Evidence map›Paper›PMID 40263538›Full record

ArticleScientific reports2025

Modeling the effect of scale deposition on heat transfer in injection molding.

Béla Zink, Anna Héri-Szuchács, Szabolcs Hajagos, József Gábor Kovács

Abstract read
In one paragraph

Article in Scientific reports, 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
–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

4 authors.

Béla ZinkDepartment of Polymer Engineering, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3, Budapest, 1111, Hungary.
Anna Héri-SzuchácsDepartment of Polymer Engineering, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3, Budapest, 1111, Hungary.
Szabolcs HajagosDepartment of Polymer Engineering, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3, Budapest, 1111, Hungary.
József Gábor KovácsDepartment of Polymer Engineering, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3, Budapest, 1111, Hungary. kovacs@pt.bme.hu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advent of additive manufacturing technologies has revolutionized the design and application of injection molds with conformal cooling systems. These mold inserts, manufactured directly from metal powder, feature complex geometries that align with the part contours, enabling more efficient and uniform heat extraction than traditional cooling methods. However, over time, even the most efficient cooling circuits degrade due to corrosion, limescale, and other deposition on the cooling channel walls, significantly decreasing heat transfer. We developed finite element models to simulate various deposition scenarios to address the complexity of modeling these depositions and their impact on heat transfer. Our study evaluates the thermal conductivity and thickness of deposit layers in conventional and conformal cooling channels. The resulting universal model accurately predicts the cooling efficiency of injection molds produced of various mold material, considering arbitrary deposition characteristics, e.g. limescale and corrosion. This model makes optimizing cooling systems for injection molds easier, thus providing crucial information on the time limit of the predictive maintenance and the mold performance change.

Indexed as

Additive manufacturingConformal cooling channelsFinite element modelingHeat transfer efficiencyInjection moldingScale deposition

Identifiers

PMID40263538
PMCPMC12015324

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.