Extraction of Isotropic Electron-Nuclear Hyperfine Coupling Constants of Paramagnetic Point Defects from Near Zerp Field Magnetyoresistance Spectra via Least-Squares Fitting to Models Developed from the Stochastic Quantum Liouville Equation
We report on a method by which we can systematically extract spectroscopic information such as isotropic electron–nuclear hyperfine coupling constants from near-zero field magnetoresistance (NZFMR) spectra. The method utilizes a least squares fitting of models developed from the stochastic quantum Liouville equation. We applied our fitting algorithm to two distinct material systems: Si/SiO2 metal oxide semiconductor field effect transistors and a-Si:H metal insulator semiconductor capacitors. Our fitted results and hyperfine parameters are in reasonable agreement with existing knowledge of the defects present in the systems. Our work indicates that the NZFMR response and fitting of the NZFMR spectrum via models developed from the stochastic quantum Liouville equation could be a relatively simple yet powerful addition to the family of spin-based techniques used to explore the chemical and structural nature of point defects in semiconductor devices and insulators.
This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Extraction of isotropic electron-nuclear hyperfine coupling constants of paramagnetic point defects from near-zero field magnetoresistance spectra via least squares fitting to models developed from the stochastic quantum Liouville equation. Journal of Applied Physics 128, 12 p124504 (2020) and may be found at https://doi.org/10.1063/5.0019875.
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Work Title | Extraction of Isotropic Electron-Nuclear Hyperfine Coupling Constants of Paramagnetic Point Defects from Near Zerp Field Magnetyoresistance Spectra via Least-Squares Fitting to Models Developed from the Stochastic Quantum Liouville Equation |
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License | In Copyright (Rights Reserved) |
Work Type | Article |
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Publication Date | September 28, 2020 |
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Deposited | May 09, 2022 |
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