Comparison of multireference <b> <i>ab initio</i> </b> wavefunction methodologies for X-ray absorption edges: A case study on [Fe(II/III)Cl4]2–/1– molecules
Bibliographic record
Abstract
In this work, we present a detailed comparison of wavefunction-based multireference (MR) techniques for the prediction of transition metal L-edge X-ray absorption spectroscopy (XAS) using [Fe(II)Cl4]2− and [Fe(III)Cl4]1− complexes as prototypical test cases. We focus on the comparison of MR Configuration Interaction (MRCI) and MR Equation of Motion Coupled Cluster (MREOM-CC) methods, which are employed to calculate valence excitation as well as core to valence Fe L-edge XAS spectra of [Fe(II)Cl4]2− and [Fe(III)Cl4]1− complexes. The two investigated approaches are thoroughly analyzed with respect to their information content regarding (1) metal-ligand covalency, (2) ligand field splittings, (3) relativistic effects, (4) electron correlation, (5) energy distribution, and (6) intensity modulation of the experimentally observed spectral features. It is shown that at the level of MRCI calculations in both [Fe(II)Cl4]2− and [Fe(III)Cl4]1− cases, very good agreement with the experimental Fe L-edge XAS spectra is obtained provided that the employed active space is extended to include ligand-based orbitals in addition to metal-based molecular orbitals. It is shown that this is necessary in order to correctly describe the important σ− and π− Fe-Cl covalent interactions. By contrast, MREOM-CC calculations yield excellent agreement relative to experiment even with small active spaces. The efficiency of the employed MR computational protocols is thoroughly discussed. Overall, we believe that this study serves as an important reference for future developments and applications of MR methods in the field of X-Ray spectroscopy.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".