Accelerating Hierarchical ZSM‑5 Engineering via Bayesian Optimization-Guided Discovery
Tzu-Hung Wen, Cheng-Yi You, Ting-Hao Liu, Bryan R. Goldsmith, Yu-Chuan Lin
TL;DR
This paper uses Bayesian optimization to speed up the creation of a special type of zeolite with a balanced pore structure.
Contribution
The study introduces a data-driven workflow using Bayesian optimization to efficiently design hierarchical ZSM-5 structures.
Findings
The optimized ZSM-5 sample achieved a hierarchy factor of 0.17 with improved microporosity.
NaOH and TPAOH mixture synergistically created uniform mesopores while preserving crystallinity.
Sensitivity analysis identified TPAOH fraction and temperature as key factors affecting the hierarchy factor.
Abstract
Bayesian optimization (BO) was used to accelerate the synthesis of hierarchical ZSM-5 with a balanced micro–mesoporous structure. Using mesoporosity and microporosity as dual objectives, a Gaussian process regression surrogate guided three successive BO iterations informed by 15 initial experiments. The optimized sample (HZ-R0.55T50t2) exhibited the highest hierarchy factor (0.17), featuring similar mesoporosity (0.44) but higher microporosity (0.38) than the benchmark, indicating reduced diffusional resistance with preserved framework. Characterizations revealed that NaOH induced framework dissolution, whereas TPAOH moderated desilication; their mixture synergistically created uniform mesopores while maintaining crystallinity. 27Al and 29Si NMR confirmed realumination and silanol generation, and acidity analysis showed redistributed acid sites. Sensitivity analysis identified the TPAOH…
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Taxonomy
TopicsZeolite Catalysis and Synthesis · Mesoporous Materials and Catalysis · Catalytic Processes in Materials Science