ArticleMembranes2023
Investigating Mass Transfer and Reaction Engineering Characteristics in a Membrane Biofilm Using
Article in Membranes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Membrane biofilm reactors are a growing trend in wastewater treatment whereby gas-transfer membranes provide efficient bubbleless aeration. Recently, there has been a growing interest in using these bioreactors for industrial biotechnology using microorganisms that can metabolise gaseous substrates. Since gas fermentation is limited by the low solubilities of gaseous substrates in liquid media, it is critical to characterise mass transfer rates of gaseous substrates to enable the design of membrane biofilm reactors. The objective of this study is to measure and analyse mass transfer rates and reaction engineering characteristics for a single tube membrane biofilm reactor using
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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.