Molecular Simulations of Aqueous Electrolyte Solubility: 1. The Expanded-Ensemble Osmotic Molecular Dynamics Method for the Solution Phase
Bibliographic record
Abstract
We have developed a molecular-level simulation technique called the expanded-ensemble osmotic molecular dynamics (EEOMD) method, for studying electrolyte solution systems. The EEOMD method performs simulations at a fixed number of solvent molecules, pressure, temperature, and overall electrolyte chemical potential. The method combines elements of constant pressure-constant temperature molecular dynamics and expanded-ensemble grand canonical Monte Carlo. The simulated electrolyte solution systems contain, in addition to solvent molecules, full and fractional ions and undissociated electrolyte molecular units. The fractional particles are coupled to the system via a coupling parameter that varies between 0 (no interaction between the fractional particle and the other particles in the system) and 1 (full interaction between the fractional particle and the other particles in the system). The time evolution of the system is governed by the constant pressure-constant temperature equations of motion and accompanied by random changes in the coupling parameter. The coupling-parameter changes are accepted with a probability derived from the expanded-ensemble osmotic partition function corresponding to the prescribed electrolyte chemical potential. The coupling-parameter changes mimic insertion/deletion of particles as in a crude grand canonical Monte Carlo simulation; if the coupling parameter becomes 0, the fractional particles disappear from the system, and as the coupling parameter reaches unity, the fractional particles become full particles. The method is demonstrated for a model of NaCl in water at ambient conditions. To test our approach, we first determine the chemical potential of NaCl in water by the thermodynamic integration technique and by the expanded-ensemble method. Then, we carry out EEOMD simulations for different specified values of the overall NaCl chemical potential and measure the concentration of ions resulting from the simulations. Both computations give consistent results, validating the EEOMD methodology.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".