Evidence map›Paper›PMID 40599611›Full record

ArticleCurrent research in food science2025

Controllable liquid metal boundaries to improve microwave heating efficiency and uniformity in food processing.

Junwei Wang, Bin Yao, Rui Gong, Qinhong Zheng, Yingkai Liu, Runeng Zhong, Tai Xiang

Abstract read
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Article in Current research in food science, 2025. 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
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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

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

7 authors.

Junwei WangSchool of Physics and Electronic Information, Yunnan Normal University, Kunming, 650500, China.
Bin YaoSchool of Physics and Electronic Information, Yunnan Normal University, Kunming, 650500, China.
Rui GongSchool of Physics and Electronic Information, Yunnan Normal University, Kunming, 650500, China.
Qinhong ZhengSchool of Physics and Electronic Information, Yunnan Normal University, Kunming, 650500, China.
Yingkai LiuSchool of Physics and Electronic Information, Yunnan Normal University, Kunming, 650500, China.
Runeng ZhongSchool of Physics and Electronic Information, Yunnan Normal University, Kunming, 650500, China.
Tai XiangSchool of Physics and Electronic Information, Yunnan Normal University, Kunming, 650500, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study proposes an innovative microwave reaction cavity (MRC) design incorporating height-controllable liquid metal boundaries (HCLMBs) to address the persistent challenges of low heating efficiency and poor heating uniformity associated with conventional microwave heating in food processing. Firstly, the HCLMBs are realized by strategically positioning glass tube arrays along the wall-side of the MRC and injecting specified liquid metal volume into the glass tubes. Then, based on the proposed HCLMBs, three boundary modulation heating methods are systematically developed to achieve different microwave heating performances. Furthermore, the influence of the adjustment sequence of the liquid metal columns on the heating performance is also investigated. Numerical simulations demonstrated significant improvements over conventional MRC (CMRC) systems, with the MRC incorporating HCLMB achieving maximum enhancements of 107.54 % in heating efficiency and 201.85 % in heating uniformity. In addition, a corresponding experimental microwave heating system is built to validate the simulation results. Finally, the applicability of the HCLMB and boundary modulation heating methods to foods of different shapes and materials is discussed, demonstrating its potential for food processing applications.

Indexed as

Adjustment sequenceBoundary modulationHeating efficiency and uniformityLiquid metal boundariesMicrowave heating

Identifiers

PMID40599611
PMCPMC12209936

What OpenQuestion holds

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Registered trials

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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.