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Record W4405890436 · doi:10.1002/adma.202410703

Electro‐ and Photo‐ Dual Responsive Chromatic Devices for High‐Contrast Dimmers

2024· article· en· W4405890436 on OpenAlexaff
Bin Wang, Pengcheng Liu, Feifei Zhao, Bingkun Huang, Wu Zhang, A. Y. Elezzabi, Linhua Liu, William W. Yu, Haizeng Li

Bibliographic record

VenueAdvanced Materials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicTransition Metal Oxide Nanomaterials
Canadian institutionsUniversity of Alberta
FundersYoung Scientists FundBasic and Applied Basic Research Foundation of Guangdong ProvinceGuangxi UniversityNational Natural Science Foundation of ChinaShandong UniversityState Key Laboratory of Vanadium and Titanium Resources Comprehensive Utilization
KeywordsElectrochromismMaterials scienceTransmittanceOptoelectronicsContrast (vision)High contrastOpacityChromatic scaleElectrochromic devicesOpticsContrast ratioPhotochromismNanotechnologyElectrode

Abstract

fetched live from OpenAlex

Electrochromism stands out as a highly promising technology for applications including variable optical attenuators, optical switches, transparent displays, and dynamic windows. The pursuit of high-contrast tunability in electrochromic devices remains a challenging goal. Here, the first photochromic hydrogel electrolyte is reported for electro- and photo-dual responsive chromatic devices that yield a high transmittance contrast at 633 nm (ΔT = 83.1%), along with a tinted transmittance below 1.5%. Such high-contrast devices not only hold great promise for dynamic windows but also enable seamless transitions between transparent augmented reality (AR) glass and opaque virtual reality (VR) glass. These findings introduce an innovative strategy for the design of high-contrast dimmers, opening new avenues for the development of chromatic devices.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.008
GPT teacher head0.261
Teacher spread0.253 · 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.

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

Citations17
Published2024
Admission routes1
Has abstractyes

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