Enhancing chemical analysis with signal derivatization using simple available software packages
Derivative techniques for analytical signal processing are useful for solving some noise and signal resolution problems in various fields of study such as titrimetry, spectrophotometry, chromatography and electrochemistry. The broad use of these techniques, however, is often limited by costly inflex...
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th-cmuir.6653943832-609622018-09-10T04:02:02Z Enhancing chemical analysis with signal derivatization using simple available software packages Kritsana Jitmanee Jaroon Jakmunee Somchai Lapanantnoppakhun Sunanta Wangkarn Norio Teshima Tadao Sakai Gary D. Christian Kate Grudpan Chemistry Derivative techniques for analytical signal processing are useful for solving some noise and signal resolution problems in various fields of study such as titrimetry, spectrophotometry, chromatography and electrochemistry. The broad use of these techniques, however, is often limited by costly inflexible built-in software packages in commercial analytical instruments. We propose here the application of commercial simple software packages such as Microsoft® Excel and Microcal Origin for signal smoothing and fitting, and for obtaining derivative analytical signals in batch and flow-based analyses, including potentiometric titration, spectrophotometry, chromatography, voltammetry and sequential injection analysis (SIA). The worldwide (especially Excel) software packages are easy-to-use for less experienced users and have also capabilities for advanced users, and therefore employing such packages can result in expansion of useful derivative techniques. We demonstrate application of the available package-aided derivative capabilities for enhancing some chemical analyses, including potentiometric acid-base titration, Bradford assay of protein, chromatographic separation of ajmaline and reserpine and anodic stripping voltammetry of copper. The derivative signals from smoothed and fitted curves offer better accuracy and precision, even for non-resolving peaks and tailing peaks. In some cases, the optimization of experimental conditions is not further required, which can lead to fast method development. © 2007. 2018-09-10T04:02:02Z 2018-09-10T04:02:02Z 2007-08-01 Journal 0026265X 2-s2.0-34249300079 10.1016/j.microc.2007.03.005 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=34249300079&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/60962 |
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Chemistry Kritsana Jitmanee Jaroon Jakmunee Somchai Lapanantnoppakhun Sunanta Wangkarn Norio Teshima Tadao Sakai Gary D. Christian Kate Grudpan Enhancing chemical analysis with signal derivatization using simple available software packages |
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Derivative techniques for analytical signal processing are useful for solving some noise and signal resolution problems in various fields of study such as titrimetry, spectrophotometry, chromatography and electrochemistry. The broad use of these techniques, however, is often limited by costly inflexible built-in software packages in commercial analytical instruments. We propose here the application of commercial simple software packages such as Microsoft® Excel and Microcal Origin for signal smoothing and fitting, and for obtaining derivative analytical signals in batch and flow-based analyses, including potentiometric titration, spectrophotometry, chromatography, voltammetry and sequential injection analysis (SIA). The worldwide (especially Excel) software packages are easy-to-use for less experienced users and have also capabilities for advanced users, and therefore employing such packages can result in expansion of useful derivative techniques. We demonstrate application of the available package-aided derivative capabilities for enhancing some chemical analyses, including potentiometric acid-base titration, Bradford assay of protein, chromatographic separation of ajmaline and reserpine and anodic stripping voltammetry of copper. The derivative signals from smoothed and fitted curves offer better accuracy and precision, even for non-resolving peaks and tailing peaks. In some cases, the optimization of experimental conditions is not further required, which can lead to fast method development. © 2007. |
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Journal |
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Kritsana Jitmanee Jaroon Jakmunee Somchai Lapanantnoppakhun Sunanta Wangkarn Norio Teshima Tadao Sakai Gary D. Christian Kate Grudpan |
author_facet |
Kritsana Jitmanee Jaroon Jakmunee Somchai Lapanantnoppakhun Sunanta Wangkarn Norio Teshima Tadao Sakai Gary D. Christian Kate Grudpan |
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Kritsana Jitmanee |
title |
Enhancing chemical analysis with signal derivatization using simple available software packages |
title_short |
Enhancing chemical analysis with signal derivatization using simple available software packages |
title_full |
Enhancing chemical analysis with signal derivatization using simple available software packages |
title_fullStr |
Enhancing chemical analysis with signal derivatization using simple available software packages |
title_full_unstemmed |
Enhancing chemical analysis with signal derivatization using simple available software packages |
title_sort |
enhancing chemical analysis with signal derivatization using simple available software packages |
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2018 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=34249300079&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/60962 |
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