Browsing by Subject "Etching"
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Item Improving process monitoring and modeling of batch-type plasma etching tools(2015-05) Lu, Bo, active 21st century; Edgar, Thomas F.; Stuber, John D; Djurdjanovic, Dragan; Ekerdt, John G; Bonnecaze, Roger T; Baldea, MichaelManufacturing equipments in semiconductor factories (fabs) provide abundant data and opportunities for data-driven process monitoring and modeling. In particular, virtual metrology (VM) is an active area of research. Traditional monitoring techniques using univariate statistical process control charts do not provide immediate feedback to quality excursions, hindering the implementation of fab-wide advanced process control initiatives. VM models or inferential sensors aim to bridge this gap by predicting of quality measurements instantaneously using tool fault detection and classification (FDC) sensor measurements. The existing research in the field of inferential sensor and VM has focused on comparing regressions algorithms to demonstrate their feasibility in various applications. However, two important areas, data pretreatment and post-deployment model maintenance, are usually neglected in these discussions. Since it is well known that the industrial data collected is of poor quality, and that the semiconductor processes undergo drifts and periodic disturbances, these two issues are the roadblocks in furthering the adoption of inferential sensors and VM models. In data pretreatment, batch data collected from FDC systems usually contain inconsistent trajectories of various durations. Most analysis techniques requires the data from all batches to be of same duration with similar trajectory patterns. These inconsistencies, if unresolved, will propagate into the developed model and cause challenges in interpreting the modeling results and degrade model performance. To address this issue, a Constrained selective Derivative Dynamic Time Warping (CsDTW) method was developed to perform automatic alignment of trajectories. CsDTW is designed to preserve the key features that characterizes each batch and can be solved efficiently in polynomial time. Variable selection after trajectory alignment is another topic that requires improvement. To this end, the proposed Moving Window Variable Importance in Projection (MW-VIP) method yields a more robust set of variables with demonstrably more long-term correlation with the predicted output. In model maintenance, model adaptation has been the standard solution for dealing with drifting processes. However, most case studies have already preprocessed the model update data offline. This is an implicit assumption that the adaptation data is free of faults and outliers, which is often not true for practical implementations. To this end, a moving window scheme using Total Projection to Latent Structure (T-PLS) decomposition screens incoming updates to separate the harmless process noise from the outliers that negatively affects the model. The integrated approach was demonstrated to be more robust. In addition, model adaptation is very inefficient when there are multiplicities in the process, multiplicities could occur due to process nonlinearity, switches in product grade, or different operating conditions. A growing structure multiple model system using local PLS and PCA models have been proposed to improve model performance around process conditions with multiplicity. The use of local PLS and PCA models allows the method to handle a much larger set of inputs and overcome several challenges in mixture model systems. In addition, fault detection sensitivities are also improved by using the multivariate monitoring statistics of these local PLS/PCA models. These proposed methods are tested on two plasma etch data sets provided by Texas Instruments. In addition, a proof of concept using virtual metrology in a controller performance assessment application was also tested.Item Mechanistic study of plasma damage to porous low-k : process development and dielectric recovery(2010-05) Shi, Hualiang; Ho, Paul S.; Niu, Qian; Shi, Li; Swift, Jack B.; Yao, ZhenLow-k dielectrics with porosity are being introduced to reduce the RC delay of Cu/low-k interconnect. However, during the O2 plasma ashing process, the porous low-k dielectrics tend to degrade due to methyl depletion, moisture uptake, and densification, increasing the dielectric constant and leakage current. This dissertation presents a study of the mechanisms of plasma damage and dielectric recovery. The kinetics of plasma interaction with low-k dielectrics was investigated both experimentally and theoretically. By using a gap structure, the roles of ion, photon, and radical in producing damage on low-k dielectrics were differentiated. Oxidative plasma induced damage was proportional to the oxygen radical density, enhanced by VUV photon, and increased with substrate temperature. Ion bombardment induced surface densification, blocking radical diffusion. Two analytical models were derived to quantify the plasma damage. Based on the radical diffusion, reaction, and recombination inside porous low-k dielectrics, a plasma altered layer model was derived to interpret the chemical effect in the low ion energy region. It predicted that oxidative plasma induced damage can be reduced by decreasing pore radius, substrate temperature, and oxygen radical density and increasing carbon concentration and surface recombination rate inside low-k dielectrics. The model validity was verified by experiments and Monte-Carlo simulations. This model was also extended to the patterned low-k structure. Based on the ion collision cascade process, a sputtering yield model was introduced to interpret the physical effect in the high ion energy region. The model validity was verified by checking the ion angular and energy dependences of sputtering yield using O2/He/Ar plasma, low-k dielectrics with different k values, and a Faraday cage. Low-k dielectrics and plasma process were optimized to reduce plasma damage, including increasing carbon concentration in low-k dielectrics, switching plasma generator from ICP to RIE, increasing hard mask thickness, replacing O2 by CO2 plasma, increasing CO addition in CO/O2 plasma, and increasing N2 addition in CO2/N2 plasma. By combining analytical techniques with the Kramers-Kronig dispersion relation and quantum chemistry calculation, the origin of dielectric loss was ascribed to the physisorbed water molecules. Post-ash CH4 plasma treatment, vapor silylation process, and UV radiation were developed to repair plasma damage.