A stainless steel multi-well plate (SS-MWP) for high-throughput Raman analysis of dilute solutions

  • Alan G. Ryder
  • , John De Vincentis
  • , Boyan Li
  • , Paul W. Ryan
  • , Narayana M.S. Sirimuthu
  • , Kirk J. Leister

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

22 Citations (Scopus)

Abstract

The use of Raman spectroscopy for the qualitative and quantitative analysis of dilute aqueous solutions is of interest to the biopharmaceutical manufacturing sector. However, the inherent weakness of the Raman effect, coupled with spectral variability due to spurious signals from sample holders, can produce significant problems for chemometric-based high-throughput assays. Therefore, there is a need for a multi-well sample holder that ensures robust and repeatable measurements, in particular from dilute aqueous solutions such as cell culture media. Here we demonstrate the efficacy of a novel, electropolished, stainless steel multi-well plate (SS-MWP) sample holder with 96 wells for dilute aqueous solution analysis. A comprehensive study of the spectroscopic behaviour was carried out and comparisons made with multi-well plates fabricated from polystyrene, polypropylene, and aluminium. A key factor in the validation studies is the use of intrinsically weak Raman scattering systems, e.g. water and dilute glucose solutions. The data collected show that the SS-MWPs are much superior in terms of robustness, resistance to chemical attack, and measurement reproducibility and as such are the ideal sample holders for Raman analysis of dilute solutions.

Original languageEnglish
Pages (from-to)1266-1275
Number of pages10
JournalJournal of Raman Spectroscopy
Volume41
Issue number10
DOIs
Publication statusPublished - Oct 2010

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • Aqueous solution
  • High throughput
  • Raman spectroscopy
  • Sample holder
  • Similarity analysis

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