JOURNAL ARTICLE

Experimental Investigation of Quasi‐Static Compressive Properties of Polymer‐Bonded Explosives (PBX) Based on UV‐Curing 3D Printing.

  • Published In: Propellants, Explosives, Pyrotechnics, 2024, v. 49, n. 12. P. 1 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Guo, Chao; Cui, Hao; Ren, Hao; Xiao, Lei; Gu, Xiaohui; Tang, Yuyong; Zhou, Hao; Yang, Yongliang; Guo, Rui 3 of 3

Abstract

Ultraviolet(UV)‐curing 3D printing in the preparation of explosives has get more attention due to its manufacturing flexibility. To study the effects of binder formulations on compressive properties of PBX for UV‐curing, cast HMX‐based polymer‐bonded explosives (PBX) with 5 groups of binder formulations are prepared by extruded‐based UV curing 3D printer. The test shows that the density of printed explosives exceeds 90% of the theoretical density and quasi‐static compression tests are conducted to analyze the mechanical properties of printed explosives. The results suggest that the elastic modulus and compressive strength of printed explosives with photocurable monomer TMP3EOTA as binder resin have increased by 693.1% and 424%, respectively, compared to those using polyether resin. Moreover, the mechanical properties improve as the content of Isophorone diisocyanate(IPDI) increases from 1 wt. % to 22 wt. %. The addition of aluminum powder decreases the elastic modulus and strength of samples printed by 59.5% and 62%. Meanwhile, the failure modes of printed grains have been also determined. This work provides practical references for future research of PBX on UV‐curing. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Propellants, Explosives, Pyrotechnics. 2024/12, Vol. 49, Issue 12, p1
  • Document Type:Article
  • Subject Area:Chemistry
  • Publication Date:2024
  • ISSN:07213115
  • DOI:10.1002/prep.202400090
  • Accession Number:181569510
  • Copyright Statement:Copyright of Propellants, Explosives, Pyrotechnics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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