The DFT study of the structural, hydrogen, electronic, mechanical, thermal, and optical properties of KXH3 (X = Ca, Sc, Ti, & Ni) perovskites for H2 storage applications
Bibliographic record
Abstract
Abstract In this study, we employ density functional theory calculations to comprehensively investigate the structural, electronic, hydrogen storage capacity, mechanical, thermal, and optical properties of KXH3 (X = Ca, Sc, Ti, & Ni) hydride perovskites, unveiling their potential for H2 storage applications. The lattice parameters, calculated using the GGA-PBE functional, are found to be 4.482 Å, 4.154 Å, 3.974 Å, and 3.686 Å for KCaH3, KScH3, KTiH3, and KNiH3, respectively. Interestingly, the electronic structure analysis reveals that while KScH3, KTiH3, and KNiH3 exhibit metallic behavior, KCaH3 stands out as a semiconductor. Population analysis indicates that these compounds possess a strong potential for hydrogen storage due to their strong bonding and long bond lengths. Furthermore, the investigation of dynamic and mechanical stability suggests that the studied materials are promising candidates for experimental synthesis, as they exhibit both thermodynamic and mechanical stability. Gravimetric analysis reveals promising hydrogen storage capacities of 3.646 wt%, 3.452 wt%, 3.346 wt%, and 3.005 wt% for KCaH3, KScH3, KTiH3, and KNiH3, respectively. The calculated hydrogen desorption temperatures are 442.40 K for KCaH3, 518.68 K for KScH3, 592.47 K for KTiH3, and 614.82 K for KNiH3, indicating the suitability of these materials for hydrogen storage applications within practical operating temperature ranges. Novelty Statement: In this study, we present a comprehensive theoretical investigation of the novel perovskite materials KXH3(X = Ca, Sc, Ti, Ni), encompassing their structural, electronic, hydrogen storage, mechanical, thermal, and optical properties. To the best of our knowledge, this is the first report providing insights into these unexplored compounds, as no previous theoretical or experimental studies have been conducted on them.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".