Harmonizing life cycle assessment studies of emerging technologies: The case of virgin and recycled carbon fibers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of carbon fibers has expanded beyond aerospace to renewable energy and automotive sectors, driving demand for low-cost, eco-friendly alternatives to energy-intensive PAN-based production. This study Identified 28 Life cycle assessment (LCA) articles, encompassing 56 inventories for virgin and recycled carbon fibers. Following a screening process, 10 inventories representing distinct technologies were harmonized by aligning functional units, system boundaries, and background systems for meaningful comparison. Supercritical hydrolysis, a promising alternative, showed the lowest environmental impact, while energy-autonomous pyrolysis exhibited negative greenhouse gas emissions but produced fibers with 80 % of virgin tensile strength. This study represents the first attempt to harmonize LCAs of emerging technologies, addressing incomparability issues in published research to enable meaningful comparisons. It evaluates the reproducibility of LCA studies and offers recommendations for improvement. Additionally, it provides insights into the environmental impacts of emerging carbon fiber production and recycling technologies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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