In recent years, compact modeling of negative tone development (NTD) resists has been extensively investigated. Specific terms have been developed to address typical NTD effects, such as aerial image intensity dependent resist shrinkage and development loading. The use of photo decomposable quencher (PDQ) in NTD resists, however, brings extra challenges arising from more complicated and mixed resist effect. Due to pronounced effect of photoacid and base diffusion, the NTD resist with PDQ may exhibit opposite iso-dense bias trend compared with normal NTD resist. In this paper, we present detailed analysis of physical effects in NTD resist with PDQ, and describe respective terms to address each effect. To decouple different effects and evaluate the impact of individual terms, we identify a certain group of patterns that are most sensitive to specific resist effect, and investigate the corresponding term response. The results indicate that all the major resist effect, including PDQ-enhanced acid/base diffusion, NTD resist shrinkage and NTD development loading can be well captured by relevant terms. Based on these results, a holistic approach for the compact model calibration of NTD resist with PDQ can be established.
As the IC Industry moves towards 32nm technology node and below, it becomes important to study the impact of
process window variations on yield. PVBands is a technique to express process parameter variations such as dose, focus,
mask size, etc. However, PVBands width and area ratio alone are insufficient as a quantitative measure for judging the
PVBand performance, as it does not take into consideration how far away the contours are from the target.
In this paper, a novel mathematical formulation is developed to better judge the PVBands performance. It expresses the
PVBand width and symmetry with respect to the target through a single score. This score can be used in OPC (Optical
Proximity Correction) iterations instead of working with the nominal EPE (Edge Placement Error). Not only does this
approach provide a better measure of the PVBands performance through the value of the score, but it also presents a
straightforward method for PWOPC optimization by using the PV Score directly in the iterations.
To maximize the process window and CD control of main features, sizing and placement rules for sub-resolution assist
features (SRAF) need to be optimized, subject to the constraint that the SRAFs not print through the process window.
With continuously shrinking target dimensions, generation of traditional rule-based SRAFs is becoming an expensive
process in terms of time, cost and complexity. This has created an interest in other rule optimization methodologies, such
as image contrast and other edge- and image-based objective functions.
In this paper, we propose using an automated model-based flow to obtain the optimal SRAF insertion rules for a design
and reduce the time and effort required to define the best rules. In this automated flow, SRAF placement is optimized by
iteratively generating the space-width rules and assessing their performance against process variability metrics. Multiple
metrics are used in the flow. Process variability (PV) band thickness is a good indicator of the process window
enhancement. Depth of focus (DOF), the total range of focus that can be tolerated, is also a highly descriptive metric for
the effectiveness of the sizing and placement rules generated. Finally, scatter bar (SB) printing margin calculations
assess the allowed exposure range that prevents scatter bars from printing on the wafer.
As the industry moves toward 45nm technology node and beyond, further reduction of lithographic process window is anticipated. The consequence of this is twofold: first, the manufactured chip will have pattern sizes that are different from the designed pattern sizes and those variations may become more dominated by systematic components as the process windows shrink; second, smaller process windows will lead to yield loss as, at small dimensions, lithographic process windows are often constrained by catastrophic fails such as resist collapse or trench scumming, rather than by gradual pattern size variation. With this notion, Optical Proximity Correction (OPC) for future technology generations must evolve from the current single process point OPC to algorithms that provide an OPC solution optimized for process variability and yield. In this paper, a Process Window OPC (PWOPC) concept is discussed, along with its place in the design-to-manufacturing flow. Use of additional models for process corners, integration of process fails and algorithm optimization for a production-worthy flow are described. Results are presented for 65nm metal levels.