First-principles study of the rotational transitions of H2 physisorbed over benzene
Bibliographic record
Abstract
In the ongoing search for promising compounds for hydrogen storage, novel porous metal-organic frameworks (MOFs) have been discovered recently [M. Eddadoudi, J. Kim, N. L. Rosi, D. Vodak, J. Wachter, M. O'Keeffe, and O. M. Yaghi, Science 295, 469 (2002); N. L. Rosi, J. Eckert, M. Eddadoudi, D. Vodak, J. Kim, M. O'Keeffe, and O. M. Yaghi, Science 300, 1127 (2003)]. Binding sites in these MOFs were deduced from inelastic neutron scattering (INS) spectroscopy of the rotational transitions of the adsorbed molecular hydrogen. In light of this discovery, it is important to have a fundamental understanding of hydrogen adsorption at different sites in this class of MOF materials. As a first step, here we study the case of H(2) adsorbed on benzene as a model of the organic linkers in the microporous crystal. We access the density functional theory results by comparing with correlated ab initio methods, e.g., second-order Møller-Plesset and coupled cluster with noniterative triple excitations. Different approximations for the exchange-correlation potentials were accessed for a set of relevant properties (binding energy, energetically favored configuration, and distance between the adsorbents and adsorbates). In particular, theoretical rotational spectra of the adsorbed H(2) were obtained that could be compared to the experimental INS spectra.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".