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Releasing chemical energy in spatiallyprogrammed ferroelectrics.

Yong HuJennifer L GottfriedRose Pesce-RodriguezChi-Chin WuScott D WalckZhiyu LiuSangeeth BalakrishnanScott BroderickZipeng GuoQiang ZhangLu AnRevant AdlakhaMostafa NouhChi ZhouPeter W ChungShenqiang Ren
Published in: Nature communications (2022)
Chemical energy ferroelectrics are generally solid macromolecules showing spontaneous polarization and chemical bonding energy. These materials still suffer drawbacks, including the limited control of energy release rate, and thermal decomposition energy well below total chemical energy. To overcome these drawbacks, we report the integrated molecular ferroelectric and energetic material from machine learning-directed additive manufacturing coupled with the ice-templating assembly. The resultant aligned porous architecture shows a low density of 0.35 g cm -3 , polarization-controlled energy release, and an anisotropic thermal conductivity ratio of 15. Thermal analysis suggests that the chlorine radicals react with macromolecules enabling a large exothermic enthalpy of reaction (6180 kJ kg -1 ). In addition, the estimated detonation velocity of molecular ferroelectrics can be tuned from 6.69 ± 0.21 to 7.79 ± 0.25 km s -1 by switching the polarization state. These results provide a pathway toward spatially programmed energetic ferroelectrics for controlled energy release rates.
Keyphrases
  • machine learning