Journal of Materials Science

, Volume 52, Issue 11, pp 6150–6160 | Cite as

Investigating the nanomechanical properties and reversible color change properties of the beetle Dynastes tityus

  • Jiyu Sun
  • Wei Wu
  • Chao Liu
  • Jin Tong
Original Paper


The wing cases (elytra) of Dynastes tityus are able to change coloration from yellow-green in a dry state to deep brown in a wet state due to different degrees of water absorption. An environmental scanning electron microscope was used to investigate the elytra’s reversible color change properties. Because the elytra cuticle has a spongy structure that is composed of laminated chitin and protein, a UV–Vis–NIR spectrophotometer was used to investigate the elytra’s optical properties. The width of the curve peak gradually decreased from 60 to 10 nm when the color of the elytra varied from deep brown to yellow-green. In a humid environment, air between the voids was replaced by water with a higher refractive index that induced an elytra color changed from yellow-green to deep brown. Interestingly, when both humidity and elytra color changed, the elytra’s mechanical properties varied too. When the humidity of the environment changed from 100 to 34%, the reduced modulus (E r) and hardness (H) of the elytra increased 230 and 440%, respectively. The storage modulus (E′) of the elytra is 1.98 ± 0.65 and 1.17 ± 0.22 GPa in yellow-green and deep brown color at 10 Hz, respectively, while their loss modulus (E″) is similar. tan δ of deep brown elytra is 0.072 ± 0.017, which is nearly two times higher than that of yellow-green. It can be demonstrated that when the elytra’s color turns to yellow-green, they are more elastic with less energy loss. The relationship between the elytra’s mechanical properties and structure color will not only help us gain insight into the biological functionality of the color change but also inspire the designs of artificial biomimetic devices.


Color Change Color Statement Nanomechanical Property Insect Cuticle Spongy Layer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by National Natural Science Foundation of China (No. 31672348), China-EU H2020 FabSurfWAR Project (No. S2016G4501 and 644971), and by 111 Project (B16020) of China.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10853_2017_895_MOESM1_ESM.tif (14.1 mb)
Supplementary material 1 (TIFF 14489 kb)
10853_2017_895_MOESM2_ESM.tif (67 kb)
Supplementary material 2 (TIFF 67 kb)


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Key Laboratory of Bionic Engineering (Ministry of Education, China)Jilin UniversityChangchunPeople’s Republic of China
  2. 2.Collaborative Innovation Center of Grain Production Capacity Improvement in Heilongjiang ProvinceHarbinPeople’s Republic of China

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