Design, Fabrication, and Characterization of Multi-Scale Materials for Integration on Lab-on-a-Chip Devices
Bibliographic record
Abstract
Currently, molecular diagnosis is conducted by professionals in centralized laboratories, which can be time consuming, expensive, and not readily available in remote locations. This motivates the efforts to develop highly accurate, highly sensitive, and high speed lab-on-a-chip (LOC) platforms for inexpensive point-of-care (POC) diagnostics. Multi-scale materials – with tunable features from the nanometer to millimeter length-scales – have shown to enhance performance of electrodes in LOC biosensing and bioprocessing applications. The controlled fabrication of three-dimensional metallic hierarchical electrodes using standard lithographic, machining, printing, etc. techniques is complex and not suitable for rapid, dynamic, and inexpensive prototyping. The work presented herein addresses the need to develop a benchtop rapid prototyping approach to create tunable multi-scale electrodes for integration in LOC devices. In this work, rapid benchtop fabrication is carried out through a combination of xurography, to create electrodes with specific configurations, and controlled thin film wrinkling using pre-stressed polymer substrates, to structure sputtered electrodes on the nanoscale and microscale. This method creates wrinkled structures with sufficient adhesion (no peeling) and conductance (<1 Ω/󠆾󠆾 sheet resistance) for electrical applications. Further development of this method allows fabrication to be carried out completely on the benchtop using all-solution processing methods to deposit high quality thin films, with similar adhesion (no peeling) and conductance (<1 Ω/󠆾󠆾sq sheet resistance) as sputtered films, on the polymer substrates. Moreover, this fabrication technique is extended to create wrinkled nanoparticle films presenting sub-100 nm wavelengths and a dual degree of tunability, as the nanoparticles tune both the thickness and mechanical properties of the films. Structural tuning of the nanoscale and microscale architectures of wrinkled electrodes is studied with scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM), and white light interferometry, and then related to functional tuning via four-point probe measurements and electrochemical measurements. As the structure is shown to determine key functional parameters, such as resistance and surface area, various electrodes structures are designed and applied to important LOC bioprocessing and sensing applications. For example, structurally optimized electrodes are applied to low voltage cell lysis and are able to lyse bacteria at only 4 V. Furthermore, the problem of integrating three-dimensional, multi-scale wrinkled electrodes into microfluidic devices is investigated. New approaches combining surface treatment and partial curing of microchannels are developed to solve these issues and create fully contained, functional electro-fluidic devices that can withstand flow rates greater than 25 mL/min and pressures of greater than 125 kPa. Ultimately, we are able to create and integrate high quality, tunable, functional, multi-scale electrodes on the laboratory benchtop at low cost and high speed. Thus, this research enables the expedited development of LOC electrode devices that are functionally optimized through structural tuning.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".