3D printed graphene aerogels using conductive nanofibrillar network formulation
Bibliographic record
Abstract
Despite recent progress in 3D printing of graphene, formulation of aqueous 3D printable graphene inks with desired rheological properties for direct ink writing (DIW) of multifunctional graphene macrostructures remains a major challenge. In this work, we develop a novel 3D printable pristine graphene ink in aqueous phase using conductive nanofibrillar network formulation by controlling the interfacial interactions between graphene and PEDOT:PSS nanofibrils. The formulated inks, tailored for energy applications, provide excellent 3D printability for fabricating multilayer 3D structures (up to 30 layers) with spanning features and high aspect ratio. The 3D printed aerogels, comprising interconnected networks of graphene flakes and PEDOT:PSS nanofibrils, exhibit excellent electrical conductivity as high as ∼630 S m − 1 and can be converted into conductive hydrogels via swelling in water/electrolyte. The formulated graphene inks were used for fabricating 3D printed supercapacitor electrodes (power density of 11.3 kW kg−1 and energy density of 7.3 Wh kg−1) with excellent performance and durability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".