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Updated: Jun 24, 2025

Synthesis and Characterization of Functionalized Metal-organic Frameworks
Published on: September 5, 2014
Unprecedented Packing Polymorphism of Oxindole: An Exploration Inspired by Crystal Structure Prediction
Emily J Wu1, Andrew W Kelly1, Luca Iuzzolino2
1Analytical Research & Development, Merck & Co., Inc., Rahway, New Jersey, 07065, United States.
This study used crystal structure prediction to explore oxindole polymorphism, successfully identifying known and discovering four new crystal forms. The approach aids in understanding disappearing polymorphs and mapping molecular solid-state landscapes.
Area of Science:
- Solid-state chemistry
- Materials science
- Crystallography
Background:
- Crystal polymorphism significantly impacts molecular physical properties.
- Determining a molecule's polymorphic landscape is challenging and time-consuming.
- Disappearing polymorphs present reproducibility issues in the pharmaceutical industry.
Purpose of the Study:
- To assess the solid-state landscape and thermodynamic stability of oxindole (OX).
- To validate crystal structure prediction (CSP) by comparing predicted structures with experimental data.
- To investigate the formation of novel polymorphs and understand disappearing forms.
Main Methods:
- Crystal structure prediction (CSP) was employed to model OX's solid-state landscape.
- Melt and solution crystallization experiments were conducted in bulk and nanoconfined environments.
- Predicted structures were compared with experimentally observed and novel polymorphs.
Main Results:
- CSP successfully predicted known oxindole polymorphs and identified potential new forms.
- Experimental crystallization reproduced known forms and yielded four previously undiscovered polymorphs.
- The study established a new record for packing polymorphism in rigid molecules.
Conclusions:
- The combined CSP and experimental approach enhances the understanding of molecular polymorphism.
- This methodology aids in reconstructing disappearing polymorphs and building comprehensive polymorphic landscapes.
- The findings offer valuable insights for pharmaceutical development and materials science.
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