A characterization method and model for predicting coal conversion behaviour
This paper considers the development of a predictive macromolecular network decomposition model for coal conversion which is based on a variety of modern analytical techniques for coal characterization. Six concepts which are the foundation of the functional group-depolymerization-vaporization-cross...
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description | This paper considers the development of a predictive macromolecular network decomposition model for coal conversion which is based on a variety of modern analytical techniques for coal characterization. Six concepts which are the foundation of the functional group-depolymerization-vaporization-cross-linking (FG-DVC) model are considered:
1.
(1) The decomposition of functional group sources in the coal yields the light gas species in thermal decomposition. The amount and evolution kinetics can be measured by t.g.-FT-i.r., the functional group changes by FT-i.r. and n.m.r.
2.
(2) The decomposition of a macromolecular network yields tar and metaplast. The amount and kinetics of the tar evolution can be measured by t.g.-FT-i.r. and the molecular weight by f.i.m.s. The kinetics of metaplast formation and destruction can be determined by solvent extraction, by Gieseler plastometer measurements and by proton magnetic resonance thermal analysis (p.m.r.t.a.).
3.
(3) The molecular weight distribution of the metaplast depends on the network coordination number (average number of attachments on aromatic ring clusters). The coordination number can be determined by solvent swelling and n.m.r.
4.
(4) The network decomposition is controlled by bridge breaking. The number of bridges broken is limited by the available donatable hydrogen.
5.
(5) The network solidification is controlled by cross-linking. The changing cross-link density can be measured by solvent swelling and n.m.r. Cross-linking appears to occur with evolution of both CO
2 (before bridge breaking) and CH
4 (after bridge breaking). Thus low-rank coals (which evolve much CO
2) cross-link before bridge breaking and are thus thermosetting. High-volatile bituminous coals (which form little CO
2) undergo significant bridge breaking before cross-linking and become highly fluid. Weathering, which increases the CO
2 yield, causes increased cross-linking and lowers fluidity.
6.
(6) The evolution of tar is controlled by mass transport in which the tar molecules evaporate into the light gas or tar species and are carried out of the coal at rates proportional to their vapour pressure and the volume of light species. High pressures reduce the volume of light species and hence reduce the yield of heavy molecules with low vapour pressures. These changes can be studied with f.i.m.s. The paper describes how the coal kinetic and composition parameters are obtained by t.g.-FT-i.r., solvent swelling, solvent extraction and Giesel |
doi_str_mv | 10.1016/0016-2361(93)90106-C |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_25967719</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>001623619390106C</els_id><sourcerecordid>25967719</sourcerecordid><originalsourceid>FETCH-LOGICAL-c400t-441f71a6343b7ec2ddad878f98a0159c85dcab05780f8defd0a400b68daf5e03</originalsourceid><addsrcrecordid>eNp9kD1PwzAQhi0EEqXwDxgyIARDwM6XnQUJRXxJlVi6Wxf7TI2SuNhpJfj1OLTqyHK3PO97uoeQS0bvGGXVPY0jzfKK3dT5bU0ZrdLmiMyY4HnKWZkfk9kBOSVnIXxSSrkoixlZPCZqBR7UiN7-wGjdkPQ4rpxOYNBJ7zR2iXE-WXvUVo12-EiUgy6OYYs-THyLK9hat_Hn5MRAF_Biv-dk-fy0bF7TxfvLW_O4SFVB6ZgWBTOcQZUXectRZVqDFlyYWgBlZa1EqRW0tOSCGqHRaAox11ZCgymR5nNyvatde_e1wTDK3gaFXQcDuk2QWVlXnLM6gsUOVN6F4NHItbc9-G_JqJzMyUmLnLTIOpd_5mQTY1f7fggKOuNhUDYcskWVFSyrIvawwzC-urXoZVAWBxU9eVSj1M7-f-cXUxGCuw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>25967719</pqid></control><display><type>article</type><title>A characterization method and model for predicting coal conversion behaviour</title><source>ScienceDirect Journals (5 years ago - present)</source><creator>Solomon, Peter R. ; Hamblen, David G. ; Serio, Michael A. ; Yu, Zhen-Zhong ; Charpenay, Sylvie</creator><creatorcontrib>Solomon, Peter R. ; Hamblen, David G. ; Serio, Michael A. ; Yu, Zhen-Zhong ; Charpenay, Sylvie</creatorcontrib><description>This paper considers the development of a predictive macromolecular network decomposition model for coal conversion which is based on a variety of modern analytical techniques for coal characterization. Six concepts which are the foundation of the functional group-depolymerization-vaporization-cross-linking (FG-DVC) model are considered:
1.
(1) The decomposition of functional group sources in the coal yields the light gas species in thermal decomposition. The amount and evolution kinetics can be measured by t.g.-FT-i.r., the functional group changes by FT-i.r. and n.m.r.
2.
(2) The decomposition of a macromolecular network yields tar and metaplast. The amount and kinetics of the tar evolution can be measured by t.g.-FT-i.r. and the molecular weight by f.i.m.s. The kinetics of metaplast formation and destruction can be determined by solvent extraction, by Gieseler plastometer measurements and by proton magnetic resonance thermal analysis (p.m.r.t.a.).
3.
(3) The molecular weight distribution of the metaplast depends on the network coordination number (average number of attachments on aromatic ring clusters). The coordination number can be determined by solvent swelling and n.m.r.
4.
(4) The network decomposition is controlled by bridge breaking. The number of bridges broken is limited by the available donatable hydrogen.
5.
(5) The network solidification is controlled by cross-linking. The changing cross-link density can be measured by solvent swelling and n.m.r. Cross-linking appears to occur with evolution of both CO
2 (before bridge breaking) and CH
4 (after bridge breaking). Thus low-rank coals (which evolve much CO
2) cross-link before bridge breaking and are thus thermosetting. High-volatile bituminous coals (which form little CO
2) undergo significant bridge breaking before cross-linking and become highly fluid. Weathering, which increases the CO
2 yield, causes increased cross-linking and lowers fluidity.
6.
(6) The evolution of tar is controlled by mass transport in which the tar molecules evaporate into the light gas or tar species and are carried out of the coal at rates proportional to their vapour pressure and the volume of light species. High pressures reduce the volume of light species and hence reduce the yield of heavy molecules with low vapour pressures. These changes can be studied with f.i.m.s. The paper describes how the coal kinetic and composition parameters are obtained by t.g.-FT-i.r., solvent swelling, solvent extraction and Gieseler plastometer data. The model is compared with a variety of experimental data in which heating rate, temperature and pressure are all varied. There is good agreement with theory for most of the data available from the authors' laboratory and in the literature.</description><identifier>ISSN: 0016-2361</identifier><identifier>EISSN: 1873-7153</identifier><identifier>DOI: 10.1016/0016-2361(93)90106-C</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Applied sciences ; characterization ; coal ; Combustion of solid fuels ; Combustion. Flame ; conversion ; Energy ; Energy. Thermal use of fuels ; Exact sciences and technology ; Fuel processing. Carbochemistry and petrochemistry ; Fuels ; Solid fuel processing (coal, coke, brown coal, peat, wood, etc.) ; Theoretical studies. Data and constants. Metering</subject><ispartof>Fuel (Guildford), 1993-04, Vol.72 (4), p.469-488</ispartof><rights>1993</rights><rights>1993 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c400t-441f71a6343b7ec2ddad878f98a0159c85dcab05780f8defd0a400b68daf5e03</citedby><cites>FETCH-LOGICAL-c400t-441f71a6343b7ec2ddad878f98a0159c85dcab05780f8defd0a400b68daf5e03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/0016-2361(93)90106-C$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,27923,27924,45994</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=4624126$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Solomon, Peter R.</creatorcontrib><creatorcontrib>Hamblen, David G.</creatorcontrib><creatorcontrib>Serio, Michael A.</creatorcontrib><creatorcontrib>Yu, Zhen-Zhong</creatorcontrib><creatorcontrib>Charpenay, Sylvie</creatorcontrib><title>A characterization method and model for predicting coal conversion behaviour</title><title>Fuel (Guildford)</title><description>This paper considers the development of a predictive macromolecular network decomposition model for coal conversion which is based on a variety of modern analytical techniques for coal characterization. Six concepts which are the foundation of the functional group-depolymerization-vaporization-cross-linking (FG-DVC) model are considered:
1.
(1) The decomposition of functional group sources in the coal yields the light gas species in thermal decomposition. The amount and evolution kinetics can be measured by t.g.-FT-i.r., the functional group changes by FT-i.r. and n.m.r.
2.
(2) The decomposition of a macromolecular network yields tar and metaplast. The amount and kinetics of the tar evolution can be measured by t.g.-FT-i.r. and the molecular weight by f.i.m.s. The kinetics of metaplast formation and destruction can be determined by solvent extraction, by Gieseler plastometer measurements and by proton magnetic resonance thermal analysis (p.m.r.t.a.).
3.
(3) The molecular weight distribution of the metaplast depends on the network coordination number (average number of attachments on aromatic ring clusters). The coordination number can be determined by solvent swelling and n.m.r.
4.
(4) The network decomposition is controlled by bridge breaking. The number of bridges broken is limited by the available donatable hydrogen.
5.
(5) The network solidification is controlled by cross-linking. The changing cross-link density can be measured by solvent swelling and n.m.r. Cross-linking appears to occur with evolution of both CO
2 (before bridge breaking) and CH
4 (after bridge breaking). Thus low-rank coals (which evolve much CO
2) cross-link before bridge breaking and are thus thermosetting. High-volatile bituminous coals (which form little CO
2) undergo significant bridge breaking before cross-linking and become highly fluid. Weathering, which increases the CO
2 yield, causes increased cross-linking and lowers fluidity.
6.
(6) The evolution of tar is controlled by mass transport in which the tar molecules evaporate into the light gas or tar species and are carried out of the coal at rates proportional to their vapour pressure and the volume of light species. High pressures reduce the volume of light species and hence reduce the yield of heavy molecules with low vapour pressures. These changes can be studied with f.i.m.s. The paper describes how the coal kinetic and composition parameters are obtained by t.g.-FT-i.r., solvent swelling, solvent extraction and Gieseler plastometer data. The model is compared with a variety of experimental data in which heating rate, temperature and pressure are all varied. There is good agreement with theory for most of the data available from the authors' laboratory and in the literature.</description><subject>Applied sciences</subject><subject>characterization</subject><subject>coal</subject><subject>Combustion of solid fuels</subject><subject>Combustion. Flame</subject><subject>conversion</subject><subject>Energy</subject><subject>Energy. Thermal use of fuels</subject><subject>Exact sciences and technology</subject><subject>Fuel processing. Carbochemistry and petrochemistry</subject><subject>Fuels</subject><subject>Solid fuel processing (coal, coke, brown coal, peat, wood, etc.)</subject><subject>Theoretical studies. Data and constants. Metering</subject><issn>0016-2361</issn><issn>1873-7153</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1993</creationdate><recordtype>article</recordtype><recordid>eNp9kD1PwzAQhi0EEqXwDxgyIARDwM6XnQUJRXxJlVi6Wxf7TI2SuNhpJfj1OLTqyHK3PO97uoeQS0bvGGXVPY0jzfKK3dT5bU0ZrdLmiMyY4HnKWZkfk9kBOSVnIXxSSrkoixlZPCZqBR7UiN7-wGjdkPQ4rpxOYNBJ7zR2iXE-WXvUVo12-EiUgy6OYYs-THyLK9hat_Hn5MRAF_Biv-dk-fy0bF7TxfvLW_O4SFVB6ZgWBTOcQZUXectRZVqDFlyYWgBlZa1EqRW0tOSCGqHRaAox11ZCgymR5nNyvatde_e1wTDK3gaFXQcDuk2QWVlXnLM6gsUOVN6F4NHItbc9-G_JqJzMyUmLnLTIOpd_5mQTY1f7fggKOuNhUDYcskWVFSyrIvawwzC-urXoZVAWBxU9eVSj1M7-f-cXUxGCuw</recordid><startdate>19930401</startdate><enddate>19930401</enddate><creator>Solomon, Peter R.</creator><creator>Hamblen, David G.</creator><creator>Serio, Michael A.</creator><creator>Yu, Zhen-Zhong</creator><creator>Charpenay, Sylvie</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>19930401</creationdate><title>A characterization method and model for predicting coal conversion behaviour</title><author>Solomon, Peter R. ; Hamblen, David G. ; Serio, Michael A. ; Yu, Zhen-Zhong ; Charpenay, Sylvie</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c400t-441f71a6343b7ec2ddad878f98a0159c85dcab05780f8defd0a400b68daf5e03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1993</creationdate><topic>Applied sciences</topic><topic>characterization</topic><topic>coal</topic><topic>Combustion of solid fuels</topic><topic>Combustion. Flame</topic><topic>conversion</topic><topic>Energy</topic><topic>Energy. Thermal use of fuels</topic><topic>Exact sciences and technology</topic><topic>Fuel processing. Carbochemistry and petrochemistry</topic><topic>Fuels</topic><topic>Solid fuel processing (coal, coke, brown coal, peat, wood, etc.)</topic><topic>Theoretical studies. Data and constants. Metering</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Solomon, Peter R.</creatorcontrib><creatorcontrib>Hamblen, David G.</creatorcontrib><creatorcontrib>Serio, Michael A.</creatorcontrib><creatorcontrib>Yu, Zhen-Zhong</creatorcontrib><creatorcontrib>Charpenay, Sylvie</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>Fuel (Guildford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Solomon, Peter R.</au><au>Hamblen, David G.</au><au>Serio, Michael A.</au><au>Yu, Zhen-Zhong</au><au>Charpenay, Sylvie</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A characterization method and model for predicting coal conversion behaviour</atitle><jtitle>Fuel (Guildford)</jtitle><date>1993-04-01</date><risdate>1993</risdate><volume>72</volume><issue>4</issue><spage>469</spage><epage>488</epage><pages>469-488</pages><issn>0016-2361</issn><eissn>1873-7153</eissn><abstract>This paper considers the development of a predictive macromolecular network decomposition model for coal conversion which is based on a variety of modern analytical techniques for coal characterization. Six concepts which are the foundation of the functional group-depolymerization-vaporization-cross-linking (FG-DVC) model are considered:
1.
(1) The decomposition of functional group sources in the coal yields the light gas species in thermal decomposition. The amount and evolution kinetics can be measured by t.g.-FT-i.r., the functional group changes by FT-i.r. and n.m.r.
2.
(2) The decomposition of a macromolecular network yields tar and metaplast. The amount and kinetics of the tar evolution can be measured by t.g.-FT-i.r. and the molecular weight by f.i.m.s. The kinetics of metaplast formation and destruction can be determined by solvent extraction, by Gieseler plastometer measurements and by proton magnetic resonance thermal analysis (p.m.r.t.a.).
3.
(3) The molecular weight distribution of the metaplast depends on the network coordination number (average number of attachments on aromatic ring clusters). The coordination number can be determined by solvent swelling and n.m.r.
4.
(4) The network decomposition is controlled by bridge breaking. The number of bridges broken is limited by the available donatable hydrogen.
5.
(5) The network solidification is controlled by cross-linking. The changing cross-link density can be measured by solvent swelling and n.m.r. Cross-linking appears to occur with evolution of both CO
2 (before bridge breaking) and CH
4 (after bridge breaking). Thus low-rank coals (which evolve much CO
2) cross-link before bridge breaking and are thus thermosetting. High-volatile bituminous coals (which form little CO
2) undergo significant bridge breaking before cross-linking and become highly fluid. Weathering, which increases the CO
2 yield, causes increased cross-linking and lowers fluidity.
6.
(6) The evolution of tar is controlled by mass transport in which the tar molecules evaporate into the light gas or tar species and are carried out of the coal at rates proportional to their vapour pressure and the volume of light species. High pressures reduce the volume of light species and hence reduce the yield of heavy molecules with low vapour pressures. These changes can be studied with f.i.m.s. The paper describes how the coal kinetic and composition parameters are obtained by t.g.-FT-i.r., solvent swelling, solvent extraction and Gieseler plastometer data. The model is compared with a variety of experimental data in which heating rate, temperature and pressure are all varied. There is good agreement with theory for most of the data available from the authors' laboratory and in the literature.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/0016-2361(93)90106-C</doi><tpages>20</tpages></addata></record> |
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subjects | Applied sciences characterization coal Combustion of solid fuels Combustion. Flame conversion Energy Energy. Thermal use of fuels Exact sciences and technology Fuel processing. Carbochemistry and petrochemistry Fuels Solid fuel processing (coal, coke, brown coal, peat, wood, etc.) Theoretical studies. Data and constants. Metering |
title | A characterization method and model for predicting coal conversion behaviour |
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