Quantum software interfaced with crystal-structure databases: tools, results and perspectives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Version 2.0 of Toth's Materials Toolkit runs under Windows and prepares ASCII input files for popular ab initio packages such as ABINIT , VASP etc . Those packages, obtainable from their respective developers, may run in desktop or supercomputer setups with Linux or Windows operating systems. The Toolkit input is taken at will from a direct plug into CRYSTMET, with 93000 crystal-structure entries for metals and inorganic compounds, from CIF files of public-domain crystal-structure databases, or cut-and-paste from electronic journals followed by minimal free-format editing. The collection of fully general and highly graphical tools grouped on two command screens operates on the structure description stored in an editable ASCII screen. After the model has been searched, modified and evaluated in a few keystrokes with the above tools, its ASCII input files for a selection of ab initio packages are produced by selecting the meaningful flags and run options on a dialog. The tedious structure manipulation or decomposition into multiple simulations is performed in the background. Execution is followed by production of a plain-English job report. Four examples among the numerous possible applications of the Toolkit illustrate the fact that daunting topics, like the symmetry of chlorapatite, the voids and channels in the hydrogen-storage material EuNi 5 , the energy per unit area of the contact plane for spinel twin in diamond, and the hardness of lonsdaleite versus diamond, are amenable to processing by materials scientists more versed in experiment than theory. The manual with tutorials and availability information can be found at http://www.tothcanada.com/toolkit/.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it