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Display Omitted Free-standing EUV pellicle is desirable to avoid non-uniform intensity.Nonlinear deflection model is used to predict deflection of EUV pellicle.Deflection of pellicle satisfies the desired specification at full scale.Trade-off between mechanical and optical properties is highlighted. In extreme ultraviolet lithography (EUVL), a pellicle is a thin (a few nanometers in scale) protective membrane that can prevent the mask from suffering from defects. However, this thin film can be easily deformed by gravity and other forces. Although the hexagonal-shaped mesh support structure can decrease the stress caused by external pressure, its structural shape can degrade the image quality on the wafer. Therefore, studying the deflection of a free-standing EUV pellicle is needed. We revisited the plate theory and found that a nonlinear deflection term should be added to the deflection equation. The deflection of a 50nm thick polysilicon pellicle is about 100µm for a full-scale (100mmi?100mm) pellicle. Previously, researchers have tried to include graphene in multi-layer EUV pellicles in order to enhance the mechanical properties of the film. We found that the addition of graphene did not cause any serious deflection problems. This study shows that a free-standing EUV pellicle without mesh support can be used without any noticeable deflection effect on the pattern fidelity.

We consider optimal state discrimination in a general convex operational framework, so-called generalized probabilistic theories (GPTs), and present a general method of optimal discrimination by applying the complementarity problem from convex optimization. The method exploits the convex geometry of states but not other detailed conditions or relations of states and effects. We also show that properties in optimal quantum state discrimination are shared in GPTs in general: i) no measurement sometimes gives optimal discrimination, and ii) optimal measurement is not unique., 13 pages

In x Ga1−x N/GaN multiple quantum wells (MQWs), composed of 28-A In0.29Ga0.71N wells and 24-A In0.23Ga0.77N wells, were grown by using metal-organic chemical vapor deposition. Temperaturedependent photoluminescence (PL) spectra showed that the energies of the two dominant peaks in the In x Ga1−x N/GaN MQWs decreased with increasing temperature. The electronic subband energies and the wavefunctions in the In x Ga1−x N/GaN MQWs were calculated by solving the Schrodinger equation in the 8-band envelope function approximation. The effects of the spontaneous polarization, strain and piezoelectric polarizations on the electronic structures of the In x Ga1−x N/GaN MQWs were examined to explain the PL data. The calculated interband transition energies from the ground electronic subbands to the ground hole subbands in In x Ga1−x N/GaN MQWs were in reasonable agreement with those obtained from the PL spectra.

High resolution patterning on the chip could be achieved by extreme ultraviolet lithography (EUVL). However, the defect on the mask becomes more important issue with very short wavelength (13.5 nm). Using the pellicle which could protect the mask from the defects can support high volume manufacturing (HVM). Most of the materials considered for pellicle have relatively high extinction coefficient in EUV region. Therefore, the thickness of the pellicle should be ~ nm thin. The stress of the pellicle is dependent not only on the temperature but also on the mechanical properties of the pellicle. The stress induced by the gravity was small compared to the thermal stress. However, the residual stress should be also considered since it is dependent on the pellicle manufacturing environment and this stress is comparable with the thermal stress. Our result shows the importance of the lowering the pellicle fabrication temperature in terms of the extending the lifetime during the scanning process.

Strained InGaAlP/In0.5Al0.5P multiple quantum wells (MQWs) with digital alloy wells made of alternating 3-monolayer In0.5Ga0.5P and 2-monolayer In0.5Al0.5P layers were grown by using molecular-beam epitaxy. The electronic subband energy states and the interband transition energies of the InGaAlP/InAlP MQWs were calculated by using the finite element method to solve the Schrodinger equation in an 8-band envelope function approximation including the strain effects. The calculated interband transitions of the InGaAlP/InAlP MQWs were in reasonable agreement with the excitonic transitions obtained from the photoluminescence spectra.

A central issue in principal component analysis (PCA) is that of choosing the appropriate number of principal components to be retained. Bishop (1999a) suggested a Bayesian approach for PCA for determining the effective dimensionality automatically on the basis of the probabilistic latent variable model. This paper extends this approach by using mixture priors, in that the choice dimensionality and estimation of principal components are done simultaneously via MCMC algorithm. Also, the proposed method provides a probabilistic measure of uncertainty on PCA, yielding posterior probabilities of all possible cases of principal components.

A new algorithm to analyze digitized Langmuir probe (LP) data was developed with wavelet transforms to provide the electron energy distribution function (EEDF) for bi-Maxwellian plasmas. Because most algorithms to analyze probe data have been developed with the Druyvesteyn formula, which is based on the second derivative of the current with respect to the probe voltage, the accuracy of the analysis is very sensitive to the noise level during the acquisition of the data’s derivative. Especially, the number of hot electrons in the bi-Maxwellian plasma is small enough to compare the noise level, and the noise-filtering method is the kernel in the development of the algorithm to analyze the bi-Maxwellian EEDF. Here, a bi-orthogonal wavelet and continuous wavelet transforms are chosen for the de-noising and the dierentiation processes, respectively. This provides the filtered data with minimum loss of important information. Artificial LP data sets composed of electrons were generated with various bulk and hot temperatures, and the developed algorithm was evaluated for various white noise levels. For the case of noise levels 10 times ion saturation current, the plasma parameters, such as the population of hot electrons and the temperatures of hot and bulk electrons, were accurately analyzed with only a few percent deviations from the input.

When a part of data is unobserved the marginal likelihood of parameters given the observed data often involves analytically intractable high dimensional integral and hence it is hard to find the maximum likelihood estimate of the parameters. Simulated maximum likelihood(SML) method which estimates the marginal likelihood via Monte Carlo importance sampling and optimize the estimated marginal likelihood has been used in many applications. A key issue in SML is to find a good proposal density from which Monte Carlo samples are generated. The optimal proposal density is the conditional density of the unobserved data given the parameters and the observed data, and attempts have been given to find a good approximation to the optimal proposal density. Algorithms which adaptively improve the proposal density have been widely used due to its simplicity and efficiency. In this paper, we describe a fully adaptive algorithm which has been used by some practitioners but has not been well recognized in statistical literature, and evaluate its estimation performance and robustness via a simulation study. The simulation study shows a great improvement in the order of magnitudes in the mean squared error, compared to non-adaptive or partially adaptive SML methods. Also, it is shown that the fully adaptive SML is robust in a sense that it is insensitive to the starting points in the optimization routine.

In general, it is very hard to correctly predict the elongated contact hole resist reflow process ( CH RRP) due to position shift and pattern size irregularity of RRP, because simple RRP simulator uses isotropic resist flow. Therefore RRP simulator was upgraded which can correctly predict the elongated CH RRP by adding the bulk effect and anisotropic reflow. Optical proximity correction for 32 nm node was also applied to the elongated CH RRP to correctly predict the anisotropic elongated CH. The experimental and simulated CH patterns after RRP were compared and found that the simulator can correctly predict the behavior of complex CH array after RRP.

A new blind data hiding scheme is proposed in which data is decomposed using the Fresnelet transform. The inverse Fresnelet transform is performed on decomposed subbands by choosing different key parameters, and the coded pattern of the information data is obtained. This coded pattern is embedded into particular subbands of the cover image using the wavelets. The proposed method has good imperceptibility and large capacity of the information embedded data. Using the Fresnelet transform with a family of wavelet transforms makes the scheme more efficient in terms of extracted accuracy of hidden information. Moreover, the hidden data can be recovered without access to the original cover data. The proposed method is used to resolve privacy and security issues raised with respect to emerging internet applications for the effective handling of confidential data.

A new algorithm to analyze Langmuir probe (LP) data has been developed with Daubechies (DWT) and bi-orthogonal wavelet transforms (BWT), which remove the noise from the raw data without losing important information. The first derivative of the LP signal is processed using BWT and its result readily provides the peak value, which corresponds to the plasma potential. The LP data processed using DWT provides the saturation current lines directly, which corresponds to the electron and ion saturation currents. The region required to obtain the electron temperature can be automatically determined from the plasma potential to the end of the ion saturation current line so that the input from the analyzer is not required to continue the analysis. The plasma density can be obtained from the electron saturation current and the electron temperature. Accuracy tests of the algorithm are carried out with simulation probe data containing various levels of random noise. The results show that the algorithm based on the wavelet transforms removes noise effectively and that the plasma parameters are obtained accurately.

By utilizing singular value decomposition (SVD) and shift averaged Harr wavelet transform (WT) with a set of Daubechies wavelet coefficients (1/2, -1/2), a method that can simultaneously eliminate an unwanted large solvent peak and noise peaks from NMR data has been developed. Noise elimination was accomplished by shift-averaging the time domain NMR data after a large solvent peak was suppressed by SVD. The algorithms took advantage of the WT, giving excellent results for the noise elimination in the Gaussian type NMR spectral lines of NMR data pretreated with SVD, providing superb results in the adjustment of phase and magnitude of the spectrum. SVD and shift averaged Haar wavelet methods were quantitatively evaluated in terms of threshold values and signal to noise (S/N) ratio values.

A new modified singular value decomposition method, piecewise polynomial truncated SVD (PPTSVD), which was originally developed to identify discontinuity of the earth’s radial density function, has been used for large solvent peak suppression and noise elimination in nuclear magnetic resonance (NMR) signal processing. PPTSVD consists of two algorithms of truncated SVD (TSVD) and L1 problems. In TSVD, some unwanted large solvent peaks and noise are suppressed with a certain soft threshold value, whereas signal and noise in raw data are resolved and eliminated in L 1 problems. These two algorithms were systematically programmed to produce high quality of NMR spectra, including a better solvent peak suppression with good spectral line shapes and better noise suppression with a higher signal to noise ratio value up to 27% spectral enhancement, which is applicable to multidimensional NMR data processing.

The magnetoresistance (MR) of Co (1)/Permalloy (t)/Co (0.4)/Cu (3.6)/Co (5) (nm) multilayers has been measured as a function of the free-layer thickness and temperature down 30 K. The MR ratio decreases with small oscillations as the thickness of the free layer increases from 5 to 11 nm, where the oscillation period is about 1 nm. The MR behavior is dominantly affected by volume magnetic characteristics. The MR ratio increases as the measuring temperature decreases down to 100 K, but then is followed by an increase, where the increasing rate of change of MR with decreasing temperature is also oscillatory with free-layer thickness.

Latent class models have recently drawn considerable attention among many researchers and practitioners as a class of useful tools for capturing heterogeneity across different segments in a target market or population. In this paper, we consider a latent class logit model with parameter constraints and deal with two important issues in the latent class models--parameter estimation and selection of an appropriate number of classes--within a Bayesian framework. A simple Gibbs sampling algorithm is proposed for sample generation from the posterior distribution of unknown parameters. Using the Gibbs output, we propose a method for determining an appropriate number of the latent classes. A real-world marketing example as an application for market segmentation is provided to illustrate the proposed method.

A new multiscale implementation of nonlocal means filtering (MHNLM) for image denoising is proposed. The proposed algorithm also introduces a modification of the similarity measure for patch comparison. Assuming the patch as an oriented surface, the notion of a normal vectors patch is introduced. The inner product of these normal vectors patches is defined and then used in the weighted Euclidean distance of intensity patches as the weight factor. The algorithm involves two steps: the first step is a multiscale implementation of an accelerated nonlocal means filtering in the discrete stationary wavelet domain to obtain a refined version of the noisy patches for later comparison. The next step is to apply the proposed modification of standard nonlocal means filtering to the noisy image using the reference patches obtained in the first step. These refined patches contain less noise, and consequently the computation of normal vectors and partial derivatives is more precise. Experimental results show equivalent or better performance of the proposed algorithm compared to various state-of-the-art algorithms.

For spatial regressions with sinusoidal surfaces, the ordinary least squares estimator (OLSE) is shown to be asymptotically as efficient as the geeralized least squares estimator (GLSE) in that the covariance matrices of the two estimators have the same nontrivial limit under the same normalization.

A new method of digital off-axis hologram reconstruction based on the Fresnel transform is proposed. A combination of composite filtering, Abbe’s limitation, and digital lens formulae has been used with an appropriate handling of Fresnel impulse response propagator. A clear image of microscopic object is efficiently reconstructed from hologram using a plane wave with involvement of electric field along bi-cubic interpolation in the final reconstruction step. In particular, the proposed method automatically suppresses the zero order term and virtual image. The image can be reconstructed with large size using interpolation scheme with the Haar wavelet. The proposed method facilitates the transverse high resolution of microscopic image, which has better applicability than other approaches. Moreover, the advantages of this method are its simplicity and convenience in data processing.

Medical images are commonly stored in digital media and transmitted via Internet for certain uses. If a medical information image alters, this can lead to a wrong diagnosis which may create a serious health problem. Moreover, medical images in digital form can easily be modified by wiping off or adding small pieces of information intentionally for certain illegal purposes. Hence, the reliability of medical images is an important criterion in a hospital information system. In this paper, Fresnelet transform is employed along with appropriate handling of the Arnold transform and the discrete cosine transform to provide secure distribution of medical images. This method presents a new data hiding system in which steganography and cryptography are used to prevent unauthorized data access. The experimental results exhibit high imperceptibility for embedded images and significant encryption of information images., Comment: 16 pages, 11 figures, Journal Paper

Robust solutions are recently needed to handle the unusual modification of extensively distributed medical information images. If a medical information image is modified, it may cause to have wrong diagnosis that may arouse a serious problem. Moreover, medical images of digital form are easy to alter for illegal purposes. For instance, by wiping off or adding small information intentionally, it is possible to modify the digital medical images for certain illegal purposes; like insurance claims etc. Hence, the reliability of medical image is an important criterion in a Hospital Information System (HIS). In this paper Fresnelet transform is used for secure distribution of medical images based on Fresnelet coefficient. The experimental results exhibit the high imperceptibility for host image and the significant robustness of embedded image.

The minimum feature size of the semiconductor device will be smaller and smaller because of the increasing demand for the high integration of the device. According to recently proposed roadmap, ArF immersion lithography will be used for 65 nm to 45 nm technology nodes. Polarization effect becomes a more important factor due to the increasing demand for high NA optical system and the use of immersion lithography. It is important to know that the polarization effect is induced by mask in small size patterning. The unpolarized plane waves leaving the illumination system are diffracted by the mask. So the light beam going through the mask will experience induced polarization by the mask. In this paper, we considered the change of polarization state as a function of mask properties. We calculated vector diffraction of 193 nm incident light. The masks considered are the chromeless mask, a binary chrome mask and 6 % attenuated phase shifting mask. We use the finite-difference time-domain method to solve the Maxwell equation. The aerial image depends on the polarization states induced by the mask properties such as materials, thickness, and pitch.

Resist reflow is a simple and cost effective technique by which the resist is baked above the glass transition temperature (Tg) after the typical contact hole pattern has been exposed, baked and developed. Resist reflow method can obtain very high resolution without the loss of process margin than any other resolution enhancement techniques that can make the same linewidth. But it is difficult to predict the results of the thermal flow and the process optimization. If the results of reflow process can be exactly predicted, we can save great time and cost. In order to optimize the layout design and process parameters, we develop the resist flow model which can predict the resist reflow tendency as a function of the contact hole size, initial shape and reflow temperature for the normal and elongated contact hole. The basic fluid equation is used to express the flow of resist and the variation of viscosity and density as a function of reflow temperature and time are considered. Moreover surface tension and gravity effects are also considered. In order to build a basic algorism, we assume that the fluid is incompressible, irrotational and Newtonian. First, we consider the boundary movement of side wall and we think the basic equations for free surface flow of fluid as 2-dimensional time-dependent Navier-Stokes equations with the mass conservation equation. Surface tension acting on the interface pressure difference and gravity force that enable the resist flow are also included.

Electron energy distribution function (EEDF) from the Langmuir probe (LP) data is important in the analysis of accurate plasma density and electron temperature. The determination of EEDF requires the 2nd derivative of LP data with respect to the probe voltage, which may enhance the noises in the probe data seriously. In order to filter the noise effectively, the wavelet transformation technique, especially the bi-orthogonal wavelet transform (BWT), was adapted to separate the noises from the 2nd derivative LP data. The accuracy of algorithm based on the BWT was evaluated with various noise levels for the Maxwellian distribution electrons. It provides the EEDF without losing the important information that has an advantage of minimizing the operator's choices to precede the analysis of LP data.

Summary form only given. In this paper, we configured the open type DBD (dielectric barrier discharge) system. Discharge character was remained as a stable feature and its properties were successfully investigated. Power absorption was measured as product of voltage and current as a function of frequency under open-air atmosphere. We observed the existence of an optimum frequency for power absorption. It is suggested that the optimum frequency occurs because the phase difference between voltage and current decreases as frequency increases. Helium addition to O/sub 2/-discharge under open-air condition shows OES intensity changes as He flow rate. This means that generation rate of radical may change according to the gas species although inert gas is added. Physical meaning of the area of current and voltage trajectory on 1-V plain is supposed to reactive part. To increase the power efficiency, we should reduce the area, i.e. the phase difference of voltage and current. Contact angle is measured on PR (photoresist) surface after some treatment conditions. Helium addition on the main O/sub 2/-discharge results in the increase of contact angle. It means that the He addition changes the radicals generated from oxygen and affects the surface of PR.

The polarization effects on the elastic dust grain collisions are investigated in unmagnetized complex dusty plasmas. The result shows that the polarization effect enhances the scattering cross section in dusty plasmas. In addition, it is found that the polarization effect on the scattering cross section increases with an increase of the collision velocity. The polarization effect increases with increasing Coulomb radius of interaction between thermal ions and the dust grain in high collision velocities.

Summary form only given. Surface passivation plays a crucial role in the fabrication process of high efficiency multi-crystalline silicon (mc-Si) solar cells. Plasma enhanced chemical vapor deposition (PECVD) of silicon nitride (SiN) is a proven technique for obtaining layers that meet the needs of surface passivation and anti-reflection coatings. In addition, the deposition process appears to provoke bulk passivation as well due to diffusion of atomic hydrogen. This bulk passivation is an important advantage of PECVD deposition when compared to the conventional CVD techniques. A further advantage of PECVD is that the process takes place at a relatively low temperature of 300/spl deg/C, keeping the total thermal budget of the cell processing to a minimum. This paper deals with the fabrication of multicrystalline silicon solar cells with PECVD SiN layers combined with high-throughput screen printing and RTF firing. Using this sequence we were able to obtain solar cells with an efficiency of 13.5% for multi crystalline polished Si wafers of size 125 mm square. POCl/sub 3/ doped polished silicon wafers with a junction depth of about 0.5 /spl mu/m and an emitter sheet resistance of 35 /spl Omega//sq were selected for the cell fabrication. The mean cell efficiency, fill factor and Voc for the cells prepared in the present study were found to be 13.5%, 0.76 and 0.602 V respectively.