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Crystallisation Degree Analysis during Cryopreservation of Biological Tissue Applying Interval Arithmetic
Alicja Piasecka-Belkhayat1, Anna Skorupa1
1Department of Computational Mechanics and Engineering, Silesian University of Technology, Konarskiego 18A, 44-100 Gliwice, Poland.
Materials (Basel, Switzerland)
|March 29, 2023
Summary
This study models heat transfer during cryopreservation vitrification, focusing on ice crystallization in microfluidic systems. Numerical methods simulate the process, providing insights into temperature changes and crystallization dynamics for improved cryopreservation techniques.
Area of Science:
- Biophysics
- Heat Transfer
- Cryopreservation
Background:
- Cryopreservation using vitrification is crucial for preserving biological samples.
- Understanding heat transfer and ice crystallization is vital for successful vitrification.
- Previous models often lack consideration for interval parameters and two-phase flow dynamics.
Purpose of the Study:
- To numerically model heat transfer and crystallization during vitrification.
- To analyze heat transfer in a microfluidic system with single-phase and two-phase flow.
- To investigate the impact of interval parameters on the cryopreservation process.
Main Methods:
- Utilized the Fourier equation with a heat source incorporating ice crystallization degree.
- Employed the interval version of the finite difference method with directed interval arithmetic.
- Applied the fourth-order Runge-Kutta algorithm to determine the degree of crystallization.
Main Results:
- Simulated heat transfer and crystallization phenomena in a homogeneous sample during vitrification.
- Analyzed single-phase flow during warming and two-phase flow during cooling in micro-channels.
- Presented numerical computation examples illustrating the model's application.
Conclusions:
- The numerical model effectively simulates heat transfer and crystallization during vitrification.
- The study highlights the importance of considering interval parameters and two-phase flow.
- Findings contribute to optimizing cryopreservation protocols through advanced modeling.
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