ArticlePolymers2021
Cellulose and Graphene Based Polyurethane Nanocomposites for FDM 3D Printing: Filament Properties and Printability.
Article in Polymers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Biopolymer-Nanoparticle Interactions in 3D-Printing for Biomedical Applications: Advantages, Limitations and Future Perspectives.Polymers · 2026Review
- 3D Printing of Hydrocortisone-loaded Eudragit RS Tablets: Influence of Plasticizers and Their Concentration on the Printability of Filaments.AAPS PharmSciTech · 2026Article
- Fused Deposition Modeling of Polymer Composites: Development, Properties and Applications.Polymers · 2025Review
- Article
- Article
- Nanocellulose-Based Biomaterial Ink Hydrogel for Uptake/Release of Bovine Serum Albumin.Polymers · 2023Article
- An Overview of Various Additive Manufacturing Technologies and Materials for Electrochemical Energy Conversion Applications.ACS omega · 2022Review
- Effect of Cellulose Nanofibers' Structure and Incorporation Route in Waterborne Polyurethane-Urea Based Nanocomposite Inks.Polymers · 2022Article
- Waterborne Polyurethane Acrylates Preparation towards 3D Printing for Sewage Treatment.Materials (Basel, Switzerland) · 2022Article
- Design of a Waterborne Polyurethane-Urea Ink for Direct Ink Writing 3D Printing.Materials (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
3D printing has exponentially grown in popularity due to the personalization of each printed part it offers, making it extremely beneficial for the very demanding biomedical industry. This technique has been extensively developed and optimized and the advances that now reside in the development of new materials suitable for 3D printing, which may open the door to new applications. Fused deposition modeling (FDM) is the most commonly used 3D printing technique. However, filaments suitable for FDM must meet certain criteria for a successful printing process and thus the optimization of their properties in often necessary. The aim of this work was to prepare a flexible and printable polyurethane filament parting from a biocompatible waterborne polyurethane, which shows potential for biomedical applications. In order to improve filament properties and printability, cellulose nanofibers and graphene were employed to prepare polyurethane based nanocomposites. Prepared nanocomposite filaments showed altered properties which directly impacted their printability. Graphene containing nanocomposites presented sound enough thermal and mechanical properties for a good printing process. Moreover, these filaments were employed in FDM to obtained 3D printed parts, which showed good shape fidelity. Properties exhibited by polyurethane and graphene filaments show potential to be used in biomedical applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.