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Record W3009242458 · doi:10.5772/intechopen.89524

Ultrasound for Membrane Fouling Control in Wastewater Treatment and Protein Purification Downstream Processing Applications

2020· book-chapter· en· W3009242458 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIntechOpen eBooks · 2020
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsToronto Metropolitan UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsFoulingMembrane foulingMembraneMicrofiltrationUltrafiltration (renal)NanofiltrationFiltration (mathematics)Membrane technologyReverse osmosisChromatographyChemical engineeringChemistryPermeationWastewaterForward osmosisMaterials scienceEnvironmental engineeringEnvironmental science

Abstract

fetched live from OpenAlex

Membrane fouling is one of the major issues encountered in membrane filtration including microfiltration, ultrafiltration, nanofiltration, and reverse osmosis. Membrane fouling can occur due to the reversible and irreversible deposition of particles, colloids, macromolecules, salts, and other types of elements. As a consequence, fouling causes a significant decrease in the permeate flux due to plugging of membrane pores, and adsorption of fouling material on the membrane’s surface and/or in the pore walls. A lot of research efforts have been directed towards fouling remediation techniques or membrane cleaning alternatives. Although most of these methods are relatively functional, they have drawbacks and limitations. Among these methods, the use of ultrasound has been shown to be effective in enhancing mass transfer, cleaning, disinfection, and controlling fouling. In membrane filtration processes, ultrasound can help accelerating the permeate flux towards the membrane and decreasing the concentration of solutes accumulated in the membrane pores and on the membrane surfaces. Ultrasonic fouling control does not require chemical cleaning and can maintain a high permeate flux throughout the filtration process. In addition, wastewater contaminants can be degraded by ultrasound. Therefore, ultrasound creates unique physicochemical conditions, which can be used as an effective tool for membrane fouling control. In this chapter, ultrasound radiation as a unique method to modify physical and chemical properties of a complex fluid with applications in wastewater treatment and protein purification process is highlighted. At first, ultrasonic parameters and how their ability to enhance the delivery of fluid flow to the membrane surface and affect the physical and chemical properties of foulants are discussed. Furthermore, various ultrasonic methods, including continuous and intermittent waves, and its influences on membrane fouling, permeate flux, membrane cleaning and flux recovery are reviewed. The main role of wave streaming as a driving force for fluid acceleration and antifouling control, and the impact of ultrasound-generated bubble cavitation on preventing and removing fouling deposits are described. The challenges of current ultrasonic techniques, which need to be addressed so as to facilitate their widespread and successful implementation, are explored. This chapter examines how the periodic compression/rarefaction cycles of ultrasound can influence mass transfer and membrane fouling. Also, the current knowledge and approaches to advance ultrasonic technology as an effective method for membrane fouling remediation in wastewater treatment and protein purification downstream processing are presented in this chapter.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.801
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.244
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it