Re-evaluation of the second thermodynamic dissociation constants of α-alanine, valine, and leucine using potentiometric data measured for aqueous potassium chloride solutions at 298.15 K
Bibliographic record
Abstract
Equations were developed for the calculation of the second stoichiometric (molality scale) dissociation constants (K m2 ) of α-alanine, valine, and leucine in aq. KCl solutions at 298.15 K from the revised thermodynamic dissociation constants (K a2 ) of these acids and the ionic strength (I m ) of the solutions. The ionic strength of the solutions considered in this study is determined mostly by KCl alone, and the equations for K m2 were based on the single-ion activity coefficient equations of the Hückel type. The existing literature data obtained from Harned cell measurements and new potentiometric titration data were used to revise the K a2 values of the three amino acids. The values (1.295 ± 0.013) × 10 10 , (1.894 ± 0.009) × 10 10 , and (1.685 ± 0.011) × 10 10 were obtained from the new potentiometric titration data for α-alanine, valine, and leucine, respectively. For alanine and valine, the new K a2 values are also supported by the Harned cell data used, but the value (1.80 ± 0.02) × 10 10 obtained for leucine from these data is significantly different. The potentiometric values are recommended here. The activity coefficient equations for the calculation of K m2 values were also determined from the new potentiometric data. By means of the activity coefficient equations obtained for these three amino acids for KCl solutions, K m2 can be evaluated almost within experimental error up to an I m of about 1.0 mol kg 1 . The K m2 values calculated by this method are also compared with the values suggested in the literature.Key words: ionic strength dependence, stoichiometric dissociation constant, Debye-Hückel equation, potentiometry, α-alanine, valine, leucine.
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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 | 0.001 |
| 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) | 0.000 | 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".