Tailoring recognition clefts from non-specific recognition matrices in mixed molecular arrays

Area of Science:

• Materials Science
• Surface Chemistry
• Nanotechnology

Background:

• Fabricating multi-component organic interfaces with controlled molecular arrangements is crucial for advanced applications.
• Understanding ligand-surface interactions and self-assembly is key to designing functional interfaces.

Purpose of the Study:

• To prepare and characterize multi-component organic interfaces with molecular-level mixing on gold surfaces.
• To investigate the self-assembly behavior and pattern formation of mixed ligands.
• To explore the potential of these interfaces as recognition matrices for dopamine detection.

Main Methods:

• Self-assembly of 4-(6-(thiophene-3-carbonyloxy)hexyloxy)benzoic acid (T6BA) and (±)-α-lipoic acid on gold surfaces.
• Characterization of molecular-level mixing using host-guest chemistry with β-cyclodextrin.
• Surface pattern analysis revealing stripe-like structures due to ligand length mismatch.
• Cyclic voltammetry to study charge transfer properties and anion effects.

Main Results:

• Successfully prepared multi-component organic interfaces with molecular-level mixing.
• Observed stripe-like patterns formed by co-adsorbed T6BA and (±)-α-lipoic acid due to conformational entropy.
• Demonstrated the utility of the mixed molecular array as a recognition matrix for dopamine detection in the presence of ascorbic acid.
• Confirmed that charge transfer in T6BA self-assembled monolayers is influenced by the electrolyte's anion type.

Conclusions:

• Mixed organic interfaces with tunable stripe patterns can be fabricated by controlling ligand composition and exploiting length mismatch.
• These patterned interfaces show promise for selective dopamine detection, applicable to various surface geometries.
• The charge transport properties of the self-assembled monolayers are sensitive to the surrounding electrolyte environment.