Adsorption Energy of<i>tert</i>-Butyl on Pt(111) by Dissociation of<i>tert</i>-Butyl Iodide: Calorimetry and DFT
Bibliographic record
Abstract
Dissociative and molecular adsorption of tert -butyl iodide on Pt(111) has been studied by single-crystal adsorption calorimetry (SCAC), photoelectron spectroscopy (XPS), reflection/adsorption infrared spectroscopy (RAIRS), and density functional theory (DFT) calculations. Up to a t -BuI total coverage of 0.07 ML, t -BuI adsorbs dissociatively at 100 K to form t -Bu ad plus I ad, with an integral heat of reaction of 223 kJ/mol. At higher coverage, up to a total coverage of 0.15 ML, t -BuI adsorbs molecularly directly to the Pt surface atoms with an average heat of adsorption of 91 kJ/mol. At 0.15 ML, the first layer is saturated. Between 0.15 and 0.38 ML, t -BuI adsorbs molecularly on top of the first layer with a constant heat of adsorption of 44.5 ± 1.9 kJ/mol. The standard enthalpy of formation of adsorbed tert -butyl on Pt(111) at 1/25 ML coverage is estimated from the heat measurements to be −168 ± 20 kJ/mol, giving a (CH 3 ) 3 C–Pt(111) bond enthalpy of 216 ± 20 kJ/mol. DFT calculations were performed using the GGA-PBE and optB86b vdW density functionals to determine the heats of reaction and binding energies of relevant adsorbates. Comparison to the measured energies shows that optB86b vdW-DF is more accurate than GGA-PBE for describing the adsorption and bonding of t -buI and t -Bu on Pt(111) because these energies contain large contributions from dispersion forces.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".