Bond dissociation energies of the fifth‐row elements (<scp>InI</scp>): A quantum theoretical benchmark study
Bibliographic record
Abstract
Abstract The bond dissociation energies (BDE) of most main‐group elements have been accurately measured. However, the BDE values for heavy elements, particularly those from the fifth period (InI), are still missing or poorly validated. This study aims to identify the most accurate computational methods for calculating BDE values of compounds containing fifth‐row elements, including In, Sn, Sb, Te, and I, with a focus on readily accessible methods in software packages. The investigation involved a benchmark study using density functional theory (DFT), in addition to the 2nd order Møller–Plesset perturbation theory (MP2) and the coupled cluster with single, double, and perturbative triple excitations CCSD(T). The DFT functionals used in the study include APFD, B3LYP, B3LYP‐D3, B3P86, B97‐D3, BHandH, HSEH1PBE, M06‐2X, MN12‐SX, MN15‐L, and TPSSH. The functionals were carefully selected to cover some popular functionals as well as to cover all levels of the Jacob's ladder of DFT accuracy. The computed BDE values were compared with experimental values, and the results were filtered to remove any possible outliers. The statistical errors (MAPE, RMSE, and Pearson's) were then calculated and used to assess the performance of the methods.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".