Study of energetics of end‐on and side‐on peroxide coordination in ligated Cu<sub>2</sub>O<sub>2</sub> models with State‐Specific Equation of Motion Coupled Cluster Method
Bibliographic record
Abstract
Abstract Newly developed State‐Specific Equation of Motion Coupled Cluster method (SS‐EOMCC) is used to study the relative energetics of μ‐1:2(trans end‐on) and μ‐η2:η2(side‐on) peroxo isomers of Cu2O2 fragments with 0 and 2 ammonia ligands. These model systems had been shown to be problematic to multireference perturbation theory (MRPT) and density functional theory (DFT) methods. In spite of the small reference space used, SS‐EOMCC gives much improved results by comparison to benchmark CR‐CC results. In addition to the fully symmetric 1Ag state, 1Bg and 3Bg states are also computed, demonstrating the complexity of the systems under study, as seen from the energy crossing at intermediate geometries. Spin‐flip idea is natural in our current theoretical framework and is tried for the model systems. It is argued that an important feature of the SS‐EOMCC method is that orbitals are optimized in the presence of dynamical correlation. This is the prime reason that a very small set of active orbitals can be used to achieve satisfactory results. © 2008 Wiley Periodicals, Inc. Int J Quantum Chem, 2008
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".