The calibration of optical proximity correction (OPC) models has become increasingly challenging, especially when the behavior of photoresist on wafers cannot be adequately interpreted using conventional model terms assembled in a linear fashion. Additionally, fine-tuning such linearly separable physical components proves difficult due to evidence of nonlinear interactions among physical effects. In this study, we propose leveraging an advanced regression technique that progressively augments the linear model assembly with perturbative nonlinear neural network units the sharing same set of physics-inspired model terms as its base model, aiming to enhance model accuracy while maintaining stability. The research approach involves setting up initial models using conventional model calibration techniques, including optical model optimization and resist model optimization. Subsequently, we incorporate the Synopsys Advanced Regression (AR) neural network to identify essential non-linear interactions among modeling components. We selectively include these non-linear components into the existing linear model to capture on-wafer behavior. The entire process is designed to integrate seamlessly into the existing OPC production flow, ensuring a balance between model accuracy and efficiency. To evaluate the efficacy of the Synopsys AR method, we conduct tests on layers from 3D-NAND. The results demonstrate that this approach significantly reduces calibration costs due to its simpler calibration requirements.
In photolithography, we need accurate models as computation engine for optical proximity correction (OPC). Traditional OPC modeling consists of a series of components for photo mask, optical exposure system, and resist materials. These models are trained using compact model forms based on wafer-level critical dimension (CD) or edge placement error (EPE) measurements. In recent years, advancements in neural networks and machine learning have had significant advancements. In this work, we evaluated advanced neural network-based resist models on a Tensor Flow machine learning platform. This work describes resist and optical response of machine learning (ML) model through process window to achieve improved model representation of lithography process. Using ML OPC vias mask as an example, we will show improved accuracy through dose and focus process conditions and verify model accuracy with physical hardware data. Also, we will compare multiple neural network-based modeling approaches, investigate the ML models’ impacts on OPC correction and verification recipes, and dataprep runtime. The machine learning based OPC with ML model and best practice will be implemented in cloud production environment.
As feature resolution and process variations continue to shrink for new nodes of both DUV and EUV lithography, the density and number of devices on advanced semiconductor masks continue to increase rapidly. These advances cause significantly increased pressure on the accuracy and efficiency of OPC mask output. To meet manufacturing yield requirements, systematic errors from all sources are important to consider during mask synthesis. Specifically, accurately considering etch effects within OPC and ILT is becoming more critical. Mask synthesis flows have typically accounted for etch proximity effects using rule-based approaches, and the accuracy limitations of fast etch models has limited wide-spread adoption of model-based etch mask correction approaches. Several publications and industry presentations have discussed the use of neural networks or other machine learning techniques to provide improvements in both accuracy and efficiency in mask synthesis flows. In this paper, we present results of using machine learning in etch models to improve model accuracy without sacrificing TAT. Then we demonstrate an ILT based etch correction method using the machine learning etch model that converges quickly and outputs an ADI target contour to be used as the target for OPC or ILT mask correction.
We provide background on differences between traditional and machine learning modeling. We then discuss how these differences impact the different validation needs of traditional and machine learning OPC compact models. We then provide multiple diverse examples of how machine learning OPC compact validation modeling can be appropriately validated both for modeling-specific production requirements such as model signal/contour accuracy, predictiveness, coverage and stability; and also general OPC mask synthesis requirements such as OPC/ILT stability, convergence, etc. Finally we conclude with thoughts on how machine learning modeling methods and their required validation methods are likely to evolve for future technology nodes.
Wavelength calibrators are a critical component of high precision and accuracy radial velocity measurements. An order of magnitude improvement of the state-of-the-art of calibration of echelle spectrographs is amongst the requirements needed to achieve detection of earth-mass planets around sun-like stars in the habitable zone. We present studies of calibrators using a custom Fourier Transform Spectrograph (FTS) optimized for characterizing broadband, high repetition-rate laser frequency combs ("astro-combs") as well as other calibration sources including Th:Ar lamps and white-light etalons.
Searches for extrasolar planets using precision radial velocity (PRV) techniques are approaching Earth-like planet sensitivity, however require an improvement of one order of magnitude to identify earth-mass planets in the habitable zone of sun-like stars. A key limitation is spectrograph calibration. An astro-comb, an octave-spanning laser frequency comb and a Fabry-Pérot cavity, producing evenly spaced frequencies with large wavelength coverage, is a promising tool for improved wavelength calibration. We demonstrate the calibration of a high-resolution astrophysical spectrograph below the 1 m/s level in the 8000-9000 Å and 4200 Å spectral bands.
Searches for Earth-like exoplanets using the stellar radial velocity measurements require accuracy <10 cm/s over years.
To achieve such high accuracy requires a wavelength reference that provides many calibration lines with fractional
frequency accuracy of 10-10 in the visible spectral range. We have developed a green astro-comb that generates ~6000 lines equally spaced by ~0.15 Å over 1000-Å bandwidth (centered at 5500 Å). The frequency of each line is directly locked to a frequency standard with fractional accuracy of 10-12 over decades. We plan to bring this green astro-comb to the HARPS-north spectrograph at the TNG telescope for tests in 2012.
Fiber-optic Cherenkov radiation has emerged as a wavelength conversion technique to achieve isolated
spectrum in the visible wavelength range. Most published results have reinforced the impression that CR
forms a narrowband spectrum with poor efficiency. We both theoretically and experimentally investigate
fiber-optic Cherenkov radiation excited by few-cycle pulses. We introduce the coherence length to quantify
the Cherenkov-radiation bandwidth and its dependence on propagation distance. Detailed numerical
simulations verified by experimental results reveal three unique features that are absent when pumped with
often-used, long pulses; that is, continuum generation (may span one octave in connection with the pump
spectrum), high conversion efficiency (up to 40%), and broad bandwidth (70 nm experimentally obtained)
for the isolated Cherenkov radiation spectrum. These merits allow achieving broadband visible-wavelength
spectra from low-energy ultrafast sources which opens up new applications.
We describe recent work calibrating a cross-dispersed spectrograph with an "astro-comb" i.e., a high repetition rate,
octave spanning femtosecond laser frequency comb; and a filter cavity suppressing laser modes to match the resolution
of the spectrograph. Our astro-comb provides ~1500 evenly spaced (~0.6 A) calibration lines of roughly 100 nW per line
between 7800 and 8800 Angstroms. The calibration lines of the laser are stabilized to atomic clocks which can be
referenced to GPS providing intrinsic stability of the source laser below 1 cm/s in stellar radial velocity sensitivity, as
well as long term stability and reproducibility over years. We present calibration of the TRES spectrograph at the 1.5 m
telescope at the Fred L Whipple Observatory below 1 m/s radial velocity sensitivity in six orders from 7800-8800 A.
Sampling rates of high-performance electronic analog-to-digital converters (ADC) are fundamentally limited by the timing jitter of the electronic clock. This limit is overcome in photonic ADC's by taking advantage of the ultra-low timing jitter of femtosecond lasers. We have developed designs and strategies for a photonic ADC that is capable of 40 GSa/s at a resolution of 8 bits. This system requires a femtosecond laser with a repetition rate of 2 GHz and timing jitter less than 20 fs. In addition to a femtosecond laser this system calls for the integration of a number of photonic components including: a broadband modulator, optical filter banks, and photodetectors. Using silicon-on-insulator (SOI) as the platform we have fabricated these individual components. The silicon optical modulator is based on a Mach-Zehnder interferometer architecture and achieves a VπL of 2 Vcm. The filter banks comprise 40 second-order microring-resonator filters with a channel spacing of 80 GHz. For the photodetectors we are exploring ion-bombarded silicon waveguide detectors and germanium films epitaxially grown on silicon utilizing a process that minimizes the defect density.
In this report, we will review our recent development on the sub-wavelength plastic fiber for THz waveguiding.
The proposed and demonstrated terahertz single-mode sub-wavelength waveguide is similar to an optical taper
fiber, having a low attenuation constant (~10-2cm-1), a high coupling efficiency, and a free-space direct coupling
capability, comprised with a sub-wavelength PE fiber core with air cladding. The spectral characteristic of the
sub-wavelength THz fiber will be discussed, with an effective attenuation minimum of THz waves on the order
of or less than 10-3cm-1 at a specific wavelength range which depends on the fiber diameter. More over, the
application of the sub-wavelength plastic fiber will also be discussed, including a first demonstration of a singlemode
fiber-based THz directional coupler.
We report a simple subwavelength-diameter plastic wire, similar to an optical fiber, for guiding terahertz wave with a low attenuation constant. With a large wavelength-to-fiber-core ratio, the fractional power delivered inside the lossy core is reduced, thus lowering the effective fiber attenuation constant. In our experiment, we adopt a polyethylene fiber with a 200-500 μm diameter for guiding terahertz waves in the frequency range of 0.2-0.5 THz in which the attenuation constant is reduced to the order of or less than 0.01 cm-1. Direct free-space coupling efficiency, as high as 20%, can be achieved by using an off-axis parabolic mirror. Furthermore, all the plastic wires are easily available in our daily life without complex processes and expensive costs.
The accurate detection of minute amounts of chemical and biological substances has been a major goal in bioanalytical technology throughout the twentieth century. Fluorescence dye labeling detection remains the effective analysis method, but it modifies the surroundings of molecules and lowering the precision of detection. An alternative label free detecting tool with little disturbance of target molecules is highly desired. Theoretical calculations and experiments have demonstrated that many biomolecules have intrinsic resonance due to vibration or rotation level transitions, allowing terahertz (THz)-probing technique as a potential tool for the label-free and noninvasive detection of biomolecules. In this paper, we first ever combined the THz optoelectronic technique with biochip technology to realize THz biosensing. By transferring the edge-coupled photonic transmitter into a thin glass substrate and by integrating with a polyethylene based biochip channel, near field THz detection of the biomolecules is demonstrated. By directly acquiring the absorption micro-spectrum in the THz range, different boiomecules can then be identified according to their THz fingerprints. For preliminary studies, the capability to identity different illicit drug powders is successfully demonstrated. This novel biochip sensing system has the advantages including label-free detection, high selectivity, high sensitivity, ease for sample preparation, and ease to parallel integrate with other biochip functionality modules. Our demonstrated detection capability allows specifying various illicit drug powders with weight of nano-gram, which also enables rapid identification with minute amounts of other important molecules including DNA, biochemical agents in terrorism warfare, explosives, viruses, and toxics.
Since the first demonstration in 1990, two-photon fluorescence microscopy (TPFM) has made a great impact on biomedical researches. With its high penetration ability, low out-of-focus photodamage, and intrinsic three-dimensional (3D) sectioning capability, TPFM has been widely applied to various medical diagnosis and genome researches. Recently, single-mode optical fibers were introduced into the TPFM systems for remote optical pulse delivery. Fiber-based TPFM has advantages including isolating the vibration from laser and electronic devices, flexible system design, and low cross-talks. It is also the first step toward an all-fiber based two-photon endoscope. However, due to serious temporal broadening when conventional Ti:sapphire based femtosecond pulses propagate through the fiber, the two-photon excitation efficiency of the fiber-optic TPFM is much lower than the conventional one. The temporal broadening effect mainly comes from group velocity dispersion (GVD) and self-phase modulation (SPM), which also leads to significant spectral broadening. To reduce the temporal broadening effect, here we present a hollow-core photonic-bandgap fiber based TPFM. By replacing the conventional single-mode fiber with the hollow core photonic bandgap fiber, the GVD and SPM effects can be greatly reduced for high intensity, ultra-short pulse delivery. Femtosecond Ti:sapphire pulses passing through the fiber with negligible GVD and SPM effects is demonstrated in this paper. Much improvement of two-photon fluorescence excitation efficiency is thus achieved with the hollow-core photonic-bandgap fiber based TPFM.
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