A derivation of the electric field inside MAPS detectors from beam-test data and limited TCAD simulations Article Swipe
A. Santra
,
N. Hod
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1088/1748-0221/18/05/p05007
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1088/1748-0221/18/05/p05007
Solid semiconductor sensors are used as detectors in high-energy physics experiments, in medical applications, in space missions and elsewhere. Minimal knowledge of the electric field inside the elementary cells of these sensors is highly important for their performance understanding. The field governs the charge propagation processes and ultimately determines the size and quality of the electronic signal of the cell. Hence, the simulation of these sensors as detectors in different analyses relies strongly on the field knowledge. For a certain voltage applied to the cell, the field depends on the specifics of the device's growth and fabrication. The information about these is often commercially protected or otherwise very difficult to encode in state-of-the-art technology computer-aided-design (TCAD) software. In this work, we show that by taking the top-down approach, combining public beam-test data and a very limited public TCAD knowledge, we are able to effectively approximate the 3D electric field function in the pixel cell of one important and widely used example, namely the ALPIDE sensor, for simulating the charge propagation processes. Despite its broad usage worldwide, the ALPIDE field is not available to the community. We provide an effective field function, that adequately describes the sensor behaviour without trying to reconstruct further details about the device or the details behind its processing. We comment on the process by which the effective field function is derived with the help of the Allpix 2 software, and on how similar work can be performed for other devices, starting from the same grounds.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1748-0221/18/05/p05007
- https://iopscience.iop.org/article/10.1088/1748-0221/18/05/P05007/pdf
- OA Status
- hybrid
- Cited By
- 1
- References
- 27
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
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- DOI
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https://doi.org/10.1088/1748-0221/18/05/p05007Digital Object Identifier
- Title
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A derivation of the electric field inside MAPS detectors from beam-test data and limited TCAD simulationsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-05-01Full publication date if available
- Authors
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A. Santra, N. HodList of authors in order
- Landing page
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https://doi.org/10.1088/1748-0221/18/05/p05007Publisher landing page
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https://iopscience.iop.org/article/10.1088/1748-0221/18/05/P05007/pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://iopscience.iop.org/article/10.1088/1748-0221/18/05/P05007/pdfDirect OA link when available
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Computer science, Field (mathematics), Detector, Electric field, Software, Electronic engineering, Physics, Electrical engineering, Telecommunications, Engineering, Mathematics, Quantum mechanics, Pure mathematics, Programming languageTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.signal | 57 |
| abstract_inverted_index.taking | 125 |
| abstract_inverted_index.trying | 199 |
| abstract_inverted_index.widely | 159 |
| abstract_inverted_index.Despite | 172 |
| abstract_inverted_index.Minimal | 20 |
| abstract_inverted_index.applied | 82 |
| abstract_inverted_index.certain | 80 |
| abstract_inverted_index.comment | 214 |
| abstract_inverted_index.depends | 88 |
| abstract_inverted_index.derived | 225 |
| abstract_inverted_index.details | 203, 209 |
| abstract_inverted_index.further | 202 |
| abstract_inverted_index.governs | 42 |
| abstract_inverted_index.limited | 136 |
| abstract_inverted_index.medical | 13 |
| abstract_inverted_index.physics | 10 |
| abstract_inverted_index.process | 217 |
| abstract_inverted_index.provide | 187 |
| abstract_inverted_index.quality | 53 |
| abstract_inverted_index.sensor, | 165 |
| abstract_inverted_index.sensors | 3, 32, 66 |
| abstract_inverted_index.similar | 237 |
| abstract_inverted_index.voltage | 81 |
| abstract_inverted_index.without | 198 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.analyses | 71 |
| abstract_inverted_index.device's | 94 |
| abstract_inverted_index.devices, | 244 |
| abstract_inverted_index.electric | 24, 148 |
| abstract_inverted_index.example, | 161 |
| abstract_inverted_index.function | 150, 223 |
| abstract_inverted_index.grounds. | 249 |
| abstract_inverted_index.missions | 17 |
| abstract_inverted_index.starting | 245 |
| abstract_inverted_index.strongly | 73 |
| abstract_inverted_index.top-down | 127 |
| abstract_inverted_index.approach, | 128 |
| abstract_inverted_index.available | 182 |
| abstract_inverted_index.beam-test | 131 |
| abstract_inverted_index.behaviour | 197 |
| abstract_inverted_index.combining | 129 |
| abstract_inverted_index.describes | 194 |
| abstract_inverted_index.detectors | 7, 68 |
| abstract_inverted_index.different | 70 |
| abstract_inverted_index.difficult | 109 |
| abstract_inverted_index.effective | 189, 221 |
| abstract_inverted_index.function, | 191 |
| abstract_inverted_index.important | 35, 157 |
| abstract_inverted_index.knowledge | 21 |
| abstract_inverted_index.otherwise | 107 |
| abstract_inverted_index.performed | 241 |
| abstract_inverted_index.processes | 46 |
| abstract_inverted_index.protected | 105 |
| abstract_inverted_index.software, | 233 |
| abstract_inverted_index.software. | 117 |
| abstract_inverted_index.specifics | 91 |
| abstract_inverted_index.adequately | 193 |
| abstract_inverted_index.community. | 185 |
| abstract_inverted_index.determines | 49 |
| abstract_inverted_index.electronic | 56 |
| abstract_inverted_index.elementary | 28 |
| abstract_inverted_index.elsewhere. | 19 |
| abstract_inverted_index.knowledge, | 139 |
| abstract_inverted_index.knowledge. | 77 |
| abstract_inverted_index.processes. | 171 |
| abstract_inverted_index.simulating | 167 |
| abstract_inverted_index.simulation | 63 |
| abstract_inverted_index.technology | 114 |
| abstract_inverted_index.ultimately | 48 |
| abstract_inverted_index.worldwide, | 176 |
| abstract_inverted_index.approximate | 145 |
| abstract_inverted_index.effectively | 144 |
| abstract_inverted_index.high-energy | 9 |
| abstract_inverted_index.information | 99 |
| abstract_inverted_index.performance | 38 |
| abstract_inverted_index.processing. | 212 |
| abstract_inverted_index.propagation | 45, 170 |
| abstract_inverted_index.reconstruct | 201 |
| abstract_inverted_index.commercially | 104 |
| abstract_inverted_index.experiments, | 11 |
| abstract_inverted_index.fabrication. | 97 |
| abstract_inverted_index.applications, | 14 |
| abstract_inverted_index.semiconductor | 2 |
| abstract_inverted_index.understanding. | 39 |
| abstract_inverted_index.state-of-the-art | 113 |
| abstract_inverted_index.computer-aided-design | 115 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5089558504 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I53964585 |
| citation_normalized_percentile.value | 0.82348159 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |