The Role of Exchange Energy in Modeling Core-Electron Binding Energies of Strongly Polar Bonds
Bibliographic record
Abstract
Accurate determination of carbon core-electron binding energies (C1s CEBEs) is crucial for X-ray photoelectron spectroscopy (XPS) assignments and predictive computational modeling. This study evaluates density functional theory (DFT)-based methods for calculating C1s core-electron binding energies (CEBEs), comparing three functionals-PW86x-PW91c (DFTpw), mPW1PW, and PBE50-across 68 C1s cases in small hydrocarbons and halogenated molecules (alkyl halides), using the delta self-consistent field ΔSCF (or ΔDFT) method developed by one of the authors over the past decade. The PW86x-PW91c functional achieves a root mean square deviation (RMSD) of 0.1735 eV, with improved accuracy for polar C-X bonds (X=O, F) using mPW1PW and PBE50, reducing the average absolute deviation (AAD) to ~0.132 eV. The study emphasizes the role of Hartree-Fock (HF) exchange in refining CEBE predictions and highlights the synergy between theoretical and experimental approaches. These insights lay the groundwork for machine learning (ML)-driven spectral analysis, advancing materials characterization, and catalysis through more reliable automated XPS assignments.
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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".