Effect of Electric Field on Interfacial Thermal Resistance Between Silicon and Water at Nanoscales
Bibliographic record
Abstract
In this study, heat transfer rate of a nano-confined liquid is controlled by applying an electric field parallel to the heat transfer direction.Molecular Dynamics simulations are performed for deionized water confined between silicon slabs, where their surfaces oppositely charged to create an electric field perpendicular to the silicon wall to promote the electrowetting.Electric field strengths used in this study are 0, 0.18 and 0.35 V/nm.To investigate the effect of electric field on heat transfer, first water density profiles near the silicon walls are examined.Results shows that by applying electric field, water molecules near the silicon walls develop layering, which indicates the increased solid/liquid coupling.With the increasing electric field strength, an increase in the peak of the density layering is observed.Furthermore, heat transfer at the solid/liquid interface is characterized with the Kapitza length values.The results show that applying electric field reduces the interfacial thermal resistance between water and silicon due to the increased solid/liquid coupling and doubles the total heat flux.
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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 | 0.000 | 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".