A DFT study of the effect of hydrostatic pressure on the structure and electronic properties of sarcosine crystal
Bibliographic record
Abstract
CONTEXT: We perform density functional theory calculations to study the dependence of the structural and electronic properties of the amino acid sarcosine crystal structure on hydrostatic pressure application. The results are analyzed and compared with the available experimental data. Our findings indicate that the crystal structure and properties of sarcosine calculated using the Grimme dispersion-corrected PBE functional (PBE-D3) best agree with the available experimental results under hydrostatic pressure of up to 3.7 GPa. Critical structural rearrangements, such as unit cell compression, head-to-tail compression, and molecular rotations, are investigated and elucidated in the context of experimental findings. Band gap energy tuning and density of state shifts indicative of band dispersion are presented concerning the structural changes arising from the elevated pressure. The calculated properties indicate that sarcosine holds great promise for application in electronic devices that involve pressure-induced structural changes. METHODS: Three widely used generalized gradient approximation functionals-PBE, PBEsol, and revPBE-are employed with Grimme's D3 dispersion correction. The non-local van der Waals density functional vdW-DF is also evaluated. The calculations are performed using the projector-augmented wave method in the Quantum Espresso software suite. The geometry optimization results are visualized using VMD. The Multiwfn and NCIPlot programs are used for wavefunction and intermolecular interaction analyses.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".