Computational and Experimental Study of the Structure, Binding Preferences, and Spectroscopy of Nickel(II) and Vanadyl Porphyrins in Petroleum
Bibliographic record
Abstract
We present a computational exploration of five- and six-coordinate Ni(II) and vanadyl porphyrins, including prediction of UV-vis spectroscopic behavior and metalloporphyrin structure as well as determination of a binding energy threshold between strongly bound complexes that have been isolated as single crystals and weakly bound ones that we detect by visible absorption spectroscopy. The excited states are calculated using the tandem of the time-dependent density functional theory (TD-DFT) and the conductor-like polarizable continuum model (CPCM). The excited-state energies in chloroform solvent obtained by using two density functionals are found to correlate linearly with the experimental Soret and alpha-band energies for a known series of five-coordinate vanadyl porphyrins. The established linear correction allows simulation of the excited states for labile octahedral vanadyl porphyrins that have not been isolated and yields Soret and alpha-band bathochromic shifts that are in agreement with our UV-vis spectroscopic results. The PBE0 and PW91 functionals in combination with DNP basis set perform best for both structure and binding energy prediction. The reactivity preferences of Ni(II) and vanadyl porphyrins toward aromatic fragments of large petroleum molecules are explored by using the density functional theory (DFT). Analysis of electrostatic potentials and Fukui functions matching shows that axial coordination and hydrogen bonding are the preferred aggregation modes between vanadyl porphyrins and nitrogen-containing heterocycle fragments. This investigation improves our understanding on the cause for broadening of the Ni and V porphyrin Soret band in heavy oils. Our findings can be useful for the development of metals removal methods for heavy oil upgrading.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".