Evidence map›Paper›PMID 37101459›Full record

ArticleACS environmental Au2022

Exceptional Mineral Scaling Resistance from the Surface Gas Layer: Impacts of Surface Wetting Properties and the Gas Layer Charging Mechanism.

Thomas Horseman, Shihong Lin

Abstract read
In one paragraph

Article in ACS environmental Au, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Thomas HorsemanDepartment of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, Tennessee 37235, United States.ORCID https://orcid.org/0000-0002-4660-1448
Shihong LinDepartment of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, Tennessee 37235, United States.ORCID https://orcid.org/0000-0001-9832-9127

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mineral scaling is a phenomenon that occurs on submerged surfaces in contact with saline solutions. In membrane desalination, heat exchangers, and marine structures, mineral scaling reduces process efficiency and eventually leads to process failure. Therefore, achieving long-term scaling resistance is beneficial to enhancing process performance and reducing operating and maintenance costs. While evidence shows that superhydrophobic surfaces may reduce mineral scaling kinetics, prolonged scaling resistance is limited due to the finite stability of the entrained gas layer present in a Cassie-Baxter wetting state. Additionally, superhydrophobic surfaces are not always feasible for all applications, but strategies for long-term scaling resistance with smooth or even hydrophilic surfaces are often overlooked. In this study, we elucidate the role of interfacial nanobubbles on the scaling kinetics of submerged surfaces of varied wetting properties, including those that do not entrain a gas layer. We show that both solution conditions and surface wetting properties that promote interfacial bubble formation enhances scaling resistance. In the absence of interfacial bubbles, scaling kinetics decrease as surface energy decreases, while the presence of bulk nanobubbles enhances the scaling resistance of the surface with any wetting property. The findings in this study allude to scaling mitigation strategies that are enabled by solution and surface properties that promote the formation and stability of interfacial gas layers and provide insights to surface and process design for greater scaling resistance.

Identifiers

PMID37101459
PMCPMC10125293

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.