<i>Ab initio</i> structure determination of the low-temperature phase of succinonitrile from laboratory X-ray powder diffraction data—Coping with potential poor powder quality using DFT <i>ab initio</i> methods
Bibliographic record
Abstract
Without experimental or predicted literature crystal structures for succinonitrile at low temperature, structure solution was attempted from powder diffraction data taken at 173 and 90 K from a solid sample. Its room-temperature plastic-crystal state makes production of a sample with good particle statistics and random orientation almost impossible. Combining constrained models, simulated annealing, and careful application of second-order spherical harmonic corrections nevertheless produced viable-looking structures at 90 and 173 K, yielding two distinct structure models with the same projection down c . VASP optimization of atom coordinates in the experimental cell agreed well with the 90 K model but poorly with the model derived from the 173 K data. The refined 90 K structure changed little on optimization and fitted all datasets from 85 to 225 K. Plots of cell data, torsion angles, and isotropic displacement parameters against temperature suggest possible phase transitions around 100, 120, and 180 K. Cell data at 90 K: monoclinic P 2 1 / a , a =9.0851(5) Å, b =8.5617(5) Å, c =5.8343(3) Å, β =79.295(2)°, and Z =4. Succinonitrile has gauche conformation, in agreement with literature spectroscopy data.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".