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| Format: | Preprint |
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2025
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| Online Access: | https://arxiv.org/abs/2507.10645 |
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| _version_ | 1866908449426636800 |
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| author | Saucedo, Joel Lamba, Uday Mahabaduge, Hasitha |
| author_facet | Saucedo, Joel Lamba, Uday Mahabaduge, Hasitha |
| contents | Connecting plasma processing parameters to the resultant film microstructure remains a fundamental challenge in materials synthesis, one that has largely confined process design to empirical approaches. To bridge this gap, we develop a predictive analysis of coupling by applying a renormalization group (RG) analysis to an effective Hamiltonian for the stochastic dynamics of the plasma-surface interface, derived systematically from microscopic principles. The central result from this formalism is the system's exhibition of asymptotic freedom; the effective dimensionless coupling, $g$, between the plasma and the growing surface is found to weaken systematically at macroscopic length scales, a finding that provides a rigorous justification for the success of continuum-level models in describing large-scale film evolution. The RG framework yields a non-perturbative scaling relation for the mean grain area, $\langle A \rangle \propto \exp(κ/g)$, where $g$ itself is defined by fundamental parameters such as ion flux ($Φ$) and ion collision time ($τ_{\text{ion}}$). This relation reveals the origin of widely-observed empirical power-law scaling, showing it to be an effective behavior limited to specific process regimes. Crucially, the model furnishes sharp, testable predictions, including the pressure-independence of grain size within collision-dominated plasmas and a parameter-free criterion, $Λ_c = 1/(n^2-1)$, for the onset of morphological instability and faceting based on crystal symmetry. This work establishes a quantitative, parameter-sparse engine for predicting and ultimately controlling microstructural outcomes in thin film synthesis. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_10645 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Scaling Relations, Morphological Stability, and Asymptotic Freedom of Plasma-Surface Deposition Dynamics Saucedo, Joel Lamba, Uday Mahabaduge, Hasitha Plasma Physics Materials Science Statistical Mechanics Connecting plasma processing parameters to the resultant film microstructure remains a fundamental challenge in materials synthesis, one that has largely confined process design to empirical approaches. To bridge this gap, we develop a predictive analysis of coupling by applying a renormalization group (RG) analysis to an effective Hamiltonian for the stochastic dynamics of the plasma-surface interface, derived systematically from microscopic principles. The central result from this formalism is the system's exhibition of asymptotic freedom; the effective dimensionless coupling, $g$, between the plasma and the growing surface is found to weaken systematically at macroscopic length scales, a finding that provides a rigorous justification for the success of continuum-level models in describing large-scale film evolution. The RG framework yields a non-perturbative scaling relation for the mean grain area, $\langle A \rangle \propto \exp(κ/g)$, where $g$ itself is defined by fundamental parameters such as ion flux ($Φ$) and ion collision time ($τ_{\text{ion}}$). This relation reveals the origin of widely-observed empirical power-law scaling, showing it to be an effective behavior limited to specific process regimes. Crucially, the model furnishes sharp, testable predictions, including the pressure-independence of grain size within collision-dominated plasmas and a parameter-free criterion, $Λ_c = 1/(n^2-1)$, for the onset of morphological instability and faceting based on crystal symmetry. This work establishes a quantitative, parameter-sparse engine for predicting and ultimately controlling microstructural outcomes in thin film synthesis. |
| title | Scaling Relations, Morphological Stability, and Asymptotic Freedom of Plasma-Surface Deposition Dynamics |
| topic | Plasma Physics Materials Science Statistical Mechanics |
| url | https://arxiv.org/abs/2507.10645 |