Predictions of thermodynamic properties of energetic materials using COSMO-RS
Bibliographic record
Abstract
In this work, conductor-like screening for real solvents (COSMO-RS) calculations were carried out using COSMOtherm program in conjunction with Gaussian03 packages. The objective was to predict thermodynamic properties for two nitrogen-rich energetic materials which are less harmful for the environment than the conventional ones, namely 3,6-di(hydrazino)-1,2,4,5- tetrazine (DHT) and 3,3’-azo-bis(6-amino-1,2,4,5-tetrazine) (DAAT) for which no experimental data are available to our best knowledge. COSMO-RS approach is a combination of quantum chemical and statistical thermodynamic basis, which allow a physically meaningful description of molecular interactions between pure molecules and solvents in solution. Recently, this approach has been used for the prediction of an enormous number of physicochemical properties especially aqueous solubility, Henry’s law constant, vapor pressure and partition coefficient. The vapor pressure of pure compounds is one of the most important thermodynamic properties required for the chemical process design as well as for the fate assessment of pollutants in the environment. To validate the accuracy of COSMO-RS approach for the two molecules of interest, six reference energetic molecules have been studied, for which experimental data are available, such as cyclotetramethylene-tetranitramine (HMX), 2,4,6-trinitrotoluene (TNT), cyclotrimethylenetrinitramine (RDX), 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20), 1,1-diamino-2,2-dinitroethylene (FOX-7) and n-methyl-p-nitroaniline (MNA). From predicted results, a good agreement has been noted. DAAT molecule shows a lower volatility in the medium so that a low detectability compared to the DHT and other reference molecules. Both DHT and DAAT showed negative logarithmic values of Octanol-Water partition coefficients, this means that they don’t have the tendency to enhance the bioaccumulation process in soils.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".