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Monte Carlo standardless approach for laser induced breakdown spectroscopy based on massive parallel graphic processing unit computing

  • The improved Monte-Carlo (MC) method for standard-less analysis in laser induced breakdown spectroscopy (LIBS) is presented. Concentrations in MC LIBS are found by fitting model-generated synthetic spectra to experimental spectra. The current version of MC LIBS is based on the graphic processing unit (GPU) computation and reduces the analysis time down to several seconds per spectrum/sample. The previous version of MC LIBS which was based on the central processing unit (CPU) computation requested unacceptably long analysis times of 10's minutes per spectrum/sample. The reduction of the computational time is achieved through the massively parallel computing on the GPU which embeds thousands of co-processors. It is shown that the number of iterations on the GPU exceeds that on the CPU by a factor > 1000 for the 5-dimentional parameter space and yet requires > 10-fold shorter computational time. The improved GPU-MC LIBS outperforms the CPU-MS LIBS in terms of accuracy, precision, andThe improved Monte-Carlo (MC) method for standard-less analysis in laser induced breakdown spectroscopy (LIBS) is presented. Concentrations in MC LIBS are found by fitting model-generated synthetic spectra to experimental spectra. The current version of MC LIBS is based on the graphic processing unit (GPU) computation and reduces the analysis time down to several seconds per spectrum/sample. The previous version of MC LIBS which was based on the central processing unit (CPU) computation requested unacceptably long analysis times of 10's minutes per spectrum/sample. The reduction of the computational time is achieved through the massively parallel computing on the GPU which embeds thousands of co-processors. It is shown that the number of iterations on the GPU exceeds that on the CPU by a factor > 1000 for the 5-dimentional parameter space and yet requires > 10-fold shorter computational time. The improved GPU-MC LIBS outperforms the CPU-MS LIBS in terms of accuracy, precision, and analysis time. The performance is tested on LIBS-spectra obtained from pelletized powders of metal oxides consisting of CaO, Fe2O3, MgO, and TiO2 that simulated by-products of steel industry, steel slags. It is demonstrated that GPU-based MC LIBS is capable of rapid multi-element analysis with relative error between 1 and 10's percent that is sufficient for industrial applications (e.g. steel slag analysis). The results of the improved GPU-based MC LIBS are positively compared to that of the CPU-based MC LIBS as well as to the results of the standard calibration-free (CF) LIBS based on the Boltzmann plot method.zeige mehrzeige weniger

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Metadaten
Autoren/innen:Alexandr Demidov, S. Eschlböck-Fuchs, A. Ya. Kazakov, Igor B. Gornushkin, P. J. Kolmhofer, J. D. Pedarnig, N. Huber, J. Heitz, Thomas Schmid, R. Rössler, Ulrich Panne
Dokumenttyp:Zeitschriftenartikel
Veröffentlichungsform:Verlagsliteratur
Sprache:Englisch
Titel des übergeordneten Werkes (Englisch):Spectrochimica Acta B
Jahr der Erstveröffentlichung:2016
Organisationseinheit der BAM:P Präsidium
1 Analytische Chemie; Referenzmaterialien
1 Analytische Chemie; Referenzmaterialien / 1.4 Prozessanalytik
1 Analytische Chemie; Referenzmaterialien / 1.9 Chemische und optische Sensorik
P Präsidium / P.0 Präsident und Vizepräsident
Verlag:Elsevier B.V.
Jahrgang/Band:125
Erste Seite:97
Letzte Seite:102
DDC-Klassifikation:Naturwissenschaften und Mathematik / Chemie / Analytische Chemie
Freie Schlagwörter:Calibration-free laser-induced breakdown spectroscopy; Monte Carlo simulation; Parallel computing; Post-breakdown laser induced plasma; Quaternary oxides
Themenfelder/Aktivitätsfelder der BAM:Analytical Sciences
Analytical Sciences / Zerstörungsfreie Prüfung und Spektroskopie
DOI:https://doi.org/10.1016/j.sab.2016.09.016
URL:http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS&DestLinkType=FullRecord;UT=WOS:000387526800010
Verfügbarkeit des Volltexts:Volltext-PDF im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:30.11.2016
Referierte Publikation:Ja
Datum der Eintragung als referierte Publikation:01.12.2016