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Record W4405106028 · doi:10.1016/j.nanoen.2024.110554

Cultivation of In situ foam 3D-printing: Lightweight and flexible triboelectric nanogenerators employing polyvinylidene fluoride/graphene nanocomposite foams with superior EMI shielding and thermal conductivity

2024· article· en· W4405106028 on OpenAlexafffund
Amirjalal Jalali, Araz Rajabi‐Abhari, Haonan Zhang, Tanmay Gupta, Otávio Augusto Titton Dias, Md Akibul Islam, Tobin Filleter, Ning Yan, Mohini Sain, Chul B. Park

Bibliographic record

VenueNano Energy · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsMaterials sciencePolyvinylidene fluorideTriboelectric effectComposite materialGrapheneNanocompositeEMIElectromagnetic shieldingThermal conductivityGraphene foamPolymerElectromagnetic interferenceNanotechnologyGraphene oxide paperElectronic engineering

Abstract

fetched live from OpenAlex

This study explores the novel realm of foam 3D-printing, a convergence of foaming and 3D-printing techniques, with profound implications for multifunctional stretchable electronics. Through scalable in situ foam printing, lightweight and stretchable foamed polyvinylidene fluoride (PVDF)/graphene nanocomposites were successfully fabricated. By incorporating varying percentages (2, 3, 5, and 7 wt.%) of graphene into PVDF, alongside a 3 wt.% foaming agent for foamed 3D-printing filaments, a diverse range of filaments were fabricated. Next, employing fused filament fabrication (FFF), 3D-printed PVDF nanocomposites and nanocomposites foams were produced. Both shear and elongational rheological tests, respectively, corroborated that the incorporation of a foaming agent and graphene amplified the shear-thinning behavior and instigated strain hardening in the PVDF nanocomposite foam, rendering them viable options for foam 3D-printing. The resulting materials exhibited promising electrical and thermal conductivity attributes, as well as effective electromagnetic interference (EMI) shielding properties. The additional nanofiller content significantly augmented both electrical and thermal conductivity, further enhanced by the introduction of a cellular structure. Notably, foamed 3D-printed PVDF nanocomposites containing 7 wt.% of graphene demonstrated an EMI shielding effectiveness (SE) of 36 dB distinguished by minimal reflectivity and predominant absorption characteristics. X-ray diffraction (XRD) analysis indicated that the in situ foam 3D-printing facilitates the formation of the β-phase. The printed specimens were deployed as the tribonegative element in the Triboelectric Nanogenerator (TENG) system. The fabricated TENG displayed notable efficiency, as evidenced by the foamed 3D-printed PVDF, which generated an output voltage of 270 V and a current of 5 μA, successfully illuminating 80 Light Emitting Diode (LED) lights. Meanwhile, the 3D-printed nanocomposite foams with 3 wt.% nanofiller exhibited superior performance, achieving an output voltage of 550 V and a current of 11 μA. This investigation underscores the potential of the in situ foam 3D-printing for the development of advanced lightweight and flexible energy storage devices. • Lightweight and stretchable foamed polyvinylidene fluoride (PVDF)/graphene nanocomposites were effectively fabricated using a scalable in situ foam printing technique. • Foamed 3D-printed PVDF nanocomposites exhibited an EMI shielding effectiveness (SE) of 36 dB, characterized by low reflectivity and primarily absorption-driven properties. • The 3D-printed nanocomposite foams with 3 wt.% nanofiller demonstrated exceptional performance, attaining an output voltage of 550 V and a current of 11 μA.

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 categoriesMeta-epidemiology (narrow)
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 score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.213
Teacher spread0.203 · 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

Citations29
Published2024
Admission routes2
Has abstractyes

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