# Graph similarity drives zeolite diffusionless transformations and intergrowth

## TL;DR

This study combines computational and theoretical tools to analyze zeolite framework similarities, revealing that graph similarity predicts diffusionless transformations and intergrowth, enabling targeted design of new zeolite structures.

## Contribution

It introduces a supercell-invariant graph theory metric to predict zeolite transformations, linking structural similarity to diffusionless intergrowths and guiding synthesis.

## Key findings

- Graph similarity predicts diffusionless transformations.
- Intergrowth occurs between structurally or graph-similar frameworks.
- Hundreds of promising framework pairs identified for new transformations.

## Abstract

Predicting and directing polymorphic transformations is a critical challenge in zeolite synthesis. Although interzeolite transformations enable selective crystallization, their design lacks predictions to connect framework similarity and experimental observations. Here, computational and theoretical tools are combined to data-mine, analyze and explain interzeolite relations. It is observed that building units are weak predictors of topology interconversion and insufficient to explain intergrowth. By introducing a supercell-invariant metric that compares crystal structures using graph theory, we show that topotactic and reconstructive (diffusionless) transformations occur only between graph-similar pairs. Furthermore, all known instances of intergrowth occur between either structurally-similar or graph-similar frameworks. Backed with exhaustive literature results, we identify promising pairs for realizing novel diffusionless transformations and intergrowth. Hundreds of low-distance pairs are identified among known zeolites, and thousands of hypothetical frameworks are connected to known zeolites counterparts. The theory opens a venue to understand and control zeolite polymorphism.