Optimization of RF-ICP Tungsten Deposits for Plasma Facing Components
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
Tungsten (W) and its alloys are promising candidate materials for plasma facing components (PFC) in future fusion reactors. Despite having many advantages (the highest melting point of all metals, high density, low vapor pressure), tungsten also possesses several drawbacks, such as poor machinability and weldability. One of the nowadays considered PFC production routes is plasma spraying. For this, the conventional gas-stabilized atmospheric plasma torches have inherent critical limitations (insufficient plasma enthalpy to efficiently melt the tungsten particles, susceptibility to oxidation at elevated temperatures). The novel radio frequency inductively coupled plasma (RF-ICP) is a unique system capable of overcoming these limitations. Using RF-ICP, more efficient melting of tungsten particles and controlled atmosphere provide a unique possibility to produce dense, oxides-free deposits.\nIn our study, TekSpray-15 RF-ICP (Tekna, Canada) was used for the preparation of tungsten coatings from two different feedstock powders under varying system parameters (torch power, chamber pressure). Their influence was studied via SEM observations of the deposits microstructure as well as XRD analyses.
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