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Bayesian Optimized Crystallization of a Hydroxamate-Functionalized Covalent Organic Framework for Enhanced Uranyl
Zhen-Wu Shao1, Zhiyuan Zhang1, Yunrui Kuang1
1School of Chemical Engineering, Sichuan University, Chengdu, 610065, China.
Small (Weinheim an Der Bergstrasse, Germany)
|March 25, 2025
Summary
Bayesian optimization (BO) enhances covalent organic framework (COF) synthesis, improving crystallinity by 80% and boosting uranyl adsorption capacity by 23.7%. This method optimizes COF performance for applications like water purification.
Area of Science:
- Materials Science
- Chemical Engineering
- Computational Chemistry
Background:
- Covalent organic frameworks (COFs) present synthetic challenges, particularly with interfering functional groups.
- Optimizing COF synthesis for improved crystallinity and selectivity is crucial for their application.
Purpose of the Study:
- To develop and implement a Bayesian optimization (BO) centered approach for COF synthesis.
- To enhance the crystallinity and selectivity of COFs, enabling improved performance in downstream applications.
Main Methods:
- A Bayesian optimization (BO) protocol was developed and applied to COF synthesis.
- Proof-of-concept BO improved crystallinity of TAPB-PDA COF by ~80%.
- An efficient BO protocol with 6 iterations optimized hydroxamate-functionalized TpPa COF (SUM-99) synthesis.
Main Results:
- The optimized SUM-99 COF exhibited enhanced crystallinity.
- SUM-99 demonstrated effective, reversible, and selective sorption of aquatic uranyl.
- Improved crystallinity led to a 23.7% increase in uranyl adsorption capacity.
Conclusions:
- The developed BO protocol offers an efficient method for optimizing COF synthesis.
- Enhanced COF crystallinity significantly improves performance in applications like uranyl uptake.
- The BO toolkit facilitates the evolution of COF synthesis for superior material performance.
