Bibliographic record
Abstract
Zeolite-templated carbon (ZTC) is a unique porous carbonaceous material in that its structure is ordered at the nanometre scale, enabling a representative periodic description at the atomistic level. A structural library for ZTC of varying compositions was created using density functional tight binding (DFTB) potentials parameterized for materials science applications (matsci-0-3). We provide here quantum chemical-refined structures of models with CH, CHO, CHON, CHOB, and CHOBN compositions with various degrees of heteroatom substitution. The "initial ZTC structure" files correspond to the initial model used in our work that was developed using molecular mechanics, empirical force fields. These structural models comprise the characteristic morphological features of highly porous carbon materials, such as open-blade surfaces, edges, saddles, and closed-strut formations, spanning a range of curvatures and characteristic sizes. The optimized structures in CIF and native DFTB file formats are organized in the "stationary structure" file based on the optimization pathways that lead to the stationary structures. Secondly, we carried out alternating compression and expansion of the CHO model unit cell to determine the lowest energy structure as well as to obtain the bulk modulus. The file "bulk modulus" contains two data sets that describe the deformational energy landscape of pure faujasite zeolite, Na-substituted zeolite, and the ZTC model structure. The file "analysis tools" is a representative compilation of utilities for file format conversion, fractional vs. Cartesian crystal coordinates, and structural analysis spreadsheets. The agreement between experimental measurements and the computational model is remarkable that demonstrates the power of approximate density functional theory as a cost-effective computational tool with chemical accuracy for the investigation of structure/property relationships in real-world carbon-based solids.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.221 | 0.003 |
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; both teacher heads agree on what is shown here.
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".