Interface circuits for affinity-free, label-free molecular detection platform
Abstract/Contents
- Abstract
- The field of molecular diagnostics is dominated by affinity-based techniques (e.g., ELISA) where the critical signal processing steps are implemented in the chemical domain. This makes affinity-based techniques time consuming, expensive, and difficult to execute reliably outside of a laboratory environment. Affinity-free techniques address these problems by implementing the critical signal processing steps in the digital domain, where computation is more flexible and efficient. In this thesis we describe the development and implementation of electronic instrumentation for an affinity-free molecular sensing platform that records the vibrational signatures of proteins in blood using a nanoscale electrochemical interface. The sensing mechanism relies on coherent interference of electron wave functions at the interface between a nanoscale working electrode and a liquid electrolyte. Coherence at the sensing interface is enabled by low-noise potentiostatic feedback, which reduces the effective temperature of the electrons.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2019; ©2019 |
| Publication date | 2019; 2019 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Fischer, Sean |
|---|---|
| Degree supervisor | Murmann, Boris |
| Thesis advisor | Murmann, Boris |
| Thesis advisor | Arbabian, Amin |
| Thesis advisor | Howe, Roger Thomas |
| Degree committee member | Arbabian, Amin |
| Degree committee member | Howe, Roger Thomas |
| Associated with | Stanford University, Department of Electrical Engineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Sean Fischer. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2019. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2019 by Sean Fischer
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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