The DOI matches its Crossref record; 93 of the 93 references it cites were found in a registry or an index.
Recent progress and scientific challenges in multi-material additive manufacturing via laser-based powder bed fusion
Open accessAbstract
Multi-material additive manufacturing provides a new route for fabricating components with tailored physical properties. Laser-based powder bed fusion (L-PBF), also known as selective laser melting, is a powder bed-based additive manufacturing technology. This technology affords the advantage of manufacturing metallic and non-metallic materials with high geometrical resolution. An emerging field relevant to the foregoing is multi-material L-PBF. This paper reviews the latest progress in this field including multiple material powder deposition mechanisms, molten pool behaviour, process characteristics of printing metal–metal, metal–ceramic, and metal–polymer multiple material components, and potential applications. Finally, scientific and technological challenges are presented.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Khairallah, S. A., Anderson, A. T., Rubenchik, A., & King, W. E. (2016) · Acta Materialia · doi:10.1016/j.actamat.2016.02.014 · Cited by 2,766
Additive manufacturing and its societal impact: a literature review
Huang, S. H., Liu, P., Mokasdar, A., & Hou, L. (2013) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-012-4558-5 · Cited by 1,862
King, W. E., Anderson, A. T., Ferencz, R. M., Hodge, N. E., Kamath, C., Khairallah, S. A., & Rubenchik, A. M. (2015) · Applied Physics Reviews · doi:10.1063/1.4937809 · Cited by 1,258
Zhang, J., Song, B., Wei, Q., Bourell, D., & Shi, Y. (2019) · Journal of Materials Science & Technology · doi:10.1016/j.jmst.2018.09.004 · Cited by 1,205
Additive manufacturing of multi-material structures
Bandyopadhyay, A., & Heer, B. (2018) · Materials Science and Engineering: R: Reports · doi:10.1016/j.mser.2018.04.001 · Cited by 1,029
Defect formation mechanisms in selective laser melting: a review
Zhang, B., Li, Y., & Bai, Q. (2017) · Chinese Journal of Mechanical Engineering · doi:10.1007/s10033-017-0121-5 · Cited by 924
Process defects and in situ monitoring methods in metal powder bed fusion: a review
Grasso, M., & Colosimo, B. M. (2017) · Measurement Science and Technology · doi:10.1088/1361-6501/aa5c4f · Cited by 833
Aboulkhair, N. T., Maskery, I., Tuck, C., Ashcroft, I., & Everitt, N. M. (2016) · Materials Science and Engineering: A · doi:10.1016/j.msea.2016.04.092 · Cited by 675
State of the Art in Directed Energy Deposition: From Additive Manufacturing to Materials Design
Dass, A., & Moridi, A. (2019) · Coatings · doi:10.3390/coatings9070418 · Cited by 667
Multi‐Material 3D and 4D Printing: A Survey
Rafiee, M., Farahani, R. D., & Therriault, D. (2020) · Advanced Science · doi:10.1002/advs.201902307 · Cited by 662
Cited by
Nazir, A., Gokcekaya, O., Md Masum Billah, K., Ertugrul, O., Jiang, J., Sun, J., & Hussain, S. (2023) · Materials & Design · doi:10.1016/j.matdes.2023.111661 · Cited by 773
Kafle, A., Luis, E., Silwal, R., Pan, H. M., Shrestha, P. L., & Bastola, A. K. (2021) · Polymers · doi:10.3390/polym13183101 · Cited by 587
Heat treatment for metal additive manufacturing
Laleh, M., Sadeghi, E., Revilla, R. I., Chao, Q., Haghdadi, N., Hughes, A. E., Xu, W., De Graeve, I., Qian, M., Gibson, I., et al. (2023) · Progress in Materials Science · doi:10.1016/j.pmatsci.2022.101051 · Cited by 538
Recent progress on additive manufacturing of multi-material structures with laser powder bed fusion
Wang, D., Liu, L., Deng, G., Deng, C., Bai, Y., Yang, Y., Wu, W., Chen, J., Liu, Y., Wang, Y., et al. (2022) · Virtual and Physical Prototyping · doi:10.1080/17452759.2022.2028343 · Cited by 363
Mukherjee, T., Elmer, J. W., Wei, H. L., Lienert, T. J., Zhang, W., Kou, S., & DebRoy, T. (2023) · Progress in Materials Science · doi:10.1016/j.pmatsci.2023.101153 · Cited by 267
Metadata
- Authors
- Wei, C., & Li, L.
- Venue
- Virtual and Physical Prototyping
- Publisher
- Informa UK Limited
- Published
- 2021-05-04
- Volume
- 16
- Issue
- 3
- Pages
- 347-371
- ISSN
- 1745-2759 (ISSN-L)
- 1745-2767
- OpenAlex
- W3165018672
- Cited by
- 316
- References
- 93
- FWCI
- 17.11
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Recent progress and scientific challenges in multi-material additive manufacturing via laser-based powder bed fusion. https://app.cochat.ai/papers/10.1080/17452759.2021.1928520
- The paper
- Wei, C., & Li, L. (2021). Recent progress and scientific challenges in multi-material additive manufacturing via laser-based powder bed fusion. Virtual and Physical Prototyping. https://doi.org/10.1080/17452759.2021.1928520
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
