A simple strategy based on combinatorial gold nanoparticle sizes for enhanced sensitivity in colorimetric bioanalysis

Taking advantage of salt-induced aggregation, gold nanoparticles (AuNPs) have been intensively employed in non-cross-linking strategies (NCLs) for colorimetric bioanalysis. Such a classical method is popular due to its simplicity and cost-effectiveness, but it still suffers from poor sensitivity in analytical practice. To address this issue, we simply mixed the four sizes of non-functional AuNPs (10 nm/20 nm/30 nm/40 nm) to establish a highly sensitive combinatorial system in a non-cross-linking strategy (cNCL). For comparison, we also designed four independent systems with individual sizes of AuNPs (10 nm, 20 nm, 30 nm and 40 nm, respectively) as typical non-cross-linking strategies (tNCLs). Interestingly, the cNCLs were found to have significantly enhanced sensitivity compared to each of the tNCLs in analytical performance. TEM and theoretical calculation were employed to explore this phenomenon, and it is indicated that the aggregation behaviours of cNCLs show more compact morphology by particle-to-particle stacking. We then tuned the size proportions of various AuNPs in cNCLs to evaluate the contribution of each size of the AuNPs. It appears that 10 nm AuNPs are mainly responsible for minimizing background intensity, and 40 nm AuNPs for maximizing signal intensity. Moreover, with the well-studied effect of combinatorial AuNP sizes in cNCLs, an excellent signal-to-background (S/B) ratio can be obtained, achieving at least 500-fold and 2.5-fold improvement in the aspects of optical and visual sensitivity, respectively. Such a combinatorial AuNP size-based NCL (cNCL) strategy is modification-free towards AuNPs, and the whole process can be accomplished within 10 min. The aggregation behaviour significantly impacts the optical properties and morphology, and therefore improves analytical sensitivity. With these findings, valuable insight is provided in developing sensitive and versatile colorimetric assays based on classic AuNP aggregation.