OPC model error study through mask and SEM measurement error

International audienceMask and metrology errors such as SEM (Scanning Electron Microscopy) measurement errors are currently not accounted for when calibrating OPC models. Nevertheless, they can lead to erroneous model parameters therefore causing inaccuracies in the model prediction if these errors are of the same order of magnitude than targeted modeling accuracy. In this study, we used a dedicated design of hundreds of features exposed through a Focus Exposure Matrix (FEM). We measured the mask bias from target for these structures and investigated its impact on the model accuracy. For the metrology error, we compared the SEM measurements to AFM measurements for as much as 105 features exposed in various process conditions of dose and defocus. These data have then been used in a OPC model calibration procedure. We show that the impact of the metrology error is not negligible and demonstrate the importance of taking into account these errors in order to improve the reliability of the OPC models

Outliers detection by fuzzy classification method for model building

International audienceOptical Proximity Correction (OPC) is used in lithography to increase the achievable resolution and pattern transfer fidelity for IC manufacturing. Nowadays, immersion lithography scanners are reaching the limits of optical resolution leading to more and more constraints on OPC models in terms of simulation reliability. The detection of outliers coming from SEM measurements is key in OPC [1]. Indeed, the model reliability is based in a large part on those measurements accuracy and reliability as they belong to the set of data used to calibrate the model. Many approaches were developed for outlier detection by studying the data and their residual errors, using linear or nonlinear regression and standard deviation as a metric [8]. In this paper, we will present a statistical approach for detection of outlier measurements. This approach consists of scanning Critical Dimension (CD) measurements by process conditions using a statistical method based on fuzzy CMean clustering and the used of a covariant distance for checking aberrant values cluster by cluster. We propose to use the Mahalanobis distance [2] in order to improve the discrimination of the outliers when quantifying the similarity within each cluster of the data set. This fuzzy classification method was applied on the SEM CD data collected for the Active layer of a 65 nm half pitch technology. The measurements were acquired through a process window of 25 (dose, defocus) conditions. We were able to detect automatically 15 potential outliers in a data distribution as large as 1500 different CD measurement. We will discuss about these results as well as the advantages and drawbacks of this technique as automatic outliers detection for large data distribution cleaning

Influence des défauts enterrés dans les masques pour la lithographie Extreme Ultra Violet

In microelectronic industry, the key process that permits to decrease the size of the integrated circuits is the lithography. This step will determine the minimal size on the wafer. Nowadays, standard optical lithography reaches their limits and new generation techniques rise up. Extreme Ultra Violet Lithography is one promising technique that will permit to decrease resolution size with a high wafer throughput. In EUV spectra, most of the materials absorb light that impose to work in a vacuum environment with all reflective optics based on molybdenum – silicon multilayer. Defects present during the multilayer deposition process will damage the mask performance and can be printed during the lithography process.The aim of this PhD work is to study defect influence in the EUV mask. For this, we have performed electromagnetic simulation and experimental work with the manufacture of a programmed mask defect. This mask has been exposed on a EUV tool at the ALS synchrotron. Defect growth within the multilayer has also been studied and permits to highlight smoothing effect of the defect. Finally, we have implemented an at wavelength dark field microscopy technique in order to probe tens of nanometres buried defect.Dans l'industrie de la microélectronique, l'étape clé permettant la réduction de la taille des circuits intégrés a toujours été celle de lithographie. C'est elle qui va déterminer la taille du plus petit motif réalisable. A l'heure actuelle, les techniques de lithographie optique commencent à arriver à leur limite et l'on voit émerger de nouvelles techniques qui permettraient de réduire encore ces dimensions. La lithographie Extrême Ultra Violet (EUV) allie des résolutions très agressives tout en conservant un débit élevé de plaquette. Dans la gamme de rayonnement EUV la plupart des matériaux sont absorbants. Ceci impose un fonctionnement dans un environnement sous vide avec des optiques et un masque en réflexion constitués de multicouche de molybdène – silicium. La présence de défauts lors de la réalisation du multicouche peut dégrader les performances du masque et faire que ces défauts s'impriment lors de l'étape de lithographie. L'objet de cette thèse porte sur l'influence des défauts dans les masques. Pour cela nous proposons d'aborder le problème aussi bien par le biais de simulations électromagnétique que par une étude expérimentale, pour laquelle nous avons réalisé un masque à défauts programmés. Ce masque a été insolé sur un outil d'exposition EUV au synchrotron ALS. La croissance au sein des multicouches a également été abordée et a permis de mettre en évidence les phénomènes de lissage des défauts. Nous avons mis au point une technique de microscopie en champ sombre afin de sonder les masques et d'en détecter la présence de défauts de quelques dizaines de nanomètres

Impact of process factors on the performance of hole array metallic filters

International audienc

Measurement of residual thickness usind scatterometry

International audienc

Grayscale lithography process study for sub 5µm microlens patterns

International audienceCMOS imaging has experienced significant developement in the last decades. At the center of thisprogress lies the pixel, composed of a light sensitive area (photodiode) coupled to a network of tran-sistors. As the pixels sizes shrink, the light sensitive area gets smaller and requires light focusingassistance. To address this issue, microlenses are added to the top of the pixels stack. The microlensesare made of polymer resist transparent to the wavelength of interest.Creating such structures is not straightforward and requires complex process steps, especially whenarrays of multiple shapes and sizes are needed. The grayscale approach appears as a promising al-ternative since this unconventional lithography method can produce variable shapes and sizes in asingle lithography step. Mask data preparation is the most critical step for grayscale lithography. Awidespread strategy is to experimentally establish the relationship between a given dose (correspondingto a specific chromium density on the mask) and the remaining resist thickness after development. Therelationship, also known as contrast curve, is used as a transfer function to compute a suitable maskfor the given resist.Our approach is to create a simplified grayscale model able to predict the resist response under anygiven mask and illumination condition. Using the classic contrast curve approach we have designed amask composed of sub 5μm patterns and evaluated the resist profile prediction of the contrast curve ap-proach compared to our grayscale model on various patterns including microlenses, pyramids and bowlshapes. Results show that the contrast curve approach is no longer appropriate when the dimensionsreduce below 5μm

Best focus shift mitigation for extending the depth of focus

International audienceThe low-k1 domain of immersion lithography tends to result in much smaller depths of focus (DoF) compared to prior technology nodes. For 28 nm technology and beyond it is a challenge since (metal) layers have to deal with a wide range of structures. Beside the high variety of features, the reticle induced (mask 3D) effects became non-negligible. These mask 3D effects lead to best focus shift. In order to enhance the overlapping DoF, so called usable DoF (uDoF), alignment of each individual features best focus is required. So means the mitigation of the best focus shift. This study investigates the impact of mask 3D effects and the ability to correct the wavefront in order to extend the uDoF. The generation of the wavefront correction map is possible by using computational lithographic such Tachyon simulations software (from Brion). And inside the scanner the wavefront optimization is feasible by applying a projection lens modulator, FlexWaveTM (by ASML). This study explores both the computational lithography and scanner wavefront correction capabilities. In the first part of this work, simulations are conducted based on the determination and mitigation of best focus shift (coming from mask 3D effects) so as to improve the uDoF. In order to validate the feasibility of best focus shift decrease by wavefront tuning and mitigation results, the wavefront optimization provided correction maps are introduced into a rigorous simulator. Finally these results on best focus shift and uDoF are compared to wafers exposed using FlexWave then measured by scanning electron microscopy (SEM)

OPC for curved designs in application to photonics on silicon

International audienc