Comparability of heavy mineral data – The first interlaboratory round robin test

Detalhes bibliográficos
Autor(a) principal: Dunkl, István
Data de Publicação: 2020
Outros Autores: von Eynatten, Hilmar, Andò, Sergio, Lünsdorf, Keno, Morton, Andrew, Alexander, Bruce, Aradi, László, Augustsson, Carita, Bahlburg, Heinrich, Barbarano, Marta, Benedictus, Aukje, Berndt, Jasper, Bitz, Irene, Boekhout, Flora, Breitfeld, Tim, Cascalho, João, Costa, Pedro J.M., Ekwenye, Ogechi, Fehér, Kristóf, Flores-Aqueveque, Valentina, Führing, Philipp, Giannini, Paulo, Goetz, Walter, Guedes, Carlos, Gyurica, György, Hennig-Breitfeld, Juliane, Hülscher, Julian, Jafarzadeh, Mahdi, Jagodziński, Robert, Józsa, Sándor, Kelemen, Péter, Keulen, Nynke, Kovacic, Marijan, Liebermann, Christof, Limonta, Mara, Lužar-Oberiter, Borna, Markovic, Frane, Melcher, Frank, Miklós, Dóra Georgina, Moghalu, Ogechukwu, Mounteney, Ian, Nascimento, Daniel, Novaković, Tea, Obbágy, Gabriella, Oehlke, Mathias, Omma, Jenny, Onuk, Peter, Passchier, Sandra, Pfaff, Katharina, Lincoñir, Luisa Pinto, Power, Matthew, Resentini, Alberto, Sági, Tamás, Salata, Dorota, Salgueiro, Rute, Schönig, Jan, Sitnikova, Maria, Sternal, Beata, Szakmány, György, Szokaluk, Monika, Thamó-Bozsó, Edit, Tóth, Ágoston, Tremblay, Jonathan, Verhaegen, Jasper, Villaseñor, Tania, Wagreich, Michael, Wolf, Anna, Yoshida, Kohki
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da Universidade Federal do Ceará (UFC)
Texto Completo: http://www.repositorio.ufc.br/handle/riufc/64858
Resumo: Heavy minerals are typically rare but important components of siliciclastic sediments and rocks. Their abundance, proportions, and variability carry valuable information on source rocks, climatic, environmental and transport conditions between source to sink, and diagenetic processes. They are important for practical purposes such as prospecting for mineral resources or the correlation and interpretation of geologic reservoirs. Despite the extensive use of heavy mineral analysis in sedimentary petrography and quite diverse methods for quantifying heavy mineral assemblages, there has never been a systematic comparison of results obtained by different methods and/or operators. This study provides the first interlaboratory test of heavy mineral analysis. Two synthetic heavy mineral samples were prepared with considerably contrasting compositions intended to resemble natural samples. The contributors were requested to provide (i) metadata describing methods, measurement conditions and experience of the operators and (ii) results tables with mineral species and grain counts. One hundred thirty analyses of the two samples were performed by 67 contributors, encompassing both classical microscopic analyses and data obtained by emerging automated techniques based on electron-beam chemical analysis or Raman spectroscopy. Because relatively low numbers of mineral counts (N) are typical for optical analyses while automated techniques allow for high N, the results vary considerably with respect to the Poisson uncertainty of the counting statistics. Therefore, standard methods used in evaluation of round robin tests are not feasible. In our case the ‘true’ compositions of the test samples are not known. Three methods have been applied to determine possible reference values: (i) the initially measured weight percentages, (ii) calculation of grain percentages using estimates of grain volumes and densities, and (iii) the best-match average calculated from the most reliable analyses following multiple, pragmatic and robust criteria. The range of these three values is taken as best approximation of the ‘true’ composition. The reported grain percentages were evaluated according to (i) their overall scatter relative to the most likely composition, (ii) the number of identified components that were part of the test samples, (iii) the total amount of mistakenly identified mineral grains that were actually not added to the samples, and (iv) the number of major components, which match the reference values with 95% confidence. Results indicate that the overall comparability of the analyses is reasonable. However, there are several issues with respect to methods and/or operators. Optical methods yield the poorest results with respect to the scatter of the data. This, however, is not considered inherent to the method as demonstrated by a significant number of optical analyses fulfilling the criteria for the best-match average. Training of the operators is thus considered paramount for optical analyses. Electron-beam methods yield satisfactory results, but problems in the identification of polymorphs and the discrimination of chain silicates are evident. Labs refining their electron-beam results by optical analysis practically tackle this issue. Raman methods yield the best results as indicated by the highest number of major components correctly quantified with 95% confidence and the fact that all laboratories and operators fulfil the criteria for the best-match average. However, a number of problems must be solved before the full potential of the automated high-throughput techniques in heavy mineral analysis can be achieved.
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spelling Comparability of heavy mineral data – The first interlaboratory round robin testHeavy mineral analysisProvenanceSEM-EDXRaman spectroscopyInterlaboratory comparisonHeavy minerals are typically rare but important components of siliciclastic sediments and rocks. Their abundance, proportions, and variability carry valuable information on source rocks, climatic, environmental and transport conditions between source to sink, and diagenetic processes. They are important for practical purposes such as prospecting for mineral resources or the correlation and interpretation of geologic reservoirs. Despite the extensive use of heavy mineral analysis in sedimentary petrography and quite diverse methods for quantifying heavy mineral assemblages, there has never been a systematic comparison of results obtained by different methods and/or operators. This study provides the first interlaboratory test of heavy mineral analysis. Two synthetic heavy mineral samples were prepared with considerably contrasting compositions intended to resemble natural samples. The contributors were requested to provide (i) metadata describing methods, measurement conditions and experience of the operators and (ii) results tables with mineral species and grain counts. One hundred thirty analyses of the two samples were performed by 67 contributors, encompassing both classical microscopic analyses and data obtained by emerging automated techniques based on electron-beam chemical analysis or Raman spectroscopy. Because relatively low numbers of mineral counts (N) are typical for optical analyses while automated techniques allow for high N, the results vary considerably with respect to the Poisson uncertainty of the counting statistics. Therefore, standard methods used in evaluation of round robin tests are not feasible. In our case the ‘true’ compositions of the test samples are not known. Three methods have been applied to determine possible reference values: (i) the initially measured weight percentages, (ii) calculation of grain percentages using estimates of grain volumes and densities, and (iii) the best-match average calculated from the most reliable analyses following multiple, pragmatic and robust criteria. The range of these three values is taken as best approximation of the ‘true’ composition. The reported grain percentages were evaluated according to (i) their overall scatter relative to the most likely composition, (ii) the number of identified components that were part of the test samples, (iii) the total amount of mistakenly identified mineral grains that were actually not added to the samples, and (iv) the number of major components, which match the reference values with 95% confidence. Results indicate that the overall comparability of the analyses is reasonable. However, there are several issues with respect to methods and/or operators. Optical methods yield the poorest results with respect to the scatter of the data. This, however, is not considered inherent to the method as demonstrated by a significant number of optical analyses fulfilling the criteria for the best-match average. Training of the operators is thus considered paramount for optical analyses. Electron-beam methods yield satisfactory results, but problems in the identification of polymorphs and the discrimination of chain silicates are evident. Labs refining their electron-beam results by optical analysis practically tackle this issue. Raman methods yield the best results as indicated by the highest number of major components correctly quantified with 95% confidence and the fact that all laboratories and operators fulfil the criteria for the best-match average. However, a number of problems must be solved before the full potential of the automated high-throughput techniques in heavy mineral analysis can be achieved.Earth-Science Reviews2022-04-05T19:06:25Z2022-04-05T19:06:25Z2020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfDUNKL, István et al. Comparability of heavy mineral data – The first interlaboratory round robin test. Earth-Science Reviews, [s. l.], v. 211, n. 103210, p. 1-27, 2020.0012-8252http://www.repositorio.ufc.br/handle/riufc/64858Dunkl, Istvánvon Eynatten, HilmarAndò, SergioLünsdorf, KenoMorton, AndrewAlexander, BruceAradi, LászlóAugustsson, CaritaBahlburg, HeinrichBarbarano, MartaBenedictus, AukjeBerndt, JasperBitz, IreneBoekhout, FloraBreitfeld, TimCascalho, JoãoCosta, Pedro J.M.Ekwenye, OgechiFehér, KristófFlores-Aqueveque, ValentinaFühring, PhilippGiannini, PauloGoetz, WalterGuedes, CarlosGyurica, GyörgyHennig-Breitfeld, JulianeHülscher, JulianJafarzadeh, MahdiJagodziński, RobertJózsa, SándorKelemen, PéterKeulen, NynkeKovacic, MarijanLiebermann, ChristofLimonta, MaraLužar-Oberiter, BornaMarkovic, FraneMelcher, FrankMiklós, Dóra GeorginaMoghalu, OgechukwuMounteney, IanNascimento, DanielNovaković, TeaObbágy, GabriellaOehlke, MathiasOmma, JennyOnuk, PeterPasschier, SandraPfaff, KatharinaLincoñir, Luisa PintoPower, MatthewResentini, AlbertoSági, TamásSalata, DorotaSalgueiro, RuteSchönig, JanSitnikova, MariaSternal, BeataSzakmány, GyörgySzokaluk, MonikaThamó-Bozsó, EditTóth, ÁgostonTremblay, JonathanVerhaegen, JasperVillaseñor, TaniaWagreich, MichaelWolf, AnnaYoshida, Kohkiinfo:eu-repo/semantics/openAccessengreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFC2023-10-10T19:21:54Zoai:repositorio.ufc.br:riufc/64858Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2023-10-10T19:21:54Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false
dc.title.none.fl_str_mv Comparability of heavy mineral data – The first interlaboratory round robin test
title Comparability of heavy mineral data – The first interlaboratory round robin test
spellingShingle Comparability of heavy mineral data – The first interlaboratory round robin test
Dunkl, István
Heavy mineral analysis
Provenance
SEM-EDX
Raman spectroscopy
Interlaboratory comparison
title_short Comparability of heavy mineral data – The first interlaboratory round robin test
title_full Comparability of heavy mineral data – The first interlaboratory round robin test
title_fullStr Comparability of heavy mineral data – The first interlaboratory round robin test
title_full_unstemmed Comparability of heavy mineral data – The first interlaboratory round robin test
title_sort Comparability of heavy mineral data – The first interlaboratory round robin test
author Dunkl, István
author_facet Dunkl, István
von Eynatten, Hilmar
Andò, Sergio
Lünsdorf, Keno
Morton, Andrew
Alexander, Bruce
Aradi, László
Augustsson, Carita
Bahlburg, Heinrich
Barbarano, Marta
Benedictus, Aukje
Berndt, Jasper
Bitz, Irene
Boekhout, Flora
Breitfeld, Tim
Cascalho, João
Costa, Pedro J.M.
Ekwenye, Ogechi
Fehér, Kristóf
Flores-Aqueveque, Valentina
Führing, Philipp
Giannini, Paulo
Goetz, Walter
Guedes, Carlos
Gyurica, György
Hennig-Breitfeld, Juliane
Hülscher, Julian
Jafarzadeh, Mahdi
Jagodziński, Robert
Józsa, Sándor
Kelemen, Péter
Keulen, Nynke
Kovacic, Marijan
Liebermann, Christof
Limonta, Mara
Lužar-Oberiter, Borna
Markovic, Frane
Melcher, Frank
Miklós, Dóra Georgina
Moghalu, Ogechukwu
Mounteney, Ian
Nascimento, Daniel
Novaković, Tea
Obbágy, Gabriella
Oehlke, Mathias
Omma, Jenny
Onuk, Peter
Passchier, Sandra
Pfaff, Katharina
Lincoñir, Luisa Pinto
Power, Matthew
Resentini, Alberto
Sági, Tamás
Salata, Dorota
Salgueiro, Rute
Schönig, Jan
Sitnikova, Maria
Sternal, Beata
Szakmány, György
Szokaluk, Monika
Thamó-Bozsó, Edit
Tóth, Ágoston
Tremblay, Jonathan
Verhaegen, Jasper
Villaseñor, Tania
Wagreich, Michael
Wolf, Anna
Yoshida, Kohki
author_role author
author2 von Eynatten, Hilmar
Andò, Sergio
Lünsdorf, Keno
Morton, Andrew
Alexander, Bruce
Aradi, László
Augustsson, Carita
Bahlburg, Heinrich
Barbarano, Marta
Benedictus, Aukje
Berndt, Jasper
Bitz, Irene
Boekhout, Flora
Breitfeld, Tim
Cascalho, João
Costa, Pedro J.M.
Ekwenye, Ogechi
Fehér, Kristóf
Flores-Aqueveque, Valentina
Führing, Philipp
Giannini, Paulo
Goetz, Walter
Guedes, Carlos
Gyurica, György
Hennig-Breitfeld, Juliane
Hülscher, Julian
Jafarzadeh, Mahdi
Jagodziński, Robert
Józsa, Sándor
Kelemen, Péter
Keulen, Nynke
Kovacic, Marijan
Liebermann, Christof
Limonta, Mara
Lužar-Oberiter, Borna
Markovic, Frane
Melcher, Frank
Miklós, Dóra Georgina
Moghalu, Ogechukwu
Mounteney, Ian
Nascimento, Daniel
Novaković, Tea
Obbágy, Gabriella
Oehlke, Mathias
Omma, Jenny
Onuk, Peter
Passchier, Sandra
Pfaff, Katharina
Lincoñir, Luisa Pinto
Power, Matthew
Resentini, Alberto
Sági, Tamás
Salata, Dorota
Salgueiro, Rute
Schönig, Jan
Sitnikova, Maria
Sternal, Beata
Szakmány, György
Szokaluk, Monika
Thamó-Bozsó, Edit
Tóth, Ágoston
Tremblay, Jonathan
Verhaegen, Jasper
Villaseñor, Tania
Wagreich, Michael
Wolf, Anna
Yoshida, Kohki
author2_role author
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author
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author
author
author
author
author
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author
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author
author
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author
author
author
author
author
author
author
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author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
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dc.contributor.author.fl_str_mv Dunkl, István
von Eynatten, Hilmar
Andò, Sergio
Lünsdorf, Keno
Morton, Andrew
Alexander, Bruce
Aradi, László
Augustsson, Carita
Bahlburg, Heinrich
Barbarano, Marta
Benedictus, Aukje
Berndt, Jasper
Bitz, Irene
Boekhout, Flora
Breitfeld, Tim
Cascalho, João
Costa, Pedro J.M.
Ekwenye, Ogechi
Fehér, Kristóf
Flores-Aqueveque, Valentina
Führing, Philipp
Giannini, Paulo
Goetz, Walter
Guedes, Carlos
Gyurica, György
Hennig-Breitfeld, Juliane
Hülscher, Julian
Jafarzadeh, Mahdi
Jagodziński, Robert
Józsa, Sándor
Kelemen, Péter
Keulen, Nynke
Kovacic, Marijan
Liebermann, Christof
Limonta, Mara
Lužar-Oberiter, Borna
Markovic, Frane
Melcher, Frank
Miklós, Dóra Georgina
Moghalu, Ogechukwu
Mounteney, Ian
Nascimento, Daniel
Novaković, Tea
Obbágy, Gabriella
Oehlke, Mathias
Omma, Jenny
Onuk, Peter
Passchier, Sandra
Pfaff, Katharina
Lincoñir, Luisa Pinto
Power, Matthew
Resentini, Alberto
Sági, Tamás
Salata, Dorota
Salgueiro, Rute
Schönig, Jan
Sitnikova, Maria
Sternal, Beata
Szakmány, György
Szokaluk, Monika
Thamó-Bozsó, Edit
Tóth, Ágoston
Tremblay, Jonathan
Verhaegen, Jasper
Villaseñor, Tania
Wagreich, Michael
Wolf, Anna
Yoshida, Kohki
dc.subject.por.fl_str_mv Heavy mineral analysis
Provenance
SEM-EDX
Raman spectroscopy
Interlaboratory comparison
topic Heavy mineral analysis
Provenance
SEM-EDX
Raman spectroscopy
Interlaboratory comparison
description Heavy minerals are typically rare but important components of siliciclastic sediments and rocks. Their abundance, proportions, and variability carry valuable information on source rocks, climatic, environmental and transport conditions between source to sink, and diagenetic processes. They are important for practical purposes such as prospecting for mineral resources or the correlation and interpretation of geologic reservoirs. Despite the extensive use of heavy mineral analysis in sedimentary petrography and quite diverse methods for quantifying heavy mineral assemblages, there has never been a systematic comparison of results obtained by different methods and/or operators. This study provides the first interlaboratory test of heavy mineral analysis. Two synthetic heavy mineral samples were prepared with considerably contrasting compositions intended to resemble natural samples. The contributors were requested to provide (i) metadata describing methods, measurement conditions and experience of the operators and (ii) results tables with mineral species and grain counts. One hundred thirty analyses of the two samples were performed by 67 contributors, encompassing both classical microscopic analyses and data obtained by emerging automated techniques based on electron-beam chemical analysis or Raman spectroscopy. Because relatively low numbers of mineral counts (N) are typical for optical analyses while automated techniques allow for high N, the results vary considerably with respect to the Poisson uncertainty of the counting statistics. Therefore, standard methods used in evaluation of round robin tests are not feasible. In our case the ‘true’ compositions of the test samples are not known. Three methods have been applied to determine possible reference values: (i) the initially measured weight percentages, (ii) calculation of grain percentages using estimates of grain volumes and densities, and (iii) the best-match average calculated from the most reliable analyses following multiple, pragmatic and robust criteria. The range of these three values is taken as best approximation of the ‘true’ composition. The reported grain percentages were evaluated according to (i) their overall scatter relative to the most likely composition, (ii) the number of identified components that were part of the test samples, (iii) the total amount of mistakenly identified mineral grains that were actually not added to the samples, and (iv) the number of major components, which match the reference values with 95% confidence. Results indicate that the overall comparability of the analyses is reasonable. However, there are several issues with respect to methods and/or operators. Optical methods yield the poorest results with respect to the scatter of the data. This, however, is not considered inherent to the method as demonstrated by a significant number of optical analyses fulfilling the criteria for the best-match average. Training of the operators is thus considered paramount for optical analyses. Electron-beam methods yield satisfactory results, but problems in the identification of polymorphs and the discrimination of chain silicates are evident. Labs refining their electron-beam results by optical analysis practically tackle this issue. Raman methods yield the best results as indicated by the highest number of major components correctly quantified with 95% confidence and the fact that all laboratories and operators fulfil the criteria for the best-match average. However, a number of problems must be solved before the full potential of the automated high-throughput techniques in heavy mineral analysis can be achieved.
publishDate 2020
dc.date.none.fl_str_mv 2020
2022-04-05T19:06:25Z
2022-04-05T19:06:25Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv DUNKL, István et al. Comparability of heavy mineral data – The first interlaboratory round robin test. Earth-Science Reviews, [s. l.], v. 211, n. 103210, p. 1-27, 2020.
0012-8252
http://www.repositorio.ufc.br/handle/riufc/64858
identifier_str_mv DUNKL, István et al. Comparability of heavy mineral data – The first interlaboratory round robin test. Earth-Science Reviews, [s. l.], v. 211, n. 103210, p. 1-27, 2020.
0012-8252
url http://www.repositorio.ufc.br/handle/riufc/64858
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Earth-Science Reviews
publisher.none.fl_str_mv Earth-Science Reviews
dc.source.none.fl_str_mv reponame:Repositório Institucional da Universidade Federal do Ceará (UFC)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
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reponame_str Repositório Institucional da Universidade Federal do Ceará (UFC)
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repository.name.fl_str_mv Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)
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