Investigation of Carbon Nanotubes Mixing Methods and Functionalizations for Electrically Conductive Polymer Composites
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Bibliographic record
Abstract
The growing popularity of Poly lactic acid (PLA) is related to its biocompatibility, good mechanical properties, and its synthesis from renewable resources. PLA can be compounded with electrically conductive fillers (e.g., carbon nanotubes (CNTs)) to form carbon polymer composites (CPC). These fillers provide the conductive functionality by forming percolative paths. Featuring very low weight densities, CPCs have the potential to replace metals in the electronic industry if they exhibit similar electrical conductivities. The current challenges being faced during the mixing of CNTs in a polymer matrix are the formation of aggregates due to the strong van der Waals forces and the breakage of the CNTs during dispersion. In this study, we compare: (1) two fabrication methods to create CPCs (i.e., solution mixing by sonication and extrusion) and (2) effects of various CNT functionalization techniques (i.e., acid and plasma treatments) on the conductivity of the CPCs. First, the composites comprising of 30% PLA by weight in Dichloromethane (DCM) and CNTs in different concentrations (up to 5wt.%) are fabricated by two step sonication method (i.e., dissolving PLA in DCM and then dispersing the CNTs in the polymer solution). Second, CPCs are fabricated using a micro twin screw extruder operating at 180°C. To verify the effects of functionalization of the CNTs on the conductivity of composites, the CNTs are functionalized via three methods: - HNO3 acid functionalization, 3:1 ratio HNO3 + H2SO4 acid (stronger) functionalization and N2 plasma functionalization. CPC fibers are drawn using the solvent-cast printing method. These fibers are then tested for their electrical conductivity using the two probe method. The maximum electrical conductivity is showed by the 5% CNT concentration samples at 3.97 S/m and 25.16 S/m for the CPC fibers obtained via the solution blend and the extrusion methods, respectively. Regarding the functionalized CNTs, conductivity measurements show a negative effect of the CNTs functionalization on the electrical properties of the CPC.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it