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Optimal Experimental Design for Physicochemical Models: A Partial Review

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Trends in Mathematical, Information and Data Sciences

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 445))

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Abstract

This paper presents a partial review of optimal experimental design applied to physicochemical models. The goal is to serve as an introduction to the discipline for all those who carry out laboratory experiments observing phenomena related to physical chemistry. The optimal design of experiments does not make sense unless the proposed designs can be implemented in practice, and therefore the involvement of the experimenters is essential. This chapter provides a motivated introduction to optimal experimental design, as well as some of the results obtained by applying these techniques to widely used physicochemical models: the Michaelis-Menten model used in the kinetics of enzyme systems; the Arrhenius model used to describe the relationship between the rate of a chemical reaction and the temperature; adsorption isotherms that describe adsorption equilibrium, and the Tait equation, which characterizes relations between the pressure, volume and temperature of gases, liquids and mixtures.

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Acknowledgements

This work was sponsored by Ministerio de Economía y Competitividad MTM2016-80539-C2-1-R and by Consejería de Educación, Cultura y Deportes of Junta de Comunidades de Castilla-La Mancha and Fondo Europeo de Desarrollo Regional SBPLY/17/180501/000380.

López-Fidalgo wants to thank Leandro for his support, trust and friendship in some of his professional milestones.

Rodríguez-Aragón wants to thank Professor LJ Rodríguez (Professor of Physical Chemistry at the University of Salamanca) who has always generously answered the questions and shared the applied point of view of the physicochemical models and techniques.

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Authors and Affiliations

  1. Universidad de Castilla-La Mancha, Escuela de Ingeniería Industrial y Aeroespacial de Toledo, Instituto de Matemática Aplicada a la Ciencia y la Ingeniería, Avda. Carlos III s/n, 45071, Toledo, Spain

    Carlos de la Calle Arroyo & Licesio J. Rodríguez-Aragón

  2. Universidad de Navarra, Institute of Data Science and Artificial Intelligence, Campus Universitario, 31009, Pamplona, Navarra, Spain

    Jesús López-Fidalgo

Authors
  1. Carlos de la Calle Arroyo
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  2. Jesús López-Fidalgo
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  3. Licesio J. Rodríguez-Aragón
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Corresponding author

Correspondence to Carlos de la Calle Arroyo .

Editor information

Editors and Affiliations

  1. Department of Mathematics and Statistics, McMaster University, Hamilton, ON, Canada

    Narayanaswamy Balakrishnan

  2. Department of Statistics and OR and TM, University of Oviedo, Oviedo, Asturias, Spain

    María Ángeles Gil

  3. Department of Financial and Actuarial Economics & Statistics, Complutense University of Madrid, Madrid, Spain

    Nirian Martín

  4. Department of Statistics, Mathematics and Informatics, Miguel Hernández University of Elche, Elche, Spain

    Domingo Morales

  5. Department of Statistics and Operational Research, Complutense University of Madrid, Madrid, Spain

    María del Carmen Pardo

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de la Calle Arroyo, C., López-Fidalgo, J., Rodríguez-Aragón, L.J. (2023). Optimal Experimental Design for Physicochemical Models: A Partial Review. In: Balakrishnan, N., Gil, M.Á., Martín, N., Morales, D., Pardo, M.d.C. (eds) Trends in Mathematical, Information and Data Sciences. Studies in Systems, Decision and Control, vol 445. Springer, Cham. https://doi.org/10.1007/978-3-031-04137-2_26

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  • DOI: https://doi.org/10.1007/978-3-031-04137-2_26

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  • Online ISBN: 978-3-031-04137-2

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