Bibliographic record
Abstract
The focus of this dissertation is on the deployment and characterization of a micro-scale aerosol-jet additive manufacturing technology to print highly conductive and flexible graphene-based patterns. For this purpose, a highly concentrated graphene ink with a viscosity of 21 cP and 3.1 mg/ml graphene flakes with the lateral size below 200 nm was developed and adopted for the aerosol-jet printing process to make a reliable and repeatable graphene deposition on the treated Si/SiO2 wafers. To this end, the influence of the most significant process parameters, including the atomizer power, the atomizer flow rate, and the number of the printed layers, on the size and properties of graphene patterns was studied. Results showed that the aerosol-jet printing process is capable of printing micro-scale graphene pattern with variable widths in the range of 10 to 90 micron. These patterns, as the finest printed graphene patterns, with resistivity as low as 0.018 Ω.cm and a sheet resistance of 1.64 kΩ/□ may ease the development of miniaturized printed electronic applications of graphene. \nIn this work, a laser processing protocol for the heat treatment of the printed graphene patterns was also developed, and the results were compared with the counterpart results obtained by the conventional heat treatment process carried out in a furnace. A continuous-wave Erbium fiber laser was used to enhance electrical properties of the aerosol-jet printed graphene patterns through removing solvents and a stabilizer polymer. The laser power and the process speed were optimized to effectively treat the printed patterns without compromising the quality of the graphene flakes. Furthermore, a heat transfer model was developed, and its results were utilized to optimize the laser treatment process. It was found that the laser heat treatment process with a laser speed of 0.03 mm/s, a laser beam diameter ~50 µm, and a laser power of 10 W results in pure graphene patterns with no excessive components. The results suggested that the laser processing has the capability of removing stabilizer polymers and solvents through a localized moving heat source, which is preferable for flexible electronics with low working temperature substrates. \nThis dissertation also addresses the deployment of a graphene/silver nanoparticle (Ag NP) ink in an aerosol-jet additive manufacturing system in order to print highly conductive and flexible graphene/Ag patterns for flexible printed electronics. A graphene/Ag NP ink was developed using stabilized graphene powder, viscose Ag NP ink, and solvents compatible with the printing system. Printing with this ink produced a uniform microstructure and crack-free printed interconnects. With a mean resistivity of 1.07×〖10〗^(-4) Ω.cm, these interconnects are about 100 times more conductive than graphene and three times more conductive than Ag NP interconnects printed with the same printing system. With their high degree of conductivity and a level of flexibility identical to that of graphene printed patterns, concluded from bending test results, graphene/Ag aerosol-jet printed patterns may therefore be considered as an efficient candidate compared to either graphene or Ag NP printed patterns for flexible electronics.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".