Electrochemical potentials and pressures of biofluids from common experimental data

E. Mamontov, M. Willander

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Many biosystems are complex mixtures of disparate biofluids. To study contact and transport phenomena in these mixtures, one has to apply much information on the biofluids which are components of the mixtures. A lot of the corresponding data can be extracted by means of experiments. However, it is not always easy to obtain experimental results on rather deep physical characteristics of biofluids, especially if the bioparticles are complicated systems and the fluid coexists in the mixture with a large number of other fluids. In these cases, the necessary data can, in principle, be extracted from those results which are easier to obtain experimentally. The present work proposes a method to evaluate the biofluid equilibrium pressure and electrochemical potential from common experimental values of the fluid concentration and absolute temperature as well as the fluid-particle mass, volume and spin. In so doing, the nonzero values of the particle volume are accounted for. The procedure is illustrated with a numerical example on the fluid of red blood cells (or erythrocytes) in human blood. The pressure values obtained are 49.1 and 38.8 micropascals for men and women respectively whereas the electrochemical-potential values are -2.124 and -2.130 electronvolts for men and women respectively.

Original languageEnglish
Pages (from-to)173-180
Number of pages8
JournalActa Biotheoretica
Volume51
Issue number3
DOIs
StatePublished - 2003
Externally publishedYes

Keywords

  • Biofluid
  • Biological heterostructure
  • Electrochemical potential
  • Erythrocyte
  • Experimental data
  • Heisenberg's uncertainty principle
  • Maxwell-Boltzmann distribution
  • Particle of nonzero volume
  • Pressure
  • Red blood cell

Fingerprint

Dive into the research topics of 'Electrochemical potentials and pressures of biofluids from common experimental data'. Together they form a unique fingerprint.

Cite this