Daniel Gutiérrez-González
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Daniel Gutiérrez-González has a total of 16 co-authors. Here are the top co-authors by number of shared publications:
- Abdullah Al Kafi
College of Agricultural Sciences, IUBAT- International University of Business Agriculture and Technology, Dhaka 1230, Bangladesh
2 shared publications - Carlos Ivan Gutierrez Gonzalez2 shared publications
- Denis Cantú-Lozano
Instituto Tecnológico de Orizaba
1 shared publication - Eusebio Bolaños Reynoso
División de Estudios de Posgrado e Investigación, Tecnológico Nacional de México Campus Orizaba
1 shared publication - Galo Rafael Urrea García
Tecnológico Nacional de México, Instituto Tecnológico de Orizaba, Orizaba 94320, Veracruz, Mexico
1 shared publication - Guadalupe Luna-Solano
Departamento de Posgrado e Investigación, Instituto Tecnológico de Orizaba, Oriente 9, Emiliano Zapata, Orizaba 94320, Veracruz, Mexico
1 shared publication
Latest Publications
- Open Access
- 26 May 2026
- Published by Springer Nature in Discover Agriculture
- Vol. 4 (1)
Effect of different biofertilizer applications on soil health, tomato growth, and yield
- 26 May 2026
- Published by Springer Nature in Discover Agriculture
- Vol. 4 (1)
Open AccessEffect of different biofertilizer applications on soil health, tomato growth, and yield
- Open Access
Improving Breakthrough Curve Calculations in Dynamic PSA Processes Through a Rigorous Cubic State Equation
This study evaluates the improvement of numerical accuracy in the PSA model for ethanol dehydration using molecular sieves. By incorporating cubic state equations for vapor density determination, significant errors were identified when applying the ideal gas assumption to the ethanol–water mixture, particularly under moderate pressure conditions. The integration of the Peng–Robinson equation demonstrated a 5–10% improvement in calculation accuracy compared to the ideal gas law. This enhancement is crucial for achieving reliable predictions under non-ideal conditions, enabling more accurate estimations of real process dynamics across varying scenarios. Notably, improved accuracy in the PSA model is essential for designing more efficient and reliable industrial applications, especially at moderate pressures. The results indicate that the Peng–Robinson equation provides a more accurate representation of the density of the ethanol–water vapor mixture, contributing significantly to more accurate simulation results of the PSA process.
Open AccessImproving Breakthrough Curve Calculations in Dynamic PSA Processes Through a Rigorous Cubic State Equation
This study evaluates the improvement of numerical accuracy in the PSA model for ethanol dehydration using molecular sieves. By incorporating cubic state equations for vapor density determination, significant errors were identified when applying the ideal gas assumption to the ethanol–water mixture, particularly under moderate pressure conditions. The integration of the Peng–Robinson equation demonstrated a 5–10% improvement in calculation accuracy compared to the ideal gas law. This enhancement is crucial for achieving reliable predictions under non-ideal conditions, enabling more accurate estimations of real process dynamics across varying scenarios. Notably, improved accuracy in the PSA model is essential for designing more efficient and reliable industrial applications, especially at moderate pressures. The results indicate that the Peng–Robinson equation provides a more accurate representation of the density of the ethanol–water vapor mixture, contributing significantly to more accurate simulation results of the PSA process.