Non-analyte signals and supervised learning to evaluate matrix effects and predict analyte recoveries in inductively coupled plasma optical emission spectrometry-Reference-Cited by-同舟云学术

Non-analyte signals and supervised learning to evaluate matrix effects and predict analyte recoveries in inductively coupled plasma optical emission spectrometry

Published:2020 Issue:4 Volume:35 Page:679-692
ISSN:0267-9477
Container-title:Journal of Analytical Atomic Spectrometry
language:en
Short-container-title:J. Anal. At. Spectrom.

Author:

Carter Jake A.¹²³⁴^ORCID,Sloop John T.¹²³⁴^ORCID,Harville Tina⁵⁶⁴,Jones Bradley T.¹²³⁴,Donati George L.¹²³⁴^ORCID

Affiliation:

1. Department of Chemistry

2. Wake Forest University

3. Winston-Salem

4. USA

5. Agilent Technologies

6. Cary

Abstract

Plasma species of Ar, H and O are monitored and used for modeling and for correcting signal bias caused by high concentrations of easily ionizable elements in ICP OES.

Funder

Wake Forest University

Publisher

Royal Society of Chemistry (RSC)

Subject

Spectroscopy,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2020/JA/D0JA00007H

Reference83 articles.

1. X. Hou , R. S.Amais , B. T.Jones and G. L.Donati , Inductively coupled plasma optical emission spectrometry , in Encyclopedia of Analytical Chemistry , ed. R.A. Meyers , Wiley , Chichester , 2016

2. A. Montaser , Inductively coupled plasmas in analytical atomic spectrometry , VCH Publishers , New York , 2nd edn, 1992

3. A. Montaser , Inductively coupled plasma mass spectrometry , J. Wiley , New York , 1st edn, 1998

4. Is it still possible, necessary and beneficial to perform research in ICP-atomic emission spectrometry?

5. Recent advances in inductively coupled plasma optical emission spectrometry

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