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Record W2992963434 · doi:10.1002/cssc.201902753

Recent Progress in Two‐Dimensional Layered Double Hydroxides and Their Derivatives for Supercapacitors

2019· review· en· W2992963434 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemSusChem · 2019
Typereview
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsUniversité de Sherbrooke
FundersNational Natural Science Foundation of China
KeywordsLayered double hydroxidesSupercapacitorNanotechnologyChemistryDouble layeredMaterials scienceChemical engineeringCatalysisElectrochemistryOrganic chemistryElectrodePhysical chemistryEngineering

Abstract

fetched live from OpenAlex

High-performance supercapacitors have attracted great attention due to their high power, fast charging/discharging, long lifetime, and high safety. However, the generally low energy density and overall device performance of supercapacitors limit their applications. In recent years, the design of rational electrode materials has proven to be an effective pathway to improve the capacitive performances of supercapacitors. Layered double hydroxides (LDHs), have shown great potential in new-generation supercapacitors, due to their unique two-dimensional layered structures with a high surface area and tunable composition of the host layers and intercalation species. Herein, recent progress in LDH-based, LDH-derived, and composite-type electrode materials targeted for applications in supercapacitors, by tuning the chemical/metal composition, growth morphology, architectures, and device integration, is reviewed. The complicated relationships between the composition, morphology, structure, and capacitive performance are presented. A brief projection is given for the challenges and perspectives of LDHs for energy research.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.865
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
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 head0.083
GPT teacher head0.335
Teacher spread0.252 · 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