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Doklady Physical Chemistry

, Volume 464, Issue 2, pp 231–233 | Cite as

Maximum permissible estimates of parameters of physicochemical models

  • S. I. Spivak
  • O. G. Kantor
  • D. S. Yunusova
  • S. I. Kuznetsov
  • S. V. Kolesov
Physical Chemistry
  • 24 Downloads

Abstract

In this work, we studied the problem of determining the concentrations of substances in multicomponent mixtures with components with known extinction coefficients on the basis of absorbance expressions written under the assumption that Beer’s law for each component and the additivity principle for their mixture are valid. The main result of this work is the development of a method for calculating the uncertainty ranges of parameters of models from experimental information on the maximum permissible error of measurement.

Keywords

Fullerene Model Mixture Equimolar Mixture Uncertainty Range DOKLADY Physical Chemistry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Bershtein, I.Ya. and Kaminskii, Yu.A., Spektrofotometrcheskii analiz v organicheskoi khimii (Spectrophotometric Analysis in Organic Chemistry), Leningrad: Khimiya, 1986.Google Scholar
  2. 2.
    Kantorovich, L.V., Sib. Mat. Zh., 1962, vol. 3, no. 5, pp. 701–709.Google Scholar
  3. 3.
    Gun’kin, I.F. and Loginova, N.Yu., Zh. Org. Khim., 2006, vol. 76, no. 12, pp. 2000–2002.Google Scholar
  4. 4.
    Silvestrini, S., Dalle Nogare, D., et al., Eur. J. Org. Chem., 2011, no. 28, pp. 5571–5576.CrossRefGoogle Scholar
  5. 5.
    Geerts, Y.H., Debever, O., Amato, C., et al., Beilstein J. Org. Chem., 2009, vol. 5, no. 49.CrossRefGoogle Scholar
  6. 6.
    Biglova, Yu.N., Kraikin, V.A., et al., Zh. Strukt. Khim., 2013, vol. 54, no. 4, pp. 674–678.Google Scholar
  7. 7.
    Yumagulova, R.Kh., Biglova, Yu.N., Kolesov, S.V., and Monakov, Yu.B., Dokl. Chem., 2006, vol. 408, part 2, pp. 90–91.CrossRefGoogle Scholar
  8. 8.
    Hirsch, A., Lamparth, I., and Grosser, T., J. Am. Chem. Soc., 1994, vol. 116, no. 20, pp. 9385–9386.CrossRefGoogle Scholar
  9. 9.
    Cardullo, F., Seiler, P., Isaacs, L., et al., Helv. Chim. Acta, 1997, vol. 80, no. 2, pp. 343–371.CrossRefGoogle Scholar
  10. 10.
    Biglova, Yu.N., Kraikin, V.A., Torosyan, S.A, et al., Zh. Fiz. Khim., 2013, vol. 87, no. 10, pp. 1705–1708.Google Scholar
  11. 11.
    Zukhovitskii, S.I. and Avdeeva, L.I., Lineinoe i vypukloe programmirovanie (Linear and Convex Programming), Moscow: Nauka, 1967.Google Scholar
  12. 12.
    Remez, E.Ya., Osnovy chislennykh metodov chebyshevskogo priblizheniya (Foundations of Numerical Methods of Chebyshev Approximation), Kiev: Naukova Dumka, 1969.Google Scholar
  13. 13.
    Spivak, S.I., Timoshenko, V.I., and Slin’ko, M.G., Khim. Prom-st., 1979, no. 3, pp. 33–36.Google Scholar
  14. 14.
    Spivak, S.I., Kantor, O.G., and Yunusova, D.S., Izv. Ufim. Nauchn. Tsentra Ross. Akad. Nauk, 2014, no. 2, pp. 62–67.Google Scholar

Copyright information

© Pleiades Publishing, Ltd. 2015

Authors and Affiliations

  • S. I. Spivak
    • 1
  • O. G. Kantor
    • 2
  • D. S. Yunusova
    • 1
  • S. I. Kuznetsov
    • 3
  • S. V. Kolesov
    • 3
  1. 1.Bashkir State UniversityUfaRussia
  2. 2.Institute of Social-Economic Studies, Ufa Scientific CenterRussian Academy of SciencesUfaRussia
  3. 3.Institute of Organic Chemistry, Ufa Scientific CenterRussian Academy of SciencesUfaRussia

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