<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Journal Article</dc:product_type><dc:title>Experimental Investigation of the Combustion Properties of an Average Thermal Runaway Gas Mixture from Li-Ion Batteries</dc:title><dc:creator>Olivier Mathieu, Claire M.</dc:creator><dc:corporate_author/><dc:editor/><dc:description>To assess the fire hazard associated with venting gases coming from a
lithium-ion battery during a thermal runaway, a mixture representative of such venting
gas was determined by averaging 40 gas compositions presented in the literature. The
final mixture is composed of C3H8, C2H6, C2H4, CH4, H2, CO, and CO2. The
combustion properties of this mixture were determined using various combustion
devices: shock tubes for ignition delay time measurements in air and for H2O time
histories in very dilute mixtures (99% Ar), as well as a closed bomb to measure the
laminar flame speeds. Experiments were performed at around atmospheric pressure and
for several equivalence ratios in all cases. Several detailed kinetics models from the
literature were assessed against the data generated with this very complex mixture, and it
was found that modern detailed kinetics mechanisms were capable of appropriately
predicting the combustion properties of thermal runaway gases from a battery in most
cases, with the NUIGMech 1.1 model being the most accurate. A numerical analysis was
conducted with the two most modern models to explain the results and highlight the most important reactions.</dc:description><dc:publisher/><dc:date>2022-02-23</dc:date><dc:nsf_par_id>10351057</dc:nsf_par_id><dc:journal_name>Energy  fuels</dc:journal_name><dc:journal_volume>36</dc:journal_volume><dc:journal_issue/><dc:page_range_or_elocation>3247-3258</dc:page_range_or_elocation><dc:issn>0887-0624</dc:issn><dc:isbn/><dc:doi>https://doi.org/</dc:doi><dcq:identifierAwardId>2037795</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>