A metal-oxide-semiconductor radiation dosimeter with a thick and defect-rich oxide layer

Abstract

Enhancing the density of defects in the oxide layer is the main factor in improving the sensitivity of a metal-oxide-semiconductor (MOS) radiation dosimeter. This paper reports a novel MOS dosimeter with a very thick and defect-rich oxide layer fabricated by MEMS technology. The category of defects in SiO2 and their possible effect on the radiation dose sensing was analyzed. Then, we proposed combining deep-reactive-ion etching, thermal oxidation and low pressure chemical vapor deposition to realize an oxide layer containing multiple and large interfaces which can increase defects significantly. The trench-and-beam structure of silicon was considered in detail. The fabrication process was developed for obtaining a thick and compact MEMS-made SiO2. Our devices were irradiated by γ-rays of 60Co at 2 Gy per minute for 2 h and a thermally stimulated current (TSC) method was used to determine the readout of the dosimeters. Results show that there is a peak current of about 450 nA, indicating a total TSC charge of 158 μC and sensitivity of 1.1 μC mm−3·Gy, which is 40 times the sensitivity of previous MOS dosimeters.

Radiation sensitive MOSFETs irradiated with various positive gate biases

“…The most common name for pMOSFETs used as radiation dosimeters (dosimetric pMOSFETs) is radiation sensitive field-effect transistors (RADFETs). New types of these transistors are being intensively investigated, with the use of new technologies (Abe et al, 2020;Cramer et al, 2018;Jain et al, 2020;Kahraman et al, 2020;Lai et al, 2017;Lee et al, 2018;Liu et al, 2016;Tamersit, 2019;Zeidell et al, 2020), as well as the commercial transistors (Carvajal et al, 2017). Very intensive researches are being carried out in order to improve the characteristics of RADFETs, primarily their sensitivity and recovery (Andreev et al, 2020;Aleksandrov, 2015;Biasi et al, 2020;Carbonetto et al, 2020;Dubey et al, 2018;Kulhar et al, 2019;Sampaio et al, 2020;Yilmaz et al, 2017).…”