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Title: MECHANICAL CLASSIFICATION OF CARBON FIBERS FROM RAMAN AND X-RAY SCATTERING

Abstract

Carbon fibers for application are produced from a wide variety of precursor phases and exhibit a broad range of mechanical characteristics that result from variations in the manufacturing process [1]. Raman spectroscopy, a nondestructive and potentially high-throughput tool, is highly sensitive to a host of phenomena in carbon-based materials [2]. Carbon fibers used in applications are naturally delineated along lines of macroscopic strength properties, and control of the macroscopic strength properties is well understood to be linked to the manufacturing process and ultimate firing temperature of the carbon fibers. Consequently, there are numerous characterizations of spectroscopic observables connected to macroscopic properties of carbon fibers, particularly to optimize production by attempting to quantify signatory changes in fibers [3]. Here we are specifically concerned with the evolution of spectroscopic data collected from carbon fibers as they connect to bulk mechanical properties as a baseline for studying spectral evolution under temperature and strain application. To this end, we present correlative results of experimental studies investigating the ability to connect the macroscopic properties of carbon fibers with microscopic observables across a broad range of macroscopic values.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1566980
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: American Carbon Society Carbon Conference (Carbon 2019) - Lexington, Kentucky, United States of America - 7/14/2019 8:00:00 AM-7/19/2019 8:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

Niedziela, Jennifer L., Miskowiec, Andrew J., Langford Jr, John, and Kapsimalis, Roger J. MECHANICAL CLASSIFICATION OF CARBON FIBERS FROM RAMAN AND X-RAY SCATTERING. United States: N. p., 2019. Web.
Niedziela, Jennifer L., Miskowiec, Andrew J., Langford Jr, John, & Kapsimalis, Roger J. MECHANICAL CLASSIFICATION OF CARBON FIBERS FROM RAMAN AND X-RAY SCATTERING. United States.
Niedziela, Jennifer L., Miskowiec, Andrew J., Langford Jr, John, and Kapsimalis, Roger J. Mon . "MECHANICAL CLASSIFICATION OF CARBON FIBERS FROM RAMAN AND X-RAY SCATTERING". United States. https://www.osti.gov/servlets/purl/1566980.
@article{osti_1566980,
title = {MECHANICAL CLASSIFICATION OF CARBON FIBERS FROM RAMAN AND X-RAY SCATTERING},
author = {Niedziela, Jennifer L. and Miskowiec, Andrew J. and Langford Jr, John and Kapsimalis, Roger J.},
abstractNote = {Carbon fibers for application are produced from a wide variety of precursor phases and exhibit a broad range of mechanical characteristics that result from variations in the manufacturing process [1]. Raman spectroscopy, a nondestructive and potentially high-throughput tool, is highly sensitive to a host of phenomena in carbon-based materials [2]. Carbon fibers used in applications are naturally delineated along lines of macroscopic strength properties, and control of the macroscopic strength properties is well understood to be linked to the manufacturing process and ultimate firing temperature of the carbon fibers. Consequently, there are numerous characterizations of spectroscopic observables connected to macroscopic properties of carbon fibers, particularly to optimize production by attempting to quantify signatory changes in fibers [3]. Here we are specifically concerned with the evolution of spectroscopic data collected from carbon fibers as they connect to bulk mechanical properties as a baseline for studying spectral evolution under temperature and strain application. To this end, we present correlative results of experimental studies investigating the ability to connect the macroscopic properties of carbon fibers with microscopic observables across a broad range of macroscopic values.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {7}
}

Conference:
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