Evidence map›Paper›PMID 40735245›Full record

ArticleApplied sciences (Basel, Switzerland)2024

Simulation of a Radio-Frequency Wave Based Bacterial Biofilm Detection Method in Dairy Processing Facilities.

Ranajoy Bhattacharya, Ken Cornell, Jim Browning

Abstract read
In one paragraph

Article in Applied sciences (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Review
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

3 authors.

Ranajoy BhattacharyaDepartment of Electrical and Computer Engineering, Boise State University, Boise, ID 83725, USA.
Ken CornellDepartment of Chemistry and Biochemistry, Boise State University, Boise, ID 83725, USA.
Jim BrowningDepartment of Electrical and Computer Engineering, Boise State University, Boise, ID 83725, USA.

Funding

Optimizing Deep Brain Stimulation for Parkinson's Disease.P20GM148321 · NIGMS · BOISE STATE UNIVERSITY · PI Karthik Srinivasan · 2023 to 2026
$10.2M
NIGMS NIH HHS P20 GM148321
6 · The paper itself

Abstract

This paper describes the principles behind the radio-frequency (RF) sensing of bacterial biofilms in pipes and heat exchangers in a dairy processing plant using an electromagnetic simulation. Biofilm formation in dairy processing plants is a common issue where the absence of timely detection and subsequent cleaning can cause serious illness. Biofilms are known for causing health issues and cleaning requires a large volume of water and harsh chemicals. In this work, milk transportation pipes are considered circular waveguides, and pasteurizers/heat exchangers are considered resonant cavities. Simulations were carried out using the CST studio suite high-frequency solver to determine the effectiveness of the real-time RF sensing. The respective dielectric constants and loss tangents were applied to milk and biofilm. In our simulation, it was observed that a 1 μm thick layer of biofilm in a milk-filled pipe shifted the reflection coefficient of a 10.16 cm diameter stainless steel circular waveguide from 0.229 GHz to 0.19 GHz. Further sensitivity analysis revealed a shift in frequency from 0.8 GHz to 1.2 GHz for a film thickness of 5 μm to 10 μm with the highest wave reflection (S11) peak of ≈-120 dB for a 6 μm thick biofilm. A dielectric patch antenna to launch the waves into the waveguide through a dielectric window was also designed and simulated. Simulation using the antenna demonstrated a similar S11 response, where a shift in reflection coefficient from 0.229 GHz to 0.19 GHz was observed for a 1 μm thick biofilm. For the case of the resonant cavity, the same antenna approach was used to excite the modes in a 0.751 m × 0.321 m × 170 m rectangular cavity with heat exchange fins and filled with milk and biofilm. The simulated resonance frequency shifted from 1.52 GHz to 1.54 GHz, for a film thickness varying from 1 μm to 10 μm. This result demonstrated the sensitivity of the microwave detection method. Overall, these results suggest that microwave sensing has promise in the rapid, non-invasive, and real-time detection of biofilm formation in dairy processing plants.

Indexed as

biofilm detectiondairy facilitiesreal-time monitoringRF-based method

Identifiers

PMID40735245
PMCPMC12306623

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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.