Limiting Conductivities and Ion Association in Aqueous NaCF<sub>3</sub>SO<sub>3</sub> and Sr(CF<sub>3</sub>SO<sub>3</sub>)<sub>2</sub> from (298 to 623) K at 20 MPa. Is Triflate a Non-Complexing Anion in High-Temperature Water?
Bibliographic record
Abstract
Frequency-dependent electrical conductivities of solutions of aqueous sodium trifluoromethanesulfonate (“triflate”) and strontium triflate have been measured from T = 298 K to T = 623 K at p = 20 MPa, over a very wide range of ionic strength [(2·10 –5 to 0.35) mol·kg –1 ], using a unique high-precision flow-through AC electrical conductance instrument. Experimental values for the equivalent conductivity, Λ, of each electrolyte were used to calculate their equivalent conductivities at infinite dilution, Λ°, with the Turq–Blum–Bernard–Kunz (TBBK) ionic conductivity model. Values were derived for the limiting equivalent conductivity of the triflate ion, λ°(CF 3 SO 3 – ), and the strontium ion, λ°(Sr 2+ ). The TBBK fits to the concentration-dependent equivalent conductivity data for both NaCF 3 SO 3 and Sr(CF 3 SO 3 ) 2 required statistically significant ionic association constants for the species NaCF 3 SO 3 0 at temperatures T > 448 K, SrCF 3 SO 3 + at T > 448 K, and for Sr(CF 3 SO 3 ) 2 0 at T > 548 K. The stepwise association constants, K A, for the charged species SrCF 3 SO 3 +, were found to be greater or equal to than the ones for the neutral species Sr(CF 3 SO 3 ) 2 0 . The experimental value of K A for Sr(CF 3 SO 3 ) 2 0 was found to be similar to that for NaCF 3 SO 3 0 at 548 K but increased more steeply with temperature. At temperatures above 548 K, association constants derived from the concentration-dependent equivalent conductivities were increasingly sensitive to the assumptions used to calculate solution densities. Procedures for minimizing these effects are reported. The temperature dependence of the experimental association constants and limiting equivalent conductivities from (298 to 623) K could be represented accurately as functions of solvent density and viscosity, respectively.
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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) | 0.000 | 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".