Leibniz-Institute for New Materials

Using the tabular foundation model TabPFN informed by a small library of living hydrogels, this work predicts macroscopic material properties of Escherichia coli-produced living hydrogels containing CsgA-based fibres fused to genetically encoded PEG-like biopolymers from genetic and process parameters, achieving the strongest prediction for storage modulus G' (R2 = 85.1%) on an independent validation set with a 48.0% RMSE reduction versus linear regression, and further enabling property-guided design to identify parameters for desired properties.

Using the tabular foundation model TabPFN informed by a small library of living hydrogels, this work predicts macroscopic material properties of Escherichia coli-produced living hydrogels containing CsgA-based fibres fused to genetically encoded PEG-like biopolymers from genetic and process parameters, achieving the strongest prediction for storage modulus G' (R2 = 85.1%) on an independent validation set with a 48.0% RMSE reduction versus linear regression, and further enabling property-guided design to identify parameters for desired properties.