Browsing by Subject "2D-ordered linear-chain carbon"

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    Harnessing phonon wave resonance in carbyne-enriched nano-interfaces to enhance energy release in nanoenergetic materials
    (Begell House, Inc., 2024-07-30) Lukin, Alexander; Gülseren, Oğuz
    This paper introduces a new nanotechnology-driven approach that provides a transformative pathway to substantially enhance the energy release efficiency of nanoenergetic materials (nEMs) without altering their chemical composition. The groundbreaking concept involves strategically harnessing, self-synchronized collective atomic vibrations and phonon wave resonance phenomena within the transition domain's interconnecting nanocomponents. A key novelty is the incorporation of meticulously engineered two-dimensional-ordered linear-chain carbon-based multilayer nano-enhanced interfaces as programmable nanodevices into these transition domains, facilitated by advanced multistage processing and assembly techniques. These programmable nanodevices enable unprecedented control over the initiation, propagation, and coupling of self-synchronized collective atomic vibrations and phonon waves, unleashing powerful synergistic effects. Central to this approach is the bidirectional, self-reinforcing interaction between precisely tailored nano-architectures and phonon dynamics within the multilayer nano-enhanced interfaces. This synergistic coupling facilitates the rational programming of energy transfer pathways, granting access to previously inaccessible energy reserves inherently locked within the nEM systems. To optimally activate and harness these synergistic mechanisms, a strategic combination of cutting-edge methods is judiciously employed. These include energy-driven stimulation of allotropic phase transformations, surface acoustic wave-assisted manipulation at micro-/nanoscales, heteroatom doping, directed self-assembly driven by high-frequency electromagnetic fields, and a data-driven inverse design framework. Notably, by leveraging a data-driven inverse design strategy rooted in multi-factorial neural network predictive models, we uncover previously hidden structure-property relationships governing the nano-enhanced interfaces. This novel data-driven "nanocarbon genome" approach enables rational maximization of energy release efficiency in nEM systems. Overall, this transformative nanoscale concept not only unlocks unprecedented high-energy functionalities but also ushers in significant improvements in environmental sustainability and operational safety for nEMs