five

Elucidation of the structural transformation of MIL-53(Al) upon D2 responsive 2nd Breathing

收藏
DataCite Commons2025-07-09 更新2025-04-16 收录
下载链接:
https://data.isis.stfc.ac.uk/doi/STUDY/126608196/
下载链接
链接失效反馈
官方服务:
资源简介:
MIL-53(Al), a well-known flexible MOF, exhibits a dynamic 'breathing' phenomenon, transitioning from narrow pore (np) to large pore (lp) states. Understanding the structural flexibility of MIL-53(Al) holds the key for advancements, making it ideal for precise gas separation, including hydrogen isotopes. This proposal seeks beamtime to investigate unresolved questions concerning MIL-53(Al)'s isotope-specific second 'breathing' transitions induced by D2 adsorption below 25 K. To date, neutron powder diffraction (NPD) studies have been hampered by high noise levels. Leveraging the superior flux of the WISH beamline, we aim for precise identification of D2 adsorption sites and their site-specific binding energies as functions of pressure. Concurrently, we will examine how crystal size influences the kinetics of these transitions. We can readily prepare pure-phase MIL-53(Al) with high crystallinity over 1 g of the material for gas loading experiments. To complete these experiments, it will require approximately three days for in situ NPD measurements. We believe that NPD, benefiting from the high flux of WISH, is the optimal tool for this purpose, allowing us to identify hydrogen isotope adsorption sites within MIL-53(Al).

MIL-53(Al)是一种知名的柔性金属有机框架(Metal-Organic Framework, MOF),具备独特的动态“呼吸”效应,可在窄孔(narrow pore, np)与大孔(large pore, lp)两种状态之间发生可逆转变。解析MIL-53(Al)的结构柔性是推动相关领域研究进展的核心关键,也使其成为包括氢同位素在内的高精度气体分离的理想候选材料。本申请申请束流时间,旨在探究尚未解决的科学问题:即MIL-53(Al)在25K以下由氘气(D2)吸附诱导的、具有同位素特异性的第二次“呼吸”相变。迄今为止,中子粉末衍射(Neutron Powder Diffraction, NPD)相关研究受限于较高的本底噪声,难以获得可靠的实验结果。本研究将依托WISH束流线的超高通量优势,精准识别氘气的吸附位点,并解析各吸附位点的结合能随压力的变化规律。同时,我们还将探究晶体尺寸对上述呼吸相变动力学过程的影响机制。我们可便捷制备高结晶度的纯相MIL-53(Al)样品,单批次产量可超过1克,完全满足气体负载实验的需求。完成本项实验的原位中子粉末衍射测试约需3天时间。我们认为,依托WISH束流线的高通量优势开展中子粉末衍射测试,是本研究的最优实验方案,可实现MIL-53(Al)内部氢同位素吸附位点的精准识别。
提供机构:
ISIS Facility
创建时间:
2024-12-10
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作