Noncovalent interactions of 1,<scp>4‐dithiafulvene</scp> and nitroaromatics: A combined <scp>DFT</scp> and ab initio molecular dynamics (<scp>AIMD</scp>) study
Bibliographic record
Abstract
Abstract The noncovalent interactions between a redox‐active molecule, phenyl‐substituted 1,4‐dithiafulvene ( Ph‐DTF ), and ten commonly encountered nitroaromatic compounds (NACs) were systematically investigated by means of density functional theory (DFT) calculations and ab initio molecular dynamics (AIMD) simulations. Our modeling studies examined their 1:1 complexes in terms of equilibrium geometries, frontier molecular orbitals (FMOs), nature of noncovalent forces, intermolecular charge transfer (ICT), and interaction energies at the ωB97XD/6‐31+G(d,p) level of theory. Vertical electronic transition properties were investigated through time‐dependent density functional theory (TD‐DFT) calculations, and energy decomposition analysis was conducted according to the symmetry‐adapted perturbation theory (SAPT). The computational results indicate that Ph‐DTF can form thermodynamically stable 1:1 complexes with trinitro‐substituted benzenes (e.g., 2,4,6‐trinitrotoluene and picric acid), but its interactions with mono‐ and dinitrobenzenes do not exhibit such stability. The selective binding properties are further corroborated by AIMD simulations. Overall, this computational work establishes a comprehensive understanding of the nature of noncovalent interactions of Ph‐DTF with various NACs, and the results can be used as theoretical guidance for the rational design of selective receptors and/or chemosensors for certain NACs that are of great concern in current industrial applications and environmental control.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".