Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 35,
  • Issue 6,
  • pp. 525-531
  • (1981)

ICP-AES as a Multiple Element Detector for Metal Chelates Separated by HPLC

Not Accessible

Your library or personal account may give you access

Abstract

ICP-AES was used for the simultaneous multiple element detection of trace metals species separated by high-pressure liquid chromatography (HPLC). The technique is demonstrated for the determination of nitrilotriacetic acid (NTA) and ethylenediaminetetraacetic acid (EDTA) chelates of copper, zinc, calcium, and magnesium. Multi-element chromatograms were obtained using a 32-channel polychromator programmed to perform a series of time-resolved intensity integrations. Data were retrieved channel-by-channel and plotted in histographic form. Comparison with UV absorbance and single-channel ICP-AES tracings reveals that the histograms reflect reliable chromatographic data. Linearity and precision of the system were found to be good in the 20 to 2000 ng range.

PDF Article
More Like This
Detection of lithium in breast milk and in situ elemental analysis of the mammary gland

Irfan Ahmed, Francis A. M. Manno, Sinai H. C. Manno, Yuanchao Liu, Yanpeng Zhang, and Condon Lau
Biomed. Opt. Express 9(9) 4184-4195 (2018)

Determination of trace heavy metal elements in aqueous solution using surface-enhanced laser-induced breakdown spectroscopy

Shixiang Ma, Yun Tang, Yuyang Ma, Yanwu Chu, Feng Chen, Zhenlin Hu, Zhihao Zhu, Lianbo Guo, Xiaoyan Zeng, and Yongfeng Lu
Opt. Express 27(10) 15091-15099 (2019)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.