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Record W4415354548 · doi:10.1139/cjc-2025-0044

Tuning the structural, optoelectronic, mechanical, and hydrogen storage properties of metal hydride RbGeCl <sub>3</sub> : DFT insight

2025· article· en· W4415354548 on OpenAlexvenueno aff
Ahmed E. Kamal, Uzma Hira

Bibliographic record

VenueCanadian Journal of Chemistry · 2025
Typearticle
Languageen
FieldMaterials Science
TopicSolid-state spectroscopy and crystallography
Canadian institutionsnot available
Fundersnot available
KeywordsHydrogen storageGravimetric analysisHydrogenHydrideDensity functional theoryDesorptionWork (physics)Cryo-adsorption

Abstract

fetched live from OpenAlex

This work analyzed the impact of hydrogenation on the structural, mechanical, optoelectronic, and hydrogen storage properties of cubic RbGeCl 3 using density functional theory with the generalized gradient approximation PBE functional. As hydrogen is incorporated, the pristine direct band gap of 1.02 eV is systematically reduced, resulting in the material transitioning from an indirect band gap to a metallic one. Based on the negative formation energies, hydrogenated systems are stable and potentially synthesizable. The mechanical properties, including bulk modulus, shear modulus, and Young’s modulus, exhibited nonlinear behaviour with increasing hydrogen concentration. A nonlinear variation in mechanical properties is observed, with optimal performance at x = 0.6. Hydrogen storage parameters, such as gravimetric capacity and desorption temperature, are calculated to assess the material’s likelihood for hydrogen storage applications. The value of gravimetric capacity (0.89 cw%) with lower desorption temperature suggests that RbGeCl 1.2 H 1.8 is a suitable candidate for solid-state hydrogen storage applications. As a whole, RbGeCl 3- x H x exhibits tunable multifunctional properties that are suitable for applications in the advanced energy and electronic sectors.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.201
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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