Kun-Yu Lai1,Thi Anh Nguyet Nguyen1
National Central University1
Kun-Yu Lai1,Thi Anh Nguyet Nguyen1
National Central University1
Detecting single molecules is a formidable challenge. Surface-enhanced Raman spectroscopy (SERS) is one of the few techniques that can achieve the goal. To verify the presence of single molecules with SERS, the bianalyte proof is the most adopted approach since it is a statistical result from thousands of spectra, rather than the conclusion based on the blinking signals at few selected spots. However, the bianalyte method relies on an undesirable nature of SERS, i.e., the hot spot (SERS-active regions) is too small (< 10 nm) to cover two or more molecules. Since it is extremely difficult to control the size of a hot spot in a scalable manner, only a very limited portion (< 1%) of the diluted molecules can yield detectable Raman signals.<br/><br/>In this work, we demonstrate an abnormal single-molecule signal by SERS, covering 89.6% of the scanned spots. The result was achieved by making the hot spot big enough to simultaneously boost the signals from two or more single molecules. The hot-spot expansion was accomplished by coupling the localized surface plasmons at every Au nanoparticle with electrons confined by the subsurface InGaN quantum dots (QDs). This SERS configuration allows all of the dense Au nanoparticles to become the intensity-boost centers. Thus, any single molecule adsorbed on the SERS substrate can be easily captured by the Au-QD complexes, making single-molecule detection a prevailing event, instead of a rare instance.<br/><br/>With the greatly expanded SERS-active region, the single molecules can deliver stable signals by staying within the “hot surface” before and after the thermal diffusion upon laser excitation. This is not achievable with the conventional hot spots, where blinking signals are often observed by the SERS detection of diluted analytes. Our approach not only changes the bianalyte principle, but also allows researchers to analyze the molecular dynamics with reliable data.