Literature DB >> 19339630

Calculation of the equilibrium pH in a multiple-buffered aqueous solution based on partitioning of proton buffering: a new predictive formula.

Minhtri K Nguyen1, Liyo Kao, Ira Kurtz.   

Abstract

Upon the addition of protons to an aqueous solution containing multiple buffers, the final H+ concentration ([H+]) at equilibrium is determined by the partitioning of added H+ among the various buffer components. In the analysis of acid-base chemistry, the Henderson-Hasselbalch equation and the Stewart strong ion formulation can only describe (rather than predict) the equilibrium pH following a proton load since these formulas calculate the equilibrium pH only when the reactant concentrations at equilibrium(1) 1The term "equilibrium" refers to the steady state proton and reactant concentrations when the buffering of excess protons by the various buffers is complete. are already known. In this regard, it is simpler to directly measure the equilibrium pH rather than measure the equilibrium reactant concentrations to calculate the equilibrium pH. As these formulas cannot predict the final equilibrium [H+] following a proton load to a multiple-buffered aqueous solution, we developed a new quantitative approach for predicting the equilibrium [H+] that is based on the preequilibrium(2)2 The term "preequilibrium" refers to the initial proton and reactant concentrations immediately upon addition of protons and before the buffering of excess protons by the various buffers. concentrations of all buffers in an aqueous solution. The mathematical model used to derive our equation is based on proton transfer buffer equilibria without requiring the incorporation of electroneutrality considerations. The model consists of a quartic polynomial equation that is derived based solely on the partitioning of H+ among the various buffer components. We tested the accuracy of the model using aqueous solutions with various buffers and measured the equilibrium pH values following the addition of HCl. Our results confirmed the accuracy of our new equation (r2 = 1; measured pH vs. predicted pH), indicating that it quantitatively accounts for the underlying acid-base phenomenology.

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Year:  2009        PMID: 19339630      PMCID: PMC2692448          DOI: 10.1152/ajprenal.90651.2008

Source DB:  PubMed          Journal:  Am J Physiol Renal Physiol        ISSN: 1522-1466


  8 in total

Review 1.  Acid-base analysis: a critique of the Stewart and bicarbonate-centered approaches.

Authors:  Ira Kurtz; Jeffrey Kraut; Vahram Ornekian; Minhtri K Nguyen
Journal:  Am J Physiol Renal Physiol       Date:  2008-01-09

2.  Independent and dependent variables of acid-base control.

Authors:  P A Stewart
Journal:  Respir Physiol       Date:  1978-04

Review 3.  Clinical assessment of acid-base status. Strong ion difference theory.

Authors:  P D Constable
Journal:  Vet Clin North Am Food Anim Pract       Date:  1999-11       Impact factor: 3.357

4.  A simplified strong ion model for acid-base equilibria: application to horse plasma.

Authors:  P D Constable
Journal:  J Appl Physiol (1985)       Date:  1997-07

5.  Modern quantitative acid-base chemistry.

Authors:  P A Stewart
Journal:  Can J Physiol Pharmacol       Date:  1983-12       Impact factor: 2.273

6.  Determination of sodium with ion-selective electrodes.

Authors:  G B Levy
Journal:  Clin Chem       Date:  1981-08       Impact factor: 8.327

7.  Clinical assessment of acid-base status: comparison of the Henderson-Hasselbalch and strong ion approaches.

Authors:  Peter D. Constable
Journal:  Vet Clin Pathol       Date:  2000       Impact factor: 1.180

Review 8.  Clinical review: reunification of acid-base physiology.

Authors:  John A Kellum
Journal:  Crit Care       Date:  2005-08-05       Impact factor: 9.097

  8 in total
  2 in total

1.  The standard strong ion difference, standard total titratable base, and their relationship to the Boston compensation rules and the Van Slyke equation for extracellular fluid.

Authors:  E Wrenn Wooten
Journal:  J Clin Monit Comput       Date:  2010-03-31       Impact factor: 2.502

2.  Defining the buffering process by a triprotic acid without relying on Stewart-electroneutrality considerations.

Authors:  Minhtri K Nguyen; Liyo Kao; Ira Kurtz
Journal:  Theor Biol Med Model       Date:  2011-08-17       Impact factor: 2.432

  2 in total

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