Dipole Moment Surfaces of the CH<sub>4</sub>+<sup>•</sup>X → CH<sub>3</sub><sup>•</sup>+ HX (X = F, Cl) Reactions from Atomic Dipole Moment Surfaces, and the Origins of the Sharp Extrema of the Dipole Moments near the Transition States
Bibliographic record
Abstract
The partitioning of the dipole moment of an isolated molecule or that of a reacting system is reviewed and applied to a dynamic reacting system whereby the system's dipole moment surface is constructed in parallel to its potential energy surface. The dipole moment surface is then decomposed into two origin-independent surfaces: (1) an atomic polarization (AP) surface and a charge transfer (CT) surface. The dipole moment surface as well as its two composing AP and CT surfaces are all further broken down into atomic and/or group contributions with the aid of the quantum theory of atoms in molecules (QTAIM). This approach is applied to the title's laser-induced chemical reactions [CH4 + (•)X → CH3(•) + HX (X = F, Cl)] previously studied by Bandrauk et al. [ J. Chem. Phys. 2004 , 121 , 7764 - 7775 ], and which were found to exhibit marked peaks in the dipole moment and in the polarizability tensor component at (or near) the transition state. These peaks afford a means to control the kinetics of these reactions with the proper adjustment of an external laser field intensity and phase. The entrance channel potentials of these reactions have recently been probed by photodetachment spectroscopy by Bowman and collaborators [ J. Chem. Phys. 2011 , 134 , 191102_1 - 4 ]. The understanding of the origin of the peaks in the dipole moment can provide, eventually, an additional layer of control in the design of reactions tunable by external fields through the proper selection of the reactants to maximize the field-molecule interaction.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".