Bayesian optimization for stable properties amid processing fluctuations in sputter deposition

arXiv:2405.03092v1 Announce Type: cross
Abstract: We introduce a Bayesian optimization approach to guide the sputter deposition of molybdenum thin films, aiming to achieve desired residual stress and sheet resistance while minimizing susceptibility to stochastic fluctuations during deposition. Thin films are pivotal in numerous technologies, including semiconductors and optical devices, where their properties are critical. Sputter deposition parameters, such as deposition power, vacuum chamber pressure, and working distance, influence physical properties like residual stress and resistance. Excessive stress and high resistance …

abstract arxiv bayesian cond-mat.mtrl-sci cs.lg devices films guide math.oc optical optimization pivotal processing residual semiconductors stochastic stress technologies type while