Effect of Pressure, Particle Size, and Time on Optimizing Performance in Liquid Chromatography

Peter W. Carr* and Xiaoli Wang†
Department of Chemistry, University of Minnesota, 207 Pleasant Street, S.E., Minneapolis, Minnesota 55455
Dwight R. Stoll
Department of Chemistry, Gustavus Adolphus College, 800 West College Avenue, Saint Peter, Minnesota 56082
Anal. Chem., 2009, 81 (13), pp 5342–5353
DOI: 10.1021/ac9001244
Publication Date (Web): June 8, 2009
Copyright © 2009 American Chemical Society
* To whom correspondence should be addressed. E-mail: petecarr@chem.umn.edu., †

Current address: 1800 Concord Pike, Wilmington, DE 19850.

Surface Chemistry and Colloids

Abstract

Although the principles of optimization of high-performance liquid chromatography (HPLC) have a long history starting with the work of Giddings in the 1960s and continuing with work by Knox and Guiochon extending into the 1990s we continue to see statements that flatly contradict theory. A prominent example is the notion that optimum “performance”, as measured by plate count, is always obtained by operating conventional length columns (e.g., 5−15 cm) at eluent velocities corresponding to the minimum plate height in the van Deemter curve. In the past decade the introduction of “Poppe plots” by Poppe and “kinetic plots” by Desmet and others has simplified the selection of “optimum” conditions, but it is evident that many workers are not entirely comfortable with this framework. Here we derive a set of simple, yet accurate, equations that allow rapid calculation of the column length and eluent velocity that will give either the maximum plate count in a given time or a given plate count in the shortest time. Equations are developed for the optimum column length, eluent velocity, and thus plate count for both the cases when particle size is preselected and when particle size is optimized along with eluent velocity and column length. Although both of these situations have been previously considered the implications of the resulting equations have not been previously made explicit. Lack of full understanding of the consequences of the differences between these two cases is very important and responsible for many erroneous conclusions. The simple closed-form equations that result from this work complement the graphical, iterative approaches of Poppe and Desmet; the resulting compact framework allows practitioners to rapidly and effectively find the operating parameters needed to achieve a specific separation goal in the shortest time and to compare emerging technologies (e.g., high pressure, high temperature, and different particle types) in terms of their impact on achievable plate counts and speeds in HPLC. A Web-based calculator based on the equations presented here is now available (http://homepages.gac.edu/dstoll/calculators/optimize.html).

View: Full Text HTML | Hi-Res PDF | PDF w/ Links

Citing Articles

View all 3 citing articles

Citation data is made available by participants in CrossRef's Cited-by Linking service. For a more comprehensive list of citations to this article, users are encouraged to perform a search in SciFinder.

This article has been cited by 3 ACS Journal articles (3 most recent appear below).

Tools

SciFinder Links

SciFinder subscribers: Click to sign in | Not a SciFinder subscriber? Learn more at www.cas.org

Explore by:

History

  • Published In Issue July 01, 2009
  • Article ASAPJune 08, 2009
  • Received: January 19, 2009
    Accepted: March 24, 2009

Recommend & Share

  • Share on ACS NetworkACS Network
  • Add to FacebookFacebook
  • Tweet ThisTweet This
  • Add to CiteULikeCiteULike
  • Add to NewsvineNewsvine
  • Digg ThisDigg This
  • Add to DeliciousDelicious

Related Content

Other ACS content by these authors: