Vertically-grown ZnO nanorod arrays (NRAs) on indium tin oxide (ITO)-coated polyethylene terephthalate (PET), as a top electrode of nanogenerators, were investigated for the antireflective property as well as an efficient contact surface in bare polydimethysiloxane (PDMS)-based triboelectric nanogenerators. Compared to conventional ITO-coated PET (i.e., ITO/PET), the ZnO NRAs considerably suppressed the reflectance from 20 to 9.7% at wavelengths of 300-1100 nm, creating a highly transparent top electrode, as demonstrated by theoretical analysis. Also, the interval time between the peaks of generated output voltage under external pushing forces was significantly decreased from 1.84 to 0.19 s because the reduced contact area of the PDMS by discrete surfaces of the ZnO NRAs on ITO/PET causes a rapid sequence for triboelectric charge generation process including rubbing and separating. Therefore, the use of this top electrode enabled to operate the transparent PDMS-based triboelectric nanogenerator at high frequency of external pushing force. Under different external forces of 0.3-10 kgf, the output voltage and current were also characterized.

We report the development of a surface-enhanced Raman spectroscopy sensor chip by decorating gold nanoparticles (AuNPs) on ZnO nanorod (ZnO NR) arrays vertically grown on cellulose paper (C). We show that these chips can enhance the Raman signal by 1.25 × 10 with an excellent reproducibility of <6%. We show that we can measure trace amounts of human amniotic fluids of patients with subclinical intra-amniotic infection (IAI) and preterm delivery (PTD) using the chip in combination with a multivariate statistics-derived machine-learning-trained bioclassification method. We can detect the presence of prenatal diseases and identify the types of diseases from amniotic fluids with >92% clinical sensitivity and specificity. Our technology has the potential to be used for the early detection of prenatal diseases and can be adapted for point-of-care applications.

Surface-enhanced Raman scattering (SERS) is an ultrasensitive molecular screening technique with greatly enhanced Raman scattering signals from trace amounts of analytes near plasmonic nanostructures. However, research on the development of a sensor that balances signal enhancement, reproducibility, and uniformity has not yet been proposed for practical applications. In this study, we demonstrate the potential of the practical application for detecting or predicting asymptomatic breast cancer from human tears using a portable Raman spectrometer with an identification algorithm based on multivariate statistics. This potentiality was realized through the fabrication of a plasmonic SERS substrate equipped with a well-aligned, gold-decorated, hexagonal-close-packed polystyrene (Au/HCP-PS) nanosphere monolayer that provided femtomole-scale detection, giga-scale enhancement, and <5% relative standard deviation for reliability and reproducibility, regardless of the measuring site. Our results can provide a first step toward developing a noninvasive, real-time screening technology for detecting asymptomatic tumors and preventing tumor recurrence.

A series of Eu3+-activated Gd2MoO6 phosphors were synthesized via a citric acid-assisted sol–gel route.

No abstract