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Record W2588140587 · doi:10.1021/acs.chemrev.6b00614

Odyssey of Multivalent Cathode Materials: Open Questions and Future Challenges

2017· review· en· W2588140587 on OpenAlexfundno aff
Pieremanuele Canepa, Gopalakrishnan Sai Gautam, Daniel C. Hannah, Rahul Malik, Miao Liu, Kevin G. Gallagher, Kristin A. Persson, Gerbrand Ceder

Bibliographic record

VenueChemical Reviews · 2017
Typereview
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryBasic Energy SciencesOffice of ScienceUniversity of Illinois at Urbana-ChampaignBar-Ilan UniversityUniversity of Illinois at ChicagoUniversity of WaterlooU.S. Department of Energy
KeywordsCathodeIntercalation (chemistry)Battery (electricity)ChemistryNanotechnologyEngineering physicsInorganic chemistryMaterials sciencePhysical chemistryPhysics

Abstract

fetched live from OpenAlex

The rapidly expanding field of nonaqueous multivalent intercalation batteries offers a promising way to overcome safety, cost, and energy density limitations of state-of-the-art Li-ion battery technology. We present a critical and rigorous analysis of the increasing volume of multivalent battery research, focusing on a wide range of intercalation cathode materials and the mechanisms of multivalent ion insertion and migration within those frameworks. The present analysis covers a wide variety of material chemistries, including chalcogenides, oxides, and polyanions, highlighting merits and challenges of each class of materials as multivalent cathodes. The review underscores the overlap of experiments and theory, ranging from charting the design metrics useful for developing the next generation of MV-cathodes to targeted in-depth studies rationalizing complex experimental results. On the basis of our critical review of the literature, we provide suggestions for future multivalent cathode studies, including a strong emphasis on the unambiguous characterization of the intercalation mechanisms.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0020.006
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.002

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 head0.247
GPT teacher head0.435
Teacher spread0.188 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1,144
Published2017
Admission routes1
Has abstractyes

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