Non-destructive 3D doping imaging of silicon sensors
Abstract
Silicon sensors are the foundational detection medium for X-rays and charged particles. While their bulk dopant distribution determines device performance, it is conventionally assumed homogeneous because traditional profiling is destructive, spatially restricted, and insensitive at the relevant concentrations. Here we introduce a non-destructive 3D doping imaging technique that turns the readout electronics of a charge-integrating hybrid pixel detector into a massively parallelized capacitance-voltage profiler. With a few tens of micrometres of 3D resolution over wafer-scale areas at concentrations on the order of 1011 cm−3, we image the bulk doping concentration of operational sensors. Macroscopically, we resolve depth-evolving concentric doping rings; microscopically, we uncover scattered doping anomalies that distort local electric fields. The rings modulate the depletion voltage, while the anomalies disrupt local charge collection, a previously overlooked cause of pixel yield and performance degradation. By bridging manufacturing signatures with microscopic defects, this approach provides a non-destructive framework for sensor characterization and yield optimization.
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BibTeX
@misc{xie2026nondestructive,
title = {{Non-destructive 3D doping imaging of silicon sensors}},
author = {Xiangyu Xie and Anna Bergamaschi and Maria Carulla and Roberto Dinapoli and Erik Fröjdh and Viktoria Hinger and Davide Mezza and Aldo Mozzanica and Jonathan Mulvey and Bernd Schmitt and Saverio Silletta and Jiaguo Zhang},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.08769},
eprint = {2609.08769},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.08769},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Non-destructive 3D doping imaging of silicon sensors
AU - Xiangyu Xie
AU - Anna Bergamaschi
AU - Maria Carulla
AU - Roberto Dinapoli
AU - Erik Fröjdh
AU - Viktoria Hinger
AU - Davide Mezza
AU - Aldo Mozzanica
AU - Jonathan Mulvey
AU - Bernd Schmitt
AU - Saverio Silletta
AU - Jiaguo Zhang
PY - 2026
DA - 2026/09/08
PB - arXiv
DO - 10.48550/arxiv.2609.08769
UR - https://arxiv.org/abs/2609.08769
AB - Silicon sensors are the foundational detection medium for X-rays and charged particles. While their bulk dopant distribution determines device performance, it is conventionally assumed homogeneous because traditional profiling is destructive, spatially restricted, and insensitive at the relevant concentrations. Here we introduce a non-destructive 3D doping imaging technique that turns the readout electronics of a charge-integrating hybrid pixel detector into a massively parallelized capacitance-voltage profiler. With a few tens of micrometres of 3D resolution over wafer-scale areas at concentrations on the order of 10^11 cm^−3, we image the bulk doping concentration of operational sensors. Macroscopically, we resolve depth-evolving concentric doping rings; microscopically, we uncover scattered doping anomalies that distort local electric fields. The rings modulate the depletion voltage, while the anomalies disrupt local charge collection, a previously overlooked cause of pixel yield and performance degradation. By bridging manufacturing signatures with microscopic defects, this approach provides a non-destructive framework for sensor characterization and yield optimization.
ER -