Multiscale orthogonal matching pursuit algorithm combined with peak model for interpreting ion mobility spectra and achieving quantitative analysis
Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zhang, Genwei [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020transfer abstract |
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| Schlagwörter: |
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| Umfang: |
9 |
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| Übergeordnetes Werk: |
Enthalten in: Neuro-Brucellosis - Gouider, R. ELSEVIER, 2015, an international journal devoted to all branches of analytical chemistry, Amsterdam |
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| Übergeordnetes Werk: |
volume:1110 ; year:2020 ; day:8 ; month:05 ; pages:181-189 ; extent:9 |
| Links: |
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| DOI / URN: |
10.1016/j.aca.2020.03.010 |
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ELV049943146 |
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| 520 | |a Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. | ||
| 520 | |a Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. | ||
| 650 | 7 | |a Ion mobility spectrometry |2 Elsevier | |
| 650 | 7 | |a Multiscale orthogonal matching pursuit |2 Elsevier | |
| 650 | 7 | |a Peak model |2 Elsevier | |
| 650 | 7 | |a Quantitative analysis |2 Elsevier | |
| 700 | 1 | |a Peng, Silong |4 oth | |
| 700 | 1 | |a Xie, Qiong |4 oth | |
| 700 | 1 | |a Yang, Liu |4 oth | |
| 700 | 1 | |a Cao, Shuya |4 oth | |
| 700 | 1 | |a Huang, Qibin |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Gouider, R. ELSEVIER |t Neuro-Brucellosis |d 2015 |d an international journal devoted to all branches of analytical chemistry |g Amsterdam |w (DE-627)ELV013501887 |
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10.1016/j.aca.2020.03.010 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000969.pica (DE-627)ELV049943146 (ELSEVIER)S0003-2670(20)30317-2 DE-627 ger DE-627 rakwb eng 610 VZ 540 VZ 35.10 bkl Zhang, Genwei verfasserin aut Multiscale orthogonal matching pursuit algorithm combined with peak model for interpreting ion mobility spectra and achieving quantitative analysis 2020transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. Ion mobility spectrometry Elsevier Multiscale orthogonal matching pursuit Elsevier Peak model Elsevier Quantitative analysis Elsevier Peng, Silong oth Xie, Qiong oth Yang, Liu oth Cao, Shuya oth Huang, Qibin oth Enthalten in Elsevier Science Gouider, R. ELSEVIER Neuro-Brucellosis 2015 an international journal devoted to all branches of analytical chemistry Amsterdam (DE-627)ELV013501887 volume:1110 year:2020 day:8 month:05 pages:181-189 extent:9 https://doi.org/10.1016/j.aca.2020.03.010 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 GBV_ILN_120 35.10 Physikalische Chemie: Allgemeines VZ AR 1110 2020 8 0508 181-189 9 |
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10.1016/j.aca.2020.03.010 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000969.pica (DE-627)ELV049943146 (ELSEVIER)S0003-2670(20)30317-2 DE-627 ger DE-627 rakwb eng 610 VZ 540 VZ 35.10 bkl Zhang, Genwei verfasserin aut Multiscale orthogonal matching pursuit algorithm combined with peak model for interpreting ion mobility spectra and achieving quantitative analysis 2020transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. Ion mobility spectrometry Elsevier Multiscale orthogonal matching pursuit Elsevier Peak model Elsevier Quantitative analysis Elsevier Peng, Silong oth Xie, Qiong oth Yang, Liu oth Cao, Shuya oth Huang, Qibin oth Enthalten in Elsevier Science Gouider, R. ELSEVIER Neuro-Brucellosis 2015 an international journal devoted to all branches of analytical chemistry Amsterdam (DE-627)ELV013501887 volume:1110 year:2020 day:8 month:05 pages:181-189 extent:9 https://doi.org/10.1016/j.aca.2020.03.010 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 GBV_ILN_120 35.10 Physikalische Chemie: Allgemeines VZ AR 1110 2020 8 0508 181-189 9 |
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10.1016/j.aca.2020.03.010 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000969.pica (DE-627)ELV049943146 (ELSEVIER)S0003-2670(20)30317-2 DE-627 ger DE-627 rakwb eng 610 VZ 540 VZ 35.10 bkl Zhang, Genwei verfasserin aut Multiscale orthogonal matching pursuit algorithm combined with peak model for interpreting ion mobility spectra and achieving quantitative analysis 2020transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. Ion mobility spectrometry Elsevier Multiscale orthogonal matching pursuit Elsevier Peak model Elsevier Quantitative analysis Elsevier Peng, Silong oth Xie, Qiong oth Yang, Liu oth Cao, Shuya oth Huang, Qibin oth Enthalten in Elsevier Science Gouider, R. ELSEVIER Neuro-Brucellosis 2015 an international journal devoted to all branches of analytical chemistry Amsterdam (DE-627)ELV013501887 volume:1110 year:2020 day:8 month:05 pages:181-189 extent:9 https://doi.org/10.1016/j.aca.2020.03.010 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 GBV_ILN_120 35.10 Physikalische Chemie: Allgemeines VZ AR 1110 2020 8 0508 181-189 9 |
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10.1016/j.aca.2020.03.010 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000969.pica (DE-627)ELV049943146 (ELSEVIER)S0003-2670(20)30317-2 DE-627 ger DE-627 rakwb eng 610 VZ 540 VZ 35.10 bkl Zhang, Genwei verfasserin aut Multiscale orthogonal matching pursuit algorithm combined with peak model for interpreting ion mobility spectra and achieving quantitative analysis 2020transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. Ion mobility spectrometry Elsevier Multiscale orthogonal matching pursuit Elsevier Peak model Elsevier Quantitative analysis Elsevier Peng, Silong oth Xie, Qiong oth Yang, Liu oth Cao, Shuya oth Huang, Qibin oth Enthalten in Elsevier Science Gouider, R. ELSEVIER Neuro-Brucellosis 2015 an international journal devoted to all branches of analytical chemistry Amsterdam (DE-627)ELV013501887 volume:1110 year:2020 day:8 month:05 pages:181-189 extent:9 https://doi.org/10.1016/j.aca.2020.03.010 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 GBV_ILN_120 35.10 Physikalische Chemie: Allgemeines VZ AR 1110 2020 8 0508 181-189 9 |
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10.1016/j.aca.2020.03.010 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000969.pica (DE-627)ELV049943146 (ELSEVIER)S0003-2670(20)30317-2 DE-627 ger DE-627 rakwb eng 610 VZ 540 VZ 35.10 bkl Zhang, Genwei verfasserin aut Multiscale orthogonal matching pursuit algorithm combined with peak model for interpreting ion mobility spectra and achieving quantitative analysis 2020transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. Ion mobility spectrometry Elsevier Multiscale orthogonal matching pursuit Elsevier Peak model Elsevier Quantitative analysis Elsevier Peng, Silong oth Xie, Qiong oth Yang, Liu oth Cao, Shuya oth Huang, Qibin oth Enthalten in Elsevier Science Gouider, R. ELSEVIER Neuro-Brucellosis 2015 an international journal devoted to all branches of analytical chemistry Amsterdam (DE-627)ELV013501887 volume:1110 year:2020 day:8 month:05 pages:181-189 extent:9 https://doi.org/10.1016/j.aca.2020.03.010 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 GBV_ILN_120 35.10 Physikalische Chemie: Allgemeines VZ AR 1110 2020 8 0508 181-189 9 |
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However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. 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Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. 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multiscale orthogonal matching pursuit algorithm combined with peak model for interpreting ion mobility spectra and achieving quantitative analysis |
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Multiscale orthogonal matching pursuit algorithm combined with peak model for interpreting ion mobility spectra and achieving quantitative analysis |
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Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. |
| abstractGer |
Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. |
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Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. |
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Multiscale orthogonal matching pursuit algorithm combined with peak model for interpreting ion mobility spectra and achieving quantitative analysis |
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