Ion Association and Hydrogen Bonding in Potassium Dihydrogen Phosphate Solutions: Insights from Molecular Dynamics Simulations
Bibliographic record
Abstract
Potassium dihydrogen phosphate (KDP) is a critical material in non-linear optics, with significant applications in electro-optical and laser technologies. Despite its importance, the solution properties of KDP remain poorly understood, and to the best of our knowledge, no prior molecular dynamics (MD) simulation studies have directly probed the structure and behavior of KDP in aqueous solutions. This study presents results from MD simulations of KDP in both solution and solid states and compares four dihydrogen phosphate (DP) force-field models in 5 different water models. Our results reveal that the solution structure is strongly dominated by the association of the dihydrogen phosphate anions through direct hydrogen bonding, where the degree of association exhibits a marked concentration dependence in accord with the experiment. Of the four DP models evaluated, two are much better able to reproduce experimental data, including from neutron scattering, and ab-initio MD simulation results demonstrating their effectiveness in capturing the hydrogen bonding patterns that appear to govern local solution structure. We find that the extent hydrogen bonding between dihydrogen phosphate anions is also sensitive to the choice of water models, with stronger hydration reducing DP-DP association. This sensitivity underscores the importance of selecting appropriate models to achieve a reasonable representation of KDP solution behavior. We have also examined the two models for both tetragonal and monoclinic crystal structures of KDP and found that these models are able to reproduce the experimental unit cell and bonding parameters relatively well. The findings of this study enhance our understanding of KDP solutions and lay the groundwork for future investigations into its solution and solid-state properties, for example in providing insights into the origins for pseudo-one-dimensional crystal growth observed from supersaturated solutions.
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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 | 0.000 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".