Evidence map›Paper›PMID 39659519›Full record

ArticleAdvanced composites and hybrid materials2024

Meta-structure of amorphous-inspired 65.1Co28.2Cr5.3Mo lattices augmented by artificial intelligence.

Seong Je Park, Woongbeom Heogh, Jeongho Yang, Sukhyun Kang, Wonjong Jeong, Hoyoung Lee, Tae-Sik Jang, Hyun-Do Jung, Mohammad Jahazi, Seung Chul Han and 10 more

Abstract read
In one paragraph

Article in Advanced composites and hybrid materials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. AI-Driven TENGs for Self-Powered Smart Sensors and Intelligent Devices.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  7. Article
  8. Article
  9. Fully bio-based composite and modular metastructures.Advanced composites and hybrid materials · 2025
    Article
  10. Article
  11. Article
  12. Review
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

20 authors.

Seong Je Park *School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798 Singapore.
Woongbeom Heogh *Satellite System 5 Team, Hanwha Systems, Yongin, Gyeonggi-do 17121 Republic of Korea.
Jeongho YangSchool of Mechanical Engineering, Pusan National University, Busan, 46241 Republic of Korea.
Sukhyun KangProcess Research 3 Team, LG Display Co., Ltd., Paju, Gyeonggi-do 10845 Republic of Korea.
Wonjong JeongDepartment of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141 Republic of Korea.
Hoyoung LeeDepartment of Materials Science and Engineering & RIAM, Seoul National University, Seoul, 08826 Republic of Korea.
Tae-Sik JangSchool of Biomedical Convergence Engineering, Pusan National University, Yangsan, Gyeongsangbuk-do 50612 Republic of Korea.
Hyun-Do JungDivision of Materials Science and Engineering, Hanyang University, Seoul, 04763 Republic of Korea.
Mohammad JahaziDepartment of Mechanical Engineering, École de Technologie Supérieure, Montreal, QC H3C 1K3 Canada.
Seung Chul HanMaterial & Component Convergence R&D Center, Korea Construction Equipment Technology Institute, Gunsan, Jeollabuk-do 54002 Republic of Korea.
Hyoung Seop KimGraduate Institute of Ferrous and Eco Materials Technology, Pohang University of Science and Technology, Pohang, Gyeongsangbuk-do 37673 Republic of Korea.
Myoung-Gyu LeeDepartment of Materials Science and Engineering & RIAM, Seoul National University, Seoul, 08826 Republic of Korea.
Susmita BoseSchool of Mechanical and Materials Engineering, Washington State University, Pullman, WA 99164 USA.
Amit BandyopadhyaySchool of Mechanical and Materials Engineering, Washington State University, Pullman, WA 99164 USA.
Martin Byung-Guk JunSchool of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 USA.
Young Won KimSchool of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 USA.
Xingyu FuSchool of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 USA.
Rigoberto C AdvinculaDepartment of Macromolecular Science and Engineering, Case Western Reserve University, Cleveland, OH 44106 USA.
Clodualdo AranasDepartment of Mechanical Engineering, University of New Brunswick, Fredericton, New Brunswick E3B 5A3 Canada.
Sang Hoon KimPower Generation Laboratory, Korea Electric Power Research Institute, Daejeon, 34056 Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A hatching-distance-controlled lattice of 65.1Co28.2Cr5.3Mo is additively manufactured via laser powder bed fusion with a couple of periodic and aperiodic arrangements of nodes and struts. Thus, the proposed lattice has an amorphous-inspired structure in the short- and long-range orders. From the structural perspective, an artificial intelligence algorithm is used to effectively align lattices with various hatching distances. Then, the metastable lattice combination exhibits an unexpectedly high specific compression strength that is only slightly below that of a solid structure. From the microstructural perspective, the nodes in the newly designed lattice, where the thermal energy from laser irradiation is mainly concentrated, exhibit an equiaxial microstructure. By contrast, the struts exhibit a columnar microstructure, thereby allowing the thermal energy to pass through the narrow ligaments. The heterogeneous phase differences between the nodal and strut areas explain the strength-deteriorating mechanism, owing to the undesirable multi-phase development in the as-built state. However, solid-solution heat treatment to form a homogeneous phase bestows even higher specific compression strength. Furthermore, electrochemical leaching leads to the formation of nanovesicles on the surface of the microporous lattice system, thereby leading to a large surface area. A more advanced valve cage for use in a power plant is designed by using artificial intelligence both to (i) effectively preserve its mechanical stiffness and (ii) actively dissipate the generated stress through the large surface area provided by the nanovesicles. Supplementary Information: The online version contains supplementary material available at 10.1007/s42114-024-01039-6.

Indexed as

Amorphous-inspired structureArtificial intelligenceHatching-distance-controlled latticeHeterogeneous phase differencesMetastable lattice combination

Identifiers

PMID39659519
PMCPMC11627464

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LicenceCC BY-NC-ND
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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.