Flood Exposure Assisted Chemical Gradient Enhancement Technology (FACET) is introduced for improvement in EUV resist resolution, process control, roughness, patterning failure and sensitivity. Experimental EUV exposure latitude was enhanced (~1.5 times) with FACET using the assist of UV flood exposure. The mechanism of the process window improvement by FACET is explained by non-linear resist coloring (enhancement of UV absorption) vs. EUV exposure dose to enhance acid image contrast during UV flood exposure. To balance chemical gradient enhancement and stochastic effects, Stochastic Aware Resist Formulation and Process optimizer (SARF-Pro) with a fast stochastic simulation model is created. SARF-Pro predicts stochastic patterning failure risks, and optimizes resist formulation and processes by putting emphasis on stochastic variation across patterns. Photosensitized Chemically Amplified ResistTM (PSCARTM) 2.0 with FACET and standard chemically amplified resist (CAR) optimized in SARF-Pro suggests that PSCAR 2.0 with FACET has the potential of better process window, roughness, sensitivity and, we hypothesize, reduced risk of stochastic defects compared with standard CAR.
Resist Formulation Optimizer (RFO) is created to optimize resist formulation under EUV stochastic effects. Photosensitized Chemically Amplified ResistTM (PSCARTM) 2.0 reaction steps are included in the resist reaction model in RFO in addition to standard Chemically Amplified Resists (CAR) reaction steps. A simplified resist roughness calculation method is introduced in RFO. RFO uses “fast stochastic resist model” which uses continuous model information for stochastic calculation. “Resist component’s dissolution inhibition model” is also introduced for better prediction of different resist formulations in RFO. The resist component’s dissolution inhibition model is used for calculation of both Dissolution Inhibition Slope (DIS) and Dissolution Inhibition Deviation (DID). By dividing DID by DIS at a pattern edge, Line Edge Roughness (LER) can be predicted. The RFO performance is validated to give low residual errors after calibration even for different resist formulations. RFO is designed to optimize the resist formulation to minimize resist roughness as a cost function with keeping target CD. RFO suggests that PSCAR 2.0 with Polarity Switching photosensitizer precursor (POLAS) in combination with photosensitizer (PS) image enhancement may provide reduced resist roughness. Simulations using a calibrated rigorous stochastic resist model for S-Litho show a good prediction of PSCAR 2.0 process performance.
Photosensitized Chemically Amplified ResistTM (PSCARTM) has been demonstrated as a promising solution for a high sensitivity resist in EUV lithography mass production. This paper describes the successful calibration of a PSCAR resist model for deployment within rigorous lithography process simulation, capturing continuum as well as stochastic effects. Verification of the calibrated model parameters was performed with new patterns or with new resist formulations with good agreement. The reduction of required EUV dose of PSCAR resist while maintaining similar roughness levels have been achieved both from experimental result and from simulated result. The simulation of PSCAR continues to be a great tool for understanding, predicting, and optimizing the process of PSCAR.
This paper presents a design and technology co-optimization (DTCO) study of metal cut formation in the sub-20-nmregime. We propose to form the cuts by applying grapho-epitaxial directed self-assembly. The construction of a DTCO flow is explained and results of a process variation analysis are presented. We examined two different DSA models and evaluated their performance and speed tradeoff. The applicability of each model type in DTCO is discussed and categorized.
Photosensitized Chemically Amplified ResistTM (PSCARTM) **2.0’s advantages and expectations are reviewed in this paper. Alpha PSCAR in-line UV exposure system (“Litho Enhancer”) was newly installed at imec in a Tokyo Electron Ltd. (TELTM)’s CLEAN TRACKTM LITHIUS ProTM Z connected to an ASML’s NXE:3300. Using the Litho Enhancer, PSCAR 2.0 sensitization preliminary results show that suppression of roughness enhancement may occur while sensitivity is increased. The calibrated PSCAR 2.0 simulator is used for prediction of resist formulation and process optimization. The simulation predicts that resist contrast enhancement could be realized by resist formulation and process optimization with UV flood exposure.
KEYWORDS: 3D modeling, Calibration, Data modeling, Optical lithography, Nanotechnology, Very large scale integration, System on a chip, Logic, Research facilities
Direct Optimization (DO) of a 3D DSA model is a more optimal approach to a DTCO study in terms of accuracy and speed compared to a Cahn Hilliard Equation solver. DO’s shorter run time (10X to 100X faster) and linear scaling makes it scalable to the area required for a DTCO study. However, the lack of temporal data output, as opposed to prior art, requires a new calibration method. The new method involves a specific set of calibration patterns. The calibration pattern’s design is extremely important when temporal data is absent to obtain robust model parameters. A model calibrated to a Hybrid DSA system with a set of device-relevant constructs indicates the effectiveness of using nontemporal data. Preliminary model prediction using programmed defects on chemo-epitaxy shows encouraging results and agree qualitatively well with theoretical predictions from a strong segregation theory.
In this paper, we study the impact of topographic guide or template properties on pattern formation in a directed self-assembly (DSA) process. In particular, we investigate the relationship between free energy and defect generation or process robustness, and analyze the influence of guide affinity. The good correlation between experimental and simulation results confirms the role of certain setup parameters and process conditions on the DSA patterning.
Contact- and proximity lithography in a Mask Aligner is a very cost effective technique for photolithography, as it
provides a high throughput and very stable mature processes for critical dimensions of typically some microns. For
shadow lithography, the printing quality depends much on the proximity gap and the properties of the illumination light.
SUSS MicroOptics has recently introduced a novel illumination optics, referred as MO Exposure Optics, for all SUSS
MicroTec Mask Aligners. MO Exposure Optics provides excellent uniformity of the illumination light, telecentric
illumination and a full freedom to shape the angular spectrum of the mask illuminating light. This allows to simulate and
optimize photolithography processes in a Mask Aligner from the light source to the final pattern in photoresist. The
commercially available software LayoutLab (GenISys) allows to optimize Mask Aligner Lithography beyond its current
limits, by both shaping the illumination light (Customized Illumination) and optimizing the photomask pattern (Optical
Proximity Correction, OPC). Dr.LiTHO, a second simulation tool developed by Fraunhofer IISB fro Front-End
Lithography, includes rigorous models and algorithms for the simulation, evaluation and optimization of lithographic
processes. A new exposure module in the Dr.LiTHO software now allows a more flexible definition of illumination geometries coupled to the standard resist modules for proximity lithography in a Mask Aligner. Results from simulation and experiment will be presented.
This paper studies the application of resist models to AIMSTM images. Measured AIMSTM data were coupled with
resist simulations of the Fraunhofer IISB research and development lithography simulator Dr.LiTHO and with a
compact resist model developed by Carl Zeiss SMS. Through-focus image data of the AIMSTM are transformed into a
bulk image--the intensity distribution within the resist. This bulk image is used to compute the concentration of photo-acid
after exposure and the following resist processing. In the result a resist profile is obtained, which can be used to
extract the printed wafer linewidth and other data. Additionally, a compact resist model developed by Carl Zeiss SMS
was directly applied to the AIMSTM data. The described procedures are used to determine dose latitudes for lines and
spaces with different pitches. The obtained data are compared to actual wafer prints for a 1.2 NA system.
The paper presents a simulation approach for mask proximity printing. The simulation steps include image formation in air and in photoresist, post-exposure bake, and chemical development and analysis of resist profiles. The intensity distribution in air and in resist in proximity distance from the mask is described by a fast frequency domain method that is based on scalar diffraction analysis. The accuracy and the performance of the method are compared with rigorous electromagnetic field computations that take mask topography effects and the finite conductivity of absorber materials into account. The computed intensity distributions inside the resist are coupled to an established standard simulation flow, which is also used in the simulation of projection printing. The resulting resist profiles can be evaluated in terms of linewidth, sidewalls, and other parameters. Finally, an application of the simulation procedure for the simulation of process windows and optimization of linewidth biasing is shown.
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