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Record W4386467185 · doi:10.1021/acs.inorgchem.3c02398

Stability and Semiconducting Behavior of Magnesium Polysulfides by Nonequivalent sp<sup>3</sup> Hybridizations

2023· article· en· W4386467185 on OpenAlexaff
Guang Zhang, Kai Wang, Qiaoyu Liu, Mingyuan Pan, Ding Shen, Yansun Yao, Lailei Wu, Huiyang Gou

Bibliographic record

VenueInorganic Chemistry · 2023
Typearticle
Languageen
FieldMaterials Science
TopicMXene and MAX Phase Materials
Canadian institutionsUniversity of Saskatchewan
FundersLiaoning Technical UniversityDepartment of Education of Hebei ProvinceDepartment of Education of Liaoning ProvinceNational Natural Science Foundation of China
KeywordsChemistryMagnesiumElectrochemistryBattery (electricity)CrystallographyDimerPhysical chemistryElectrode

Abstract

fetched live from OpenAlex

The Mg/S battery has attracted enormous interest in recent years due to its high theoretical capacity, low cost, and high security. However, the understanding of many intermediate magnesium polysulfides in the Mg/S battery remains elusive. Combining extensive structural search and first-principles calculations, we investigate the phase stability, structural character, and electronic structure of magnesium polysulfides in a wide range from MgS to MgS 8 . The pyrite-type MgS 2 (space group: Pa 3̅) is predicted to be stable. Five magnesium polysulfides, MgS x ( x = 3, 4, 5, 6, and 8), are found to be metastable, with formation enthalpies slightly above the convex hull. S 2 dimer, “V”-like S 3, and highly distorted S x chains are found for the polysulfides with bond lengths close to or slightly longer than S 8 and bond angles similar to S 8 . A wide range of band gaps (0.77–2.82 eV) are revealed for the polysulfides due to the contribution of the nonequivalent sp 3 hybridization of the S atoms in S x 2– . Our results can help to further understand the electrochemical process in the Mg/S battery.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.023
GPT teacher head0.255
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations6
Published2023
Admission routes1
Has abstractyes

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