Evidence map›Paper›PMID 41681303›Full record

ArticleMaterials (Basel, Switzerland)2026

Enhancing the Mechanical Performance of Laser Powder Bed Fusion Prepared 316L Stainless Steel by Deformation Post-Processing at Ambient Temperature.

Radim Kocich, Lenka Kunčická

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 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

2 authors.

Radim KocichDepartment of Metallurgical Technologies, Faculty of Materials Science and Technology, VŠB Technical University of Ostrava, 17. listopadu 2172-15, 708 00 Ostrava, Czech Republic.
Lenka KunčickáDepartment of Metallurgical Technologies, Faculty of Materials Science and Technology, VŠB Technical University of Ostrava, 17. listopadu 2172-15, 708 00 Ostrava, Czech Republic.

Funding

Ministry of Education Youth and Sports CZ.02.01.01/00/23_021/0010117
6 · The paper itself

Abstract

Preparation of metallic materials via laser powder bed fusion has gained high popularity primarily due to the versatility of the processed materials and the complexity of the available component geometries. However, the prepared components feature characteristic shortcomings. Among the ways to successfully reduce/eliminate printing issues and homogenize the properties within additively prepared materials is optimized post-processing. In this study, we present the positive effects of deformation post-processing at ambient (room) temperature on the microstructure and mechanical properties of AISI 316L stainless steel prepared by laser powder bed fusion. The post-processing was performed by the industrially applicable method of rotary swaging, for which varying swaging degrees were applied. The selected swaging degree influenced primarily the interactions between the dynamic strengthening and softening processes and consequently the strength/plasticity ratio, although all the applied swaging degrees successfully eliminated the residual porosity and imparted (sub)structure development and grain refinement. The ultimate tensile strength (UTS) for the original workpiece was 282 MPa, and it increased up to more than 1400 MPa after the final swaging while maintaining favorable plasticity (elongation to failure over 30%). The study thus proposes a way to successfully enhance the performance of additively manufactured AISI 316L steel with the use of a commercially applicable plastic deformation technology.

Indexed as

316L stainless steellaser powder bed fusionmechanical propertiesmicrostructurerotary swaging

Identifiers

PMID41681303
PMCPMC12898212

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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.