Evidence map›Paper›PMID 42354730›Full record

ArticleMicromachines2026

Manufacturing of Bioinspired SS316L-Based Multimaterials: Processing, Mechanical Properties and Modeling.

Vinod Kumar Darapureddy, Tuhin Mukherjee, Sonia Mary Chacko, Zahabul Islam

Abstract read
In one paragraph

Article in Micromachines, 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.

Vinod Kumar DarapureddyMechanical and Manufacturing Engineering, School of Engineering, Bowling Green State University, Bowling Green, OH 43403, USA.ORCID 0009-0003-8273-6643
Tuhin MukherjeeMechanical Engineering, Iowa State University, Ames, IA 50011, USA.ORCID 0000-0001-5372-4887
Sonia Mary ChackoRobotics Engineering, School of Engineering, Bowling Green State University, Bowling Green, OH 43403, USA.ORCID 0000-0002-2057-2132
Zahabul IslamMechanical and Manufacturing Engineering, School of Engineering, Bowling Green State University, Bowling Green, OH 43403, USA.ORCID 0000-0001-6961-3209

Funding

Bowling Green State University 33900032: SU IslamU.S. National Science Foundation 2206952
6 · The paper itself

Abstract

This study presents a hybrid additive manufacturing approach to fabricate bioinspired stainless steel 316L-copper (SS316L-Cu) multimaterial structures using laser powder bed fusion (LPBF). The present study incorporates honeycomb lattice structures with varying wall thicknesses (0.25 mm, 0.5 mm, 0.75 mm, and 1.0 mm) to investigate the effect of geometric parameters on mechanical performance. Mechanical testing was conducted according to ISO 6892 standards, and the results revealed a strong dependence of tensile strength and ductility on lattice thickness. Copper (Cu) infiltration into SS316L lattice structures improved ductility by 30% compared to the monolithic SS316L lattice, with minimal compromise in tensile strength. To complement experimental results, molecular dynamics (MD) simulations were performed to study atomic-scale deformation and validate the trend of strength enhancement with increasing wall thickness. The findings demonstrate the potential of combining LPBF and liquid Cu infiltration to develop multifunctional, mechanically robust, and thermally conductive metallic composites. This approach provides valuable insight into structure-property relationships and supports the design of next-generation multifunctional composites for structural and thermal applications.

Indexed as

additive manufacturingbioinspired lattice structureslaser powder bed fusion (LPBF)molecular dynamics (MD) simulationSS316L-Cu multimaterial

Identifiers

PMID42354730
PMCPMC13304474

What OpenQuestion holds

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LicenceCC BY
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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.