Graphene-Assisted Electrostatic Screening of Resonant Transport in MR-DWELL Dosimeters with Tunable Sensitivity--Radiation Tolerance Trade-off: A Reduced-Order Benchmark and Self-Consistent Perspective
Abstract
We propose a Multi-Resonant Double-barrier Quantum-dot-in-a-Well (MR-DWELL) dosimeter with a tunable trade-off between sensitivity and radiation tolerance, realized through graphene-assisted electrostatic screening. The sensing mechanism relies on radiation-induced trapped charge that shifts and broadens resonant tunneling states in the DWELL heterostructure. The~dimensionless capacitance ratio η=CQ/Cgeo is introduced as the universal design parameter: it~controls the screening factor S=η/(1+η) and thereby the trade-off between sensitivity and radiation hardness. For η=2.09 the effective low-dose shift coefficient is reduced threefold (from $0.14$~to 0.045 meV/mGy), while the screened architecture retains ∼ 83% of the peak tunneling current and a peak-to-valley ratio ∼ 10 after 1 MGy, thereby preserving the dosimetric sensitivity required for practical readout. The~second-derivative spectroscopy d2I/dV2 is identified as a robust experimental readout. A~reduced-order Landauer model calibrated against literature data is employed for the screening physics, while a self-consistent NEGF-Poisson-trap framework is formulated for future quantitative validation. Explicit design rules for three operating regimes (high sensitivity, balanced, maximum hardness) are provided, together with a three-population trap model that conceptually enables dose-rate discrimination in the FLASH radiotherapy regime. A~comparative analysis of model vintages and their methodological foundations is included to guide interpretation of numerical predictions.
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BibTeX
@misc{dosymova2026grapheneassisted,
title = {{Graphene-Assisted Electrostatic Screening of Resonant Transport in MR-DWELL Dosimeters with Tunable Sensitivity--Radiation Tolerance Trade-off: A Reduced-Order Benchmark and Self-Consistent Perspective}},
author = {Bigul U. Dosymova and Mikhail V. Dolgopolov},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2608.06616},
eprint = {2608.06616},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.06616},
}
RIS
TY - UNPB
TI - Graphene-Assisted Electrostatic Screening of Resonant Transport in MR-DWELL Dosimeters with Tunable Sensitivity--Radiation Tolerance Trade-off: A Reduced-Order Benchmark and Self-Consistent Perspective
AU - Bigul U. Dosymova
AU - Mikhail V. Dolgopolov
PY - 2026
DA - 2026/09/06
PB - arXiv
DO - 10.48550/arxiv.2608.06616
UR - https://arxiv.org/abs/2608.06616
AB - We propose a Multi-Resonant Double-barrier Quantum-dot-in-a-Well (MR-DWELL) dosimeter with a tunable trade-off between sensitivity and radiation tolerance, realized through graphene-assisted electrostatic screening. The sensing mechanism relies on radiation-induced trapped charge that shifts and broadens resonant tunneling states in the DWELL heterostructure. The~dimensionless capacitance ratio η=C_Q/C_geo is introduced as the universal design parameter: it~controls the screening factor S=η/(1+η) and thereby the trade-off between sensitivity and radiation hardness. For η=2.09 the effective low-dose shift coefficient is reduced threefold (from $0.14$~to 0.045 meV/mGy), while the screened architecture retains ∼ 83% of the peak tunneling current and a peak-to-valley ratio ∼ 10 after 1 MGy, thereby preserving the dosimetric sensitivity required for practical readout. The~second-derivative spectroscopy d^2I/dV^2 is identified as a robust experimental readout. A~reduced-order Landauer model calibrated against literature data is employed for the screening physics, while a self-consistent NEGF-Poisson-trap framework is formulated for future quantitative validation. Explicit design rules for three operating regimes (high sensitivity, balanced, maximum hardness) are provided, together with a three-population trap model that conceptually enables dose-rate discrimination in the FLASH radiotherapy regime. A~comparative analysis of model vintages and their methodological foundations is included to guide interpretation of numerical predictions.
ER -