Semiconductor Superlattice with Remarkable Raman Enhancement for Ultrafast Culture-Free Sensing of Multiple Pathogens

Surface-enhanced Raman spectroscopy (SERS) is an optical ultrasensitive analytical method, which provides special chemical fingerprints and enables noninvasive identification of trace biological species. Traditional noble-metal SERS substrates often require surface engineering to mitigate nonspecific adsorption and background interference in complex biological matrices. Recently, semiconductors have demonstrated great potential as a complementary route, where weaker nonspecific adsorption and energy-level-matched charge transfer-based enhancement can yield highly selective readouts. Unfortunately, low enhancement performance limits their practical applications for trace analysis. Here, we report a Ga-doped ZnO superlattice SERS substrate exhibiting a record-high free carrier density of 9.23 × 10 21 cm –3 among semiconductors as well as a remarkable SERS performance factor on par with noble metals. The exceptional Raman enhancement arises from unique characteristics of atomic-level alternating interfaces, enabling effective charge separation and a novel light-induced hot electron transfer pathway. Notably, self-trapped states induced by strong electron–phonon coupling inherent to superlattices further facilitate charge separation and magnify SERS signals. We subsequently integrate this substrate into an ultrafast culture-free SERS platform for the simultaneous identification of five ventilator-associated pneumonia (VAP) pathogens with a detection limit of 1.0 CFU/mL, exhibiting 100% accuracy involving 50 hospitalized patients suspected of VAP. Significantly, the total detection time is reduced from more than 48–72 h to 10 min, and the per-test cost is estimated down to US$0.15. To our knowledge, this is the first report of Raman enhancement based on semiconductor superlattice, which offers a promising strategy for multiplex screening of biological species, paving the way for next-generation point-of-care diagnostic technologies.