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Record W4414610100 · doi:10.3390/batteries11100354

Investigation of Pr3+ and Nd3+ Doping Effects on Sodium Gadolinium Silicate Ceramics as Fast Na+ Conductors

2025· article· en· W4414610100 on OpenAlexaff
Abinaya Sivakumaran, Shantel Butler, Samuel Reid, Venkataraman Thangadurai

Bibliographic record

VenueBatteries · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsAlberta EnergyUniversity of Calgary
Fundersnot available
KeywordsIonic conductivityCeramicSinteringDopingSodium silicateElectrolyteIonic bondingGadoliniumMetal

Abstract

fetched live from OpenAlex

Sodium metal batteries (SMBs) with ceramic solid electrolytes offer a promising route to improve the energy density of conventional Na-ion batteries (SIBs). Silicate-based ceramics have recently gained attention for their favourable properties, including better ionic conduction and wider stability windows. In this study, 10% Pr3+ and Nd3+ were doped into sodium gadolinium silicate ceramics to examine the effects on phase purity, ionic conductivity, and interfacial compatibility with sodium metal anodes. The materials were synthesized via solid-state methods and sintered at 950–1075 °C to study the impact of sintering temperature on densification and microstructure. Na5Gd0.9Pr0.1Si4O12 (NGPS) and Na5Gd0.9Nd0.1Si4O12 (NGNS) sintered at 1075 °C showed the highest room temperature total ionic conductivities of 1.64 and 1.74 mS cm−1, respectively. The highest critical current density of 0.5 mA cm−2 is achieved with a low interfacial area-specific resistance of 29.47 Ω cm2 for NGPS and 22.88 Ω cm2 for NGNS after Na plating/stripping experiments. These results highlight how doping enhances phase purity, ionic conductivity, and interfacial stability of silicates with Na metal anodes.

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 score0.004
Threshold uncertainty score0.699

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 head0.012
GPT teacher head0.243
Teacher spread0.230 · 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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