An Evaluation of Containment Materials for High Temperature Metal Thermal Storage
Bibliographic record
Abstract
Concentrated solar power (CSP) must decrease its levelized cost of electricity (LCOE) below the DOE SunShot program targets of 6 ¢/kWhe and improve its reliability to enable widespread adoption. Two features of CSP that will decrease LCOE and improve reliability are higher operating temperatures for the power cycle and thermal energy storage (TES). Thermaphase Energy and San Diego State University are developing the Liquid Metal Thermal Energy Storage System (LiMTESS), an innovative TES system based on phase change in Al-Si and Mg-Si alloys that stores thermal energy produced by gas-cooled solar receivers at temperatures above 800 C. Proper containment for Al-Si and Mg-Si alloys is critical for LiMTESS commercialization. Any containment vessel must be simultaneously compatible with the molten alloys and high-temperature oxidizing gases (e.g., air), facilitate heat transfer between the alloys and high-temperature oxidizing gases, and accommodate internal stresses associated with TES operation. A ceramic-metallic composite material (TCON) and select ceramics such as siliconized silicon carbide (SiSiC) and alumina initially showed promise in meeting these requirements. A series of thermal cycling tests were performed to check the integrity of the containment vessels. TCON produced macroscopic nodules during the thermal cycling that eliminated it from further consideration. On the other hand, SiSiC performed well when exposed to high-temperature, AlSi36, MgSi56, and air. To further evaluate SiSiC as a containment material, the research team conducted multiple thermal cycles with variable temperature profiles, duration of test, and gas environments. Before and after each thermal cycle, the team conducted a mass analysis and performed SEM and EDS analysis on prepared, treated samples. The results confirm SiSiC is a good candidate for a containment vessel. At this point the research team is evaluating Morcoset, a silicon carbide-based mortar, for creating an air-tight seal for SiSiC. The research team assessed the quality of the seal by using the mortar to seal MgSi56 and conducted thermal cycling tests to compare the mass loss of the system due to Mg vapor escaping the system to that of a controlled system with no alloys sealed. Results confirmed that Mg vapor did not exit the system. There is still more work to do, but preliminary results indicate the Morcoset + SiSiC system is a good containment system for AlSi36/MgSi56. In this paper the results of the long-duration thermal cycling tests as well as electron micrographs of the containment seals and phase change materials are presented.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".