ArticlePolymers2019
Processing and Characterization of Polymer-Based Far-Infrared Composite Materials.
Article in Polymers, 2019. 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Polymer-based far-infrared radiation (FIR) composite materials are receiving increasing attention due to their significant influence on bioactivity. This study reports the processing of FIR composite films based on a polymer matrix and FIR radiation ceramic powders, as well as the characterization of the FIR composites. Field-emission scanning electron microscopy (SEM) and laser particle size analysis were employed to analyze the characteristic of the ceramic powders. The average size, dispersity, and specific surface area of the ceramic powders were 2602 nm, 0.97961, and 0.76 m
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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.