Supercritical Water: A Simulation Study to Unravel the Heterogeneity of Its Molecular Structures
Bibliographic record
Abstract
(1) Background: In the quest to accurately model the radiolysis of water in its supercritical state, a detailed understanding of water's molecular structure, particularly how water molecules are arranged in this unique state, is essential. (2) Methods: We conducted molecular dynamics simulations using the SPC/E water model to investigate the molecular structures of supercritical water (SCW) over a wide temperature range, extending up to 800 °C. (3) Results: Our results show that at a constant pressure of 25 MPa, the average intermolecular distance around a reference water molecule remains remarkably stable at ~2.9 Å. This uniformity persists across a substantial temperature range, demonstrating the unique heterogeneous nature of SCW under these extreme conditions. Notably, the simulations also reveal intricate patterns within SCW, indicating the simultaneous presence of regions with high and low density. As temperatures increase, we observe a rise in the formation of molecular clusters, which are accompanied by a reduction in their average size. (4) Conclusions: These findings highlight the necessity of incorporating the molecular complexity of SCW into traditional track-structure chemistry models to improve predictions of SCW behavior under ionizing radiation. The study establishes a foundational reference for further exploration of the properties of supercritical water, particularly for its application in advanced nuclear technologies, including the next generation of water-cooled reactors and their small modular reactor variants that utilize SCW as a coolant.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".