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Record W2887939787 · doi:10.1073/pnas.1805029115

Strongly correlated perovskite lithium ion shuttles

2018· article· en· W2887939787 on OpenAlexfundno aff
Yifei Sun, Michele Kotiuga, Dawgen Lim, Badri Narayanan, Mathew J. Cherukara, Zhen Zhang, Yongqi Dong, Ronghui Kou, Cheng-Jun Sun, Qiyang Lu, Iradwikanari Waluyo, Adrian Hunt, Hidekazu Tanaka, Azusa N. Hattori, Sampath Gamage, Yohannes Abate, Vilas G. Pol, Hua Zhou, Subramanian K. R. S. Sankaranarayanan, Bilge Yildiz, Karin M. Rabe, Shriram Ramanathan

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsnot available
FundersAir Force Office of Scientific ResearchLaboratory Directed Research and DevelopmentDivision of Materials ResearchOffice of Naval ResearchMaterials Research Science and Engineering Center, Harvard UniversityArmy Research OfficeBasic Energy SciencesCanadian Light SourceMassachusetts Institute of TechnologyU.S. ArmyBrookhaven National LaboratoryArgonne National LaboratoryU.S. Department of EnergyJapan Society for the Promotion of ScienceNational Science FoundationU.S. NavyOffice of ScienceMinistry of Education, Culture, Sports, Science and Technology
KeywordsDopantPerovskite (structure)Materials scienceIonDopingLithium (medication)Chemical physicsIonic conductivityFast ion conductorConductivityNanotechnologyOptoelectronicsChemistryPhysical chemistryElectrodeCrystallographyElectrolyteOrganic chemistry

Abstract

fetched live from OpenAlex

Solid-state ion shuttles are of broad interest in electrochemical devices, nonvolatile memory, neuromorphic computing, and biomimicry utilizing synthetic membranes. Traditional design approaches are primarily based on substitutional doping of dissimilar valent cations in a solid lattice, which has inherent limits on dopant concentration and thereby ionic conductivity. Here, we demonstrate perovskite nickelates as Li-ion shuttles with simultaneous suppression of electronic transport via Mott transition. Electrochemically lithiated SmNiO 3 (Li-SNO) contains a large amount of mobile Li + located in interstitial sites of the perovskite approaching one dopant ion per unit cell. A significant lattice expansion associated with interstitial doping allows for fast Li + conduction with reduced activation energy. We further present a generalization of this approach with results on other rare-earth perovskite nickelates as well as dopants such as Na + . The results highlight the potential of quantum materials and emergent physics in design of ion conductors.

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 score0.025
Threshold uncertainty score0.278

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 studies0.0000.001
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 head0.024
GPT teacher head0.264
Teacher spread0.240 · 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

Citations70
Published2018
Admission routes1
Has abstractyes

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