材料科学
无定形固体
纳米尺度
扫描透射电子显微镜
纳米结构
原子单位
纳米孔
对分布函数
非晶态金属
金属有机骨架
透射电子显微镜
散射
纳米技术
复合材料
合金
结晶学
光学
化学
吸附
数学分析
物理
数学
有机化学
量子力学
作者
Joonatan E. M. Laulainen,Duncan N. Johnstone,I. N. Bogachev,Louis Longley,Courtney Calahoo,Lothar Wondraczek,David A. Keen,Thomas D. Bennett,Sean M. Collins,Paul A. Midgley
出处
期刊:Nanoscale
[Royal Society of Chemistry]
日期:2022-01-01
卷期号:14 (44): 16524-16535
被引量:11
摘要
Characterization of nanoscale changes in the atomic structure of amorphous materials is a profound challenge. Established X-ray and neutron total scattering methods typically provide sufficient signal quality only over macroscopic volumes. Pair distribution function analysis using electron scattering (ePDF) in the scanning transmission electron microscope (STEM) has emerged as a method of probing nanovolumes of these materials, but inorganic glasses as well as metal-organic frameworks (MOFs) and many other materials containing organic components are characteristically prone to irreversible changes after limited electron beam exposures. This beam sensitivity requires 'low-dose' data acquisition to probe inorganic glasses, amorphous and glassy MOFs, and MOF composites. Here, we use STEM-ePDF applied at low electron fluences (10 e- Å-2) combined with unsupervised machine learning methods to map changes in the short-range order with ca. 5 nm spatial resolution in a composite material consisting of a zeolitic imidazolate framework glass agZIF-62 and a 0.67([Na2O]0.9[P2O5])-0.33([AlO3/2][AlF3]1.5) inorganic glass. STEM-ePDF enables separation of MOF and inorganic glass domains from atomic structure differences alone, showing abrupt changes in atomic structure at interfaces with interatomic correlation distances seen in X-ray PDF preserved at the nanoscale. These findings underline that the average bulk amorphous structure is retained at the nanoscale in the growing family of MOF glasses and composites, a previously untested assumption in PDF analyses crucial for future non-crystalline nanostructure engineering.
科研通智能强力驱动
Strongly Powered by AbleSci AI