Controlling supramolecular self-assembly across multiple length scales to prepare gels with localised properties is challenging. Most strategies concentrate on fabricating gels with heterogeneous components, where localised properties are generated by...

Peptide‐coated surfaces are widely employed in biomaterial design, but quantifiable correlation between surface composition and biological response is challenging due to, for example, instrumental limitations, a lack of suitable model surfaces or limitations in quantitatively correlating data from different surface analytical techniques. Here, we first establish a reference material that allows control over amino acid content. Reversible addition‐fragmentation chain‐transfer (RAFT) polymerisation is used to prepare a copolymer containing alkyne and furan units with well‐defined chain length and composition. Huisgen Cu(I)‐catalysed azide‐alkyne cycloaddition reaction is used to attach the model azido‐polyethyleneglycol‐amide‐modified pentafluoro‐l‐phenylalanine to the polymer. Different compositional ratios of the polymer provide a surface with varying amino acid content that is analysed by X‐ray photoelectron spectroscopy (XPS) and time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS). Nitrogen‐related signals are compared with fluorine signals from both techniques. Fluorine and nitrogen signals from both techniques are found to be related to the copolymer compositions, but the homopolymer data deviate from this trend. The approach is then translated to a heparin‐binding peptide that supports cell adhesion. Human embryonic stem cells cultured on copolymer surfaces presenting different amounts of heparin‐binding peptide show strong cell growth while maintaining pluripotency after 72 h of culture. The early cell adhesion at 24 h can be correlated to the logarithm of the normalised CH4N+ ion intensity from ToF‐SIMS data, which is established as a suitable and generalisable marker ion for amino acids and peptides. This work contributes to the ability to use ToF‐SIMS in a more quantitative manner for the analysis of amino acid and peptide surfaces.