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 (Km2) of α-alanine, valine, and leucine in aq. KCl solutions at 298.15 K from the revised thermodynamic dissociation constants (Ka2) of these acids and the ionic strength (Im) of the solutions. The ionic strength of the solutions considered in this study is determined mostly by KCl alone, and the equations for Km2 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 Ka2 values of the three amino acids. The values (1.295 ± 0.013) × 1010, (1.894 ± 0.009) × 1010, and (1.685 ± 0.011) × 1010 were obtained from the new potentiometric titration data for α-alanine, valine, and leucine, respectively. For alanine and valine, the new Ka2 values are also supported by the Harned cell data used, but the value (1.80 ± 0.02) × 1010 obtained for leucine from these data is significantly different. The potentiometric values are recommended here. The activity coefficient equations for the calculation of Km2 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, Km2 can be evaluated almost within experimental error up to an Im of about 1.0 mol kg1. The Km2 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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".