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Highly Efficient Quantum Sieving in Porous Graphene-like Carbon Nitride for Light Isotopes Separation.


ABSTRACT: Light isotopes separation, such as (3)He/(4)He, H2/D2, H2/T2, etc., is crucial for various advanced technologies including isotope labeling, nuclear weapons, cryogenics and power generation. However, their nearly identical chemical properties made the separation challenging. The low productivity of the present isotopes separation approaches hinders the relevant applications. An efficient membrane with high performance for isotopes separation is quite appealing. Based on first-principles calculations, we theoretically demonstrated that highly efficient light isotopes separation, such as (3)He/(4)He, can be reached in a porous graphene-like carbon nitride material via quantum sieving effect. Under moderate tensile strain, the quantum sieving of the carbon nitride membrane can be effectively tuned in a continuous way, leading to a temperature window with high (3)He/(4)He selectivity and permeance acceptable for efficient isotopes harvest in industrial application. This mechanism also holds for separation of other light isotopes, such as H2/D2, H2/T2. Such tunable quantum sieving opens a promising avenue for light isotopes separation for industrial application.

SUBMITTER: Qu Y 

PROVIDER: S-EPMC4728688 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Highly Efficient Quantum Sieving in Porous Graphene-like Carbon Nitride for Light Isotopes Separation.

Qu Yuanyuan Y   Li Feng F   Zhou Hongcai H   Zhao Mingwen M  

Scientific reports 20160127


Light isotopes separation, such as (3)He/(4)He, H2/D2, H2/T2, etc., is crucial for various advanced technologies including isotope labeling, nuclear weapons, cryogenics and power generation. However, their nearly identical chemical properties made the separation challenging. The low productivity of the present isotopes separation approaches hinders the relevant applications. An efficient membrane with high performance for isotopes separation is quite appealing. Based on first-principles calculat  ...[more]

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