EFFECT OF DIELECTRIC CONSTANT ON THE SOLVATION OF SODIUM CITRATE
Bibliographic record
Abstract
The paper reports on the solvation of Sodium citrate in water, water + CH3 0 λ m CN and water + DMSO mixtures (v/v) under varying dielectric constant at different temperature. The specific conductance data obtained was analyzed by Kraus-Bray and Shedlovsky conductivity models. Limiting molar conductance ( ), dissociation constant/ association constant (KC/Ka 0 λ m ) were evaluated for all the solvent compositions. The limiting molar conductance, decreases with the increase in amount of co-solvent in water, due to increased solvent-solvent interaction and decrease in dielectric constant. Due to high viscosity and molecular size of DMSO in water, lower conductance was observed in water + DMSO media. The Ka values increases with the increase in amount co-solvent in water at all the temperatures studied. Energy of activation of the rate process and related thermodynamic parameters such as ΔHa, ΔGa and ΔSa have been evaluated. ΔGa is found to be negative indicating spontaneity of the process. Walden product (λ0mη0) and corrected Stoke’s radius (r ) have also been evaluated. Fuoss- Accascina equation was used to identify the ion-pairs and ion-triplets in the system. But the slopes of the plot were found to be less than -0.5, indicating the absence of ion-pairs or ion-triplets. Born relation of solvation was verified. These data have been used to study the nature of ion-solvent interaction and solvent-solvent interactions existing in the system
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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".