Generalized energy-based fragmentation DLPNO-CCSD(T) approach at complete basis set limit and its application to benzene clusters
Bibliographic record
Abstract
Accurate description of noncovalent interactions in large systems is challenging due to the requirement of high-level electron correlation methods. The generalized energy-based fragmentation (GEBF) approach, in conjunction with the domain-based local pair natural orbital (DLPNO) method, has been applied to assess the average binding energies (ABEs) of large benzene clusters, specifically (C6H6)13, at the coupled cluster singles and doubles with perturbative triples correction [CCSD(T)] level and the complete basis set (CBS) limit. Utilizing GEBF-DLPNO-CCSD(T)/CBS ABEs as benchmarks, various DFT functionals were evaluated. It was found that several functionals with empirical dispersion correction, including M06-2X-D3, B3LYP-D3(BJ), and PBE-D3(BJ), provide accurate descriptions of the ABEs for (C6H6)13 clusters. Additionally, the M06-2X-D3 functional was used to calculate the ABEs and relative stabilities of (C6H6)n clusters for n=11, 12, 13, 14, and 15 revealing that the (C6H6)13 cluster exhibits the highest relative stability. These findings align with experimental evidence suggesting that n=13 is one of the magic numbers for benzene clusters (C6H6)n, with n ≤ 30.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".