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Record W4408552170 · doi:10.1039/d4ra08556f

Enhancing output efficiency in self-powered hybrid nanogenerators with micro-pyramid surface design using ceramic/polymer film for flexible wearable electronic devices

2025· article· en· W4408552170 on OpenAlexfundno aff
Gwangseop Lee, Fiza Asif, Samia Rahman, Muhammad Zubair Khan, Adnan Maqbool, Rizwan Ahmed Malik, Usman Khan, Osama Gohar, Mohsin Ali Marwat, H. M. Waseem Khalil, Jung‐Hyuk Koh, Mohsin Saleem

Bibliographic record

VenueRSC Advances · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsnot available
FundersInstitute for Information and Communications Technology PromotionMinistry of Science and ICT, South KoreaIran Telecommunication Research CenterInformation Technology Research CentreHigher Education Commission, Pakistan
KeywordsKaptonMaterials scienceNanogeneratorSchematicComposite numberCeramicFOIL methodVoltageOptoelectronicsNanotechnologyComposite materialElectronic engineeringElectrical engineeringPolyimidePiezoelectricityEngineering

Abstract

fetched live from OpenAlex

-PDMS composite (containing 10-20 vol% barium titanate in polydimethylsiloxane). Micron-sized pyramid structures of 20% BT/PDMS were created on the film through optical lithography, while scanning electron microscopy and X-ray diffraction were used to assess the composite's crystal structure and phase characteristics. Altering the film's surface morphology led to substantial improvements in electrical performance, with voltage increasing from 28 V in the pristine film to 92 V in the micro-pyramid patterned film, and current rising from 2.7 μA to 11.0 μA. The enhanced power density and cyclic test suggests that surface topography optimization is highly effective, supporting long-term cyclic operation, and energy storage in capacitors. This work highlights the potential of surface-engineered nanogenerators in advancing sustainable, self-powered technologies.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
GPT teacher head0.238
Teacher spread0.227 · 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 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

Citations8
Published2025
Admission routes1
Has abstractyes

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