions for (<b>a</b>) <span class="html-italic">w</span> velocity component and tensors components (<b>b</b>) <math display="inline"><semantics> <msup> <mi>τ</mi> <mrow> <mi>x</mi> <mi>z</mi> </mrow> </msup> </semantics></math> and (<b>c</b>) <math display="inline"><semantics> <msup> <mi>τ</mi> <mrow> <mi>z</mi> <mi>z</mi> </mrow> </msup> </semantics></math>.</p>
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<p>Total residual in meshes <math display="inline"><semantics> <mrow> <mi>M</mi> <mn>1</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>M</mi> <mn>2</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>M</mi> <mn>3</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>M</mi> <mn>4</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>M</mi> <mn>5</mn> </mrow> </semantics></math> up to <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>10</mn> </mrow> </semantics></math> (or <math display="inline"><semantics> <mrow> <mover> <mi>t</mi> <mo>¯</mo> </mover> <mo>=</mo> <mn>25</mn> <mspace width="3.33333pt"/> <mi mathvariant="normal">s</mi> </mrow> </semantics></math>).</p>
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<p>Schematic of a free surface simulation in the FREEFLOW-3D software. (<b>a</b>) Schematic representation of the domain; (<b>b</b>) illustration of the extrudate swell. The fluid exits the tube and starts to swell.</p>
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<p>Flow development of a Boger fluid for two different inlet velocities (cases <math display="inline"><semantics> <mrow> <mi mathvariant="bold">C</mi> <mn>1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi mathvariant="bold">C</mi> <mn>2</mn> </mrow> </semantics></math>).</p>
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16 pages, 2539 KiB  
Article
Analysis of the Dynamic Cushioning Property of Expanded Polyethylene Based on the Stress–Energy Method
by Yueqing Xing, Deqiang Sun and Guoliang Chen
Polymers 2023, 15(17), 3603; https://doi.org/10.3390/polym15173603 - 30 Aug 2023
Cited by 2 | Viewed by 1363
Abstract
This paper aimed to experimentally clarify the dynamic crushing performance of expanded polyethylene (EPE) and analyze the influence of thickness and dropping height on its mechanical behavior based on the stress–energy method. Hence, a series of impact tests are carried out on EPE [...] Read more.
This paper aimed to experimentally clarify the dynamic crushing performance of expanded polyethylene (EPE) and analyze the influence of thickness and dropping height on its mechanical behavior based on the stress–energy method. Hence, a series of impact tests are carried out on EPE foams with different thicknesses and dropping heights. The maximum acceleration, static stress, dynamic stress and dynamic energy of EPE specimens are obtained through a dynamic impact test. Then, according to the principle of the stress–energy method, the functional relationship between dynamic stress and dynamic energy is obtained through exponential fitting and polynomial fitting, and the cushion material constants a, b and c are determined. The maximum acceleration-static stress curves of any thickness and dropping height can be further fitted. By the equipartition energy domain method, the range of static stress can be expanded, which is very fast and convenient. When analyzing the influence of thickness and dropping height on the dynamic cushioning performance curves of EPE, it is found that at the same drop height, with the increase of thickness, the opening of the curve gradually becomes larger. The minimum point on the maximum acceleration-static stress curve also decreases with the increase of the thickness. When the dropping height is 400 mm, compared to foam with a thickness of 60 mm, the tested maximum acceleration value of the lowest point of the specimen with a thickness of 40 mm increased by 45.3%, and the static stress is both 5.5 kPa. When the thickness of the specimen is 50 mm, compared to the dropping height of 300 mm, the tested maximum acceleration value of the lowest point of the specimen with a dropping height of 600 mm increased by 93.3%. Therefore, the dynamic cushioning performance curve of EPE foams can be quickly obtained by the stress–energy method when the precision requirement is not high, which provides a theoretical basis for the design of cushion packaging. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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<p>XG-HC impact testing machine system.</p>
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<p>Diagram of drop impact test of heavy hammer [<a href="#B28-polymers-15-03603" class="html-bibr">28</a>].</p>
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<p>Maximum acceleration-static stress curves (<b>a</b>) specimens with different thicknesses (<b>b</b>) specimens with different dropping heights.</p>
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<p>Dynamic stress-dynamic energy data points (<b>a</b>) specimens with different thicknesses (<b>b</b>) specimens with different dropping heights.</p>
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<p>Dynamic stress-dynamic energy fitted curves (<b>a</b>) exponential fitted curve for specimens with different thicknesses; (<b>b</b>) polynomial fitted curve for specimens with different thicknesses; (<b>c</b>) exponential fitted curve for specimens with different dropping heights; (<b>d</b>) polynomial fitted curve for specimens with different dropping height.</p>
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<p>Maximum acceleration-static stress fitted curves (<b>a</b>) exponential fitted curve for specimens with different thicknesses; (<b>b</b>) polynomial fitted curve for specimens with different thicknesses; (<b>c</b>) exponential fitted curve for specimens with different dropping heights; (<b>d</b>) polynomial fitted curve for specimens with different dropping height.</p>
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<p>Comparison of fitted curves with tested curves for EPE specimen.</p>
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<p>Comparison of fitted curves and tested curves (<b>a</b>) exponential fitted curves for EPE specimens of different thicknesses (<b>b</b>) polynomial fitted curves for EPE specimens of different thicknesses (<b>c</b>) exponential fitted curves for EPE specimens at different dropping height (<b>d</b>) polynomial fitted curves for EPE specimens at different dropping height.</p>
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<p>Comparison of fitted curves and tested curves (<b>a</b>) exponential fitted curves for EPE specimens of different thicknesses (<b>b</b>) polynomial fitted curves for EPE specimens of different thicknesses (<b>c</b>) exponential fitted curves for EPE specimens at different dropping height (<b>d</b>) polynomial fitted curves for EPE specimens at different dropping height.</p>
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18 pages, 4473 KiB  
Article
A Phenomenological Model for Enthalpy Recovery in Polystyrene Using Dynamic Mechanical Spectra
by Koh-hei Nitta, Kota Ito and Asae Ito
Polymers 2023, 15(17), 3590; https://doi.org/10.3390/polym15173590 - 29 Aug 2023
Cited by 3 | Viewed by 1550
Abstract
This paper studies the effects of annealing time on the specific heat enthalpy of polystyrene above the glass transition temperature. We extend the Tool–Narayanaswamy–Moynihan (TNM) model to describe the endothermic overshoot peaks through the dynamic mechanical spectra. In this work, we accept the [...] Read more.
This paper studies the effects of annealing time on the specific heat enthalpy of polystyrene above the glass transition temperature. We extend the Tool–Narayanaswamy–Moynihan (TNM) model to describe the endothermic overshoot peaks through the dynamic mechanical spectra. In this work, we accept the viewpoint that the enthalpy recovery behavior of glassy polystyrene (PS) has a common structural relaxation mode with linear viscoelastic behavior. As a consequence, the retardation spectrum evaluated from the dynamic mechanical spectra around the primary Tg peak is used as the recovery function of the endothermic overshoot of specific heat. In addition, the sub-Tg shoulder peak around the Tg peak is found to be related to the structural relaxation estimated from light scattering measurements. The enthalpy recovery of annealed PS is quantitatively described using retardation spectra of the primary Tg, as well as the kinetic process of the sub-Tg relaxation process. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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<p>Schematic plots of enthalpy and heat capacity during cooling and subsequent heating at a fixed rate for a glassy polymer.</p>
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<p>Schematic illustration of temperature scanning in aging experiment.</p>
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<p>Annealing time dependence of fictive temperature and normalized heat capacity curves at an annealing temperature of 80 °C.</p>
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<p>Annealing time dependence of the normalized change of enthalpy relaxation.</p>
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<p>Annealing time dependence of dynamic mechanical spectra measured at 10 Hz for PS annealed at 80 °C.</p>
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<p>Curve fitting for dynamic mechanical spectra of loss modulus <span class="html-italic">E</span>″ around glass relaxation region at 1, 30, 100, and 200 Hz for PS annealed for 1 h at 80 °C.</p>
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<p>Annealing time dependence of the activation energies of <span class="html-italic">T<sub>g</sub></span> and sub-<span class="html-italic">T<sub>g</sub></span>.</p>
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<p>Frequency dependencies of (<b>a</b>) storage elastic modulus (<span class="html-italic">E</span>′) and loss elastic modulus (<span class="html-italic">E</span>″) and (<b>b</b>) their master curves at <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> °C.</p>
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<p>Scattering angle depends of <span class="html-italic">V<sub>V</sub></span> and <span class="html-italic">H<sub>V</sub></span> scattering intensities.</p>
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<p>Annealing time dependence of correlation length.</p>
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<p>Comparison of normalized heat capacity evaluated from DSC and DMA (primary <span class="html-italic">T<sub>g</sub></span>).</p>
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<p>(<b>a</b>) Comparison of (<b>a</b>) enthalpy loss evaluated from DSC and activation energy of sub-<span class="html-italic">T<sub>g</sub></span> and (<b>b</b>) enthalpy loss <math display="inline"><semantics> <mrow> <mo>∆</mo> <msub> <mrow> <mi>H</mi> </mrow> <mrow> <mi>DSC</mi> </mrow> </msub> </mrow> </semantics></math>/kJmol<sup>−1</sup> and normalized enthalpy loss <math display="inline"><semantics> <mrow> <mo>∆</mo> <msup> <mrow> <mi>H</mi> </mrow> <mrow> <mi>N</mi> </mrow> </msup> </mrow> </semantics></math>/K.</p>
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<p>Comparison of normalized heat capacity evaluated from DSC and DMA (both sub-<span class="html-italic">T<sub>g</sub></span> and primary <span class="html-italic">T<sub>g</sub></span>).</p>
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<p>Schematic illustration of sub-<span class="html-italic">T<sub>g</sub></span> relaxation process.</p>
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15 pages, 3228 KiB  
Article
Cellulose Nanocrystal Embedded Composite Foam and Its Carbonization for Energy Application
by So Yeon Ahn, Chengbin Yu and Young Seok Song
Polymers 2023, 15(16), 3454; https://doi.org/10.3390/polym15163454 - 18 Aug 2023
Cited by 1 | Viewed by 1560
Abstract
In this study, we fabricated a cellulose nanocrystal (CNC)-embedded aerogel-like chitosan foam and carbonized the 3D foam for electrical energy harvesting. The nanocrystal-supported cellulose foam can demonstrate a high surface area and porosity, homogeneous size ranging from various microscales, and a high quality [...] Read more.
In this study, we fabricated a cellulose nanocrystal (CNC)-embedded aerogel-like chitosan foam and carbonized the 3D foam for electrical energy harvesting. The nanocrystal-supported cellulose foam can demonstrate a high surface area and porosity, homogeneous size ranging from various microscales, and a high quality of absorbing external additives. In order to prepare CNC, microcrystalline cellulose (MCC) was chemically treated with sulfuric acid. The CNC incorporates into chitosan, enhancing mechanical properties, crystallization, and generation of the aerogel-like porous structure. The weight percentage of the CNC was 2 wt% in the chitosan composite. The CNC/chitosan foam is produced using the freeze-drying method, and the CNC-embedded CNC/chitosan foam has been carbonized. We found that the degree of crystallization of carbon structure increased, including the CNCs. Both CNC and chitosan are degradable materials when CNC includes chitosan, which can form a high surface area with some typical surface-related morphology. The electrical cyclic voltammetric result shows that the vertical composite specimen had superior electrochemical properties compared to the horizontal composite specimen. In addition, the BET measurement indicated that the CNC/chitosan foam possessed a high porosity, especially mesopores with layer structures. At the same time, the carbonized CNC led to a significant increase in the portion of micropore. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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<p>Schematic of fabrication of modified CNC/chitosan composite structure.</p>
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<p>Morphological analysis of the samples: Optical microscopic images of (<b>a</b>) the CNC/chitosan foam and (<b>b</b>) the carbonized CNC/chitosan foam. (<b>c</b>) Cryo-SEM image of (<b>c</b>) the CNC/chitosan suspension and SEM images of (<b>d</b>) the carbonized chitosan foam, (<b>e</b>) the CNC/chitosan foam, and (<b>f</b>) the carbonized CNC/chitosan foam.</p>
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<p>(<b>a</b>) FT-IR result of the raw and carbonized chitosan foam. (<b>b</b>) Scanning results of carbonized CNC/Chitosan foam. (<b>c</b>) Raman spectra of the carbonized chitosan foam and CNC/chitosan foam. (<b>d</b>) WAXS spectra of the carbonized chitosan foam and CNC/chitosan foam.</p>
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<p>Cyclic voltammetry results of (<b>a</b>) the carbonized chitosan foam and (<b>b</b>) the carbonized CNC/chitosan foam.</p>
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<p>Chronoamperometry analysis of the sample: (<b>a</b>) photograph (left) and schematic image (right) of the experimental setup and (<b>b</b>) current result to time for the carbonized chitosan foam and CNC/chitosan foam.</p>
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<p>Gas physisorption result of the uncarbonized chitosan foam and CNC/chitosan foam: (<b>a</b>) hysteresis loops; (<b>b</b>) BET analysis of adsorption isotherm and pore size distributions obtained from (<b>c</b>) MP and (<b>d</b>) BJH analyses.</p>
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<p>Gas physisorption result of the carbonized chitosan foam and CNC/chitosan foam: (<b>a</b>) hysteresis loops; (<b>b</b>) BET analysis of adsorption isotherm and pore size distributions obtained from (<b>c</b>) MP and (<b>d</b>) BJH analyses.</p>
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9 pages, 2127 KiB  
Communication
Key Factors in Enhancing Pseudocapacitive Properties of PANI-InOx Hybrid Thin Films Prepared by Sequential Infiltration Synthesis
by Jiwoong Ham, Hyeong-U Kim and Nari Jeon
Polymers 2023, 15(12), 2616; https://doi.org/10.3390/polym15122616 - 8 Jun 2023
Cited by 1 | Viewed by 1488
Abstract
Sequential infiltration synthesis (SIS) is an emerging vapor-phase synthetic route for the preparation of organic–inorganic composites. Previously, we investigated the potential of polyaniline (PANI)-InOx composite thin films prepared using SIS for application in electrochemical energy storage. In this study, we investigated the [...] Read more.
Sequential infiltration synthesis (SIS) is an emerging vapor-phase synthetic route for the preparation of organic–inorganic composites. Previously, we investigated the potential of polyaniline (PANI)-InOx composite thin films prepared using SIS for application in electrochemical energy storage. In this study, we investigated the effects of the number of InOx SIS cycles on the chemical and electrochemical properties of PANI-InOx thin films via combined characterization using X-ray photoelectron spectroscopy, ultraviolet–visible spectroscopy, Raman spectroscopy, Fourier transform infrared spectroscopy, and cyclic voltammetry. The area-specific capacitance values of PANI-InOx samples prepared with 10, 20, 50, and 100 SIS cycles were 1.1, 0.8, 1.4, and 0.96 mF/cm², respectively. Our result shows that the formation of an enlarged PANI-InOx mixed region directly exposed to the electrolyte is key to enhancing the pseudocapacitive properties of the composite films. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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<p>(<b>a</b>) Schematic illustration of structure of PANI-InO<sub>x</sub>/SiO<sub>2</sub>/Si samples. InO<sub>x</sub> content shows graded concentration along film thickness direction. (<b>b</b>) XPS depth profiles showing C, In, N, O, and Si atomic concentrations for four SIS samples with different cycle numbers: 10, 20, 50, and 100 cy. (<b>c</b>) O 1s and N 1s HRXPS data obtained at different locations (i.e., InO<sub>x</sub>-rich region, PANI-InO<sub>x</sub> mixed region, and PANI-rich region) in four samples. Each location at which HRXPS data were captured are shown as arrows in (<b>b</b>).</p>
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<p>(<b>a</b>) UV-vis transmittance spectra, (<b>b</b>) ATR-FTIR absorbance spectra, and (<b>c</b>) Raman spectra of PANI-InO<sub>x</sub> samples at different number of cycles (10, 20, 50, and 100 cy) and PANI-only sample. The PANI-only sample was annealed under the same conditions as the PANI-InO<sub>x</sub> samples. Inset of (<b>a</b>) shows Tauc plot of 100 cy PANI-InO<sub>x</sub> sample. The dashed lines in panel (<b>c</b>) mark the location of Raman bands observed in the PANI-InO<sub>x</sub> film, which are also summarized in <a href="#polymers-15-02616-t001" class="html-table">Table 1</a>.</p>
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<p>CV curves of PANI-InO<sub>x</sub> films prepared with different SIS cycles (10, 20, 50, and 100 cy) and PANI-only film. The CVs were collected at a scan rate of 10 mV/s in an aqueous electrolyte of neutral pH.</p>
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12 pages, 4595 KiB  
Article
Numerical Modeling of the Mixing of Highly Viscous Polymer Suspensions in Partially Filled Sigma Blade Mixers
by Michael Roland Larsen, Tobias Ottsen, Erik Tomas Holmen Olofsson and Jon Spangenberg
Polymers 2023, 15(8), 1938; https://doi.org/10.3390/polym15081938 - 19 Apr 2023
Cited by 3 | Viewed by 2076
Abstract
This paper presents a non-isothermal, non-Newtonian Computational Fluid Dynamics (CFD) model for the mixing of a highly viscous polymer suspension in a partially filled sigma blade mixer. The model accounts for viscous heating and the free surface of the suspension. The rheological model [...] Read more.
This paper presents a non-isothermal, non-Newtonian Computational Fluid Dynamics (CFD) model for the mixing of a highly viscous polymer suspension in a partially filled sigma blade mixer. The model accounts for viscous heating and the free surface of the suspension. The rheological model is found by calibration with experimental temperature measurements. Subsequently, the model is exploited to study the effect of applying heat both before and during mixing on the suspension’s mixing quality. Two mixing indexes are used to evaluate the mixing condition, namely, the Ica Manas-Zlaczower dispersive index and Kramer’s distributive index. Some fluctuations are observed in the predictions of the dispersive mixing index, which could be associated with the free surface of the suspension, thus indicating that this index might not be ideal for partially filled mixers. The Kramer index results are stable and indicate that the particles in the suspension can be well distributed. Interestingly, the results highlight that the speed at which the suspension becomes well distributed is almost independent of applying heat both before and during the process. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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<p>The mixing setup. (1) Chamber of the mixer, (2) control panel and digital display of the temperature, (3) heat exchanger, (4) vacuum pump.</p>
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<p>Illustration of the mixer geometry from (<b>a</b>) above and (<b>b</b>) the side. W and H have a distance of <math display="inline"><semantics> <mrow> <mn>120</mn> <mo> </mo> <mi>mm</mi> </mrow> </semantics></math>, while L and u are <math display="inline"><semantics> <mrow> <mn>126.4</mn> <mo> </mo> <mi>mm</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>50.23</mn> <mo> </mo> <mi>mm</mi> </mrow> </semantics></math>, respectively.</p>
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<p>Viscosity measurements compared to the model.</p>
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<p>Experimental and simulation results of the surface temperature of the fluid as a function of time. The absolute mean error between the simulation and measurement is <math display="inline"><semantics> <mrow> <mn>1.72</mn> <mo> </mo> <mo>°</mo> <mi mathvariant="normal">C</mi> </mrow> </semantics></math>.</p>
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<p>Viscosity curve as a function of the shear rate at different temperatures.</p>
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<p>Temperature profile for <math display="inline"><semantics> <mrow> <mi>N</mi> <mi>A</mi> <mn>50</mn> </mrow> </semantics></math> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>15</mn> <mo> </mo> </mrow> </semantics></math> s.</p>
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<p>Average temperature of the fluid as a function of time.</p>
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<p>Velocity profile for an initial temperature of <math display="inline"><semantics> <mrow> <mn>80</mn> <mo> </mo> <mo>°</mo> <mi mathvariant="normal">C</mi> </mrow> </semantics></math> with adiabatic boundary conditions at different time values. The velocity values are in <math display="inline"><semantics> <mrow> <mi mathvariant="normal">m</mi> <mo>/</mo> <mi mathvariant="normal">s</mi> </mrow> </semantics></math>.</p>
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<p>Histogram of the <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mrow> <mi>m</mi> <mi>z</mi> </mrow> </msub> </mrow> </semantics></math> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>1800</mn> <mrow> <mo> </mo> <mi mathvariant="normal">s</mi> </mrow> </mrow> </semantics></math>.</p>
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<p>The mean value of <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mrow> <mi>m</mi> <mi>z</mi> </mrow> </msub> </mrow> </semantics></math> for different time step values.</p>
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<p>Kramer mixing index at different time values.</p>
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18 pages, 8414 KiB  
Article
Multiphase Flow Production Enhancement Using Drag Reducing Polymers
by Abdelsalam Alsarkhi and Mustafa Salah
Polymers 2023, 15(5), 1108; https://doi.org/10.3390/polym15051108 - 23 Feb 2023
Cited by 3 | Viewed by 1475
Abstract
This paper presents a comprehensive experimental investigation concerning the effect of drag reducing polymers (DRP) on enhancing the throughput and reducing the pressure drop for a horizontal pipe carrying two-phase flow of air and water mixture. Moreover, the ability of these polymer entanglements [...] Read more.
This paper presents a comprehensive experimental investigation concerning the effect of drag reducing polymers (DRP) on enhancing the throughput and reducing the pressure drop for a horizontal pipe carrying two-phase flow of air and water mixture. Moreover, the ability of these polymer entanglements to damp turbulence waves and changing the flow regime has been tested at various conditions, and a clear observation showed that the maximum drag reduction always occurs when the highly fluctuated waves were reduced effectively by DRP (and that, accordingly, phase transition (flow regime changed) appeared. This may also help in improving the separation process and enhancing the separator performance. The present experimental set-up has been constructed using a test section of 1.016-cm ID; an acrylic tube section was used to enable visual observations of the flow patterns. A new injection technique has been utilized and, with the use of different injection rates of DRP, the results have shown that the reduction in pressure drop occurred in all flow configurations. Furthermore, different empirical correlations have been developed which improve the ability to predict the pressure drop after the addition of DRP. The correlations showed low discrepancy for a wide range of water and air flow rates. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
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<p>Sketch of the flow facility.</p>
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<p>Comparison of the frictional pressure drop variation with respect to liquid superficial velocity at different gas superficial velocities of 2.06, 3.08 and 4.11 m/s.</p>
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<p>Effect of drag reducing polymer on the stratified flow regime.</p>
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<p>(<b>a</b>) Stratified Wavy flow without DRP (V<sub>sl</sub> = 0.1 m/s, V<sub>sg</sub> = 0.41 m/s); (<b>b</b>) Stratified Wavy flow with 40 ppm DRP.</p>
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<p>(<b>a</b>) Stratified Wavy flow without DRP (V<sub>sl</sub> = 0.1 m/s, V<sub>sg</sub> = 2.88 m/s); (<b>b</b>) Stratified Wavy flow with 40 ppm DRP.</p>
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<p>Effect of drag reducing polymer on annular flow regime.</p>
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<p>(<b>a</b>) Annular flow regime without DRP (V<sub>sl</sub> = 0.1 m/s, V<sub>sg</sub> = 9.05 m/s); (<b>b</b>) Annular flow regime with 40 ppm of DRP.</p>
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<p>Annular wavy flow regime (V<sub>sl</sub> = 0.1 m/s, V<sub>sg</sub> = 12.75 m/s).</p>
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<p>(<b>a</b>) Typical feature of a Dispersed Bubbly flow regime (V<sub>sl</sub> = 3.08 m/s, V<sub>sg</sub> = 1.03 m/s) (<b>b</b>) Transition from Dispersed Bubbly to Pseudo slug flow regime with 40 ppm DRP.</p>
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<p>Effect of drag reducing polymer on dispersed bubbly flow regime.</p>
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<p>Effect of drag reducing polymer on slug flow regime using a concentration of 40 and 100 ppm.</p>
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<p>Effect of drag reducing polymer on pseudo slug flow regime using a concentration of 40 and 100 ppm.</p>
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<p>(<b>a</b>) Slug flow regime without DRP (V<sub>sl</sub> = 0.72 m/s, V<sub>sg</sub> = 0.41 m/s); (<b>b</b>) Transition from Slug to Stratified Wavy flow regime using 100 ppm DRP.</p>
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<p>(<b>a</b>) Pseudo Slug flow without DRP (V<sub>sl</sub> = 1.03 m/s, V<sub>sg</sub> = 3.08 m/s); (<b>b</b>) Transition from Pseudo Slug to Wavy Annular flow regime using 100 ppm.</p>
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<p>Air-water (without DRP) flow pattern map using Unified [<a href="#B17-polymers-15-01108" class="html-bibr">17</a>] Model in a 1.01-cm pipe. (Dashed box is the present work flow conditions) Where: <b>DB:</b> dispersed bubble, <b>SL:</b> Slug, <b>IN:</b> Intermittent, <b>SS:</b> Smooth Stratified, <b>SW:</b> Stratified Wavy, <b>AN:</b> Annular.</p>
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<p>Friction factor variation with the mixture Reynolds number times the square root of the superficial velocities ratio for different liquid superficial velocities (1.85, 2.45, 3.08, 3.7 and 4.32 m/s).</p>
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<p>Comparison between measured friction factor and predicted by Equation (7).</p>
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<p>Dimensionless pressure drop ratio versus square root of the normalized superficial velocities (correlation is Equation (11)).</p>
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<p>Comparison between measured dimensionless pressure drop ratio and the predicted by Equation (11).</p>
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Review

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26 pages, 5353 KiB  
Review
The Elasticity of Polymer Melts and Solutions in Shear and Extension Flows
by Andrey V. Subbotin, Alexander Ya. Malkin and Valery G. Kulichikhin
Polymers 2023, 15(4), 1051; https://doi.org/10.3390/polym15041051 - 20 Feb 2023
Cited by 4 | Viewed by 3599
Abstract
This review is devoted to understanding the role of elasticity in the main flow modes of polymeric viscoelastic liquids—shearing and extension. The flow through short capillaries is the central topic for discussing the input of elasticity to the effects, which are especially interesting [...] Read more.
This review is devoted to understanding the role of elasticity in the main flow modes of polymeric viscoelastic liquids—shearing and extension. The flow through short capillaries is the central topic for discussing the input of elasticity to the effects, which are especially interesting for shear. An analysis of the experimental data made it possible to show that the energy losses in such flows are determined by the Deborah and Weissenberg numbers. These criteria are responsible for abnormally high entrance effects, as well as for mechanical losses in short capillaries. In addition, the Weissenberg number determines the threshold of the flow instability due to the liquid-to-solid transition. In extension, this criterion shows whether deformation takes place as flow or as elastic strain. However, the stability of a free jet in extension depends not only on the viscoelastic properties of a polymeric substance but also on the driving forces: gravity, surface tension, etc. An analysis of the influence of different force combinations on the shape of the stretched jet is presented. The concept of the role of elasticity in the deformation of polymeric liquids is crucial for any kind of polymer processing. Full article
(This article belongs to the Special Issue Polymers Physics: From Theory to Experimental Applications)
Show Figures

Figure 1

Figure 1
<p>Typical behavior of polymer melts. <span class="html-italic">a</span>: relaxation states of polymers: frequency dependencies of the storage <span class="html-italic">G</span>′ and loss moduli <span class="html-italic">G</span>″, <span class="html-italic">F</span>—flow (terminal) and <span class="html-italic">R</span>—rubbery states. <span class="html-italic">b</span>: ratio between flow and elastic deformations [<a href="#B7-polymers-15-01051" class="html-bibr">7</a>].</p>
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<p>The linear-to-non-linear behavior transition in increasing the deformation rate under extension.</p>
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<p>The velocity distribution in the flow through a cylinder die (capillary).</p>
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<p>Typical effects associated with the elasticity of polymer melts: secondary flows at the entrance to a die (<b>a</b>) [<a href="#B18-polymers-15-01051" class="html-bibr">18</a>] and die swell after exit from a die (<b>b</b>) (authors’ photo).</p>
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<p>The reduced dependence of the shear stress on the Deborah number for different polymer melts and solutions—PAN solutions in DMSO, LDPE, polybutadiene, SAN, solutions of PIB in toluene—presented by different symbols (according to [<a href="#B21-polymers-15-01051" class="html-bibr">21</a>]).</p>
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<p>Dependence of end correction on the Weissenberg number. Different symbols correspond to various compositions of low- and high- molecular-weight polyethylenes (according to [<a href="#B28-polymers-15-01051" class="html-bibr">28</a>]).</p>
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<p>Comparison of two jects obtained at the same volume output but with different lengths of capillaries, long (<b>left</b>) and short (<b>right</b>), authors’ photo.</p>
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<p>Successive stages of the deformation of a drop during the transition from a wide volume to a narrow capillary. Initial (<b>a</b>), intermediate (<b>b</b>), and final (<b>c</b>) stages of the process (reproduced from [<a href="#B37-polymers-15-01051" class="html-bibr">37</a>] with permission.</p>
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<p>Self-oscillations at the exit of a capillary.</p>
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<p>Self-oscillations due to the movement of a scribe along the rubbery surface.</p>
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<p>Correlation between the draw rate and the ultimate strain.</p>
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<p>Schematic picture of a thread (bridge) connecting two droplets.</p>
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<p>Stretching of a polymer solution jet by an external force <math display="inline"><semantics> <mrow> <msub> <mi>F</mi> <mrow> <mi>e</mi> <mi>x</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics></math> during continuous fiber spinning.</p>
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<p>Blistering structure formed by continuous drawing out of a 25% solution of PAN (M<sub>w</sub> = 85,000) in DMSO. Authors’ photo.</p>
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<p>A typical electrospinning jet pattern includes a Taylor cone, a straight jet, and a whipping jet. Authors’ drawing.</p>
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