[Data] Acoustic emission signature of martensitic transformation in laser powder bed fusion of Ti6Al4V-Fe, supported by operando X-ray diffraction
Bibliographic record
Abstract
Esmaeilzadeh, R., Pandiyan, V., Van Petegem, S., Van der Meer, M., Nasab, M.H., de Formanoir, C., Jhabvala, J., Navarre, C., Schlenger, L., Richter, R. and Casati, N., 2024. Acoustic emission signature of martensitic transformation in laser powder bed fusion of Ti6Al4V-Fe, supported by operando X-ray diffraction. Additive Manufacturing, 96, p.104562. DOI : https://doi.org/10.1016/j.addma.2024.104562 Open data structure The database for this publication consists of two main folders: Acoustic Recording Data and Synchrotron X-ray Measurements. The subsets within the synchrotron X-ray data are named according to sample identification, printing conditions, and alloy composition. For example, the label Ti0Fe_C_L12 indicates a sample composed of Ti-6Al-4V alloy with no Fe addition. The "C" denotes conduction mode melting with medium energy density, and "L12" refers to the 12th layer of the printed part. The Acoustic Data are similarly organized based on alloy composition. Within each folder, the labels "CM" and "KM" indicate the melting regime: conduction mode and keyhole mode, respectively. The accompanying numbers specify the corresponding layer of the build. This structured naming convention facilitates efficient navigation and interpretation of the dataset. The codes used for data processing and analysis are provided in the following repository. https://c4science.ch/diffusion/13225/
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.008 | 0.016 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.136 | 0.030 |
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".