Physiochemical Properties of Protic Ionic Liquids Mixed with Adenosine Triphosphate (ATP)/Water Mixture
Bibliographic record
Abstract
The densities of adenosine triphosphate/water/1-H-3-methyl imidazolium acetate mixture and adenosine triphosphate/water/1-H-3-methyl imidazolium hydrogen sulphate mixture at five different concentrations of adenosine triphosphate as 25 mg/ml to 45 mg/ml were estimated respectively. Ionic liquids used were 1-H-3-methyl imidazolium acetate and 1-H-3-methyl imidazolium hydrogen sulphate. The density of ionic liquids was measured from 298.15 K and 348.15 K respectively, using Rudolph Research Analytical Density Meter. The density for adenosine triphosphate and water was measured from 298.15 K and 343.15 K for 45 mg/ml concentration of adenosine triphosphate (ATP) respectively. The main objective was to access the suitable method for CO 2 capturing in order to reduce the CO 2 emission level up to 90% that may be helpful for reducing global warming. Our study of physiochemical properties of mixture of protic ionic liquids along with ATP was a novel work involving CO 2 capturing as a primary goal. Our study is a door step to help the worldwide researchers in understanding the basic properties of our used mixture however, its effects on CO 2 capturing and other purposes yet unknown. Adenosine triphosphate transports chemical energy within the cells for metabolism and is found to absorb carbon dioxide when used in dissolved form in water and is very effective when used with ionic liquids for CO 2 capturing. Therefore, the purpose of our study was CO 2 capturing and the best possible chemical for this propose. It was found that the calculated excess molar volumes were positive for a given composition range of ATP. The properties of thermal expansion coefficients, molar volumes, molecular volumes and standard entropy showed an increasing trend with increase in temperature. On the other hand, lattice potential energy showed a decrease in the graphical trend with the increasing temperature while the densities were found decreasing linearly with increase in temperature.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".