CASSCF-based explicit ligand field models clarify the ground state electronic structures of transition metal phthalocyanines (MPc; M = Mn, Fe, Co, Ni, Cu, Zn)
Bibliographic record
Abstract
Multireference electronic structure methods are used to assign ground state electronic configurations for a series of metallophthalocyanines. Ligand orbital occupancies remain constant across the period and are consistent with a formal 2– charge on the ligand. The d electron configurations of some metallophthalocyanines are straightforward and can be unambiguously assigned, (d xy ) 2 (d xz ,d yz ) 2,2 ( [Formula: see text]) 2 ([Formula: see text]) n , with n = 2, 1, 0, respectively, for ZnPc, CuPc, and NiPc. Controversies over ground state electronic structure assignments for other metallophthalocyanines arise due to multiple complicating factors: accidental near-degeneracies, environmental effects, and different ligand field models used in interpreting experimental spectra. We demonstrate that explicit ligand field models provide more reliable and consistent interpretations of experimental data than implicit, parameterized alternatives. On this basis, we assign gas-phase electronic ground states for MnPc, (d xy ) 2 (d xz ,d yz ) 1,1 ([Formula: see text]) 1 and CoPc, (d xy ) 2 (d xz ,d yz ) 2,2 ([Formula: see text]) 1 , and show that the ground state of FePc cannot be resolved to a single state, with two near-degenerate states that are likely spin-orbit coupled: (d xy ) 2 (d xz ,d yz ) 1,1 ( [Formula: see text]) 2 and (d xy ) 2 (d xz ,d yz ) 2,1 ([Formula: see text]) 1 . Remaining differences between computational predictions and experimental observations are small and may be ascribed primarily to environmental effects but are also partly due to incomplete modelling of electron correlation.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".