ABSTRACT
CdZnTe (CZT) is a promising commercial material used as a room-temperature operating semiconductor detector for gamma-ray detection. Recently, CdZnTeSe (CZTS) detectors improved upon the properties of CZT by improving homogeneity and reducing defect properties, thereby enabling higher production yield of high-quality crystals. However, addition of selenium to CZT will reduce the bandgap and increase the amount of thermally stimulated electrons, resulting in low resistivity of the crystal. In this study, the enhancement of zinc content was introduced to compensate the bandgap reduction owing to selenium addition, while maintaining the improved properties of selenium addition. The morphology and stoichiometry of CZTS were determined using scanning electron microscopy and electron probe micro-analyzer. Furthermore, the calculated bandgap with stoichiometry was compared with the measured bandgap using UV-Vis measurement and Tauc plot. The electrical, chemical, and other spectroscopic properties were characterized using an I-V curve, X-ray photoelectron spectroscopy, and gamma-spectroscopic techniques, respectively. Moreover, it was proven that the high zinc CZTS can exhibit superior properties owing to selenium addition without affecting the bandgap reduction.
ABSTRACT
Perovskite single crystals are actively studied as X-ray detection materials with enhanced sensitivity. Moreover, the feasibility of using perovskites for self-powered devices such as photodetectors, UV detectors, and X-ray detectors can significantly expand their application range. In this work, the charge carrier transport and photocurrent properties of MAPbBr3 single crystals (MSCs) are improved by the mechanochemical surface treatment using glycerin combined with an additional electrode design that forms an ohmic contact. The sensitivity of MSC-based detectors and pulse shape generated by X-rays are enhanced at various bias voltages. The synthesized MSC detectors generate direction-dependent photocurrents, which indicate the presence of a polarization-induced internal electric field. In addition, photocurrent signals are produced by X-rays with energies greater than 1 MeV under a zero-bias voltage. This work demonstrates a high application potential of perovskites as self-powered detectors for X-rays with energies exceeding 1 MeV.
ABSTRACT
In this study, we perform bone mineral density (BMD) calculation by designing a layered sensor module (LSM) that divides high- and low-energy spectra from a single shot of X-rays. Gamma-ray evaluation supports this mechanism; low-energy gamma rays are absorbed in the front detector, whereas high-energy gamma rays are absorbed in the rear detector. In this phantom study, LSM divides a single shot of X-ray into two spectra with different distributions of energy, thereby affording X-ray images with different properties, such as contrast and gray scale. The region of interest (ROI) is classified by the Prewitt operator to sort the pixels for BMD calculation or Rs value. The calculated final value is 1.2051 g/cm2 with a standard deviation (SD) of 0.3690 g/cm2, as obtained from our previous study. An improved SD results from the layered structure with two channels for signal processing, the introduction of Rs value, and the use of Prewitt filter to sort reliable data. Overall, this study displays the feasibility of LSM for BMD calculation with a small error, thereby enabling the diagnosis of osteoporosis with novel mechanism.
Subject(s)
Bone Density , Osteoporosis , Humans , Radiography , Osteoporosis/diagnostic imaging , Phantoms, Imaging , X-RaysABSTRACT
Biomedical databases grow by more than a thousand new publications every day. The large volume of biomedical literature that is being published at an unprecedented rate hinders the discovery of relevant knowledge from keywords of interest to gather new insights and form hypotheses. A text-mining tool, PubTator, helps to automatically annotate bioentities, such as species, chemicals, genes, and diseases, from PubMed abstracts and full-text articles. However, the manual re-organization and analysis of bioentities is a non-trivial and highly time-consuming task. ChexMix was designed to extract the unique identifiers of bioentities from query results. Herein, ChexMix was used to construct a taxonomic tree with allied species among Korean native plants and to extract the medical subject headings unique identifier of the bioentities, which co-occurred with the keywords in the same literature. ChexMix discovered the allied species related to a keyword of interest and experimentally proved its usefulness for multi-species analysis.
