An in-silico corrosion model for biomedical applications for coupling with in-vitro biocompatibility tests for estimation of long-term effects

Name: An in-silico corrosion model for biomedical applications for coupling with in-vitro biocompatibility tests for estimation of long-term effects
Author: Šušteršič, T., Şimsek, Görkem Muttalip, Yapıcı, Güney Güven, Nikolić, M., Vulović, R., Filipovic, N., Vrana, N. E.

İsim	An in-silico corrosion model for biomedical applications for coupling with in-vitro biocompatibility tests for estimation of long-term effects
Yazar	Šušteršič, T., Şimsek, Görkem Muttalip, Yapıcı, Güney Güven, Nikolić, M., Vulović, R., Filipovic, N., Vrana, N. E.
Basım Tarihi:	2021-09-07
Basım Yeri	- Frontiers Media
Konu	Biomaterial corrosion, Cellular automata, Implant surfaces, In silico modelling, Nickel titanium alloy, Numerical simulations
Tür	Süreli Yayın
Dil	Belirlenmemiş dil
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	2296-4185
Kayıt Numarası	d9a999d6-e47a-43ef-89af-cb453d609879
Lokasyon	Mechanical Engineering
Tarih	2021-09-07
Notlar	Ministry of Education, Science & Technological Development, Serbia ; European Union’s Horizon 2020 ; Ozyegin University
Örnek Metin	The release of metal particles and ions due to wear and corrosion is one of the main underlying reasons for the long-term complications of implantable metallic implants. The rather short-term focus of the established in-vitro biocompatibility tests cannot take into account such effects. Corrosion behavior of metallic implants mostly investigated in in-vitro body-like environments for long time periods and their coupling with long-term in-vitro experiments are not practical. Mathematical modeling and modeling the corrosion mechanisms of metals and alloys is receiving a considerable attention to make predictions in particular for long term applications by decreasing the required experimental duration. By using such in-silico approaches, the corrosion conditions for later stages can be mimicked immediately in in-vitro experiments. For this end, we have developed a mathematical model for multi-pit corrosion based on Cellular Automata (CA). The model consists of two sub-models, corrosion initialization and corrosion progression, each driven by a set of rules. The model takes into account several environmental factors (pH, temperature, potential difference, etc.), as well as stochastic component, present in phenomena such as corrosion. The selection of NiTi was based on the risk of Ni release from the implant surface as it leads to immune reactions. We have also performed experiments with Nickel Titanium (NiTi) shape memory alloys. The images both from simulation and experiments can be analyzed using a set of statistical methods, also investigated in this paper (mean corrosion, standard deviation, entropy etc.). For more widespread implementation, both simulation model, as well as analysis of output images are implemented as a web tool. Described methodology could be applied to any metal provided that the parameters for the model are available. Such tool can help biomedical researchers to test their new metallic implant systems at different time points with respect to ion release and corrosion and couple the obtained information directly with in-vitro tests.
DOI	10.3389/fbioe.2021.718026
Cilt	9

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An in-silico corrosion model for biomedical applications for coupling with in-vitro biocompatibility tests for estimation of long-term effects

Yazar Šušteršič, T., Şimsek, Görkem Muttalip, Yapıcı, Güney Güven, Nikolić, M., Vulović, R., Filipovic, N., Vrana, N. E.

Basım Tarihi 2021-09-07

Basım Yeri - Frontiers Media

Konu Biomaterial corrosion, Cellular automata, Implant surfaces, In silico modelling, Nickel titanium alloy, Numerical simulations

Tür Süreli Yayın

Dil Belirlenmemiş dil

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 2296-4185

Kayıt Numarası d9a999d6-e47a-43ef-89af-cb453d609879

Lokasyon Mechanical Engineering

Tarih 2021-09-07

Notlar Ministry of Education, Science & Technological Development, Serbia ; European Union’s Horizon 2020 ; Ozyegin University

Örnek Metin The release of metal particles and ions due to wear and corrosion is one of the main underlying reasons for the long-term complications of implantable metallic implants. The rather short-term focus of the established in-vitro biocompatibility tests cannot take into account such effects. Corrosion behavior of metallic implants mostly investigated in in-vitro body-like environments for long time periods and their coupling with long-term in-vitro experiments are not practical. Mathematical modeling and modeling the corrosion mechanisms of metals and alloys is receiving a considerable attention to make predictions in particular for long term applications by decreasing the required experimental duration. By using such in-silico approaches, the corrosion conditions for later stages can be mimicked immediately in in-vitro experiments. For this end, we have developed a mathematical model for multi-pit corrosion based on Cellular Automata (CA). The model consists of two sub-models, corrosion initialization and corrosion progression, each driven by a set of rules. The model takes into account several environmental factors (pH, temperature, potential difference, etc.), as well as stochastic component, present in phenomena such as corrosion. The selection of NiTi was based on the risk of Ni release from the implant surface as it leads to immune reactions. We have also performed experiments with Nickel Titanium (NiTi) shape memory alloys. The images both from simulation and experiments can be analyzed using a set of statistical methods, also investigated in this paper (mean corrosion, standard deviation, entropy etc.). For more widespread implementation, both simulation model, as well as analysis of output images are implemented as a web tool. Described methodology could be applied to any metal provided that the parameters for the model are available. Such tool can help biomedical researchers to test their new metallic implant systems at different time points with respect to ion release and corrosion and couple the obtained information directly with in-vitro tests.

DOI 10.3389/fbioe.2021.718026

Cilt 9