Evidence map›Paper›PMID 41606021›Full record

ArticleScientific reports2026

Volumetric additive manufacturing of complex geometries around complex inserts.

Ahmad Bagheri, Mohammad Reza Zakerzadeh, Mohammad Jafar Sadigh, Reyhaneh Salehabadi

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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.

Ahmad BagheriSchool of Mechanical Engineering, College of Engineering, University of Tehran, PO Box 4563-11155, Tehran, Iran.
Mohammad Reza ZakerzadehSchool of Mechanical Engineering, College of Engineering, University of Tehran, PO Box 4563-11155, Tehran, Iran. zakerzadeh@ut.ac.ir.
Mohammad Jafar SadighSchool of Mechanical Engineering, College of Engineering, University of Tehran, PO Box 4563-11155, Tehran, Iran.
Reyhaneh SalehabadiSchool of Mechanical Engineering, College of Engineering, University of Tehran, PO Box 4563-11155, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In tomographic Volumetric Additive Manufacturing (VAM), light is projected into a rotating vial of photosensitive resin, enabling printing of polymer structures around pre-existing inserts ('overprinting'). However, printing around complex, heavily occluding inserts remains unexplored. In this study, the capabilities and challenges of the tomographic VAM process when printing around such inserts are examined, and an occlusion-based orientation optimization is proposed to address these challenges. A cost function based on light occlusion is introduced to predict optical dose quality and optimize insert and print model orientation. By maximizing the number of directions from which the print model voxels receive light, dose quality and print fidelity are increased. Simulations showed that although the conventional tomographic VAM overprinting works well for simple convex inserts, it struggles for complex ones, and the proposed orientation optimization method improves print quality and reduces unprinted regions. A commercial resin wase used for volumetric overprinting of complex structures. Physical prints closely matched simulation results; micro-CT imagery confirmed that orientation optimization significantly improves tomographic volumetric printing around complex and occluding inserts and increases the possible depth of printing within insert recesses. This approach has enabled printing complex geometries around complex inserts, often unfeasible using conventional manufacturing methods.

Indexed as

InsertOcclusionOptimizationOrientationOverprintingVAM

Identifiers

PMID41606021
PMCPMC12909872

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.