Mining structure–property relationships in polymer nanocomposites using data driven finite element analysis and multi-task convolutional neural networks

2020 ◽  
Vol 5 (5) ◽  
pp. 962-975
Author(s):  
Yixing Wang ◽  
Min Zhang ◽  
Anqi Lin ◽  
Akshay Iyer ◽  
Aditya Shanker Prasad ◽  
...  
Keyword(s):  
Neural Networks ◽  
Polymer Nanocomposites ◽  
Data Driven ◽  
Learning Approach ◽  
Structure Property ◽  
Element Analysis ◽  
Structure Property Relationships ◽  
Structure Property Relationship ◽  
Using Data ◽  
Relationship Of

In this paper, a data driven and deep learning approach for modeling structure–property relationship of polymer nanocomposites is demonstrated. This method is applicable to understand other material mechanisms and guide the design of material with targeted performance.

On the Structure-Property Relationship of Rapidly Solidified High Temperature Application Aluminium Alloys

1990 ◽  
Vol 186 ◽  
Author(s):  
A.J.S. Chowdhury ◽  
T. Sheppard
Keyword(s):  
High Temperature ◽  
High Temperature Strength ◽  
Structure Property ◽  
High Temperature Application ◽  
Structure Property Relationships ◽  
Structure Property Relationship ◽  
Temperature Application ◽  
Rapidly Solidified ◽  
Relationship Of ◽  
Strength And Ductility

AbstractThe phases responsible for high temperature strength and ductility of Al-Fe based alloys, specifically Al-Fe-Mo alloys, have yet to be unambiguously identified. The phases appear to vary slightly under different experimental and processing conditions. This poses some queries concerning the reproducibility of mechanical properties of these alloys. In this paper an attempt is made to address these points and focus on the structure-property relationships of Al-Fe-Mo and Al-Fe-V rapidly solidified powder alloys.

scholarly journals Using data-driven activities with ChemEd X Data to practice structure-property relationships in General Chemistry

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Xavier Prat-Resina
Keyword(s):  
General Chemistry ◽  
Student Performance ◽  
Graphical Representation ◽  
Data Driven ◽  
Structure Property ◽  
Web Interface ◽  
Structure Property Relationships ◽  
Property Patterns ◽  
Using Data ◽  
Atomic Crystal

AbstractGeneral Chemistry covers a wide variety of structure-property relationships that rely upon electronic, atomic, crystal or molecular factors. Giving students experimental data will allow them to identify the structure-property patterns as well as identify the limit of predictability of such patterns. “ChemEd X Data” is a web interface designed by the author that facilitates the navigation, filtering and graphical representation of chemical and physical data. It can assist students at identifying trends in structure-property relationships, they can create controlled experiments to test a relationship as well as investigating how different molecular factors may affect a single macroscopic property. In particular, since the site offers unstructured but dynamically searchable data, it is designed to have students learn control of variable strategies (CVS). This paper describes the implementation of a five-step sequence of activities related to structure-property relationships in a General Chemistry semester. ChemEd X Data is used for the open-ended or data-driven steps of this sequence. Student performance is analyzed with the objective of understanding which activities require a higher cognitive skill, as well as identify student previous performances that correlate with success in the activities and in the course in general.

Structure–Property Relationship of Solution-Spun Ppbt/Peek and Ppbt/Nylon 6,6 Composite Fibers

1988 ◽  
Vol 134 ◽  
Author(s):  
Carmen A. Gabriel ◽  
Richard J. Farris ◽  
Michael F. Malone
Keyword(s):  
Structure Property ◽  
Composite Fibers ◽  
Property Relations ◽  
Structure Property Relationships ◽  
Nylon 6,6 ◽  
Ether Ether Ketone ◽  
Peek Composite ◽  
Poly Ether Ether Ketone ◽  
Structure Property Relationship ◽  
Relationship Of

ABSTRACTPrevious work investigated the processing/structure/property relationships for solution spun composite fibers of rodlike poly(p-phenylene benzobisthiazole) [PPBT] with nylon 6,6 [N66] and poly(ether ether ketone) [PEEK] [1]. Evidence that these composite fibers were effectively reinforced by a network-like structure of PPBT was given. In the present investigation, the morphology and properties of wet, as-spun, and heattreated PPBT/nylon 6,6 and PPBT/PEEK composite fibers are contrasted to gain insight into the structure/property relations which result from these post-spinning processes. It is concluded that heat-treatment is simply a means of perfecting the network structure, thereby enhancing the tensile properties of the composite fibers.

Structure–property relationship of acceptor-substituted oligothiophenes

Tetrahedron ◽  
2010 ◽  
Vol 66 (45) ◽  
pp. 8729-8733 ◽  
Author(s):  
M.S. Wrackmeyer ◽  
M. Hummert ◽  
H. Hartmann ◽  
M.K. Riede ◽  
K. Leo
Keyword(s):  
Structure Property ◽  
Property Relationship ◽  
Structure Property Relationship ◽  
Relationship Of

Structure-property relationship of pH-sensitive (PCL)2(PDEA-b-PPEGMA)2micelles: Experiment and DPD simulation

AIChE Journal ◽  
2014 ◽  
Vol 60 (10) ◽  
pp. 3634-3646 ◽  
Author(s):  
Wen Jing Lin ◽  
Shu Yu Nie ◽  
Quan Chen ◽  
Yu Qian ◽  
Xiu Fang Wen ◽  
...  
Keyword(s):  
Ph Sensitive ◽  
Structure Property ◽  
Property Relationship ◽  
Structure Property Relationship ◽  
Relationship Of ◽  
Dpd Simulation
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