A geant4 simulation on the application of multi-layer graphene as a detector material in high-energy physics

Nurul Hidayah Mohamad Nor, and Nur Afira Anuar, and Wan Ahmad Tajuddin Wan Abdullah, and Goh, Boon Tong and Mohd Fakharul Zaman Raja Yahya, (2022) A geant4 simulation on the application of multi-layer graphene as a detector material in high-energy physics. Sains Malaysiana, 51 (10). pp. 3423-3436. ISSN 0126-6039

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Official URL: https://www.ukm.my/jsm/malay_journals/jilid51bil10...

Abstract

The excellent properties of graphene, such as its high thermal conductivity, high electrical conductivity, and high electron density, make it an ideal candidate as a detector material in high-energy physics applications. In this work, we demonstrate the feasibility of multi-layer graphene (MLG) as a detector material in a high-energy environment. The Geant4 software package was used to estimate the energy of the deposited electrons within various thicknesses of MLG, ranging from 3 to 20 nm. The efficiency of the MLG as a detector material was further analyzed from the scattering angle and the yield of the secondary particles produced from the electron interaction with the material. The incident electron’s kinetic energy used herein ranged between 30 keV and 1 GeV, at a particle fluence of 1×107 e/cm2 . The results show that the deposited energy was relatively low for the interaction with 1 MeV electrons, and dramatically increased as the thickness increases beyond 15 nm. This result was further supported by the highest yield of gamma radiation recorded by the interaction with a kinetic energy larger than 1 MeV, for thickness larger than 15 nm. The results suggest that the MLG works best as a charged particle detector in low energy ranges, while for high energy ranges, a thickness over 15 nm is suggested. The findings demonstrate that a MLG with a thickness larger than 15 nm could potentially be used as a detector material in high-energy conditions.

Item Type:Article
Keywords:Detector material; Geant4; Monte Carlo simulation method
Journal:Sains Malaysiana
ID Code:20883
Deposited By: ms aida -
Deposited On:20 Dec 2022 06:37
Last Modified:28 Dec 2022 05:27

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