Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 59,
  • Issue 12,
  • pp. 1470-1479
  • (2005)

Optimization of Instrumental Parameters of a Near-Field Thermal-Lens Detector for Capillary Electrophoresis

Not Accessible

Your library or personal account may give you access

Abstract

The optical scheme of a near-field dual-beam mode-mismatched thermal-lens detector for capillary electrophoresis with a crossed-beam configuration employing a multimode HeCd laser (325 nm) as an excitation source was optimized. It is shown that a multimode laser can be successfully used as an excitation source in thermal lensing with minimal deviations in thermal responses from Gaussian excitation sources. An equation for diffraction thermal-lens theory for near-field measurements is deduced, and the experimental results agree with the deduced equation. The temperature rise in the capillary was estimated, and the exponential decrease of the signal with time for static conditions and low flow velocities was explained. The optimum configuration of the detector from the viewpoint of the maximum sensitivity and beam sizes was found. The detector provides a significant improvement in the detection limits for model compounds absorbing at 325 nm (nitrophenols) compared to the results obtained with a commercial absorbance detector operating at the same wavelength.

PDF Article
More Like This
Terahertz-capillary electrophoresis (THz-CE) for direct detection of separated substances in solutions

Keiko Kitagishi, Takayuki Kawai, Masayoshi Tonouchi, and Kazunori Serita
Opt. Mater. Express 14(2) 472-482 (2024)

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.