Zinc oxide is a unique n-type semiconducting material, owing to wide bandgap of ~3.37 eV, non-toxic, bio-safe and biocompatible with high isoelectric point of ~9.5, make it as promising biomaterial to be utilized as sensing matrix in biosensor applications. In addition, ZnO that possess high electron affinity provide a good conduction pathway for the electrons hence result in significant electrical signal change upon detection to target biomolecules. Moreover, high surface area of ZnO nanorod enhance immobilization of enzymes, hence, increase the device performance. Field effect transistor (FET)-based biosensor offer simplicity in handling and label-free, has also become research topic among researchers for novel biosensor development. This review aims to explore the preparation of ZnO nanorod using hydrothermal method and investigate the fabrication of ZnO nanorod-based FET biosensor. Thus, contribute to enhance understanding towards biosensor development for health monitoring, especially based on FETs structure devices.
We study the induced defects in the depth profiling of the silicon structure after being implanted with carbon and followed by high energy proton irradiation. It has been reported before that the formation of the optically active point-defect, specifically the G-centre is due to the implantation and irradiation of carbon and proton, respectively. It is crucial to quantify the diffusional broadening of the implanted ion profile especially for proton irradiation process so that the radiation damage evolution can be maximized at the point-defect formation region. Profiling analysis was carried out using computational Stopping and Range of Ions in Matter (SRIM) and Surrey University Sputter Profile Resolution from Energy Deposition (SUSPRE) simulation. The energies of carbon ions adopted for this investigation are 10, 20, 30, and 50 keV, while proton irradiation energy was kept at 2 MeV. Photoluminescence measurements on silicon implanted with carbon at different energies were carried out to study the interrelation between the numbers of vacancies produced during the damage event and the peak emission intensities.
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