Electronic structure, magnetic ordering and phonons in molecules and solids
Bibliographic record
Abstract
The present work gives an overview of the authors work in the field of electronic structure calculations. The main objective is to show how electronic structure methods in particular density functional theory (DFT) can be used for the description and interpretation of experimental results in order to enhance our understanding of physical and chemical properties of materials. The recently found superconductor MgB2 is an example where the electronic structure was the key to our understanding of the surprising properties of this material. The experimental confirmation of the predicted electronic structure from first principles calculations was very important for the acceptance of earlier theoretical suggestions. Molecular crystals build from magnetic clusters containing a few transition metal ions and organic ligands show fascinating magnetic properties at the nanoscale. DFT allows for the investigation of magnetic ordering and magnetic anisotropy energies. The magnetic anisotropy which results mainly from the spin-orbit coupling determines many of the properties which make the single molecule magnets interesting.
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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) | 0.002 | 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 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".