{'fraction_non_alphanumeric': 0.017857142857142856, 'fraction_numerical': 0.001913265306122449, 'mean_word_length': 5.276, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Simulation and optimization of etch on flexible substrates for roll-to-roll processing

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.