{'fraction_non_alphanumeric': 0.013513513513513514, 'fraction_numerical': 0.0, 'mean_word_length': 5.544186046511628, '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}}
Model-assisted complementary double exposure with source optimization

Source optimization techniques fall into two contrasting categories: The first and most common category includes methods to minimize OPC complexity and maximize process window for a specific pattern, without guaranteeing adequate image quality for the rest of the layout. The second category includes methods which optimize source and mask concurrently to deliver the largest process window and maximum resolution. This approach however, provides minimum control in the manufacturability of the mask. Our formulation is a hybrid combination of both categories. We apply a model-assisted double exposure decomposition using pre-optimized sources. By adding a second exposure we minimize possible negative impacts that the pattern specific source may have over the whole layout, while providing control over the area of interest and taking into account realistic mask constraints. We applied this technique to an SRAM design and the surrounding logic. Because of the general formulation of the model-assisted decomposition, we do not explicitly select memory or periphery logic, since by construction this method determines which feature segments correspond to each of the available exposures. We quantify the lithographic performance of this technique against other RET options via a statistical analysis of CD control and ILS behavior.