Force-Field-Based Computational Study of the Thermodynamics of a Large Set of Aqueous Alkanolamine Solvents for Post-Combustion CO <sub>2</sub> Capture
Bibliographic record
Abstract
The ability to predict the thermodynamic properties of amine species in CO 2 -loaded aqueous solutions, including their deprotonation (p K a ) and carbamate to bicarbonate reversion (p K c ) equilibrium constants and their corresponding standard reaction enthalpies, is of critical importance for the design of improved carbon capture solvents. In this study, we used isocoulombic forms of both reactions to determine these quantities for a large set of aqueous alkanolamine solvent systems. Our hybrid approach involves using classical molecular dynamics simulations with the general amber force field (GAFF) and semi-empirical AM1–BCC charges (GAFF/AM1–BCC) in the solution phase, combined with high-level composite quantum chemical ideal-gas calculations. We first determined a new force field (FF) for the hydronium ion (H 3 O + ) by matching to the single experimental p K a data point for the well-known monoethanolamine system at 298.15 K. We then used this FF to predict the p K a values for 76 other amines at 298.15 K and for all 77 amines at elevated temperatures. Additionally, we indirectly relate the H 3 O + hydration free energy to that of H + and provide expressions for intrinsic hydration free energy and enthalpy of the proton. Using the derived H 3 O + FF, we predicted the p K a values of a diverse set of alkanolamines with an overall average absolute deviation of less than 0.72 p K a units. Furthermore, the derived H 3 O + FF is able to predict the protonation enthalpy of these amines when used with the GAFF. We also predicted the carbamate reversion constants of the primary and secondary amine species in the data set and their corresponding standard heats of reaction, which we compared with the scarcely available experimental data, which are often subject to significant uncertainty. Finally, we also described the influence of electronic and steric effects of different molecular fragments/groups on the stabilities of the carbamates.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".