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  5. Adsorption separation of heavier isotope gases in subnanometer carbon pores

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Article
en
2021

Adsorption separation of heavier isotope gases in subnanometer carbon pores

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en
2021
Vol 12 (1)
Vol. 12
DOI: 10.1038/s41467-020-20744-6

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Yury Gogotsi
Yury Gogotsi

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Sanjeev Kumar Ujjain
Abhishek Bagusetty
Yuki Matsuda
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Abstract

Isotopes of heavier gases including carbon (13C/14C), nitrogen (13N), and oxygen (18O) are highly important because they can be substituted for naturally occurring atoms without significantly perturbing the biochemical properties of the radiolabelled parent molecules. These labelled molecules are employed in clinical radiopharmaceuticals, in studies of brain disease and as imaging probes for advanced medical imaging techniques such as positron-emission tomography (PET). Established distillation-based isotope gas separation methods have a separation factor (S) below 1.05 and incur very high operating costs due to high energy consumption and long processing times, highlighting the need for new separation technologies. Here, we show a rapid and highly selective adsorption-based separation of 18O2 from 16O2 with S above 60 using nanoporous adsorbents operating near the boiling point of methane (112 K), which is accessible through cryogenic liquefied-natural-gas technology. A collective-nuclear-quantum effect difference between the ordered 18O2 and 16O2 molecular assemblies confined in subnanometer pores can explain the observed equilibrium separation and is applicable to other isotopic gases.

How to cite this publication

Sanjeev Kumar Ujjain, Abhishek Bagusetty, Yuki Matsuda, Hideki Tanaka, Preety Ahuja, Carla de Tomás, Motomu Sakai, Fernando Vallejos-Burgos, Ryusuke Futamura, Irene Suarez‐Martinez, Masahiko Matsukata, Akio Kodama, Giovanni Garberoglio, Yury Gogotsi, J. Karl Johnson, Katsumi Kaneko (2021). Adsorption separation of heavier isotope gases in subnanometer carbon pores. , 12(1), DOI: https://doi.org/10.1038/s41467-020-20744-6.

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Publication Details

Type

Article

Year

2021

Authors

16

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1038/s41467-020-20744-6

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