Comparison of ab Initio and DFT Methods for Studying Chain Propagation and Chain Termination Processes with Group 4 Polymerization Catalysts. 1. The <i>ansa</i>-Bis(cyclopentadienyl)zirconium Catalyst
Bibliographic record
Abstract
In this paper we present a systematic comparison of the performance of different computational approaches to study the propagation and termination reactions of olefins with a prototype homogeneous group 4 ansa -metallocene catalyst. Chain propagation, β-H transfer to the monomer, and β-H elimination to the metal have been investigated for the H 2 Si(Cp) 2 ZrR + (R = ethyl, n -butyl) + C 2 H 4 system using ab initio and density functional theory (DFT) techniques. For all the species investigated, all the computational approaches we considered result in substantially similar geometries. A comparison of the DFT and Møller−Plesset theory (MP2) propagation and termination barriers with extrapolated coupled-cluster calculations with inclusion of single, double, and perturbatively connected triple excitation (CCSD(T)) values indicates that all the pure functionals considered underestimate the difference between termination and propagation by roughly 3−4 kcal/mol. In contrast, hybrid functionals are within 1 kcal/mol from extrapolated CCSD(T) values. For a comparison with experimental results inclusion of zero-point energy contributions and the use of an alkyl group longer than ethyl to simulate the growing chain in both termination reactions are mandatory.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".