| Autor: |
Moeid Jamalzadeh, Edoardo Cuniberto, Davood Shahrjerdi |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Advanced Physics Research, Vol 3, Iss 2, Pp n/a-n/a (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2751-1200 |
| DOI: |
10.1002/apxr.202300079 |
| Popis: |
Abstract Fast‐scan cyclic voltammetry (FSCV) in combination with carbon fiber (CF) sensors has been a longstanding tool for studying neurochemical signaling in the brain. However, further progress toward brain mapping requires improvements in sensitivity, chemical selectivity, and channel count. Addressing these critical needs has been an impetus behind the search for alternative carbon materials that could outperform CF. Given the significant research activities, an objective assessment of key sensor performance metrics is crucial for guiding the material discovery. Here, a framework for assessing the sensitivity and selectivity performance of FSCV sensors is put forth and visualizing the comparison in the form of a performance plot. An example of this analysis by using nanographitic carbon as a model material is provided. It is hoped that the proposed framework can help accelerate the research progress by providing an improved guideline for evaluating emerging FSCV sensors. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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