Quantifying the robustness of the neutron reflectometry technique for structural characterization of polymer brushes

2021 ◽  
Vol 54 (3) ◽  
Author(s):  
Isaac J. Gresham ◽  
Timothy J. Murdoch ◽  
Edwin C. Johnson ◽  
Hayden Robertson ◽  
Grant B. Webber ◽  
...  
Keyword(s):  
Polymer Brushes ◽  
Volume Fraction ◽  
Polymer Brush ◽  
Real Data ◽  
Data Interpretation ◽  
Neutron Reflectometry ◽  
Free Form ◽  
Diffuse Interfaces ◽  
Form Model

Neutron reflectometry is the foremost technique for in situ determination of the volume fraction profiles of polymer brushes at planar interfaces. However, the subtle features in the reflectometry data produced by these diffuse interfaces challenge data interpretation. Historically, data analyses have used least-squares approaches that do not adequately quantify the uncertainty of the modeled profile and ignore the possibility of other structures that also match the collected data (multimodality). Here, a Bayesian statistical approach is used that permits the structural uncertainty and multimodality to be quantified for polymer brush systems. A free-form model is used to describe the volume fraction profile, minimizing assumptions regarding brush structure, while only allowing physically reasonable profiles to be produced. The model allows the total volume of polymer and the profile monotonicity to be constrained. The rigor of the approach is demonstrated via a round-trip analysis of a simulated system, before it is applied to real data examining the well characterized collapse of a thermoresponsive brush. It is shown that, while failure to constrain the interfacial volume and consider multimodality may result in erroneous structures being derived, carefully constraining the model allows for robust determination of polymer brush compositional profiles. This work highlights that an appropriate combination of flexibility and constraint must be used with polymer brush systems to ensure the veracity of the analysis. The code used in this analysis is provided, enabling the reproduction of the results and the application of the method to similar problems.

scholarly journals Amorphous alloys and differential scanning calorimetry (DSC)

2021 ◽  
Author(s):  
Dora Janovszky ◽  
Maria Sveda ◽  
Anna Sycheva ◽  
Ferenc Kristaly ◽  
Ferenc Zámborszky ◽  
...  
Keyword(s):  
Metallic Glasses ◽  
Amorphous Alloys ◽  
Volume Fraction ◽  
Data Interpretation ◽  
Glass Temperature ◽  
Scanning Calorimetry ◽  
Scientific Papers ◽  
Kinetics Of ◽  
Temperature Crystallization

AbstractA remarkable number of scientific papers are available in the literature about the bulk amorphous alloys and metallic glasses. Today, DSC is an essential tool for amorphous alloys research and development, and of course for quality assurance. In many cases, users seek to examine the determination of only one or two properties, although much more information can be obtained from the measurements. The research involved structural relaxation, Curie temperature, glass temperature, crystallization, phase separation, nanocrystalline volume fraction, melting point and liquidus temperature determination subjects and kinetics of microstructural transformations induced by thermal treatment. We collected and present the information that can be obtained with this technique and draws the reader’s attention to some potential problems related to data interpretation.

Numerical Simulation of Collision Effect on Damage Evolution in Electromagnetic Forming of Aluminum Alloy Sheet

2018 ◽  
Vol 765 ◽  
pp. 216-221
Author(s):  
Xi Fan Zou ◽  
Shang Yu Huang ◽  
Wei Liu ◽  
Yu Lei ◽  
Jie Zhu
Keyword(s):  
Numerical Simulation ◽  
Damage Evolution ◽  
Volume Fraction ◽  
Alloy Sheet ◽  
Void Volume Fraction ◽  
Electromagnetic Forming ◽  
Void Volume ◽  
Free Form ◽  
Al Alloy ◽  
Form Model

A numerical simulation study of collision effect on damage evolution in electromagnetic forming (EMF) was presented. EMF technology can greatly improve the forming limit of metal sheet duo to the high rate. However, collision behavior is also an important factor for the formability of sheet. Free form model and conical die model were carried out to study the effect of collision behavior on mechanical properties of Al alloy sheet. The EMF process of 1050 Al alloy sheet was analyzed and discussed by numerical analysis software LS-DYNA. The combined strategy of boundary element method and finite element method was adopted to realize the coupling calculation of electromagnetic field and structural field. Based on the GTN material model, the evolution of void volume fraction of 1050 Al sheet were calculated and analyzed. Comparing the free form model results and the die form model results, showed that the collision behavior could reduce the void volume fraction of sheet, but excessively high collision speed lead to the sheet rebound, which aggravated the damage of material and reduce the accuracy of the product. Therefore, the appropriate discharge voltage in this work was found to improve mechanical property of sheet on the premise of forming precision.

Method of determination of the text direction on the image with the use of convolutional neural network

2020 ◽  
pp. 96-99
Author(s):  
P.L. Nikolaev
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Neural Network ◽  
Binary Classification ◽  
Synthetic Data ◽  
Real Data ◽  
Method Of Determination ◽  
Classification Of Images

This article deals with method of binary classification of images with small text on them Classification is based on the fact that the text can have 2 directions – it can be positioned horizontally and read from left to right or it can be turned 180 degrees so the image must be rotated to read the sign. This type of text can be found on the covers of a variety of books, so in case of recognizing the covers, it is necessary first to determine the direction of the text before we will directly recognize it. The article suggests the development of a deep neural network for determination of the text position in the context of book covers recognizing. The results of training and testing of a convolutional neural network on synthetic data as well as the examples of the network functioning on the real data are presented.

Effect and Detection of Loose Chain Ends in Crosslinked Polyurethane Elastomers

1971 ◽  
Vol 44 (1) ◽  
pp. 152-165 ◽  
Author(s):  
A. E. Oberth
Keyword(s):  
Crosslink Density ◽  
Volume Fraction ◽  
Present Theory ◽  
Swelling Ratio ◽  
Polyurethane Elastomers ◽  
Equilibrium Volume ◽  
Equilibrium Swelling ◽  
Volume Swelling

Abstract The effect of loose chain ends on tensile properties and equilibrium swelling of crosslinked polyurethane rubbers is studied. As in plasticized elastomers, tensile strength and elastic modulus are reduced approximately by a factor (1−νE,P)2, where νE,P is the volume fraction of loose chain ends, plasticizer, or both. This effect is much larger than predicted by present theory. Also the equilibrium volume swelling ratio, V0/V, of rubbers having terminal chains or an equal volume of plasticizer is the same, provided they do not differ in crosslink density. However, the volume fraction of “network rubber” in the equilibrium swollen specimen, ν2, differs owing to the non-extractability of terminal chains. On this basis a method is proposed which allows experimental determination of the volume fraction of loose ends. Elastomers abounding in loose chain ends show markedly less long term stress relaxation. This effect is not clearly understood but is useful to detect the presence of non load-bearing network.

scholarly journals A Sequential Approach for Aerodynamic Shape Optimization with Topology Optimization of Airfoils

2021 ◽  
Vol 26 (2) ◽  
pp. 34
Author(s):  
Isaac Gibert Martínez ◽  
Frederico Afonso ◽  
Simão Rodrigues ◽  
Fernando Lau
Keyword(s):  
Topology Optimization ◽  
Shape Optimization ◽  
Volume Fraction ◽  
Optimization Techniques ◽  
Free Form ◽  
Aerodynamic Shape Optimization ◽  
Sequential Approach ◽  
Airfoil Surface ◽  
Aerodynamic Shape ◽  
Design Variables

The objective of this work is to study the coupling of two efficient optimization techniques, Aerodynamic Shape Optimization (ASO) and Topology Optimization (TO), in 2D airfoils. To achieve such goal two open-source codes, SU2 and Calculix, are employed for ASO and TO, respectively, using the Sequential Least SQuares Programming (SLSQP) and the Bi-directional Evolutionary Structural Optimization (BESO) algorithms; the latter is well-known for allowing the addition of material in the TO which constitutes, as far as our knowledge, a novelty for this kind of application. These codes are linked by means of a script capable of reading the geometry and pressure distribution obtained from the ASO and defining the boundary conditions to be applied in the TO. The Free-Form Deformation technique is chosen for the definition of the design variables to be used in the ASO, while the densities of the inner elements are defined as design variables of the TO. As a test case, a widely used benchmark transonic airfoil, the RAE2822, is chosen here with an internal geometric constraint to simulate the wing-box of a transonic wing. First, the two optimization procedures are tested separately to gain insight and then are run in a sequential way for two test cases with available experimental data: (i) Mach 0.729 at α=2.31°; and (ii) Mach 0.730 at α=2.79°. In the ASO problem, the lift is fixed and the drag is minimized; while in the TO problem, compliance minimization is set as the objective for a prescribed volume fraction. Improvements in both aerodynamic and structural performance are found, as expected: the ASO reduced the total pressure on the airfoil surface in order to minimize drag, which resulted in lower stress values experienced by the structure.

scholarly journals Determination of the Factors Affecting King Abdul Aziz University Published Articles in ISI by Multilayer Perceptron Artificial Neural Network

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 766
Author(s):  
Rashad A. R. Bantan ◽  
Ramadan A. Zeineldin ◽  
Farrukh Jamal ◽  
Christophe Chesneau
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Multilayer Perceptron ◽  
Research Study ◽  
Real Data ◽  
Factors Affecting ◽  
King Abdulaziz University ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Deanship of scientific research established by the King Abdulaziz University provides some research programs for its staff and researchers and encourages them to submit proposals in this regard. Distinct research study (DRS) is one of these programs. It is available all the year and the King Abdulaziz University (KAU) staff can submit more than one proposal at the same time up to three proposals. The rules of the DSR program are simple and easy so it contributes in increasing the international rank of KAU. The authors are offered financial and moral reward after publishing articles from these proposals in Thomson-ISI journals. In this paper, multiplayer perceptron (MLP) artificial neural network (ANN) is employed to determine the factors that have more effect on the number of ISI published articles. The proposed study used real data of the finished projects from 2011 to April 2019.

Synthesis and Properties of Fe3O4 Ferrofluids with Narrow Particle Size Distribution

2011 ◽  
Vol 694 ◽  
pp. 575-579
Author(s):  
Jian Hui Zhang ◽  
Hai Bo Sun
Keyword(s):  
Magnetic Particles ◽  
Particle Diameter ◽  
Free Form ◽  
Narrow Particle Size Distribution ◽  
Particle Sizes ◽  
Bingham Plastic ◽  
Plastic Fluid ◽  
Form Model ◽  
The Mean ◽  
Inference Theory

Fe3O4 ferrofluids with uniform magnetic particles were prepared via improved chemical coprecipation technique. A narrow distribution of 8.6-10.8 nm particle sizes was obtained from the magnetization curve using the free-form-model based on Bayesian inference theory. The mean particle diameter about 9.8 nm is consistent with the XRD and SEM results. The hydrodynamic properties of ferrofluids were investigated with different applied magnetic field and shear rate. The experimental results show that diluted ferrofluid and concentrated ferrofluid are Newtonian-fluid and Bingham-plastic fluid, respectively.

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