Toward sustainable additive manufacturing of PEKK/Martian regolith composite for lightweight structural applications on Mars
Bibliographic record
Abstract
Advances in sustainable resource utilization and innovative manufacturing techniques are driving efforts toward the prospect of human settlement on Mars, led by programs such as SpaceX’s Occupy Mars initiative. One promising approach involves the development of materials and processes that leverage in-situ Martian resources. In this study, we investigate the fabrication and characterization of a composite material consisting of Polyether-Ketone-Ketone (PEKK) incorporated with Martian Regolith Simulant (MRS), targeting sustainable applications in outer space. Amorphous PEKK was pulverized and mixed with sieved MRS particles, followed by extrusion through a twin-screw extruder to produce a filament with a consistent diameter suitable for Fused Deposition Modeling (FDM). A post-processing protocol, including annealing, was implemented to optimize the degree of crystallinity and improve mechanical properties. The filament quality and dispersion of regolith within the matrix were evaluated, and the composite was characterized through mechanical and thermomechanical analyses. Based on the material properties achieved, a conceptual Mars rover wheel featuring a lightweight graded structure was designed and successfully fabricated. These results demonstrate the early-stage feasibility of producing high-quality, mechanically robust 3D-printed components from regolith-based composites, highlighting the potential of integrating additive manufacturing with local resources for sustainable extraterrestrial exploration.
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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".