Critical Review of Transport and Equilibrium Properties of Potassium Chloride in High Temperature Water
Bibliographic record
Abstract
Ionic diffusion coefficients are important parameters to model mass transport processes in many high temperature water systems, such as nuclear and fossil-fueled power stations and hydrothermal geochemical systems. This work is a critical assessment of the molar conductivity data for aqueous potassium chloride which is directly related to diffusion coefficients. The literature includes more than 550 experimental data sets measured from temperatures T = 273 to 1073 K, pressures p = 0.1 to 1200 MPa, and water densities ρw = 85 to 1000 kg·m–3. In some cases, the measurements were reanalyzed with modern conductivity equations to yield more accurate limiting molar conductivity data, Λ°KCl. The selected Λ°KCl data were split into single-ion conductivities (λ°) for K+ and Cl– using transference number extrapolations. Simple empirical functions of the solvent viscosity and density were derived that can reproduce the data from T = 288 to 923.15 K, p = 0.1 to 407 MPa, and ρw = 450 to 1000 kg·m–3 to less than the estimated uncertainties. A revised equation to express the temperature and density dependence of KCl ion-pair formation constant, KA, based on flow conductivity measurements (T = 491 to 873 K, p = 2.25 to 300 MPa, and ρw = 160 to 852.45 kg·m–3), is also reported. This study recommends the use of potassium chloride as a chemical standard for high temperature conductivity experiments along with the Fuoss–Hsia–Fernández–Prini (FHFP) equation and the fitted parameters for Λ°KCl and KA reported here to verify the accuracy of hydrothermal conductivity measurements.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".