Application of Synchrotron Radiation Based X‐Ray Diffraction in Zeolite Research: Advanced Analysis from Atomic Structure to Dynamic Behavior

Zeolites, as crystalline materials with regular pore channels, are widely utilized in energy, environmental, and advanced manufacturing sectors. Characterizing zeolites is crucial for understanding their structure and properties, which are essential for various applications. Synchrotron Radiation-based X-ray Diffraction (SR-XRD) has become an advanced tool in zeolite research, providing higher resolution, faster scans, and more precise structural information than laboratory X-ray diffraction methods. This technique allows for detailed studies, from atomic structures to dynamic behaviors, particularly in understanding structural evolution during synthesis and monitoring changes in the framework during reactions. Moreover, SR-XRD has made significant contributions to catalytic research by revealing structural alterations during catalytic processes and identifying active sites. However, SR-XRD still faces challenges in data interpretation and other technological limitations. To overcome these, integrating SR-XRD with other techniques and using AI-assisted analysis are expected to further advance zeolite characterization and catalytic research.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2025-11-14
DOI
https://doi.org/10.1002/advs.202515141
Citations
1
Primary Topic
Zeolite Catalysis and Synthesis
Type
article
Field-Weighted Citation Impact
0.54
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Application of Synchrotron Radiation Based X‐Ray Diffraction in Zeolite Research: Advanced Analysis from Atomic Structure to Dynamic Behavior

Jiawei Teng, Yongfeng Hu, Jingqing Zhang, Nan Zhang et al.
1 citations
Advanced Science
Zeolite Catalysis and Synthesis
0.54
article

Application of Synchrotron Radiation Based X‐Ray Diffraction in Zeolite Research: Advanced Analysis from Atomic Structure to Dynamic Behavior

Jiawei Teng, Yongfeng Hu, Jingqing Zhang, Nan Zhang, Mingming Chen, Jianqiang Wang, Jing Shi, Hongxing Liu, Chenxin Gong, Weihua Wang
article en
1 citations

Abstract

Zeolites, as crystalline materials with regular pore channels, are widely utilized in energy, environmental, and advanced manufacturing sectors. Characterizing zeolites is crucial for understanding their structure and properties, which are essential for various applications. Synchrotron Radiation-based X-ray Diffraction (SR-XRD) has become an advanced tool in zeolite research, providing higher resolution, faster scans, and more precise structural information than laboratory X-ray diffraction methods. This technique allows for detailed studies, from atomic structures to dynamic behaviors, particularly in understanding structural evolution during synthesis and monitoring changes in the framework during reactions. Moreover, SR-XRD has made significant contributions to catalytic research by revealing structural alterations during catalytic processes and identifying active sites. However, SR-XRD still faces challenges in data interpretation and other technological limitations. To overcome these, integrating SR-XRD with other techniques and using AI-assisted analysis are expected to further advance zeolite characterization and catalytic research.

Advanced ScienceVol. 12(48)
Sinopec (China) (CN), East China University of Science and Technology (CN), Shanghai Research Institute of Chemical Industry (CN), State Key Laboratory of Chemical Engineering (CN)
Openalex Percentile: Top 29%
Zeolite Catalysis and Synthesis
0.54
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.