Araştırma Makalesi
BibTex RIS Kaynak Göster

Grand Canonical Monte Carlo Modeling of Anesthetic Xe Separation from Exhale Gas Mixtures Using Metal Organic Frameworks

Yıl 2019, Cilt: 12 Sayı: 3, 1705 - 1714, 31.12.2019

Yeliz Gurdal

https://doi.org/10.18185/erzifbed.653429
Cited By: 1

Öz



Xe
has been shown to be a promising candidate for anesthetic applications.
However,  its high price prevents its
usage in clinical industry. An alternative approach is to recover Xe from
anesthetic exhale gas mixture and recycle it to the inhale gas stream.
Although, many membranes and/or adsorbents have been proposed for recovering
anesthetic Xe, using metal organic frameworks (MOFs) for adsorption based
separation of  anesthetic Xe exhale gas
mixtures has been newly studied. MOFs have 
tunable pore sizes, large surface areas, and high porosities which
make them potential candidates for gas separation applications. Currently,
very little is known about anesthetic Xe recovery  performances of MOFs. We theoretically
investigate adsorption based separation of single component and binary
mixtures of CO2, Xe, and N2 in three MOFs, namely  CECYOY, SUDBOI, and ZUQPOQ. Single
component and binary adsorption isotherms and adsorption selectivities are
calculated using Grand Canonical Monte Carlo simulations for each MOF in
order to characterize their performances as adsorbents. Results suggest that
while MOFs prefer adsorption of CO2 for  CO2/Xe
mixture,  Xe adsorption is favorable in
the case of Xe/N2 mixture. While SUDBOI shows significantly large
CO2 adsorption selectivity for CO2/Xe mixture,  ZUQPOQ has the largest adsorption
selectivity for Xe/N2 mixture.


 

Anahtar Kelimeler

: Grand Canonical Monte Carlo simulations metal organic frameworks gas separation

Teşekkür

The numerical calculations reported in this paper were fully performed at TUBITAK ULAKBIM, High Performance and Grid Computing Center (TRUBA resources), located in Turkey.

Kaynakça

  • Allen, F. H. 2002. “The Cambridge Structural Database: a quarter of a million crystal structures and rising”, Acta Crystallographica Section B- Structural Science, 58(1), 380-388.
  • Allen, M., Tildesley, J., (1987). “Computer Simulations of Liquids,” Oxford Science Publications, Oxford.
  • Altintas, C., Keskin, S. 2017. “Molecular simulations of MOF membranes for separation of ethane/ethene and ethane/methane mixtures”, RSC Advances, 7, 52283-52295.
  • Banerjee, D., Simon, C. M., Elsaidi, S. K., Haranczyk, M., Thallapally, P. K. 2018. “Xenon Gas Separation and Storage Using Metal-Organic Frameworks”, Chem, 4(3), 466-494.
  • Burov, V. P. N., Efimov, V., Makeev, G., Surnin, A., Vovk, S., (2000). “Method and Device for Regenerating Xenon from Narcotic Gas Mixture Used in Anesthesia Apparatus”. RU Patent No: 2149033.
  • Elsaidi, E., Ongari, D., Xu, W., Mohamed, M.H., Haranczyk, M., Thallapally, P. K. 2017. “Xenon Recovery at Room Temperature using Metal–Organic Frameworks”, Chemistry-A European Journal Communication, 23, 10758 – 10762.
  • Erucar, I., Manz, T. A., Keskin, S. 2014. “Effects of electrostatic interactions on gas adsorption and permeability of MOF membranes”, Molecular Simulation, 40 (7-9), 557-570.
  • Franks, N. P. 2008. “General Anaesthesia: From Molecular Targets to Neuronal Pathways of Sleep and Arousal”, Nature Reviews Neuroscience, 9, 370−386.
  • Frenkel, D., Smit, B.,(1987). “Understanding Molecular Simulation: From Algorithms to Applications”, Academic Press, San Diego.
  • Georgieff, T. M. M, Bader, S., (1996). “Anesthesia Arrangement for Recovering Gaseous Anesthetic Agents”. US Patent No: 5, 520,169. May 28.
  • Gurdal, Y., Keskin, S. 2012. “Atomically Detailed Modeling of Metal Organic Frameworks for Adsorption, Diffusion, and Separation of Noble Gas Mixtures,” Industrial & Engineering Chemistry Research, 51(21), 7373–7382.
  • Gurdal, Y., Keskin, S. 2013. “Predicting Noble Gas Separation Performance of Metal Organic Frameworks Using Theoretical Correlations”, The Journal of Physical Chemistry C, 117 (10), 5229–5241.
  • Gurdal, Y., Keskin, S. 2016. “A New Approach for Predicting Gas Separation Performances of MOF Membranes”, Journal of Membrane Science, 519, 45–54.
  • Makrodimitris, K., Papadopoulos, G. K. , Theodorou, D. N. 2001. “Prediction of Permeation Properties of CO2 and N2 through Silicalite via Molecular Simulations”, Journal of Physical Chemistry B, 105, 777- 788.
  • Neice, A. E., Zornow, M. H. 2016. “Xenon anesthesia for all, or only a select few?”, Anaesthesia, 71(11), 1267-1272.
  • Panter, S., Zarabadi-Poo, P. 2018. “Computational Exploration of IRMOFs for Xenon Separation from Air”, ACS Omega, 3(12), 18535–18541.
  • Potoff, J. J., Siepmann, J. I. 2001. “Vapor−Liquid Equilibria of Mixtures Containing Alkanes, Carbon Dioxide, and Nitrogen”, AIChE Journal, 47, 1676-1682.
  • Rappe, A. K., Casewit, C. J., Colwell, K. S. , Goddard, W. A., Skiff, W. M. 1992. “UFF, A full Periodic Table Force Field for Molecular Mechanics and Molecular Dynamics Simulations”, Journal of the American Chemical Society, 114(25), 10024–10035.
  • Wang, X., Karakiliç, P., Liu, X., Shan, M., Nijmeijer, A., Winnubst, L., Gascon, J., Kapteij, F. 2018. “One-Pot Synthesis of High-Fluxb-Oriented MFI Zeolite Membranes for Xe Recovery”, ACS Applied Materials and Interfaces, 10 (39), 33574-33580.
  • Wang, X., Zhang, Y., Wang, X., Andres-Garcia, E., Du., P., Giordano, L., Wang, L., Hong, Z., Gu, X., Murad, S., Kapteijn, F. 2019. “Xenon Recovery by DD3R Zeolite Membranes: Application in Anaesthetics”, Angewandte Chemie International Edition, 131, 15664 –15671.
  • Zhong, S., Wang, Q., Cao, D. 2016. “ZIF-Derived Nitrogen-Doped Porous Carbons for Xe Adsorption and Separation”, Science Reports, 21295-21306.

Metal Organik Çerçeveler Kullanarak Ekshale Gaz Karışımlarından Anestezik Xe Ayrılmasının Grand Canonical Monte Carlo Yöntemi ile Modellenmesi

Yıl 2019, Cilt: 12 Sayı: 3, 1705 - 1714, 31.12.2019

Yeliz Gurdal

https://doi.org/10.18185/erzifbed.653429
Cited By: 1

Öz

Xe'nin anestezi
uygulamalarında kullanılabileceği literatürdeki çalışmalarda gösterilmiştir.
Fakat, yüksek maaliyeti Xe’nin klinik uygulamalarda kullanımını
engellemektedir. Buna çözüm üretebilecek bir yaklaşım olarak, Xe’nin  solunum yoluyla verilen anestezik gaz
karışımından geri kazanılması ve  solunan
gaz akımına geri beslenmesi önerilmiştir. Anestetik Xe'nin geri kazanılması
için birçok membran ve/veya adsorban önerilmiş olsa da, anestezik Xe’nin metal
organik kafes yapılar (MOF) kullanılarak geri kazanılması yeni çalışılmaya
başlanan bir konudur. MOF'ların gaz ayırma uygulamalarında kullanılmalarına
olanak veren özellikleri ayarlanabilir gözenek boyutlarına, geniş yüzey
alanlarına ve yüksek gözenekli yapıya sahip olmalarıdır. Literatürde MOF’ların
anestezik Xe gazını geri kazanım 
performansları hakkında sınırlı sayıda çalışma vardır. Çalışmamızda  CECYOY, SUDBOI, and
ZUQPOQ isimli MOF’ların tek bileşenli ve ikili 
CO2,
Xe ve N2  karışımlarını
adsorpsiyon bazlı ayırma performansları incelenmiştir. Gazların tekli ve
karışım halindeki  adsorpsiyon
izotermleri ve adsorpsiyon seçicilikleri her bir MOF için Grand Canonical Monte
Carlo simülasyonları kullanılarak hesaplanmıştır. Sonuçlar, MOF'larda CO2/Xe
karışımı için CO2 adsorpsiyonunun tercih edildiğini, Xe
adsorpsiyonunun ise Xe/N2 karışımı durumunda tercih edildiğini
göstermiştir. SUDBOI, CO2/Xe karışımı için yüksek CO2
adsorpsiyon seçiciliği gösterirken, ZUQPOQ, Xe/N2 karışımı için en
yüksek Xe adsorpsiyon seçiciliğine sahiptir.

Anahtar Kelimeler

Grand Canonical Monte Carlo Simülasyonu metal oraganik kafes yapılar gaz ayırma

Kaynakça

  • Allen, F. H. 2002. “The Cambridge Structural Database: a quarter of a million crystal structures and rising”, Acta Crystallographica Section B- Structural Science, 58(1), 380-388.
  • Allen, M., Tildesley, J., (1987). “Computer Simulations of Liquids,” Oxford Science Publications, Oxford.
  • Altintas, C., Keskin, S. 2017. “Molecular simulations of MOF membranes for separation of ethane/ethene and ethane/methane mixtures”, RSC Advances, 7, 52283-52295.
  • Banerjee, D., Simon, C. M., Elsaidi, S. K., Haranczyk, M., Thallapally, P. K. 2018. “Xenon Gas Separation and Storage Using Metal-Organic Frameworks”, Chem, 4(3), 466-494.
  • Burov, V. P. N., Efimov, V., Makeev, G., Surnin, A., Vovk, S., (2000). “Method and Device for Regenerating Xenon from Narcotic Gas Mixture Used in Anesthesia Apparatus”. RU Patent No: 2149033.
  • Elsaidi, E., Ongari, D., Xu, W., Mohamed, M.H., Haranczyk, M., Thallapally, P. K. 2017. “Xenon Recovery at Room Temperature using Metal–Organic Frameworks”, Chemistry-A European Journal Communication, 23, 10758 – 10762.
  • Erucar, I., Manz, T. A., Keskin, S. 2014. “Effects of electrostatic interactions on gas adsorption and permeability of MOF membranes”, Molecular Simulation, 40 (7-9), 557-570.
  • Franks, N. P. 2008. “General Anaesthesia: From Molecular Targets to Neuronal Pathways of Sleep and Arousal”, Nature Reviews Neuroscience, 9, 370−386.
  • Frenkel, D., Smit, B.,(1987). “Understanding Molecular Simulation: From Algorithms to Applications”, Academic Press, San Diego.
  • Georgieff, T. M. M, Bader, S., (1996). “Anesthesia Arrangement for Recovering Gaseous Anesthetic Agents”. US Patent No: 5, 520,169. May 28.
  • Gurdal, Y., Keskin, S. 2012. “Atomically Detailed Modeling of Metal Organic Frameworks for Adsorption, Diffusion, and Separation of Noble Gas Mixtures,” Industrial & Engineering Chemistry Research, 51(21), 7373–7382.
  • Gurdal, Y., Keskin, S. 2013. “Predicting Noble Gas Separation Performance of Metal Organic Frameworks Using Theoretical Correlations”, The Journal of Physical Chemistry C, 117 (10), 5229–5241.
  • Gurdal, Y., Keskin, S. 2016. “A New Approach for Predicting Gas Separation Performances of MOF Membranes”, Journal of Membrane Science, 519, 45–54.
  • Makrodimitris, K., Papadopoulos, G. K. , Theodorou, D. N. 2001. “Prediction of Permeation Properties of CO2 and N2 through Silicalite via Molecular Simulations”, Journal of Physical Chemistry B, 105, 777- 788.
  • Neice, A. E., Zornow, M. H. 2016. “Xenon anesthesia for all, or only a select few?”, Anaesthesia, 71(11), 1267-1272.
  • Panter, S., Zarabadi-Poo, P. 2018. “Computational Exploration of IRMOFs for Xenon Separation from Air”, ACS Omega, 3(12), 18535–18541.
  • Potoff, J. J., Siepmann, J. I. 2001. “Vapor−Liquid Equilibria of Mixtures Containing Alkanes, Carbon Dioxide, and Nitrogen”, AIChE Journal, 47, 1676-1682.
  • Rappe, A. K., Casewit, C. J., Colwell, K. S. , Goddard, W. A., Skiff, W. M. 1992. “UFF, A full Periodic Table Force Field for Molecular Mechanics and Molecular Dynamics Simulations”, Journal of the American Chemical Society, 114(25), 10024–10035.
  • Wang, X., Karakiliç, P., Liu, X., Shan, M., Nijmeijer, A., Winnubst, L., Gascon, J., Kapteij, F. 2018. “One-Pot Synthesis of High-Fluxb-Oriented MFI Zeolite Membranes for Xe Recovery”, ACS Applied Materials and Interfaces, 10 (39), 33574-33580.
  • Wang, X., Zhang, Y., Wang, X., Andres-Garcia, E., Du., P., Giordano, L., Wang, L., Hong, Z., Gu, X., Murad, S., Kapteijn, F. 2019. “Xenon Recovery by DD3R Zeolite Membranes: Application in Anaesthetics”, Angewandte Chemie International Edition, 131, 15664 –15671.
  • Zhong, S., Wang, Q., Cao, D. 2016. “ZIF-Derived Nitrogen-Doped Porous Carbons for Xe Adsorption and Separation”, Science Reports, 21295-21306.
Toplam 21 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Yeliz Gurdal 0000-0002-6245-891X

Yayımlanma Tarihi 31 Aralık 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 12 Sayı: 3

Kaynak Göster

APA Gurdal, Y. (2019). Grand Canonical Monte Carlo Modeling of Anesthetic Xe Separation from Exhale Gas Mixtures Using Metal Organic Frameworks. Erzincan University Journal of Science and Technology, 12(3), 1705-1714. https://doi.org/10.18185/erzifbed.653429

Cited By

High-throughput virtual screening of metal–organic frameworks for xenon recovery from exhaled anesthetic gas mixture
Chemical Engineering Journal
https://doi.org/10.1016/j.cej.2022.138218