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Record W4292332485 · doi:10.1111/jfpe.14156

Evaluation of plasma‐activated water characteristics and its process optimization

2022· article· en· W4292332485 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Food Process Engineering · 2022
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaIndian Council of Agricultural Research
KeywordsChemistryHydrogen peroxideOzoneDielectric barrier dischargeVolumetric flow rateEnvironmental chemistryChromatographyPulp and paper industryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Plasma‐activated water (PAW) is an emerging technology for the disinfection of foods and it is also widely evaluated for its applications in medicine. The long‐lived reactive oxygen species such as hydrogen peroxide and ozone are mainly responsible for the disinfecting properties of Ar/O 2 PAW. In this study, PAW characteristics were evaluated with respect to the process conditions and the post‐treatment time to understand the effect of process conditions and the time stability of PAW. PAW was generated using a continuous flow dielectric barrier discharge Ar/O 2 atmospheric pressure plasma system at different PAW treatment times. PAW properties were evaluated based on the concentration of hydrogen peroxide, ozone, pH, and the disinfection of Escherichia coli . From the time stability analysis, it was found that the hydrogen peroxide was more stable than ozone in PAW when stored at room temperature for 2 days. The E . coli inactivation was mainly attributed to the H 2 O 2 and ozone concentration than pH. The optimum process condition was found as 104 ml/min water flow rate, 20‐min treatment time and 4 slm gas flow rate for maximum reactive species concentration in PAW. Practical Applications There is a need for non‐chemical disinfection method of fresh fruits and vegetables, as the present chemical‐based disinfection methods are inefficient in controlling food‐borne outbreaks and the residual toxicity of these chemicals. Plasma‐activated water (PAW) is an emerging technology, which has the potential in disinfecting microorganisms. The aim of the work was to analyze the disinfection properties and the time stability of PAW. It is evident from the results that PAW is effective in disinfecting Escherichia coli and its reactive species degrade with time. This will facilitate the application of PAW as a disinfectant for fresh fruits and vegetables without any residual toxicity to the food and the environment. Further, from the optimization studies, understanding of the influence of process parameters on the PAW characteristics was derived which will be helpful to scale‐up of this technology.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.365
Threshold uncertainty score0.257

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.269
Teacher spread0.248 · 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