Determination of Specific Heat of Eutectic Indium – Bismuth-Tin Liquid Metal Alloys as a Test Material for Liquid Metal - Cooled Applications
Bibliographic record
Abstract
Currently, Russia, India, China, France, South Korea, and Japan are actively pursuing liquid metal cooled applications such as liquid cooled metal nuclear reactor concepts. The liquid metal coolants being considered for these designs are sodium, lead and lead-bismuth eutectic; these designs utilize reactive and toxic materials at temperatures up to 1073 K for nuclear power plant operations and other similar applications. To simulate these systems with the actual coolant material requires a high level of safety systems. Use of these materials in university experimental laboratory settings is difficult due to the safety hazards and that lead (Pb) is a designated substance requiring special permission to use. Therefore, a less toxic and less reactive liquid metal that can be used to simulate liquid metal cooled flows will allow for a greater number of investigations and experimentation of liquid metal flow with regards to the field of thermal hydraulics. Good candidates for a liquid metal experimental fluid are alloys from the indium-bismuth-tin system such as Fields metal, which by weight percent is 51% indium, 32.5% bismuth and 16.5% tin and possesses a melting temperature of 333 K. However, the thermodynamic properties of Fields metal and similar alloys in their liquid state are not well described in literature. This work experimentally measures the specific heat of the eutectic alloys of theindium-bismuth-tin tertiary system using a differential scanning calorimeter technique and analyzes the results to determine if the thermodynamic properties of the system have sufficient scaling for experimental modeling applications. The results verify the melting temperatures of the alloys and establish a relationship between temperature and specific heat.
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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 | 0.001 | 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".