Thermodynamic Computations for Ion Exchange and Surface Protonation Reactions and the Implications for Acid Induced Contact Angle Evolution in Silica Rich Saline Aquifer Systems
Bibliographic record
Abstract
To reduce current high concentrations of anthropogenic greenhouse gases in the atmosphere to levels stipulated by the Intergovernmental Panel on Climate Change, geological sequestration has been universally proposed. On the basis of cost analysis and global availability, deep saline aquifers are the prime targets for most proposed commercial and pilot scale projects.While the geological storage of anthropogenic carbon dioxide is expected to mitigate global warming, the technical aspects of the injection deserve to be considered for efficient injection projects. The water rock interaction phenomenon occurs due to carbonic acid generation which causes surface protonation reactions and has the potential to decrease water wettability of the system leading to enhanced water mobility and efficient gas injection. Therefore, for a saline aquifer rock with minerals capable of ion exchange reactions that consume solution protons, the wettability of such a system is likely to be preserved leading to reduced water mobility and poor gas injection. Generally, the extents to which surface protonation and ion exchange reactions occur depend on the free energy change of the reaction.In this paper, we have carried out thermodynamic computations for the free energies of surface protonation and ion exchange reactions. Based on the values of computed free energies, which show that ion exchange reactions have lower free energies, we have discussed the wettability implications for geological storage in silica rich saline aquifer systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".