Soft and hard X-ray technologies are now widely used in the field of medical physics (radiation therapy), 3-D object imaging (healthcare and forensic), and in-depth material probing (microscopy), etc. Particularly, in clinical medicine, hard X-rays and charged particles are mostly used for radiation therapy and imaging to treat cancer, spot tumors, and damage malignant tumors. In this sense, the modern radiation therapy treatment is driven by the ongoing demand for suitable dosimeters for accurate dose measurement in various radiation beams (photon, proton, electron, ion, etc.). In recent times, dosimetry at small fields has emerged to deliver precise and highly controlled doses at the right location in the human body for destroying cancerous cells while sparing surrounding healthy tissues. However, the industrially developed dosimeters/detectors are ill-suited for small fields due to significant size requirements, volume averaging effect, lack of sensitivity and spatial resolution, low signal-to-noise ratio, significant corrections, Cerenkov effect, etc. Thus, quality treatment is still hampered and continues to risk the patients. Till now, no detector has been introduced to address these issues and for versatile use. In addition, scintillator-based imaging systems still suffer from low compactness, modest response time, and low spatial resolution, which present strong limitations in the existing technology.
In this context, this research project aims to design and develop a novel, small-scale, real-time, and highly sensitive X-ray/H+ Micro/Nano Scintillating Detector (X-MiND). The detectors are planned to be tested for high-energy photon and particle beam characterizations, small-field dosimetry, and high sensitivity. Subsequently, a nanometric scintillating detector is planned to be demonstrated in surface physics applications, targeting high-resolution imaging. Therefore, the medical outcomes of this research will explore miniaturized dosimetry and precise dose verification in the small fields. The physics outcomes are expected to be applied in direct surface imaging. The new fundamental knowledge developed in this project could be applied to multiple domains.
