This paper is marked retracted in the scholarly record (OpenAlex). Interpret its findings with caution.
Retraction: AI-assisted design of lightweight and strong 3D-printed wheels for electric vehicles

Abstract
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Taxonomy
TopicsMechanical Engineering and Vibrations Research · Topology Optimization in Engineering · Robotic Mechanisms and Dynamics
After this article [1] was published, concerns were raised regarding the similarity to previous work [2] by different authors and that was not cited in [1].
Specifically, the overall concept, objectives, proposed approach, study design, and methodology appear highly similar to work reported in a published article [2]. The Methodology and Results and Discussion sections, including multiple figures reported in [1], appear very similar to content previously reported in [2], including several identical numerical values, though some text and figures are not identical.
In response to these concerns, the corresponding author stated that [2] was used as a basis for [1].
In light of the concerns about similarities between this article [1] and the previous work [2], the PLOS One Editors retract this article.
TOA, OOA, SAA, and AOO agreed with the retraction. AR and MOA either did not respond directly or could not be reached.
The retracted article [1] was removed from the PLOS One website at the time of retraction due to the similarities to [2]. The article’s Copyright and Data Availability statements were also updated at the time of retraction, and the removed contents are no longer offered under the Creative Commons Attribution License.
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1Akande TO, Alabi OO, Rizwan A, Ajagbe SA, Olaleye AO, Adigun MO. AI-assisted design of lightweight and strong 3D-printed wheels for electric vehicles. P Lo S One. 2024;19(12):e 0308004. doi: 10.1371/journal.pone.0308004 39621677 PMC 11611119 · doi ↗ · pubmed ↗
- 2Yoo S, Lee S, Kim S, Hwang KH, Park JH, Kang N. Integrating deep learning into CAD/CAE system: generative design and evaluation of 3D conceptual wheel. Struct Multidisc Optim. 2021;64(4):2725–47. doi: 10.1007/s 00158-021-02953-9 · doi ↗
