Simulation and optimization of etch on flexible substrates for roll-to-roll processing
Simulation and optimization of etch on flexible substrates for roll-to-roll processing
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用于卷对卷加工的柔性基板上的蚀刻模拟和优化
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
R. Bonnecaze
中科院分区：
文献类型：
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作者：
Sofia Helpert;Yang H. Ban;Meghali Chopra;R. Bonnecaze
提出了一种方法，以虚拟地预测跨多维工艺空间的柔性基板上的蚀刻轮廓，使用最少数量的校准实验。使用商业软件SandBox StudioTM对柔性衬底上的等离子体蚀刻的物理和化学动力学进行模拟和预测。使用表面动力学模型和水平集方法计算沟槽轮廓的演变。局部蚀刻速率包括可见度效应，以解释在图案显影时蚀刻的部分屏蔽以及再沉积的效应。然后，使用实验的结果来更新校准的模型参数。如果过程目标（例如，侧壁角度、沟槽临界尺寸和横跨腹板的均匀性），则通过该方法建议一组新的实验。重复该过程，直到确定最佳工艺条件。通过对聚合物衬底上多晶硅薄膜的线间距图形刻蚀实验，验证了该方法的有效性。结果与反应性离子蚀刻与CF4和HBr显示和最佳的蚀刻配方（功率，蚀刻时间和气体流速）确定。结果发现，这种耦合的模拟实验方法是更有效地比全析因实验设计在预测过程的结果。所提出的方法需要减少66%的实验，将开发成本降低了三倍。
A methodology is presented to virtually predict etch profiles on flexible substrates across multi-dimensional process spaces using a minimal number of calibration experiments. Simulations and predictions of the physics and chemical kinetics of plasma etch on flexible substrates are performed using the commercial software SandBox StudioTM. The evolution of a trench profile is computed using surface kinetics models and the level set method. Local etch rates include visibility effects to account for partial shielding of the etch as the pattern is developed and the effects of redeposition. The results of the experiments are then used to update the calibrated model parameters. If the process objectives (e.g., sidewall angle, trench critical dimensions, and across the web uniformity) are not achieved, then a new set of experiments is suggested by the methodology. The process is repeated until the optimal process conditions are identified. The methodology is validated by experiments on etching line-space patterns of polysilicon films on polymer substrates. Results with reactive ion etching with either CF4 and HBr are shown and the optimal etch recipes (power, etch time and gas flow rates) determined. It is found that this coupled simulation-experiment approach is much more efficient than full factorial experimental design at predicting process outcomes. The methodology presented requires 66% fewer experiments reducing the cost of development by a factor of three.