Automated Endurance Characterization of Phase Change Memory Article Swipe
Henriette Padberg
,
Abbas Espiari
,
Kristoffer Schnieders
,
Alexander Kiehn
,
Abdur Rehman Jalil
,
Rainer Waser
,
Stephan Menzel
,
Stefan Wiefels
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/access.2025.3562434
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/access.2025.3562434
Phase change memory cells are outstanding candidates for processing-in-memory and neuromorphic computing. The high endurance, low cycle-to-cycle variability, and low read noise especially suit many applications, whereas the high cell-to-cell variability poses a challenge, since each cell serves slightly different results. Therefore, automated characterization is necessary to create a sufficient statistical database to thoroughly study the switching behavior. This paper introduces a sophisticated algorithm for the endurance measurement of phase change memory cells using the aixMATRIX setup by aixACCT Systems. The algorithm is able to perform endurance measurements on devices over an entire sample, adjusting the biasing parameters according to the switching behavior of each cell and sorting out nonfunctional cells. The stepping between the cells is performed automatically. We highlight the benefits of our algorithm by providing an in-depth analysis of all devices on one phase change memory in a bridge geometry sample.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2025.3562434
- OA Status
- gold
- Cited By
- 1
- References
- 23
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4409581512Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/access.2025.3562434Digital Object Identifier
- Title
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Automated Endurance Characterization of Phase Change MemoryWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-01-01Full publication date if available
- Authors
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Henriette Padberg, Abbas Espiari, Kristoffer Schnieders, Alexander Kiehn, Abdur Rehman Jalil, Rainer Waser, Stephan Menzel, Stefan WiefelsList of authors in order
- Landing page
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https://doi.org/10.1109/access.2025.3562434Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1109/access.2025.3562434Direct OA link when available
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Computer science, Characterization (materials science), Phase-change memory, Phase change, Materials science, Engineering, Engineering physics, NanotechnologyTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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23Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.sorting | 107 |
| abstract_inverted_index.whereas | 26 |
| abstract_inverted_index.Systems. | 79 |
| abstract_inverted_index.analysis | 130 |
| abstract_inverted_index.behavior | 102 |
| abstract_inverted_index.benefits | 122 |
| abstract_inverted_index.database | 51 |
| abstract_inverted_index.geometry | 142 |
| abstract_inverted_index.in-depth | 129 |
| abstract_inverted_index.results. | 40 |
| abstract_inverted_index.slightly | 38 |
| abstract_inverted_index.stepping | 112 |
| abstract_inverted_index.according | 98 |
| abstract_inverted_index.adjusting | 94 |
| abstract_inverted_index.aixMATRIX | 75 |
| abstract_inverted_index.algorithm | 63, 81, 125 |
| abstract_inverted_index.automated | 42 |
| abstract_inverted_index.behavior. | 57 |
| abstract_inverted_index.different | 39 |
| abstract_inverted_index.endurance | 66, 86 |
| abstract_inverted_index.highlight | 120 |
| abstract_inverted_index.necessary | 45 |
| abstract_inverted_index.performed | 117 |
| abstract_inverted_index.providing | 127 |
| abstract_inverted_index.switching | 56, 101 |
| abstract_inverted_index.Therefore, | 41 |
| abstract_inverted_index.candidates | 6 |
| abstract_inverted_index.challenge, | 33 |
| abstract_inverted_index.computing. | 11 |
| abstract_inverted_index.endurance, | 14 |
| abstract_inverted_index.especially | 22 |
| abstract_inverted_index.introduces | 60 |
| abstract_inverted_index.parameters | 97 |
| abstract_inverted_index.sufficient | 49 |
| abstract_inverted_index.thoroughly | 53 |
| abstract_inverted_index.measurement | 67 |
| abstract_inverted_index.outstanding | 5 |
| abstract_inverted_index.statistical | 50 |
| abstract_inverted_index.variability | 30 |
| abstract_inverted_index.cell-to-cell | 29 |
| abstract_inverted_index.measurements | 87 |
| abstract_inverted_index.neuromorphic | 10 |
| abstract_inverted_index.variability, | 17 |
| abstract_inverted_index.applications, | 25 |
| abstract_inverted_index.nonfunctional | 109 |
| abstract_inverted_index.sophisticated | 62 |
| abstract_inverted_index.automatically. | 118 |
| abstract_inverted_index.cycle-to-cycle | 16 |
| abstract_inverted_index.characterization | 43 |
| abstract_inverted_index.processing-in-memory | 8 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.4099999964237213 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.69617318 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |