Establishing a Virtual Look into Laser-Driven Shockwave Synthesis of Nanocarbon Materials

Carbon nanomaterials are of tremendous interest due to the manifold of properties they can exhibit. For example, nanodiamond is renowned its hardness and biological inertness and is found in applications spanning industrial lubricants to biological implants and drug delivery vehicles; graphitic nanoparticles including quantum dots, nanotubes, and graphitic nanoonions exhibit tunable electronic and optoelectronic properties that are being explored for quantum computing, energy harvesting, and electronic devices. However, exploration in this materials space remains nascent due to challenges associated with (1) establishing efficient, scalable synthesis strategies, and (2) navigating the massive design space. <br/>Nanocarbon design and discovery efforts have primarily focused on low pressure synthesis methods including chemical vapor deposition and flame pyrolysis, for which synthesis output is measured in mg/hr rates, and accessible states of carbon are limited. High pressure methods hold significant promise for overcoming these limitations. Decades of explosive materials (EM) research have established that detonation can be used to produce <i><u>kg to ton quantities of nanodiamond in under a single microsecond</u></i>, and that a variety of unique, technologically promising nanomaterials can be produced in this fashion simply by changing the explosive material composition. However, when appropriating detonation for <i>intentional</i> materials synthesis, a key limitation is the inherent coupling between the driver and the precursor – that is, the temperatures (T), pressures (P), and the kinetics with which those conditions are realized during detonation is characteristic to the specific EM itself, precluding independent control over precursor composition necessary to tune properties of the emergent nanocarbon materials. <br/>Recently we demonstrated that this limitation can be overcome by through use of an external shockwave source (e.g., via projectile or laser rather than detonation) to drive arbitrary precursors to high T/P in a finely controllable manner through a combined experimental and computational study. This presentation will overview the computational portion of the work including ChIMES, the unique physics-informed machine learning capability that enabled this work. Recent advances toward elucidating mechanisms and kinetics for the governing reactive phase transformation and phase separation processes will be discussed.