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Title: 3D reconstruction of carbon nanotube networks from neutron scattering experiments

Journal Article · · Nanotechnology
 [1];  [2];  [1];  [3];  [4]
  1. Univ. of Tehran (Iran)
  2. Univ. of Strasbourg (France)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  4. Univ. of New Mexico, Albuquerque, NM (United States)
+ Show Author Affiliations

Structure reconstruction from statistical descriptors, such as scattering data obtained using x-rays or neutrons, is essential in understanding various properties of nanocomposites. Scattering based reconstruction can provide a realistic model, over various length scales, that can be used for numerical simulations. In this study, 3D reconstruction of a highly loaded carbon nanotube (CNT)-conducting polymer system based on small and ultra-small angle neutron scattering (SANS and USANS, respectively) data was performed. These light-weight and flexible materials have recently shown great promise for high-performance thermoelectric energy conversion, and their further improvement requires a thorough understanding of their structure-property relationships. The first step in achieving such understanding is to generate models that contain the hierarchy of CNT networks over nano and micron scales. The studied system is a single walled carbon nanotube (SWCNT)/poly (3,4-ethylenedioxythiophene): poly (styrene sulfonate) (PEDOT: PSS). SANS and USANS patterns of the different samples containing 10, 30, and 50 wt% SWCNTs were measured. These curves were then utilized to calculate statistical two-point correlation functions of the nanostructure. These functions along with the geometrical information extracted from SANS data and scanning electron microscopy images were used to reconstruct a representative volume element (RVE) nanostructure. Generated RVEs can be used for simulations of various mechanical and physical properties. This work, therefore, introduces a framework for the reconstruction of 3D RVEs of high volume faction nanocomposites containing high aspect ratio fillers from scattering experiments.

Research Organization:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1393876
Journal Information:
Nanotechnology, Vol. 26, Issue 38; ISSN 0957-4484
Publisher:
IOP PublishingCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 7 works
Citation information provided by
Web of Science

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Cited By (2)

Numerical homogenization of coiled carbon nanotube reinforced shape memory polymer nanocomposites journal February 2019
Inverse modeling of inelastic properties of a two-phase microstructure journal September 2019

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