Use of Thermal Black as Eco-Filler in Thermoplastic Composites and Hybrids for Injection Molding and 3D Printing Applications
Bibliographic record
Abstract
Thermal black (TB) is one of the purest and cleanest forms of carbon black (CB) commercially available. TB is manufactured by the decomposition of natural gas in the absence of oxygen while the common furnace CB is derived from the burning of organic oil. TB has a larger particle size, a lower surface area, and lower level of particle aggregation, while being the most eco-friendly grade among the CB family. This study is the first-time evaluation of TB as filler in composites and hybrids based on thermoplastics such as polypropylene (PP), polyamide 6 (PA6), polyphenylene sulfide (PPS), and acrylonitrile butadiene styrene (ABS). TB loadings in composites were varied from 1 up to 40 wt. % and, in hybrids, the TB was used in combination with carbon fibers (CFs) at total contents up to 20 wt. %. TB-containing composites and hybrids based on PA6 and ABS were also extruded in filaments, used in 3D printing, and the obtained 3D printed parts were characterized. TB provided a very high loadability in thermoplastics while preserving their viscosity and performance. TB can replace a fraction of expensive CFs in composites without important changes in the composites' performance. The composites and hybrids exhibited electrical resistivity and good mechanical and thermal properties when compared to commercial compounds, while enabling significant cost savings. TB also showed to be an excellent coloring agent. TB proved to be an outstanding eco-filler for compounds to be used in injection molding and 3D printing technologies.
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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".