First evidence of dominant influence of E × B drifts on plasma cooling in an advanced slot divertor for tokamak power exhaust
Bibliographic record
Abstract
Abstract Addressing power exhaust in tokamaks is presently recognized as one of the major remaining open issues for the development of fusion reactors. At the forefront of this endeavor is the effort to develop an advanced divertor by maximizing dissipation of plasma power and momentum inside the divertor. Here, we demonstrate, for the first time, that the electromagnetic ( E × B ) drifts exert a key influence on plasma and gas dynamics in a new advanced slot divertor in the DIII-D tokamak, named the small angle slot (SAS). SAS leverages the effect of drifts to achieve a highly dissipative divertor with electron temperature T e ≲ 10 eV over a wide range of plasma densities, for ion B × ∇ B away from the divertor, as used for advanced tokamak operation on DIII-D. Modeling with the SOLPS-ITER code shows that for this drift direction, the E × B flow carries particles toward the outer common flux region (CFR) via the private flux region (PFR), reinforcing neutral recycling and enhancing divertor dissipation. In contrast, for the opposite field direction, the E × B flow carries particles away from the outer CFR into the PFR, offsetting the anticipated SAS geometric effects. This finding is an important step in the understanding of the behavior of advanced divertors for achieving a power exhaust solution for fusion reactors.
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 | 0.000 | 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".