Hybrid gold nanostructures seeded into nanotextured zinc oxide (ZnO) nanoflowers (NFs) were created for novel biosensing applications. The selected ‘spotted NFs’ had a 30-nm-thick gold nanoparticle (AuNP) layer, chosen from a range of AuNP thicknesses, sputtered onto the surface. The generated nanohybrids, characterized by morphological, physical and structural analyses, were uniformly AuNP-seeded onto the ZnO NFs with an average length of 2–3 μm. Selective capture of molecular probes onto the seeded AuNPs was evidence for the specific interaction with DNA from pathogenic Leptospirosis-causing strains via hybridization and mis-match analyses. The attained detection limit was 100 fM as determined via impedance spectroscopy. High levels of stability, reproducibility and regeneration of the sensor were obtained. Selective DNA immobilization and hybridization were confirmed by nitrogen and phosphorus peaks in an X-ray photoelectron spectroscopy analysis. The created nanostructure hybrids illuminate the mechanism of generating multiple-target, high-performance detection on a single NF platform, which opens a new avenue for array-based medical diagnostics.

No abstract

The performance of sensing surfaces highly relies on nanostructures to enhance their sensitivity and specificity. Herein, nanostructured zinc oxide (ZnO) thin films of various thicknesses were coated on glass and p-type silicon substrates using a sol-gel spin-coating technique. The deposited films were characterized for morphological, structural, and optoelectronic properties by high-resolution measurements. X-ray diffraction analyses revealed that the deposited films have a c-axis orientation and display peaks that refer to ZnO, which exhibits a hexagonal structure with a preferable plane orientation (002). The thicknesses of ZnO thin films prepared using 1, 3, 5, and 7 cycles were measured to be 40, 60, 100, and 200 nm, respectively. The increment in grain size of the thin film from 21 to 52 nm was noticed, when its thickness was increased from 40 to 200 nm, whereas the band gap value decreased from 3.282 to 3.268 eV. Band gap value of ZnO thin film with thickness of 200 nm at pH ranging from 2 to 10 reduces from 3.263eV to 3.200 eV. Furthermore, to evaluate the transducing capacity of the ZnO nanostructure, the refractive index, optoelectric constant, and bulk modulus were analyzed and correlated. The highest thickness (200 nm) of ZnO film, embedded with an interdigitated electrode that behaves as a pH-sensing electrode, could sense pH variations in the range of 2-10. It showed a highly sensitive response of 444 μAmM-1cm-2 with a linear regression of R2 =0.9304. The measured sensitivity of the developed device for pH per unit is 3.72μA/pH.

No abstract

Human chorionic gonadotropin (hCG), a glycoprotein hormone secreted from the placenta, is a key molecule that indicates pregnancy. Here, we have designed a cost-effective, label-free, in situ point-of-care (POC) immunosensor to estimate hCG using a cuneated 25 nm polysilicon nanogap electrode. A tiny chip with the dimensions of 20.5 × 12.5 mm was fabricated using conventional lithography and size expansion techniques. Furthermore, the sensing surface was functionalized by (3-aminopropyl)triethoxysilane and quantitatively measured the variations in hCG levels from clinically obtained human urine samples. The dielectric properties of the present sensor are shown with a capacitance above 40 nF for samples from pregnant women; it was lower with samples from non-pregnant women. Furthermore, it has been proven that our sensor has a wide linear range of detection, as a sensitivity of 835.88 μA mIU-1 ml-2 cm-2 was attained, and the detection limit was 0.28 mIU/ml (27.78 pg/ml). The dissociation constant Kd of the specific antigen binding to the anti-hCG was calculated as 2.23 ± 0.66 mIU, and the maximum number of binding sites per antigen was Bmax = 22.54 ± 1.46 mIU. The sensing system shown here, with a narrow nanogap, is suitable for high-throughput POC diagnosis, and a single injection can obtain triplicate data or parallel analyses of different targets.