Discovery of a molecular adsorbent for efficient CO2/CH4 separation using a computation-ready experimental database of porous molecular materials,Chemical Science

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Discovery of a molecular adsorbent for efficient CO2/CH4 separation using a computation-ready experimental database of porous molecular materials
Chemical Science ( IF 7.6 ) Pub Date : 2025-04-08 , DOI: 10.1039/d5sc01532d
Siyuan Yang _{1,

2} , Qianqian Mao ₁ , Heng Ji ₁ , Dingyue Hu ₁ , Jinjin Zhang ₁ , Linjiang Chen _{3,

4} , Ming Liu _{1,

2}

Affiliation

The development and sharing of computational databases for metal–organic frameworks (MOFs) and covalent organic frameworks (COFs) have significantly accelerated the exploration and application of these materials. Recently, molecular materials have emerged as a notable subclass of porous materials, characterized by their crystallinity, modularity, and processability. Among these, macrocycles and cages stand out as representative molecules. Experimental discovery of a target molecular material from a vast possibility of structures for defined applications is generally impractical due to high experimental costs. This study presents the most extensive Computation-ready Experimental (CoRE) database of macrocycles and cages (MCD) to date, comprising 7939 structures. Using the MCD, we conducted simulations of binary CO₂/CH₄ competitive adsorption under conditions relevant to industrial applications. These simulations established a structure–property–function relationship, enabling the identification of materials with potential for CO₂/CH₄ separation. Among them, a macrocycle, NDI-Δ, exhibited promising CO₂ adsorption capacity and selectivity, as confirmed by gas sorption and breakthrough experiments.

中文翻译：

使用多孔分子材料的计算就绪实验数据库发现用于高效 CO2/CH4 分离的分子吸附剂

金属有机框架（MOF）和共价有机框架（COF）的计算数据库的开发和共享大大加快了这些材料的探索和应用。最近，分子材料已成为多孔材料的一个显着子类，其特点是其结晶性、模块化和可加工性。其中，大环和笼作为代表性分子脱颖而出。由于实验成本高，从大量可能的结构中实验发现目标分子材料以实现特定应用通常是不切实际的。本研究提出了迄今为止最广泛的大周期和笼（MCD）计算就绪实验（CoRE）数据库，包括 7939 个结构。使用 MCD，我们在与工业应用相关的条件下对二元 CO₂/CH₄ 竞争性吸附进行了模拟。这些模拟建立了结构-性能-功能关系，能够识别具有 CO₂/CH₄ 分离潜力的材料。其中，大环 NDI-Δ 表现出良好的 CO₂ 吸附能力和选择性，气体吸附和突破性实验证实了这一点。

更新日期：2025-04-08

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