Luminescent Metal-Organic Framework with Negative Electrostatic Pores for Highly Selective GDP Sensing
Yexin Zhang1, Yuying Wei1, Yuhan Li1
1Jiangsu Key Laboratory of Green Synthetic Chemistry for Functional Materials, School of Chemistry and Materials Science, Jiangsu Normal University, Xuzhou, Jiangsu 221116, PR China.
Inorganic Chemistry
|March 4, 2025
Summary
Researchers developed a novel luminescent metal-organic framework (LMOF) for selective guanosine diphosphate (GDP) detection. This material utilizes electrostatic potential (ESP) for highly accurate sensing, guiding future sensor design.
Area of Science:
- Materials Science
- Chemical Sensing
- Nanotechnology
Background:
- Electrostatic potential (ESP) is crucial for molecular interactions.
- Developing selective probe materials based on ESP is vital but underexplored.
- Metal-organic frameworks (MOFs) offer tunable properties for sensing applications.
Purpose of the Study:
- To synthesize a luminescent metal-organic framework (LMOF) with a negative electrostatic pore environment.
- To develop a selective sensor for guanosine diphosphate (GDP) based on ESP matching.
- To provide theoretical guidance for designing efficient MOF-based sensors.
Main Methods:
- Synthesis of a luminescent MOF (Cd-DBDP) with electronegative pore environments.
- Calculation of molecular ESP distributions for the MOF and nucleotides.
- Fluorescence spectroscopy for sensing experiments.
- Characterization using FT-IR, SEM/EDS, and XPS.
Main Results:
- Cd-DBDP was successfully synthesized, exhibiting a negative electrostatic pore environment.
- Cd-DBDP demonstrated selective sensing of guanosine diphosphate (GDP).
- Experimental results aligned with theoretical ESP predictions.
- The sensing mechanism was elucidated through various spectroscopic and computational methods.
Conclusions:
- This work presents the first MOF-based sensor for GDP detection utilizing ESP.
- The findings highlight the importance of matching molecular ESP for effective analyte recognition.
- The study provides a framework for designing advanced MOF sensors for various analytes.


