Enhancing control in spatial atomic layer deposition: insights into precursor diffusion, geometric parameters, and CVD mitigation strategies

Thien Thanh Nguyen, Diem Nguyen Thi Kieu,Hao Van Bui,Loan Le Thi Ngoc,Viet Huong Nguyen

NANOTECHNOLOGY(2024)

引用 0|浏览1
暂无评分
摘要
In recent years, spatial atomic layer deposition (SALD) has gained significant attention for its remarkable capability to accelerate ALD growth by several orders of magnitude compared to conventional ALD, all while operating at atmospheric pressure. Nevertheless, the persistent challenge of inadvertent contributions from chemical vapor deposition (CVD) in SALD processes continues to impede control over film homogeneity, and properties. This research underscores the often-overlooked influence of diffusion coefficients and important geometric parameters on the close-proximity SALD growth patterns. We introduce comprehensive physical models complemented by finite element method simulations for fluid dynamics to elucidate SALD growth kinetics across diverse scenarios. Our experimental findings, in alignment with theoretical models, reveal distinctive growth rate trends in ZnO and SnO2 films as a function of the deposition gap. These trends are ascribed to precursor diffusion effects within the SALD system. Notably, a reduced deposition gap proves advantageous for both diffusive and low-volatility bulky precursors, minimizing CVD contributions while enhancing precursor chemisorption kinetics. However, in cases involving highly diffusive precursors, a deposition gap of less than 100 mu m becomes imperative, posing technical challenges for large-scale applications. This can be ameliorated by strategically adjusting the separation distance between reactive gas outlets to mitigate CVD contributions, which in turn leads to a longer deposition time. Furthermore, we discuss the consequential impact on material properties and propose a strategy to optimize the injection head to control the ALD/CVD growth mode.
更多
查看译文
关键词
spatial ALD,diffusion coefficient,deposition gap,precursor mixing,CVD
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要