Article3D printing and additive manufacturing2024
Mechanical Characterization and Constitutive Modeling of 3D Printable Soft Materials.
Article in 3D printing and additive manufacturing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed.
- Review: Application of 3D Printing Technology in Soft Robots.3D printing and additive manufacturing · 2024Review
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Numerical modeling of soft matter has the potential to enable exploration of the soft robotic field's next frontier: human/machine cooperative design. However, access to material models suitable for predicting the behavior of soft matter is limited, and analysts typically conduct their own mechanical characterization on every new material they work with. In this work we present detailed mechanical characterization of 14 3D-printable soft materials suitable for fabricating soft robots. To allow the extension of this work by other researchers, our test procedures, raw data, constitutive model coefficients, and code used for curve fitting is freely available at www.SoRoForge.com.
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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.