PATENT ABSTRACT
The invention provides a method of processing a wafer using multilayer processing sequences and Multi-Layer/Multi-Input/Multi-Output (MLMIMO) models and libraries that can include one or more measurement procedures, one or more Poly-Etch (P-E) sequences, and one or more metal-gate etch sequences. The MLMIMO process control uses dynamically interacting behavioral modeling between multiple layers and/or multiple process steps. The multiple layers and/or the multiple process steps can be associated with the creation of lines, trenches, vias, spacers, contacts, and gate structures that can be created using isotropic and/or anisotropic etch processes.

PATENT DESCRIPTION
BACKGROUND OF THE INVENTION 
       [0001]    1. Field of the Invention 
         [0002]    The present invention relates to wafer processing, and more particularly to apparatus and methods for creating metal-gate structures on a wafer in real-time using multi-layer-multi-step processing sequences and associated Multi-Layer/Multi-Input/Multi-Output (MLMIMO) models. 
         [0003]    2. Description of the Related Art 
         [0004]    Etch process behavior is inherently non-linear and interacting step-to-step (layers) or as process stacks are compiled (etch/cvd/implant). With the knowledge of the process interactions based on physical modeling of Tokyo Electron Limited (TEL) chambers and base processes and imperial data and measurements from process refinement and tuning the control of Critical Dimension (CD), Sidewall Angle (SWA), depths, film thicknesses, over etching, undercuts, surface cleaning and damage control can be recursively calculated and optimized using multi-Input multi-output non-linear models. Current low cost products use a bulk silicon technology. As the transistor continues to shrink, the impact of the channel depth is becoming critical (ultra-shallow source/drain extensions). As the SOI film shrinks, smaller variations in the gate and/or spacer thickness and thickness of the Silicon on Insulator (SOI) film can affect the transistor&#39;s performance. When etch procedures are not controlled, the removal of the material near the gate affects the electrical performance. 
         [0005]    Current high performance microprocessors use PD SOI (partially depleted Silicon-on-Insulator film—giving a threshold voltage 0.2 volts. PD SOI films are around 50 nm while the gate and/or spacer reduction amount can be a large percentage (10%) of the total gate and/or spacer thickness. Future generations of SOI films are called FD SOI (fully depleted giving a threshold voltage 0.08 volts and a thickness of ˜25 nm). Currently theses films are not in production due to limitations in thickness control uniformity and defects. Channel mobility degrades with decreasing SOI thickness. With thinner films, the control of the metal-gate structures becomes more critical. 
       SUMMARY OF THE INVENTION 
       [0006]    The invention can provide apparatus and methods of creating metal-gate structures on a wafer in real-time using multi-layer-multi-step processing sequences and associated Multi-Layer/Multi-Input/Multi-Output (MLMIMO) models. 
         [0007]    Other aspects of the invention will be made apparent from the description that follows and from the drawings appended hereto. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0008]    Embodiments of the invention will now be described, by way of example only, with reference to the accompanying schematic drawings in which corresponding reference symbols indicate corresponding parts, and in which: 
           [0009]      FIG. 1  shows an exemplary block diagram of a processing system in accordance with embodiments of the invention; 
           [0010]      FIGS. 2A-2G  shows exemplary block diagrams of etching subsystems in accordance with embodiments of the invention; 
           [0011]      FIGS. 3A-3G  shows exemplary block diagrams of additional etching subsystems in accordance with embodiments of the invention; 
           [0012]      FIG. 4  shows a simplified block diagram of an exemplary Multi-Layer/Multi-Input/Multi-Output (MLMIMO) model optimization and control methodology in accordance with embodiments of the invention; 
           [0013]      FIG. 5  illustrates an exemplary view of a multi-step processing sequence for a creating a metal gate structure in accordance with embodiments of the invention; 
           [0014]      FIG. 6  illustrates an exemplary view of a second multi-step modeling sequence for a creating a metal gate structure in accordance with embodiments of the invention; 
           [0015]      FIG. 7  illustrates an exemplary view of a third multi-step modeling sequence for a creating a metal gate structure in accordance with embodiments of the invention; 
           [0016]      FIG. 8  shows an exemplary schematic view of a Multi-Layer/Multi-Input/Multi-Output (MLMIMO) model in accordance with embodiments of the invention; 
           [0017]      FIG. 9  illustrates exemplary block diagram for a two-part Multi-Layer/Multi-Input/Multi-Output (MLMIMO) model in accordance with embodiments of the invention; 
           [0018]      FIG. 10  illustrates an exemplary flow diagram for a procedure for developing a Multi-Layer/Multi-Input/Multi-Output (MLMIMO) model in accordance with embodiments of the invention; 
           [0019]      FIG. 11  illustrates a simplified flow diagram of a procedure for using a Multi-Layer/Multi-Input/Multi-Output (MLMIMO) model in accordance with embodiments of the invention; and 
           [0020]      FIG. 12  illustrates a runtime flow diagram of a procedure for using a MLMIMO in accordance with embodiments of the invention. 
       
    
    
     DETAILED DESCRIPTION 
       [0021]    The Multi-Layer/Multi-Input/Multi-Output (MLMIMO) model can be subdivided into layers of a finite granularity based on the application need. Each layer can be a physical material, with layer separation denoted by material changes or dimensional layer boundaries. Layers can be combination of layers of layers, such as metal gate stack layers and subsequent spacer deposition and etching of the spacer layer covering the metal gate layers. Layers can be mapped to etch steps with time or EPD being used to separate the steps. Additionally a continuous real-time controller can run with real-time updates from a combination of metrology data, sensors, and etch models. 
         [0022]    DOEs can be run to model the process gain of each potential control knob and the interactions of the inputs and outputs associated with each layer, and the interactions and gains of process control loops layer to layer. A method of determining interaction between each control knob and output can be used to evaluate the and optimize the model stability such as Relative Gain Array. This information can also drive setup of individual feedback loops that are non-interacting. 
         [0023]    MLMIMO modeling is used to calculate the optimum inputs for a set of goals (or targeted outputs). Constraints can be ranges of process parameters such as time, gas flows, and temperature by layer. During MLMIMO model development, a set of weightings can be applied to guide the optimizer to prioritize the outputs with most value to the current process calculations at a given time. Target weightings can be used where an equation is applied to the weighting calculation given a target and gain constants that effectively penalize as the optimizer moves away from target in a linear or non-linear way. Targets can be a center target or and limit target (above a given value—for example with SWA). 
         [0024]    Feedback can take the form of multiple loops, one for each targeted output with a calculation of the feedback error based on the actual less predicted error. When using a MLMIMO model, each predicted output error can be calculated and matched with the feedback measurements to determine the real error. Feedback filtering methods such as EWMA or Kalman filters can be used to filter noise. Outputs from a controller associated with a multi-step sequence can include a goodness of fit value, and this GOF value can then be used as the input to a cascaded controller. 
         [0025]    MLMIMO controllers can contain updates a different times as the processing steps are performed allowing the controller to make new updates based on past calculations, errors of calculations, changes in tool state or material state then incorporated into the most recent update. 
         [0026]    In some multi-step sequences, when the resist parameters are measured, they can be used for feed forward, and can be weighted based on previous wafers feedback and chamber state information. At the beginning of a Lot, the MLMIMO model can be configured to use the best-known values for the patterned soft mask layer, and these can be weighted to the center of the previous lot&#39;s distribution. During the lot processing, the parameters for the Etch Control Layer (ECL) or the hard mask layers can be measured and filtered using a weighting method such as EWMA to smooth W2W variations and fed back to and translated to a resist SWA and used to update the current feed forward SWA value. The SWA pattern analysis function can group bimodal patterns so two threads can be managed to feedback and/or feed forward data. In one example, the SWA W2W variation is more commonly driven by scanner stage so two feed forward/feedback threads can be maintained to optimize performance. In a second example, the W2W CD variation from the lithography tool can be dominated by the hot plates, so a 2, 3, or 4 variation pattern can be observed. When IM measurements are made after the lithography processes, the pattern across the wafer can be established before wafer processing and the wafer CD and SWA patterns can be established before the wafers are sent to the etcher. When more than one processing threads are used, the thread number can be added as a context item for the wafer. In addition, when the scanner and/or track cell number, scanner module number, and hot plate number are available, they can also be used to group wafers and establish feed forward threads from the Lithography tool to the Etch Tool. Alternatively, other combinations of coater/developers may also be used. 
         [0027]    When the wafers are sorted based on context groups, then the wafers can be processed based on their group or sequence. When processing order in the etch tool is the same as the processing order in the lithography tool, the current FB controller can be programmed to adjust for W2W for incoming drift inside the lithography tool and for drift inside the etch tool 
         [0028]    The invention provides apparatus and methods for processing wafers having a large number of semiconductor devices thereon and an even larger number of transistor gate and/or spacer structures. In various embodiments, apparatus and methods are provided for creating and/or using an MLMIMO evaluation library, for performing MLMIMO processing sequences that can include one or more measurement procedures, one or more deposition procedures, one or more Partial-Etch (Partial etch) procedures, one or more Full-Etch (Poly Etch) procedures, and/or for verifying MLMIMO models and associated processing sequences. 
         [0029]    One or more periodic structures can be provided at various locations on a wafer and can be used to evaluate and/or verify MLMIMO models and associated processing sequences. Wafers can have wafer data associated with them, and the wafer data can include real-time and historical data. In addition, the wafer can have other data associated with them, and the other data can include gate structure data, the number of required sites, the number of visited sites, confidence data and/or risk data for one or more of the sites, site ranking data, transferring sequence data, or process-related data, or evaluation/verification-related data, or any combination thereof. The data associated with MLMIMO-related wafers can include transfer sequence data that can be used to establish when and where to transfer the wafers, and transfer sequences can be change using operational state data. 
         [0030]    The MLMIMO model can be subdivided into layers of a finite granularity based on the application need. Each layer can be a physical material, with layer separation denoted by material changes or dimensional layer boundaries. Layers can be combination of layers of layers, such as a metal gate stack of layers and a subsequent spacer deposition and etching of the layer covering the metal gate layers. 
         [0031]    Layers can be mapped to etch steps with time or End Point Data (EPD) being used to separate the steps. Additionally a continuous real-time controller can run with real-time updates from a combination of metrology data, sensors, and etch models. 
         [0032]    An analytical device used in process control multivariable applications, based on the comparison of single-loop control to multivariable control; expressed as an array (for all possible input-output pairs) of the ratios of a measure of the single-loop behavior between an input-output variable pair, to a related measure of the behavior of the same input-output pair under some idealization of multivariable control 
         [0033]    MLMIMO modeling is used to calculate the optimum inputs for a set of goals (or targeted outputs). Constraints can be ranges of process parameters such as time, gas flows, and temperature by layer. With MLMIMO, a set of weightings can be applied to guide the optimizer to prioritize the outputs with most value to the current process calculations at a given time. Target weightings can be used where an equation is applied to the weighting calculation given a target and gain constants that effectively penalize as the optimizer moves away from target in a linear or non-linear way. Targets&#39; can be a center target or and limit target (above a given value—for example with SWA). 
         [0034]    Feedback can take the form of multiple loops, one for each targeted output with a calculation of the feedback error based on the actual less predicted error. With MLMIMO, each prediction output error needs to be calculated and matched with the feedback measurements to determine the real error. Feedback filtering methods such as Exponentially Weighted Moving Averages (EWMA) or Kalman filters can be used to filter noise. Outputs of a layer controller can include a goodness of fit and this GOF value can then be used as the input of a cascading layer controller. 
         [0035]    The wafer can be partitioned into one or more upper edge regions, one or more center regions, and one or more lower edge regions. 
         [0036]    Layer controllers can contain updates at different times as the processing steps are performed allowing for the controller to make new updates based on past calculations, errors of calculations, changes in tool state or material state then incorporated into the most recent update. 
         [0037]    As feature sizes decrease below the 65 nm node, accurate processing and/or measurement data becomes more important and more difficult to obtain. MLMIMO models and associated processing sequences can be used to more accurately process and/or measure these ultra-small devices and features. The data from an MLMIMO procedure can be compared with the warning and/or control limits, when a run-rule is violated, an alarm can be generated indicating a processing problem, and correction procedures can be performed in real time. 
         [0038]      FIG. 1  shows an exemplary block diagram of a processing system in accordance with embodiments of the invention. In the illustrated embodiment, processing system  100  comprises a lithography subsystem  110 , a scanner subsystem  120 , an etch subsystem  130 , a deposition subsystem  140 , an inspection subsystem  150 , a metrology subsystem  160 , a transfer subsystem  170 , a manufacturing execution system (MES)  180 , a system controller  190 , and a memory/database  195 . Single subsystems ( 110 ,  120 ,  130 ,  140 ,  150 ,  160 , and  170 ) are shown in the illustrated embodiment, but this is not required for the invention. In some embodiments, multiple subsystems ( 110 ,  120 ,  130 ,  140 ,  150 ,  160 , and  170 ) can be used in a processing system  100 . In addition, one or more of the subsystems ( 110 ,  120 ,  130 ,  140 ,  150 ,  160 , and  170 ) can comprise one or more processing elements that can be used in MLMIMO models and associated processing sequences. 
         [0039]    The system controller  190  can be coupled to the lithography subsystem  110 , the scanner subsystem  120 , the etch subsystem  130 , the deposition subsystem  140 , the inspection subsystem  150 , the metrology subsystem  160 , and the transfer subsystem  170  using a data transfer subsystem  191 . The system controller  190  can be coupled to the MES  180  using the data transfer subsystem  181 . Alternatively, other configurations may be used. For example, the etch subsystem  130 , the deposition subsystem  140 , the metrology subsystem  160 , and a portion of the transfer subsystem  170  can be part of a Tactras™ System available from Tokyo Electron Limited. 
         [0040]    The lithography subsystem  110  can comprise one or more transfer/storage elements  112 , one or more processing elements  113 , one or more controllers  114 , and one or more evaluation elements  115 . One or more of the transfer/storage elements  112  can be coupled to one or more of the processing elements  113  and/or to one or more of the evaluation elements  115  and can be coupled  111  to the transfer subsystem  170 . The transfer subsystem  170  can be coupled  111  to the lithography subsystem  110 , and one or more wafers  105  can be transferred  111  between the transfer subsystem  170  and the lithography subsystem  110  in real time. For example, the transfer subsystem  170  can be coupled to one or more of the transfer/storage elements  112 , to one or more of the processing elements  113 , and/or to one or more of the evaluation elements  115 . One or more of the controllers  114  can be coupled to one or more of the transfer/storage elements  112 , to the one or more of the processing elements  113 , and/or to one or more of the evaluation elements  115 . 
         [0041]    In some embodiments, the lithography subsystem  110  can perform coating procedures, thermal procedures, measurement procedures, inspection procedures, alignment procedures, and/or storage procedures on one or more wafers using procedures and/or procedures. For example, one or more lithography-related processes can be used to deposit one or more masking layers that can include photoresist material, and/or anti-reflective coating (ARC) material, and can be used to thermally process (bake) one or more of the masking layers. In addition, lithography subsystem  110  can be used to develop, measure, and/or inspect one or more of the patterned masking layers on one or more of the wafers. 
         [0042]    The scanner subsystem  120  can comprise one or more transfer/storage elements  122 , one or more processing elements  123 , one or more controllers  124 , and one or more evaluation elements  125 . One or more of the transfer/storage elements  122  can be coupled to one or more of the processing elements  123  and/or to one or more of the evaluation elements  125  and can be coupled  121  to the transfer subsystem  170 . The transfer subsystem  170  can be coupled  121  to the scanner subsystem  120 , and one or more wafers  105  can be transferred  121  between the transfer subsystem  170  and the scanner subsystem  120  in real time. For example, the transfer subsystem  170  can be coupled to one or more of the transfer/storage elements  122 , to one or more of the processing elements  123 , and/or to one or more of the evaluation elements  125 . One or more of the controllers  124  can be coupled to one or more of the transfer/storage elements  122 , to the one or more of the processing elements  123 , and/or to one or more of the evaluation elements  125 . 
         [0043]    In some embodiments, the scanner subsystem  120  can be used to perform wet and/or dry exposure procedures, and in other cases, the scanner subsystem  120  can be used to perform extreme ultraviolet (EUV) exposure procedures. 
         [0044]    The etch subsystem  130  can comprise one or more transfer/storage elements  132 , one or more processing elements  133 , one or more controllers  134 , and one or more evaluation elements  135 . One or more of the transfer/storage elements  132  can be coupled to one or more of the processing elements  133  and/or to one or more of the evaluation elements  135  and can be coupled  131  to the transfer subsystem  170 . The transfer subsystem  170  can be coupled  131  to the etch subsystem  130 , and one or more wafers  105  can be transferred  131  between the transfer subsystem  170  and the etch subsystem  130  in real time. For example, the transfer subsystem  170  can be coupled to one or more of the transfer/storage elements  132 , to one or more of the processing elements  133 , and/or to one or more of the evaluation elements  135 . One or more of the controllers  134  can be coupled to one or more of the transfer/storage elements  132 , to the one or more of the processing elements  133 , and/or to one or more of the evaluation elements  135 . For example, one or more of the processing elements  133  can be used to perform plasma or non-plasma etching, ashing, trimming, and cleaning procedures. Evaluation procedures and/or inspection procedures can be used to measure and/or inspect one or more surfaces and/or layers of the wafers. The etch subsystem  130  can be configured as described herein in  FIGS. 2A-2G  and  FIGS. 3A-3G . 
         [0045]    The deposition subsystem  140  can comprise one or more transfer/storage elements  142 , one or more processing elements  143 , one or more controllers  144 , and one or more evaluation elements  145 . One or more of the transfer/storage elements  142  can be coupled to one or more of the processing elements  143  and/or to one or more of the evaluation elements  145  and can be coupled  141  to the transfer subsystem  170 . The transfer subsystem  170  can be coupled  141  to the deposition subsystem  140 , and one or more wafers  105  can be transferred  141  between the transfer subsystem  170  and the deposition subsystem  140  in real time. For example, the transfer subsystem  170  can be coupled to one or more of the transfer/storage elements  142 , to one or more of the processing elements  143 , and/or to one or more of the evaluation elements  145 . One or more of the controllers  144  can be coupled to one or more of the transfer/storage elements  142 , to the one or more of the processing elements  143 , and/or to one or more of the evaluation elements  145 . For example, one or more of the processing elements  143  can be used to perform physical vapor deposition (PVD) procedures, chemical vapor deposition (CVD) procedures, ionized physical vapor deposition (iPVD) procedures, atomic layer deposition (ALD) procedures, plasma enhanced atomic layer deposition (PEALD) procedures, and/or plasma enhanced chemical vapor deposition (PECVD) procedures. Evaluation procedures and/or inspection procedures can be used to measure and/or inspect one or more surfaces of the wafers. 
         [0046]    The inspection subsystem  150  can comprise one or more transfer/storage elements  152 , one or more processing elements  153 , one or more controllers  154 , and one or more evaluation elements  155 . One or more of the transfer/storage elements  152  can be coupled to one or more of the processing elements  153  and/or to one or more of the evaluation elements  155  and can be coupled  151  to the transfer subsystem  170 . The transfer subsystem  170  can be coupled  151  to the inspection subsystem  150 , and one or more wafers  105  can be transferred  151  between the transfer subsystem  170  and the inspection subsystem  150  in real time. For example, the transfer subsystem  170  can be coupled to one or more of the transfer/storage elements  152 , to one or more of the processing elements  153 , and/or to one or more of the evaluation elements  155 . One or more of the controllers  154  can be coupled to one or more of the transfer/storage elements  152 , to the one or more of the processing elements  153 , and/or to one or more of the evaluation elements  155 . 
         [0047]    The metrology subsystem  160  can comprise one or more transfer/storage elements  162 , one or more processing elements  163 , one or more controllers  164 , and one or more evaluation elements  165 . One or more of the transfer/storage elements  162  can be coupled to one or more of the processing elements  163  and/or to one or more of the evaluation elements  165  and can be coupled  161  to the transfer subsystem  170 . The transfer subsystem  170  can be coupled  161  to the metrology subsystem  160 , and one or more wafers  105  can be transferred  161  between the transfer subsystem  170  and the metrology subsystem  160  in real time. For example, the transfer subsystem  170  can be coupled to one or more of the transfer/storage elements  162 , to one or more of the processing elements  163 , and/or to one or more of the evaluation elements  165 . One or more of the controllers  164  can be coupled to one or more of the transfer/storage elements  162 , to the one or more of the processing elements  163 , and/or to one or more of the evaluation elements  165 . The metrology subsystem  160  can comprise one or more processing elements  163  that can be used to perform real-time optical metrology procedures that can be used to measure target structures at one or more sites on a wafer using library-based or regression-based techniques. For example, the sites on wafer can include MLMIMO sites, target sites, overlay sites, alignment sites, measurement sites, verification sites, inspection sites, or damage-assessment sites, or any combination thereof. For example, one or more “golden wafers” or reference chips can be stored and used periodically to verify the performance of one or more of the processing elements  163 , and/or one or more of the evaluation elements  165 . 
         [0048]    In some embodiments, the metrology subsystem  160  can include an integrated Optical Digital Profilometry (iODP) elements (not shown), and iODP elements/systems are available from Timbre Technologies Inc. (a TEL company). Alternatively, other metrology systems may be used. For example, iODP techniques can be used to obtain real-time data that can include critical dimension (CD) data, gate structure data, and thickness data, and the wavelength ranges for the iODP data can range from less than approximately 200 nm to greater than approximately 900 nm. Exemplary iODP elements can include ODP Profiler Library elements, Profiler Application Server (PAS) elements, and ODP Profiler Software elements. The ODP Profiler Library elements can comprise application specific database elements of optical spectra and its corresponding semiconductor profiles, CDs, and film thicknesses. The PAS elements can comprise at least one computer that connects with optical hardware and computer network. The PAS elements can be configured to provide the data communication, ODP library operation, measurement process, results generation, results analysis, and results output. The ODP Profiler Software elements can include the software installed on PAS elements to manage measurement recipe, ODP Profiler library elements, ODP Profiler data, ODP Profiler search/match results, ODP Profiler calculation/analysis results, data communication, and PAS interface to various metrology elements and computer network. 
         [0049]    The metrology subsystem  160  can use polarizing reflectometry, spectroscopic ellipsometry, reflectometry, or other optical measurement techniques to measure accurate device profiles, accurate CDs, and multiple layer film thickness of a wafer. The integrated metrology process (iODP) can be executed as an integrated process in an integrated group of subsystems. In addition, the integrated process eliminates the need to break the wafer for performing the analyses or waiting for long periods for data from external systems. iODP techniques can be used with the existing thin film metrology systems for inline profile and CD measurement, and can be integrated with TEL processing systems and/or lithography systems to provide real-time process monitoring and control. Simulated metrology data can be generated by applying Maxwell&#39;s equations and using a numerical analysis technique to solve Maxwell&#39;s equations. 
         [0050]    The transfer subsystem  170  can comprise transfer elements  174  coupled to transfer tracks ( 175 ,  176 , and  177 ) that can be used to receive wafers, transfer wafers, align wafers, store wafers, and/or delay wafers. For example, the transfer elements  174  can support two or more wafers. Alternatively, other transferring means may be used. The transfer subsystem  170  can load, transfer, store, and/or unload wafers based on a MLMIMO model, a MLMIMO-related processing sequence, a transfer sequence, operational states, the wafer and/or processing states, the processing time, the current time, the wafer data, the number of sites on the wafer, the type of sites on the wafers, the number of required sites, the number of completed sites, the number of remaining sites, or confidence data, or any combination thereof. 
         [0051]    In some examples, transfer subsystem  170  can use loading data to determine where and when to transfer a wafer. In other examples, a transfer system can use MLMIMO modeling data to determine where and when to transfer a wafer. Alternatively, other procedures may be used. For example, when the first number of wafers is less than or equal to the first number of available processing elements, the first number of wafers can be transferred to the first number of available processing elements in the one or more of the subsystems using the transfer subsystem  170 . When the first number of wafers is greater than the first number of available processing elements, some of the wafers can be stored and/or delayed using one or more of the transfer/storage elements ( 112 ,  122 ,  132 ,  142 ,  152 , and  162 ) and/or the transfer subsystem  170 . 
         [0052]    In addition, the one or more subsystems ( 110 ,  120 ,  130 ,  140 ,  150 ,  160 , and  170 ) can be used when performing lithography-related procedures, scanner-related procedures, inspection-related procedures, measurement-related procedures, evaluation-related procedures, etch-related procedures, deposition-related procedures, thermal processing procedures, coating-related procedures, alignment-related procedures, polishing-related procedures, storage-related procedures, transfer procedures, cleaning-related procedures, rework-related procedures, oxidation-related procedures, nitridation-related procedures, or external processing elements, or any combination thereof. 
         [0053]    Operational state data can be established for the subsystems ( 110 ,  120 ,  130 ,  140 ,  150 ,  160 , and  170 ) and can be used and/or updated by MLMIMO-related processing sequences. In addition, operational state data can be established for the transfer/storage elements ( 112 ,  122 ,  132 ,  142 ,  152 , and  162 ), processing elements ( 113 ,  123 ,  133 ,  143 ,  153 , and  163 ), and evaluation elements ( 115 ,  125 ,  135 ,  145 ,  155 , and  165 ), and can be updated by MLMIMO-related procedures. For example, the operational state data for the processing elements can include availability data, matching data for the processing elements, expected processing times for some process steps and/or sites, yield data, confidence data and/or risk data for the processing elements, or confidence data and/or risk data for one or more MLMIMO-related procedures. Updated operational states can be obtained by querying in real-time one or more processing elements, and/or one or more subsystems. Updated loading data can be obtained by querying in real-time one or more transfer elements, and/or one or more transfer subsystems. 
         [0054]    One or more of the controllers ( 114 ,  124 ,  134 ,  144 ,  154 , and  164 ) can be coupled to the system controller  190  and/or to each other using a data transfer subsystem  191 . Alternatively, other coupling configurations may be used. The controllers can be coupled in series and/or in parallel and can have one or more input ports and/or one or more output ports. For example, the controllers may include microprocessors having one or more core processing elements. 
         [0055]    In addition, subsystems ( 110 ,  120 ,  130 ,  140 ,  150 ,  160 , and  170 ) can be coupled to each other and to other devices using intranet, internet, wired, and/or wireless connections. The controllers ( 114 ,  124 ,  134 ,  144 , and  190 ) can be coupled to external devices as required. 
         [0056]    One or more of the controllers ( 114 ,  124 ,  134 ,  144 ,  154 ,  164 , and  190 ) can be used when performing real-time MLMIMO-related procedures. A controller can receive real-time data from a MLMIMO model to update subsystem, processing element, process, recipe, profile, image, pattern, simulation, sequence data, and/or model data. One or more of the controllers ( 114 ,  124 ,  134 ,  144 ,  154 ,  164 , and  190 ) can be used to exchange one or more Semiconductor Equipment Communications Standard (SECS) messages with the Manufacturing Execution Systems (MES)  180  or other systems (not shown), read and/or remove information, feed forward, and/or feedback the information, and/or send information as a SECS message. One or more of the formatted messages can be exchanged between controllers, and the controllers can process messages and extract new data in real-time. When new data is available, the new data can be used in real-time to update a model and/or procedure currently being used for the wafer and/or lot. For example, the current layout can be examined using the updated model and/or procedure when the model and/or procedure can be updated before the current layout is examined. The current layout can be examined using a non-updated model and/or procedure when an update cannot be performed before the current layout is processed. In addition, formatted messages can be used when resists are changed, when resist models are changed, when processing sequences are changed, when design rules are changed, or when layouts are changed, 
         [0057]    In some examples, the MES  180  may be configured to monitor some subsystem and/or system processes in real-time, and factory level intervention and/or judgment rules can be used to determine which processes are monitored and which data can be used. For example, factory level intervention and/or judgment rules can be used to determine how to manage the data when a MLMIMO-related error condition occurs. The MES  180  can also provide modeling data, processing sequence data, and/or wafer data. 
         [0058]    In addition, controllers ( 114 ,  124 ,  134 ,  144 ,  154 ,  164 , and  190 ) can include memory (not shown) as required. For example, the memory (not shown) can be used for storing information and instructions to be executed by the controllers, and may be used for storing temporary variables or other intermediate information during the execution of instructions by the various computers/processors in the processing system  100 . One or more of the controllers ( 114 ,  124 ,  134 ,  144 ,  154 ,  164 , and  190 ), or other system components can comprise the means for reading data and/or instructions from a computer readable medium and can comprise the means for writing data and/or instructions to a computer readable medium. 
         [0059]    The processing system  100  can perform a portion of or all of the processing steps of the invention in response to the computers/processors in the processing system executing one or more sequences of one or more instructions contained in a memory and/or received in a message. Such instructions may be received from another computer, a computer readable medium, or a network connection. 
         [0060]    In some embodiments, an integrated system can be configured using system components from Tokyo Electron Limited (TEL), and external subsystems and/or tools may be included. For example, measurement elements can be provided that can include a CD-Scanning Electron Microscopy (CDSEM) system, a Transmission Electron Microscopy (TEM) system, a focused ion beam (FIB) system, an Optical Digital Profilometry (ODP) system, an Atomic Force Microscope (AFM) system, or another optical metrology system. The subsystems and/or processing elements can have different interface requirements, and the controllers can be configured to satisfy these different interface requirements. 
         [0061]    One or more of the subsystems ( 110 ,  120 ,  130 ,  140 ,  150 ,  160 , and  170 ) can perform control applications, Graphical User Interface (GUI) applications, and/or database applications. In addition, one or more of the subsystems ( 110 ,  120 ,  130 ,  140 ,  150 ,  160 , and  170 ) and/or controllers ( 114 ,  124 ,  134 ,  144 ,  154 ,  164 , and  190 ) can include Design of Experiment (DOE) applications, Advanced Process Control (APC) applications, Fault Detection and Classification (FDC) applications, and/or Run-to-Run (R2R) applications. 
         [0062]    Output data and/or messages from MLMIMO modeling procedures can be used in subsequent procedures to optimize the process accuracy and precision. Data can be passed to MLMIMO-related procedures in real-time as real-time variable parameters, overriding current model values, and reducing DOE tables. Real-time data can be used with a library-based system, or regression-based system, or any combination thereof to optimize a MLMIMO-related procedure. 
         [0063]    When a regression-based library creation procedure is used, measured MLMIMO model-related data can be compared to simulated MLMIMO model-related data. The simulated MLMIMO data can be iteratively generated, based on sets of process-related parameters, to obtain a convergence value for the set of process-related parameters that generates the closest match simulated MLMIMO model-related data compared to the measured MLMIMO model-related data. When a library-based process is used, a MLMIMO model-related library can be generated and/or enhanced using MLMIMO model-related procedures, recipes, profiles, and/or models. For example, a MLMIMO model-related library can comprise simulated and/or measured MLMIMO-related data and corresponding sets of processing sequence data. The regression-based and/or the library-based processes can be performed in real-time. An alternative procedure for generating data for a MLMIMO-related library can include using a machine learning system (MLS). For example, prior to generating the MLMIMO-related library data, the MLS can be trained using known input and output data, and the MLS may be trained with a subset of the MLMIMO-related library data. 
         [0064]    MLMIMO models can include intervention and/or judgment rules that can be executed whenever a matching context is encountered. Intervention and/or judgment rules and/or limits can be established based on historical procedures, on the customer&#39;s experience, or process knowledge, or obtained from a host computer. Rules can be used in Fault Detection and Classification (FDC) procedures to determine how to respond to alarm conditions, error conditions, fault conditions, and/or warning conditions. The rule-based FDC procedures can prioritize and/or classify faults, predict system performance, predict preventative maintenance schedules, decrease maintenance downtime, and extend the service life of consumable parts in the system. Various actions can take place in response to an alarm/fault, and the actions taken on the alarm/fault can be context-based, and the context data can be specified by a rule, a system/process recipe, a chamber type, identification number, load port number, cassette number, lot number, control job ID, process job ID, slot number and/or the type of data. 
         [0065]    Unsuccessful procedures or processing sequences can report a failure when a limit is exceeded, and successful procedures can create warning messages when limits are being approached. Pre-specified failure actions for procedures errors can be stored in a database, and can be retrieved from the database when an error occurs. For example, MLMIMO-related procedures can reject the data at one or more of the sites for a wafer when a measurement procedure fails. 
         [0066]    MLMIMO models can be used to create, modify, and/or evaluate isolated and/or nested structures at different times and/or sites. For example, gate stack dimensions and wafer thickness data can be different near isolated and/or nested structures, and gate stack dimensions and wafer thickness data can be different near open areas and/or trench array areas. A MLMIMO model can create optimized data for isolated and/or nested structures to update and/or optimize a process recipe and/or process time. 
         [0067]    MLMIMO models can use end-point detection (EPD) data and process time data to improve the accuracy. When EPD data is used to stop an etching procedure, the EPD time data and the process rate data can be used to estimate the amount of etch and/or to estimate a thickness. 
         [0068]    In various examples, MLMIMO model-related limits can be obtained by performing the MLMIMO model-related procedure in a “golden” processing chamber, can be historical data that is stored in a library, can be obtained by performing a verified deposition procedure, can be obtained from the MES  180 , can be simulation data, and can be predicted data. Partial-Etch procedure limits can be obtained by performing the partial-etch procedure in a “golden” processing chamber, can be historical data that is stored in a library, can be obtained by performing a verified partial-etch procedure, can be obtained from the MES  180 , can be simulation data, and can be predicted data. partial-etch procedure limits can be obtained by performing the COR-etch procedure in “golden” processing chambers, can be historical data that is stored in a library, can be obtained by performing a verified partial-etch procedure, can be obtained from the MES  180 , can be simulation data, and can be predicted data. 
         [0069]      FIGS. 2A-2G  show exemplary block diagrams of etching subsystems in accordance with embodiments of the invention. 
         [0070]    A first exemplary etching subsystem  200 A is shown in  FIG. 2A , and the illustrated etching subsystem  200 A includes plasma processing chamber  210 , wafer holder  220 , upon which a wafer  225  to be processed is affixed, gas injection system  240 , and pressure control system  257 . For example, wafer holder  220  can be coupled to and insulated from plasma processing chamber  210  using base  229 . Wafer  225  can be, for example, a semiconductor wafer, a work piece, or a liquid crystal display (LCD). For example, plasma-processing chamber  210  can be configured to facilitate the generation of plasma in processing region  245  adjacent a surface of wafer  225 , where plasma is formed via collisions between heated electrons and an ionizable gas. An ionizable gas or mixture of gases is introduced via gas injection system  240 , and process pressure is adjusted. Desirably, plasma is utilized to create materials specific to a predetermined material process, and to aid either the deposition of material to wafer  225  or the removal of material from the exposed surfaces of wafer  225 . For example, controller  255  can be used to the control pressure control system  257  and the gas injection system  240 . 
         [0071]    Wafer  225  can be, for example, transferred into and out of plasma processing chamber  210  through a slot valve (not shown) and chamber feed-through (not shown) via robotic transfer system where it is received by wafer lift pins (not shown) housed within wafer holder  220  and mechanically translated by devices housed therein. After the wafer  225  is received from transfer system, it is lowered to an upper surface of wafer holder  220 . 
         [0072]    For example, wafer  225  can be affixed to the wafer holder  220  via an electrostatic clamping system (not shown). Furthermore, wafer holder  220  can further include temperature control elements  227  and temperature control system  228 . Moreover, gas can be delivered to the backside of the wafer via a dual (center/edge) backside gas system  226  to improve the gas-gap thermal conductance between wafer  225  and wafer holder  220 . A dual (center/edge) backside gas system can be utilized when additional temperature control of the wafer is required at elevated or reduced temperatures. For example, temperature control elements  227  can include cooling elements, resistive heating elements, or thermoelectric heaters/coolers. 
         [0073]    As shown in  FIG. 2A , wafer holder  220  includes a lower electrode  221  through which Radio Frequency (RF) power can be coupled to plasma in processing region  245 . For example, lower electrode  221  can be electrically biased at an RF voltage via the transmission of RF power from RF generator  230  through impedance match network  232  to lower electrode  221 . The RF bias can serve to heat electrons to form and maintain plasma. A typical frequency for the RF bias can range from 1 MHz to 100 MHz and is preferably 13.56 MHz. 
         [0074]    Alternatively, RF power may be applied to the lower electrode  221  at multiple frequencies. Furthermore, impedance match network  232  serves to maximize the transfer of RF power to plasma in processing chamber  210  by minimizing the reflected power. Various match network topologies and automatic control methods can be utilized. 
         [0075]    With continuing reference to  FIG. 2A , process gas can be introduced to one or more areas of the processing region  245  through gas injection system  240 . Process gas can, for example, include a mixture of gases such as argon, Tetrafluoromethane (CF 4 ) and Oxygen (O 2 ), or argon (Ar), C 4 F 8  and O 2  for oxide etch applications, or other chemistries such as, for example, O 2 /CO/Ar/C 4 F 8 , O 2 /CO/Ar/C 5 F 8 , O 2 /CO/Ar/C 4 F 6 , O 2 /Ar/C 4 F 6 , N 2 /H 2 , hydrogen bromide (HBr). Gas injection system  240  can be configured to reduce or minimize the introduction of contaminants to wafer  225  and can include a gas injection plenum  241 , and a multi-orifice showerhead gas injection plate  242 . For example, process gas can be supplied from a gas delivery system (not shown). Gas injection system  240  can provide different flow rates to different regions of the processing region  245 . Alternatively, gas injection system  240  may provide different process gasses to different regions of the processing region  245 . 
         [0076]    For example, pressure control system  257  can include a turbo-molecular vacuum pump (TMP)  258  capable of a pumping speed up to  5000  liters per second (and greater) and a gate valve  259  for controlling the chamber pressure. In conventional plasma processing devices utilized for dry plasma etch processes, a 1000 to 3000 liter per second TMP is generally employed. TMPs are useful for low pressure processing, typically less than 50 mTorr. At higher pressures, the TMP pumping speed falls off dramatically. For high pressure processing (i.e., greater than 100 mTorr), a mechanical booster pump and dry roughing pump can be used. Furthermore, a device for monitoring chamber pressure (not shown) may be coupled to the process chamber  210 . The pressure-measuring device can be, for example, a Type 628B Baratron absolute capacitance manometer commercially available from MKS Instruments, Inc. (Andover, Mass.). 
         [0077]    As depicted in  FIG. 2A , etching subsystem  200 A can include one or more sensors  250  coupled to plasma processing chamber  210  to obtain performance data, and controller  255  coupled to the sensors  250  to receive performance data. The sensors  250  can include both sensors that are intrinsic to the plasma processing chamber  210  and sensors extrinsic to the plasma-processing chamber  210 . Intrinsic sensors can include those sensors pertaining to the functionality of plasma processing chamber  210  such as the measurement of the Helium backside gas pressure, Helium backside flow, electrostatic clamping (ESC) voltage, ESC current, wafer holder  220  temperature (or lower electrode (LEL) temperature), coolant temperature, upper electrode (UEL) temperature, forward RF power, reflected RF power, RF self-induced DC bias, RF peak-to-peak voltage, chamber wall temperature, process gas flow rates, process gas partial pressures, chamber pressure, capacitor settings (i.e., C 1  and C 2  positions), a focus ring thickness, RF hours, focus ring RF hours, and any statistic thereof. Alternatively, extrinsic sensors can include one or more optical devices  234  for monitoring the light emitted from the plasma in processing region  245  as shown in  FIG. 2A , and/or one or more electrical measurement devices  236  for monitoring the electrical system of plasma processing chamber  210  as shown in  FIG. 2A . The optical devices  234  can include an optical sensor that can be used as an End Point Detector (EPD) and can provide EPD data. For example, an Optical Emissions Spectroscopy (OES) sensor may be used. 
         [0078]    The electrical measurement device  236  can include a current and/or voltage probe, a power meter, or spectrum analyzer. For example, electrical measurement devices  236  can include a RF Impedance analyzer. Furthermore, the measurement of an electrical signal, such as a time trace of voltage or current, permits the transformation of the signal into frequency domain using discrete Fourier series representation (assuming a periodic signal). Thereafter, the Fourier spectrum (or for a time varying signal, the frequency spectrum) can be monitored and analyzed to characterize the state of a plasma. In alternate embodiments, electrical measurement device  236  can include a broadband RF antenna useful for measuring a radiated RF field external to plasma processing chamber  210 . 
         [0079]    Controller  255  includes a microprocessor, memory, and a digital I/O port (potentially including D/A and/or A/D converters) capable of generating control voltages sufficient to communicate and activate inputs to etching subsystem as well as monitor outputs from etching subsystem. As shown in  FIG. 2A , controller  255  can be coupled to and exchange information with first RF generator  230 , impedance match network  232 , gas injection system  240 , pressure control system  257 , backside gas delivery system  226 , temperature control system  228 , optical device  234 , electrical measurement device  236 , and sensors  250 . A program stored in the memory is utilized to interact with the aforementioned components of an etching subsystem  200  according to a stored process recipe. 
         [0080]    In the exemplary embodiment shown in  FIG. 2B , the etching subsystem  200 B can be similar to the embodiment of  FIG. 2A  and further comprise either a stationary, or mechanically or electrically rotating magnetic field system  260 , in order to potentially increase plasma density and/or improve plasma processing uniformity, in addition to those components described with reference to  FIG. 2A . Moreover, controller  255  can be coupled to magnetic field system  260  in order to regulate the speed of rotation and field strength. The design and implementation of a rotating magnetic field is well known to those skilled in the art. 
         [0081]    In the embodiment shown in  FIG. 2C , the etching subsystem  200  C can be similar to the embodiment of  FIG. 2A  or  FIG. 2B , and can further comprise an upper electrode  270  to which RF power can be coupled from RF generator  272  through optional impedance match network  274 . A frequency for the application of RF power to the upper electrode can range from about 0.1 MHz to about 200 MHz. Additionally, a frequency for the application of power to the lower electrode  221  can range from about 0.1 MHz to about 100 MHz. Moreover, controller  255  can be coupled to RF generator  272  and impedance match network  274  in order to control the application of RF power to upper electrode  270 . The design and implementation of an upper electrode is well known to those skilled in the art. The upper electrode  270  and the gas injection system  240  can be coupled to each other as shown. 
         [0082]    In the embodiment shown in  FIG. 2D , the etching subsystem  200  D can be similar to the embodiments of  FIGS. 2A and 2B , and can further comprise an inductive coil  280  to which RF power can be coupled via RF generator  282  through optional impedance match network  284 . RF power is inductively coupled from inductive coil  280  through a dielectric window (not shown) to plasma processing region  245 . A frequency for the application of RF power to the inductive coil  280  can range from about 10 MHz to about 100 MHz. Similarly, a frequency for the application of power to the lower electrode  221  can range from about 0.1 MHz to about 100 MHz. In addition, a slotted Faraday shield (not shown) can be employed to reduce capacitive coupling between the inductive coil  280  and plasma. Moreover, controller  255  can be coupled to RF generator  282  and impedance match network  284  in order to control the application of power to inductive coil  280 . 
         [0083]    In an alternate embodiment (not shown), is a “spiral” coil or “pancake” coil configuration may be used for the inductive coil. The design and implementation of an inductively coupled plasma (ICP) source, or transformer coupled plasma (TCP) source, is well known to those skilled in the art. 
         [0084]    In the embodiment shown in  FIG. 2E , the etching subsystem  200  E can, for example, be similar to the embodiments of  FIGS. 2A ,  2 B,  2 C, and  2 D, and can further comprise a second RF generator  235  configured to couple RF power to wafer holder  220  through another optional impedance match network  237 . A typical frequency for the application of RF power to wafer holder  220  can range from about 0.1 MHz to about 200 MHz for either the first RF generator  230  or the second RF generator  235  or both. The RF frequency for the second RF generator  235  can be relatively greater than the RF frequency for the first RF generator  230 . Furthermore, the RF power to the wafer holder  220  from the first RF generator  230  can be amplitude modulated, the RF power to the wafer holder  220  from the second RF generator  235  can be amplitude modulated, or both RF powers can be amplitude modulated. Desirably, the RF power at the higher RF frequency is amplitude modulated. Moreover, controller  255  can be coupled to the second RF generator  235  and impedance match network  237  in order to control the application of RF power to wafer holder  220 . The design and implementation of an RF system for a wafer holder is well known to those skilled in the art. 
         [0085]    In the embodiment shown in  FIG. 2F , the etching subsystem  200 F can be similar to the embodiments of  FIGS. 2A and 2E , and can further comprise a surface wave plasma (SWP) source  285 . The SWP source  285  can comprise a slot antenna, such as a radial line slot antenna (RLSA), to which microwave power is coupled via microwave generator  286  through optional impedance match network  287 . 
         [0086]    In the embodiment shown in  FIG. 2G , the etching subsystem  200 G can be similar to the embodiment of  FIG. 2C , and can further comprise a split upper electrode ( 270   a ,  270   b ) to which RF power can be coupled from RF generator  272  through an impedance match network  274  and a power splitter  290 . A frequency for the application of RF power to the split upper electrode ( 270   a ,  270   b ) can range from about 0.1 MHz to about 200 MHz. Additionally, a frequency for the application of power to the lower electrode  221  can range from about 0.1 MHz to about 100 MHz. Moreover, controller  255  can be coupled to RF generator  272  and impedance match network  274  in order to control the application of RF power to upper electrode  270 . The power splitter and the split upper electrode can be designed and configured to provide different RF power levels to the center and the edge of the processing region  245  to facilitate the generation and control of a plasma in processing region  245  adjacent a surface of wafer  225 . The split upper electrode ( 270   a ,  270   b ) and the gas injection system  240  can be coupled to each other as shown, or other configurations may be used. 
         [0087]      FIGS. 3A-3G  show additional embodiments for etching subsystems in accordance with embodiments of the invention.  FIGS. 3A-3G  illustrate exemplary etching subsystems  300 A- 300 G that are similar to the exemplary etching subsystems  200 A- 200 G shown in  FIGS. 2A-2G , but etching subsystems  300 A- 300 G include at least one DC electrode  305  and at least one DC source  306 . 
         [0088]    During patterned etching, a dry plasma etching process is often utilized, and the plasma is formed from a process gas by coupling electromagnetic (EM) energy, such as radio frequency (RF) power, to the process gas in order to heat electrons and cause subsequent ionization and dissociation of the atomic and/or molecular composition of the process gas. In addition, negative, high voltage direct current (DC) electrical power can be coupled to the plasma processing system in order to create an energetic (ballistic) electron beam that strikes the wafer surface during a fraction of the RF cycle, i.e., the positive half-cycle of the coupled RF power. It has been observed that the ballistic electron beam can enhance the properties of the dry plasma etching process by, for example, improving the etch selectivity between the underlying thin film (to be etched) and the mask layer, reducing charging damage such as electron shading damage, etc. Additional details regarding the generation of a ballistic electron beam are disclosed in pending U.S. patent application Ser. No. 11/156,559, entitled “Plasma processing apparatus and method” and published as US patent application no. 2006/0037701A1; the entire contents of which are herein incorporated by reference in their entirety. In general, the ballistic electron beam can be implemented within various types of plasma processing system, as shown in  FIGS. 3A-3G . 
         [0089]    The DC electrode  305  may comprise a silicon-containing material and/or a doped silicon-containing material. The DC source  306  can include a variable DC power supply. Additionally, the DC source  306  can include a bipolar DC power supply. The DC source  306  can further include a system configured to perform at least one of monitoring, adjusting, or controlling the polarity, current, voltage, and/or on/off state of the DC source  306 . Once plasma is formed, the DC source  306  facilitates the formation of a ballistic electron beam. An electrical filter may be utilized to de-couple RF power from the DC source  306 . 
         [0090]    For example, the DC voltage applied to DC electrode  305  by DC source  306  may range from approximately −2000 volts (V) to approximately 1000 V. Desirably, the absolute value of the DC voltage has a value equal to or greater than approximately 100 V, and more desirably, the absolute value of the DC voltage has a value equal to or greater than approximately 500 V. Additionally, it is desirable that the DC voltage has a negative polarity. Furthermore, it is desirable that the DC voltage is a negative voltage having an absolute value greater than the self-bias voltage. 
         [0091]    In alternate embodiments, a Chemical Oxide Removal (COR) subsystem (not shown) can be used to remove or trim oxidized poly-Si material. In addition, the COR subsystem may be used to remove or trim an oxide masking layer. For example, a COR subsystem can comprise a chemical treatment module (not shown) for chemically treating exposed surface layers, such as oxide surface layers, on a wafer, whereby adsorption of the process chemistry on the exposed surfaces affects chemical alteration of the surface layers. Additionally, the COR subsystem can comprise thermal treatment module (not shown) for thermally treating the wafer, whereby the wafer temperature is elevated in order to desorb (or evaporate) the chemically altered exposed surface layers on the wafer. 
         [0092]      FIG. 4  shows a simplified block diagram of an exemplary Multi-Layer/Multi-Input/Multi-Output (MLMIMO) model optimization and control methodology in accordance with embodiments of the invention. In the illustrated MLMMIMO model methodology, exemplary images of a portion of a first patterned gate stack  401  and a post-processed gate stack  405  is shown. The soft-mask layer of the first patterned gate stack  401  can include one or more soft-mask feature CDs  402  and one or more soft-mask feature sidewall angles (SWAs)  403 . The first patterned gate stack  401  can be characterized using a first set of parameters  404  that can include center and edge profile data items, center and edge thickness (Thick C/E) data items, CD center data items, CD edge data items, SWA center data items, and SWA edge data items. Alternatively, a different set of parameters may be used. The post-processed gate stack  405  can include one or more CDs  406  and one or more SWAs  407 . The post-processed gate stack  405  can be characterized using a second set of parameters  408  that can include center and edge metal gate data items, center and edge hard-mask data items, center and edge data items for one or more silicon-containing layers, SWA center data items, and SWA edge data items. Alternatively, a different set of parameters may be used. 
         [0093]    In the illustrated methodology, a first integrated metrology (IM) tool (First ODP-IM) controller/model  410  can be coupled to one or more poly-etch (P-E) tool controllers/models  420 . One or more of the P-E controller/models  420  can be coupled to one or more cleaning/ashing tool controllers/models  421 . One or more of the cleaning/ashing tool controllers/models  421  can be coupled to one or more metal-gate etch (MGE) tool controllers/models  422 . One or more of the metal-gate etch (MGE) tool controllers/models  422  can be coupled to one or more output metrology tool (Second ODP-IM) controllers/models  430 . 
         [0094]    The first metrology tool (First ODP-IM) controller/model  410  can receive data  412  and can provide feed forward data ( 411 ,  415 ). The second metrology tool (First ODP-IM) controller/model  430  can send data  431  and can provide feed back data  435 . In some examples, wafer-to-wafer feed-forward data (W2W FF)  415  can be associated with the First ODP-IM controller/model  410 , and wafer-to-wafer feed-back data (W2W FB)  435  can be associated with the Second ODP-IM controller/models  430 . In addition, one or more of the controller/models ( 420 ,  421 , and  422 ) can be used  425  to control gate stack profiles on a wafer-to-wafer (W2W) basis and to control gate stack profiles on a Within-Wafer (WiW) basis. 
         [0095]    Data items  416  can be sent to a first calculation element  440  that can be used to calculate the gate stack bias at the center of the wafer and at the edge of the wafer. The first calculation element  440  can be used to calculate the bias at the center of the wafer and at the edge of the wafer. A first set of target parameters  441  can be provided to the first calculation element  440 , and a first set of filter outputs  471  can be provided to the first calculation element  440 . Output data items  442  from the first calculation element  440  can be provided to one or more MLMIMO model Optimizers  450 . 
         [0096]    One or more of the MLMIMO model Optimizers  450  can be provided with one or more constraint parameters  451  that can include tool limits, recipe limits, and/or time limits. In the example shown, the constraint parameters  451  can include step-based wafer temperature limits or process gas limits. One or more of the MLMIMO model Optimizers  450  can determine one or more sets of recipe/chamber parameters  456  that can be sent to one or more of the tool controller/models ( 420 ,  421 , and  422 ). 
         [0097]    One or more of the tool controller/models ( 420 ,  421 , and  422 ) can be used to calculate predicted data items  427  that can include one or more predicted etch biases, one or more predicted SWA biases, one or more predicted step times for one or more etch recipes, and one or more predicted process gas flows for one or more etch recipes. 
         [0098]    One or more of the Second ODP-IM controller/models  430  can provide one or more actual outputs  433  to one or more comparison elements  460 , and one or more of the actual outputs  433  can be compared to one of more of the predicted data items  427 . One or more of the error values  465  from one or more of the comparison elements  460  can be provided to one or more of the EWMA filters  470   
         [0099]    One or more of the EWMA filters  470  can provide one or more first filtered outputs  471  to the first calculation element  440 , and one or more of the EWMA filters  470  can provide one or more second filtered outputs  472  to one or more of the weighting controller/models  480 . Each of the EWMA filters  470  can filter and provide feedback data for a single parameter or error value. Alternatively, each of the EWMA filters  470  can filter and provide feedback data for a multiple parameters or error values. One or more of the weighting controller/models  480  can receive one or more target data items  445  and one or more feedback data items  455  from one or more of the MLMIMO model Optimizers  450 . In addition, one or more of the weighting controller/models  480  can provide one or more dynamically varying weighting inputs  481  to one or more of the MLMIMO model Optimizers  450 . The concept of using dynamic weightings based on the feedback error is to force the optimizer to prioritize the weightings (rebalance) with a goal of better control of the most important CVs—automation of a manual tuning of a control system in runtime. 
         [0100]    In some embodiments, the manipulated variables and/or the disturbance variables used for control can include a calculated value that can be dynamically modeled and updated during the runtime processing by the following method: 1) The modeling procedure can start with a basic model relationship that “pairs” OES sensor data to a controlled variable (CV). For example, the amount of Atomic O or F can be calculated by using trace gas data from the OES, and the amount of Atomic O or F that is consumed can be used to predict a CD or a SWA. This could be a feedback update loop, or a real-time adjustment during an etch step. 2) After a wet clean is performed, the first patterned gate stacks processed during conditioning or production would be used to calculate and update this trace gas model. 3) The RGA method can be used at run-time with production patterned wafers to evaluate when to use the sensor data vs. CV feedback in place of just calculating a value, The RGA matrix for the given CV value would be re-evaluated to determine if the value of the sensor based MV is stronger than the litho incoming CV for use as a real-time CV value. 4) In addition, center to edge sensor detection using OES signal—The rate of change can also be used as an example commonly understood to adjust the over etch recipe settings to improve the uniformity (correct for the non-uniformity of the previous steps etch, by adjusting the over-etch steps center to edge knobs, such as O2 flow, temp, top power, pressure. IM CV would be the film thickness of incoming wafers to separate incoming—say BARC thickness from etch rate of the current chamber center to edge. 
         [0101]    In some embodiments, the control variables associated with various features created by the poly-etch (P-E) sequence or the metal-gate-etch (MGE) sequence can center CD and SWA values, middle CD and SWA values, edge CD and SWA values, and extreme edge CD and SWA values, and this can require a total of eight IM measurements at four or more sites on the wafer. The pre- and post-IM measurements can be performed using dynamic sampling. 
         [0102]    In other embodiments, the manipulated variables can include back-side gas flows to one or more zones in the wafer holder, and the back-side gas flows can be dynamically controlled during processing to provide dynamic backside gas temperature control for improved within-wafer process uniformity by adjusting wafer areas that are non-radial in nature based on incoming CV requirements. 
         [0103]    In still other embodiments, the manipulated variables can include flow rates for edge gas injection flow rates. This approach could also be used to reduce the starvation problem at the wafer edge, and make the edge starvation a controllable variable based on the incoming signature and chamber state. 
         [0104]    In some MLMIMO models, the interaction terms can be updated between lots during a offline triggered calculation update procedure. For example, the cross term calculation update can be triggered by checking the sensitivity of the current system to changes in the cross terms, and by running a set of pre-defined delta offsets to see if adjusting the cross terms would have improved the average control. RGA could also be used in this calculation, and the trigger events can be used to perform adaptive feedback updates for the MLMIMO model. For example, adaptive feedback can be used when copying a MLMIMO model from chamber to chamber and allowing the MLMIMO model to adapt to the new chamber behavior. Another use arises when a new product is release and the old product equation can be used to start the model, then after so many wafers the model update is triggered and a new model is adjusted, and the resulting model can them be used and monitored for performance. 
         [0105]      FIG. 5  illustrates an exemplary view of a multi-step processing sequence for a creating a metal gate structure in accordance with embodiments of the invention. In the illustrated embodiment, six exemplary gate stacks ( 501 - 506 ) are shown, but this is not required for the invention. Alternatively, a different number of gates stacks with different configurations may be used. 
         [0106]    In some embodiments, the multi-layer metal-gate stacks ( 501 ,  502 ,  503 ,  504 ,  505 , and  506 ,  FIG. 5 ) can be created using a Poly-Etch (PE) processing sequence and a metal-gate etch (MGE) processing sequence. For example, the P-E processing sequence can include an Si-ARC layer etching procedure, an etch-control layer (ECL) etching procedure, a TEOS layer etching procedure, a TEOS Over-Etch (OE) etching procedure, and an Ashing procedure. In addition, the metal-gate etch (MGE) processing sequence can include a “Break-Though” (BT) etching procedure, a main etch (ME) etching procedure, an Over-Etch (OE) etching procedure, a Titanium-Nitride (TiN) etching procedure, and a HK etching procedure. 
         [0107]    A first gate stack  501  is shown that includes a wafer layer  510 , a metal gate layer  515 , a third hard mask layer  520 , a first silicon-containing layer  525 , a second silicon-containing layer  530 , a second hard mask layer  535 , a gate-width control layer  540 , a first hard mask layer  545 , and a pattern of soft mask features  550 . For example, the wafer layer  510  can include a semiconductor material; the metal gate layer  515  can include HfO 2 ; the third hard mask layer  520  can include TiN: the first silicon-containing layer  525  can include amorphous silicon (a-Si): the second silicon-containing layer  530  can include SiN; the second hard mask layer  535  can include Tetraethyl Orthosilicate, (TEOS) [Si(OC 2 H 5 ) 4 ]; the gate-width control layer  540  can include ODL; the first hard mask layer  545  can include Si-ARC material, and the soft mask features  550  can include photoresist material. 
         [0108]    The first MLMS processing sequence can be modeled using models ( 560 - 570 ), and the models ( 560 - 570 ) can exchange Measured Variable (MV) data using transfer means  575 , can exchange Disturbance Variable (DV) data using transfer means  580 , and can exchange Controlled Variable (CV) data using transfer means  585 . The models ( 560 - 570 ) can receive, process, and/or send MV data, DV data, and CV associated with the etching procedures described herein. 
         [0109]    The first model  560  can be a first integrated metrology (IM) model for the first gate stack  501 , and can include a first ODP model. The first model  560  can be used to determine profile data for the soft-mask (photoresist) features  550 . 
         [0110]    A second gate stack  502  is shown that includes a wafer layer  510 , a metal gate layer  515 , a third hard mask layer  520 , a first silicon-containing layer  525 , a second silicon-containing layer  530 , a second hard mask layer  535 , a gate-width control layer  540 , first hard mask features  545  a, and the etched soft mask features  550   a . For example, the wafer layer  510  can include a semiconductor material; the metal gate layer  515  can include HfO  2 ; the third hard mask layer  520  can include TiN: the first silicon-containing layer  525  can include amorphous silicon (a-Si): the second silicon-containing layer  530  can include SiN; the second hard mask layer  535  can include TEOS; the gate-width control layer  540  can include etch control material; the first hard mask features  545  a can include etched Si-ARC material, and the etched soft mask features  550   a  can include etched photoresist material. During a first etch procedure, the pattern of soft mask features  550  can be used to create a pattern of first hard mask features  545   a.    
         [0111]    The patterned wafers having the first gate stacks  501  thereon can be etched using a first etch procedure to create patterned wafers having the second gate stacks  502  thereon. In some embodiments, an Si-ARC layer etching procedure can be used. Alternatively, other etching procedures may be used. One or more first etch models  561  can be created for the first etch procedure. 
         [0112]    During the Si-ARC layer etching procedure, the chamber pressure can range from approximately 12 mT to approximately 18 mT; the top power can vary from approximately 450 watts to approximately 550 watts; the lower power can vary from approximately 90 watts to approximately 110 watts; the ESC voltage can be set at approximately 2500 V; the Tetrafluoromethane (CF 4 ) flow rate can vary between approximately 60 sccm and approximately 100 sccm; the Carbon Hydro-Trifluoride (CHF 3 ) flow rate can vary between approximately 40 sccm and approximately 60 sccm; the top chamber temperature can vary from approximately 70 degrees Celsius to approximately 90 degrees Celsius; the chamber wall temperature can vary from approximately 50 degrees Celsius to approximately 70 degrees Celsius; the bottom chamber temperature can vary from approximately 10 degrees Celsius to approximately 30 degrees Celsius; the temperature at the center of the wafer holder can vary from approximately 12 degrees Celsius to approximately 20 degrees Celsius; the temperature at the edge of the wafer holder can vary from approximately 8 degrees Celsius to approximately 12 degrees Celsius; the center backside pressure for the wafer holder can vary from approximately 15 Torr to approximately 25 Torr; the edge backside pressure for the wafer holder can vary from approximately 27 Torr to approximately 33 Torr; and the processing time can vary from approximately 60 seconds to approximately 90 seconds. 
         [0113]    The third model  562  can be a second integrated metrology (IM) model for the second gate stack  502 , and can include a second ODP model. The second ODP model  562  can be used to determine profile data for the etched photoresist features  550   a  and the first hard mask features  545   a.    
         [0114]    A third gate stack  503  is shown that includes a wafer layer  510 , a metal gate layer  515 , a third hard mask layer  520 , a first silicon-containing layer  525 , a second silicon-containing layer  530 , a second hard mask layer  535 , gate-width control features  540   b , and etched first hard mask features  545   b . For example, the wafer layer  510  can include a semiconductor material; the metal gate layer  515  can include HfO 2 ; the third hard mask layer  520  can include TiN: the first silicon-containing layer  525  can include amorphous silicon (a-Si): the second silicon-containing layer  530  can include SiN; the second hard mask layer  535  can include TEOS; the gate-width control features  540   b  can include etched ODL; and the etched first hard mask features  545   b  can include etched Si-ARC material. During a second etch procedure, the pattern of etched first hard mask features  545  a can be used to create a pattern of etched gate-width control features  540   b.    
         [0115]    The patterned wafers having the second gate stacks  502  thereon can be etched using a second etch procedure to create patterned wafers having the third gate stacks  503  thereon. In some embodiments, an etch-control layer (ECL) etching procedure can be used. Alternatively, other etching procedures may be used. One or more second etch models  563  can be created for the second etch procedure. 
         [0116]    During the etch-control layer (ECL) etching procedure, the chamber pressure can range from approximately 15 mT to approximately 25 mT; the top power can vary from approximately 450 watts to approximately 550 watts; the lower power can vary from approximately 90 watts to approximately 110 watts; the ESC voltage can be set at approximately 2500 V; the O 2  flow rate can vary between approximately 30 sccm and approximately 50 sccm; the CO 2  flow rate can vary between approximately 70 sccm and approximately 90 sccm; the HBr flow rate can vary between approximately 25 sccm and approximately 35 sccm; the top chamber temperature can vary from approximately 70 degrees Celsius to approximately 90 degrees Celsius; the chamber wall temperature can vary from approximately 50 degrees Celsius to approximately 70 degrees Celsius; the bottom chamber temperature can vary from approximately 10 degrees Celsius to approximately 30 degrees Celsius; the temperature at the center of the wafer holder can vary from approximately 12 degrees Celsius to approximately 20 degrees Celsius; the temperature at the edge of the wafer holder can vary from approximately 8 degrees Celsius to approximately 12 degrees Celsius; the center backside pressure for the wafer holder can vary from approximately 15 Torr to approximately 25 Torr; the edge backside pressure for the wafer holder can vary from approximately 27 Torr to approximately 33 Torr; and the processing time can vary from approximately 90 seconds to approximately 130 seconds. 
         [0117]    The fifth model  564  can be a third integrated metrology (IM) model for the third gate stack  503 , and can include a third ODP model. The third ODP model  564  can be used to determine profile data for the gate-width control features  540   b , and etched first hard mask features  545   b.    
         [0118]    A fourth gate stack  504  is shown that includes a wafer layer  510 , a metal gate layer  515 , third hard mask layer  520 , first silicon-containing layer  525 , second silicon-containing layer  530 , and second hard mask features  535   c . For example, the wafer layer  510  can include a semiconductor material; the metal gate layer  515  can include HfO 2 ; the third hard mask layer  520  can include TiN: the first silicon-containing layer  525  can include amorphous silicon (a-Si): the second silicon-containing layer  530  can include SiN; the second hard mask features  535   c  can include TEOS material. During a third etch procedure, the pattern of gate-width control layer features  540   b  can be used to create the second hard mask features  535   c.    
         [0119]    The seventh model  566  can be a fourth integrated metrology (IM) model for the fourth gate stack  504 , and can include a fourth ODP model. The fourth ODP model  566  can be used to determine profile data for the second hard mask features  535   c.    
         [0120]    The patterned wafers having the third gate stacks  503  thereon can be etched using a third etch sequence to create patterned wafers having the fourth gate stacks  504  thereon. In some embodiments, a TEOS etch sequence can be used that can include a TEOS layer etching procedure, a TEOS OE etching procedure, and an ashing procedure. Alternatively, other etching, ashing, or cleaning procedures may be used. One or more third etch models  565  can be created for the TEOS etch sequence. 
         [0121]    During the TEOS layer etching procedure, the chamber pressure can range from approximately 35 mT to approximately 45 mT; the top power can vary from approximately 550 watts to approximately 650 watts; the lower power can vary from approximately 90 watts to approximately 110 watts; the ESC voltage can be set at approximately 2500 V; the CF 4  flow rate can vary between approximately 40 sccm and approximately 60 sccm; the CHF 3  flow rate can vary between approximately 40 sccm and approximately 60 sccm; the O 2  flow rate can vary between approximately 3 sccm and approximately 7 sccm; the top chamber temperature can vary from approximately 30 degrees Celsius to approximately 90 degrees Celsius; the chamber wall temperature can vary from approximately 50 degrees Celsius to approximately 70 degrees Celsius; the bottom chamber temperature can vary from approximately 30 degrees Celsius to approximately 50 degrees Celsius; the temperature at the center of the wafer holder can vary from approximately 25 degrees Celsius to approximately 35 degrees Celsius; the temperature at the edge of the wafer holder can vary from approximately 8 degrees Celsius to approximately 12 degrees Celsius; the center backside pressure for the wafer holder can vary from approximately 15 Torr to approximately 25 Torr; the edge backside pressure for the wafer holder can vary from approximately 27 Torr to approximately 33 Torr; and the processing time can vary from approximately 50 seconds to approximately 90 seconds. 
         [0122]    During the TEOS OE etching procedure, the chamber pressure can range from approximately 35 mT to approximately 45 mT; the top power can vary from approximately 550 watts to approximately 650 watts; the lower power can vary from approximately 90 watts to approximately 110 watts; the ESC voltage can be set at approximately 2500 V; the CF 4  flow rate can vary between approximately 40 sccm and approximately 60 sccm; the CHF 3  flow rate can vary between approximately 40 sccm and approximately 60 sccm; the O 2  flow rate can vary between approximately 3 sccm and approximately 7 sccm; the top chamber temperature can vary from approximately 30 degrees Celsius to approximately 90 degrees Celsius; the chamber wall temperature can vary from approximately 50 degrees Celsius to approximately 70 degrees Celsius; the bottom chamber temperature can vary from approximately 30 degrees Celsius to approximately 50 degrees Celsius; the temperature at the center of the wafer holder can vary from approximately 25 degrees Celsius to approximately 35 degrees Celsius; the temperature at the edge of the wafer holder can vary from approximately 8 degrees Celsius to approximately 12 degrees Celsius; the center backside pressure for the wafer holder can vary from approximately 15 Torr to approximately 25 Torr; the edge backside pressure for the wafer holder can vary from approximately 27 Torr to approximately 33 Torr; and the processing time can vary from approximately 5 seconds to approximately 10 seconds. 
         [0123]    During the Ashing procedure, the chamber pressure can range from approximately 125 mT to approximately 175 mT; the top power can vary from approximately 350 watts to approximately 450 watts; the lower power can vary from approximately 20 watts to approximately 30 watts; the ESC voltage can be set at approximately 2500 V; the O 2  flow rate can vary between approximately 430 sccm and approximately 470 sccm; the top chamber temperature can vary from approximately 30 degrees Celsius to approximately 90 degrees Celsius; the chamber wall temperature can vary from approximately 50 degrees Celsius to approximately 70 degrees Celsius; the bottom chamber temperature can vary from approximately 70 degrees Celsius to approximately 80 degrees Celsius; the temperature at the center of the wafer holder can vary from approximately 70 degrees Celsius to approximately 80 degrees Celsius; the temperature at the edge of the wafer holder can vary from approximately 8 degrees Celsius to approximately 12 degrees Celsius; the center backside pressure for the wafer holder can vary from approximately 15 Torr to approximately 25 Torr; the edge backside pressure for the wafer holder can vary from approximately 27 Torr to approximately 33 Torr; and the processing time can vary from approximately 150 seconds to approximately 210 seconds. 
         [0124]    A fifth gate stack  505  is shown that includes a wafer layer  510 , a metal gate layer  515 , etched third hard mask layer features  520   d , etched first silicon-containing layer features  525   d , etched second silicon-containing layer features  530   d , and etched second hard mask layer features  535   d . For example, the wafer layer  510  can include a semiconductor material; the metal gate layer  515  can include HfO 2 ; the etched third hard mask layer features  520   d  can include TiN: the etched first silicon-containing layer features  525   d  can include amorphous silicon (a-Si): the etched second silicon-containing layer features  530   d  can include SiN; and the etched second hard mask layer features  535   d  can include TEOS. During a fourth etch procedure a cleaning procedure can be performed and the remaining gate-width control layer material  540   c  can be removed. 
         [0125]    The patterned wafers having the fourth gate stacks  504  thereon can be etched using a fourth etch sequence to create patterned wafers having the fifth gate stacks  505  thereon. In some embodiments, a first hard-mask etch sequence can be used that can include a “break-through (BT) etching procedure, a Main-Etch (ME) etching procedure, an Over-Etch (OE) etching procedure, and a Titanium-Nitride (TiN) etching procedure. Alternatively, other etching, ashing, or cleaning procedures may be used. One or more fourth etch models  567  can be created for the first hard-mask etch sequence. 
         [0126]    During the BT etching procedure, the chamber pressure can range from approximately 8 mT to approximately 12 mT; the top power can vary from approximately 600 watts to approximately 700 watts; the lower power can vary from approximately 175 watts to approximately 200 watts; the ESC voltage can be set at approximately 2500 V; the CF 4  flow rate can vary between approximately 120 sccm and approximately 150 sccm; the top chamber temperature can vary from approximately 70 degrees Celsius to approximately 90 degrees Celsius; the chamber wall temperature can vary from approximately 50 degrees Celsius to approximately 70 degrees Celsius; the bottom chamber temperature can vary from approximately 10 degrees Celsius to approximately 30 degrees Celsius; the wafer holder temperature can vary from approximately 60 degrees Celsius to approximately 70 degrees Celsius; the center backside pressure for the wafer holder can vary from approximately 8 Torr to approximately 12 Torr; the edge backside pressure for the wafer holder can vary from approximately 8 Torr to approximately 12 Torr; and the processing time can vary from approximately 5 seconds to approximately 15 seconds. 
         [0127]    During the ME etching procedure, the chamber pressure can range from approximately 8 mT to approximately 12 mT; the top power can vary from approximately 120 watts to approximately 150 watts; the ESC voltage can be set at approximately 2500 V; the O 2  flow rate can vary between approximately 2 sccm and approximately 6 sccm; the HBr flow rate can vary between approximately 220 sccm and approximately 280 sccm; the top chamber temperature can vary from approximately 70 degrees Celsius to approximately 90 degrees Celsius; the chamber wall temperature can vary from approximately 50 degrees Celsius to approximately 70 degrees Celsius; the bottom chamber temperature can vary from approximately 10 degrees Celsius to approximately 30 degrees Celsius; the wafer holder temperature can vary from approximately 60 degrees Celsius to approximately 70 degrees Celsius; the center backside pressure for the wafer holder can vary from approximately 8 Torr to approximately 12 Torr; the edge backside pressure for the wafer holder can vary from approximately 8 Torr to approximately 12 Torr; and the processing time can vary from approximately 50 seconds to approximately 70 seconds. 
         [0128]    During the OE etching procedure, the chamber pressure can range from approximately 8 mT to approximately 12 mT; the top power can vary from approximately 120 watts to approximately 150 watts; the lower power can vary from approximately 20 watts to approximately 40 watts; the ESC voltage can be set at approximately 2500 V; the O 2  flow rate can vary between approximately 2 sccm and approximately 6 sccm; the HBr flow rate can vary between approximately 220 sccm and approximately 280 sccm; the top chamber temperature can vary from approximately 70 degrees Celsius to approximately 90 degrees Celsius; the chamber wall temperature can vary from approximately 50 degrees Celsius to approximately 70 degrees Celsius; the bottom chamber temperature can vary from approximately 60 degrees Celsius to approximately 80 degrees Celsius; the wafer holder temperature can vary from approximately 60 degrees Celsius to approximately 70 degrees Celsius; the center backside pressure for the wafer holder can vary from approximately 8 Torr to approximately 12 Torr; the edge backside pressure for the wafer holder can vary from approximately 8 Torr to approximately 12 Torr; and the processing time can vary from approximately 20 seconds to approximately 30 seconds. 
         [0129]    During the TiN etching procedure, the chamber pressure can range from approximately 8 mT to approximately 12 mT; the top power can vary from approximately 180 watts to approximately 220 watts; the lower power can vary from approximately 40 watts to approximately 60 watts; the ESC voltage can be set at approximately 2500 V; the chlorine (Cl 2 ) flow rate can vary between approximately 12 sccm and approximately 18 sccm; the Ar flow rate can vary between approximately 180 sccm and approximately 220 sccm; the top chamber temperature can vary from approximately 70 degrees Celsius to approximately 90 degrees Celsius; the chamber wall temperature can vary from approximately 50 degrees Celsius to approximately 70 degrees Celsius; the bottom chamber temperature can vary from approximately 60 degrees Celsius to approximately 80 degrees Celsius; the wafer holder temperature can vary from approximately 60 degrees Celsius to approximately 70 degrees Celsius; the center backside pressure for the wafer holder can vary from approximately 8 Torr to approximately 12 Torr; the edge backside pressure for the wafer holder can vary from approximately 8 Torr to approximately 12 Torr; and the processing time can vary from approximately 50 seconds to approximately 80 seconds. 
         [0130]    The ninth model  568  can be a fifth integrated metrology (IM) model for the fifth gate stack  505 , and can include a fifth ODP model. The fifth ODP model  568  can be used to determine profile data for the cleaned third hard mask features  520   d , the cleaned first silicon-containing layer features  525   d , the cleaned second silicon-containing layer features  530   d , the cleaned second hard mask features  535   d.    
         [0131]    A sixth gate stack  506  is shown that includes a wafer layer  510  and metal gate layer features  515   e . During a fifth etch procedure, the first third mask layer features  520   d , the first silicon-containing layer features  525   d , the second silicon-containing layer features  530   d , and the second hard mask layer features  535   d  can be etched to create a pattern of metal gate layer features  515   e.    
         [0132]    The patterned wafers having the fifth gate stacks  504  thereon can be etched using a fifth etch sequence to create patterned wafers having the sixth gate stacks  506  thereon. In some embodiments, a second hard-mask etch sequence can be used that can include a metal layer (HK) etching procedure. Alternatively, other etching, ashing, or cleaning procedures may be used. One or more fifth etch models  569  can be created for the second hard-mask etch sequence. 
         [0133]    During the HK etching procedure, the HK chamber pressure can range from approximately 8 mT to approximately 12 mT; the top power can vary from approximately 550 watts to approximately 650 watts; the ESC voltage can be set at approximately 500 V; the Boron Trichloride (BCl 3 ) flow rate can vary between approximately 120 sccm and approximately 180 sccm; the top chamber temperature can vary from approximately 70 degrees Celsius to approximately 90 degrees Celsius; the chamber wall temperature can vary from approximately 40 degrees Celsius to approximately 60 degrees Celsius; the bottom chamber temperature can vary from approximately 60 degrees Celsius to approximately 80 degrees Celsius; and the processing time can vary from approximately 30 seconds to approximately 40 seconds. 
         [0134]    The eleventh model  570  can be a sixth integrated metrology (IM) model for the sixth gate stack  505 , and can include a sixth ODP model. The sixth ODP model  570  can be used to determine profile data for the metal gate layer features  515   e.    
         [0135]    During process development, Design of Experiment (DOE) techniques can be used to examine the preliminary set of models ( 560 - 570 ) and to develop a reduced set of MLMIMO models. 
         [0136]      FIG. 6  illustrates an exemplary view of a second multi-step processing sequence for a creating a metal gate structure in accordance with embodiments of the invention. In the illustrated embodiment, three exemplary gate stacks ( 601 - 603 ) are shown, but this is not required for the invention. Alternatively, a different number of gates stacks, a different number of models, and different configurations may be used. 
         [0137]    In some embodiments, the multi-layer metal-gate stacks ( 601 ,  602 , and  603 ,  FIG. 6 ) can be created using a first Multi-Layer-Multi-Step (MLMS) processing sequence and a second Multi-Layer-Multi-Step (MLMS) processing sequence. For example, the first MLMS processing sequence can include a Si-ARC layer etching procedure, as described above, and an etch-control layer (ECL) etching procedure, as described above. In addition, the second MLMS processing sequence can include a TEOS layer etching procedure, as described above, a TEOS Over-Etch (OE) etching procedure, as described above, an Ashing procedure, a “Break-Though” (BT) etching procedure, as described above, a main etch (ME) etching procedure, as described above, an Over-Etch (OE) etching procedure, as described above, a Titanium-Nitride (TiN) etching procedure, as described above, and a HK etching procedure, as described above. 
         [0138]    A first gate stack  601  is shown that includes a wafer layer  610 , a metal gate layer  615 , a third hard mask layer  620 , a first silicon-containing layer  625 , a second silicon-containing layer  630 , a second hard mask layer  635 , a gate-width control layer  640 , a first hard mask layer  645 , and a pattern of soft mask features  650 . For example, the wafer layer  610  can include a semiconductor material; the metal gate layer  615  can include HfO 2 ; the third hard mask layer  620  can include TiN: the first silicon-containing layer  625  can include amorphous silicon (a-Si): the second silicon-containing layer  630  can include SiN; the second hard mask layer  635  can include TEOS; the gate-width control layer  640  can include ODL; the first hard mask layer  645  can include Si-ARC material, and the soft mask features  650  can include photoresist material. 
         [0139]    The first ODP model  660  can be established for the first gate stack  601 , and the first ODP model  660  can be used to determine profile data for the photoresist features  650  and other layer-related data. The first ODP model  660  can provide DV data to the MLMIMO Model  661 . 
         [0140]    The patterned wafers having the first gate stacks  601  thereon can be etched using first MLMS processing sequence to create patterned wafers having the second gate stacks  602  thereon. For example, the first MLMS processing sequence can include an Si-ARC layer etching procedure, as described above, and an etch-control layer (ECL) etching procedure, as described above. 
         [0141]    The first MLMS processing sequence can be modeled using a MLMIMO Model  661 , and the MLMIMO Model  661  can exchange Measured Variable (MV) data using transfer means  675 , can exchange Disturbance Variable (DV) data using transfer means  680 , and can exchange Controlled Variable (CV) data using transfer means  685 . MLMIMO Model  661  can include MV data, DV data, and CV associated with the Si-ARC layer etching procedure, and with the etch-control layer (ECL) etching procedure, as described above. The models ( 660 - 664 ) can receive, process, create, and/or send MV data, DV data, and CV associated with the procedures described herein. 
         [0142]    A second gate stack  602  is shown that includes a wafer layer  610 , a metal gate layer  615 , a third hard mask layer  620 , a first silicon-containing layer  625 , a second silicon-containing layer  630 , a second hard mask layer  635 , etched gate-width control features  640   a , and etched first hard mask features  645   a . For example, the wafer layer  610  can include a semiconductor material; the metal gate layer  615  can include HfO 2 ; the third hard mask layer  620  can include TiN: the first silicon-containing layer  625  can include amorphous silicon (a-Si): the second silicon-containing layer  630  can include SiN; the second hard mask layer  635  can include TEOS; the gate-width control features  640   a  can include etched ECL material; and the etched first hard mask features  645   b  can include etched Si-ARC material. During a first MLMS processing sequence, the pattern of soft mask feature  650  can be used to create the pattern of etched first hard mask features  645  a and the pattern of etched gate-width control features  640   a.    
         [0143]    The second ODP model  662  can be established for the second gate stack  602 , and the second ODP model  662  can be used to determine profile data for the gate-width control features  640   a , the etched first hard mask features  645   b , and other layer-related data. 
         [0144]    The patterned wafers having the second gate stacks  602  thereon can be etched using a second MLMS processing sequence to create patterned wafers having the third gate stacks  603  thereon. For example, the second MLMS processing sequence can include a TEOS layer etching procedure, as described above, a TEOS Over-Etch (OE) etching procedure, as described above, an Ashing procedure, a “Break-Though” (BT) etching procedure, as described above, a main etch (ME) etching procedure, as described above, an Over-Etch (OE) etching procedure, as described above, a Titanium-Nitride (TiN) etching procedure, as described above, and a HK etching procedure, as described above. 
         [0145]    The second MLMS processing sequence can be modeled using a second MLMIMO Model  663 , and the MLMIMO Model  663  can exchange Measured Variable (MV) data using transfer means  675 , can exchange Disturbance Variable (DV) data using transfer means  680 , and can exchange Controlled Variable (CV) data using transfer means  685 . MLMIMO Model  663  can include MV data, DV data, and CV associated with the TEOS layer etching procedure, as described above, a TEOS Over-Etch (OE) etching procedure, as described above, an Ashing procedure, a “Break-Though” (BT) etching procedure, as described above, a main etch (ME) etching procedure, as described above, an Over-Etch (OE) etching procedure, as described above, a Titanium-Nitride (TiN) etching procedure, as described above, and a HK etching procedure, as described above. 
         [0146]    A third gate stack  603  is shown that includes a wafer layer  610  and a pattern of metal gate layer features  615   b . For example, the wafer layer  610  can include a semiconductor material; the metal gate layer features  615   b  can include HfO 2 . During a second MLMS processing sequence, the pattern of etched first hard mask features  645  a and the pattern of etched gate-width control features  640   a  can be used to create the pattern of metal gate layer features  615   b.    
         [0147]    The third ODP model  664  can be established for the third gate stack  603 , and the third ODP model  664  can be used to determine profile data for the metal gate layer features  615   b  and other layer-related data. 
         [0148]    During MLMIMO model development, manipulated variables (MVs) can be established and can be fed forward and/or fed back using various paths  675 ; disturbance variables (DVs) can be established and can be fed forward and/or fed back using various paths  680 ; and controlled variables (CVs) can be established and can be fed forward and/or fed back using various paths  685 . In addition, the number of feed forward and feed back paths ( 675 ,  680 , and  685 ) actually used in the MLMIMO model can be optimized. DOE techniques can be used to examine the this set of models ( 660 - 664 ) and to develop a reduced set of feed forward and feed back paths/variables. One or more of the three exemplary gate stacks ( 601 - 603 ) and one or more of the models ( 660 - 664 ) can be used during model development and DOE procedures. Recipe data and/or process data for one or more of the three exemplary gate stacks ( 601 - 603 ) and modeling data for one or more of the models ( 660 - 664 ) can be stored in libraries and used during MLMIMO modeling procedures. In addition, the first and second, MLMS processing sequences can be performed using one or more of the etch subsystems described herein in  FIGS. 2A-2G  and  FIGS. 3A-3G . 
         [0149]      FIG. 7  illustrates an exemplary view of a third multi-step modeling sequence for a creating a metal gate structure in accordance with embodiments of the invention. In other embodiments, the multi-layer metal-gate structures ( 701 ,  702 , and  703 ,  FIG. 7 ) can be created using a first Multi-Layer-Multi-Step (MLMS) processing sequence and a second Multi-Layer-Multi-Step (MLMS) processing sequence. For example, the first MLMS processing sequence can include a Si-ARC layer etching procedure, as described above, an etch-control layer (ECL) etching procedure, as described above, a TEOS layer etching procedure, as described above, a TEOS Over-Etch (OE) etching procedure, as described above, an Ashing procedure as described above. In addition, the second MLMS processing sequence can include, a “Break-Though” (BT) etching procedure, as described above, a main etch (ME) etching procedure, as described above, an Over-Etch (OE) etching procedure, as described above, a Titanium-Nitride (TiN) etching procedure, as described above, and a HK etching procedure, as described above. 
         [0150]    A first gate stack  701  is shown that includes a wafer layer  710 , a metal gate layer  715 , a third hard mask layer  720 , a first silicon-containing layer  725 , a second silicon-containing layer  730 , a second hard mask layer  735 , a gate-width control layer  740 , a first hard mask layer  745 , and a pattern of soft mask features  750 . For example, the wafer layer  710  can include a semiconductor material; the metal gate layer  715  can include HfO 2 ; the third hard mask layer  720  can include TiN: the first silicon-containing layer  725  can include amorphous silicon (a-Si): the second silicon-containing layer  730  can include SiN; the second hard mask layer  735  can include TEOS; the gate-width control layer  740  can include Etch Control material; the first hard mask layer  745  can include Si-ARC material, and the soft mask features  750  can include photoresist material. 
         [0151]    The first ODP model  760  can be established for the first gate stack  701 , and the first ODP model  760  can be used to determine profile data for the photoresist features  750  and other layer-related data. 
         [0152]    The patterned wafers having the first gate stacks  701  thereon can be processed using first MLMS processing sequence to create patterned wafers having the second gate stacks  702  thereon. For example, the first MLMS processing sequence can include a Si-ARC layer etching procedure, as described above, an etch-control layer (ECL) etching procedure, as described above, a TEOS layer etching procedure, as described above, a TEOS Over-Etch (OE) etching procedure, as described above, an Ashing procedure, as described above. 
         [0153]    The third MLMS processing sequence can be modeled using models ( 760 - 764 ), and the models ( 760 - 764 ) can exchange Measured Variable (MV) data using transfer means  775 , can exchange Disturbance Variable (DV) data using transfer means  780 , and can exchange Controlled Variable (CV) data using transfer means  785 . The models ( 760 - 764 ) can receive, create, process, and/or send MV data, DV data, and CV associated with the procedures described herein. 
         [0154]    A second gate stack  702  is shown that includes a wafer layer  710 , a metal gate layer  715 , a third hard mask layer  720 , a first silicon-containing layer  725 , a second silicon-containing layer  730 , a etched second hard mask features  735   a . For example, the wafer layer  710  can include a semiconductor material; the metal gate layer  715  can include HfO 2 ; the third hard mask layer  720  can include TiN: the first silicon-containing layer  725  can include amorphous silicon (a-Si): the second silicon-containing layer  730  can include SiN; and the second hard mask features  735   a  can include TEOS. During a first MLMS processing sequence, the pattern of soft mask feature  750  can be used to create the pattern of etched hard mask features  735   a.    
         [0155]    The second ODP model  762  can be established for the second gate stack  702 , and the second ODP model  762  can be used to determine profile data for the etched hard mask features  735   a  and other layer-related data. 
         [0156]    The patterned wafers having the second gate stacks  702  thereon can be etched using a second MLMS processing sequence to create patterned wafers having the third gate stacks  703  thereon. For example, the second MLMS processing sequence can include a “Break-Though” (BT) etching procedure, as described above, a main etch (ME) etching procedure, as described above, an Over-Etch (OE) etching procedure, as described above, a Titanium-Nitride (TiN) etching procedure, as described above, and a HK etching procedure, as described above. 
         [0157]    The second MLMS processing sequence can be modeled using a second MLMIMO Model  763 , and the MLMIMO Model  763  can exchange Measured Variable (MV) data using transfer means  775 , can exchange Disturbance Variable (DV) data using transfer means  780 , and can exchange Controlled Variable (CV) data using transfer means  785 . MLMIMO Model  763  can include MV data, DV data, and CV associated with a “Break-Though” (BT) etching procedure, as described above, a main etch (ME) etching procedure, as described above, an Over-Etch (OE) etching procedure, as described above, a Titanium-Nitride (TiN) etching procedure, as described above, and a HK etching procedure, as described above. 
         [0158]    The second ODP model  762  can be established for the second gate stack  702 , and the second ODP model  762  can be used to determine profile data for the gate-width control features  740   a , the etched first hard mask features  745   b , and other layer-related data. 
         [0159]    During MLMIMO model development, manipulated variables (MVs) can be established and can be fed forward and/or fed back using various paths  775 ; disturbance variables (DVs) can be established and can be fed forward and/or fed back using various paths  780 ; and controlled variables (CVs) can be established and can be fed forward and/or fed back using various paths  785 . In addition, DOE techniques can be used to examine the this set of models ( 760 - 764 ) and to develop an optimum set of MLMIMO models. One or more of the three exemplary gate stacks ( 701 - 703 ) and one or more of the models ( 760 - 764 ) can be used during model development and DOE procedures. Recipe data and/or process data for one or more of the three exemplary gate stacks ( 701 - 703 ) and modeling data for one or more of the models ( 760 - 764 ) can be stored in libraries and used during MLMIMO modeling procedures. In addition, the first and second, MLMS processing sequences can be performed using one or more of the etch subsystems described herein in  FIGS. 2A-2G  and  FIGS. 3A-3G . 
         [0160]      FIG. 8  shows an exemplary schematic view of a Multi-Layer/Multi-Input/Multi-Output (MLMIMO) model in accordance with embodiments of the invention. The exemplary schematic view  800  includes a first gate stack  810 , a second gate stack  820 , and a third gate stack  830 . A first processing sequence  815  that can be used to create the second gate stack  820  from the first gate stack  810 ; a second processing sequence  825  that can be used to create the third gate stack  830  from the second gate stack  820 ; and a third processing sequence  835  that can be used to measure the third gate stack  830 . 
         [0161]    The first processing sequence  815  can include a first measurement procedure (Meas 1 ) and a first etch procedure Etch a ; the second processing sequence  825  can include a second measurement procedure (Meas 2 ) and a second etch procedure Etch b ; and the third processing sequence  835  can include a third measurement procedure (Meas 3 ). 
         [0162]    The first model 1  can be used to model the first processing sequence  815  and can include a first set of disturbance variables DV 1a-na , a first set of manipulated variables MV 1a-na , and a first set of controlled variables CV 1a-na . The second model 2  can be used to model the second processing sequence  825  and can include a second set of disturbance variables DV 1b-nb , a second set of manipulated variables MV 1b-nb , and a second set of controlled variables CV 1b-nb . 
         [0163]      FIG. 9  illustrates exemplary block diagram for a two-part Multi-Layer/Multi-Input/Multi-Output (MLMIMO) model in accordance with embodiments of the invention. 
         [0164]    A first generalized model  910  is shown that can be associated with a poly-etch (P-E) sequence and that includes a first set of MVs( 1   a - na ), a first set of DVs( 1   a - na ), and a first set of CVs( 1   a - na ). A first set of exemplary MVs  911  is shown that includes eight manipulated variables {(MV( 1   a )-MV( 8   a )) that can be associated with the model  910 . Alternatively, a different number of different manipulated variables may be associated with the first model  910 . A first set of exemplary DVs  912  is shown that includes six disturbance variables {(DV( 1   a )-DV( 6   a )) that can be associated with the model  910 . Alternatively, a different number of different disturbance variables may be associated with the first model  910 . A first set of exemplary CVs  913  is shown that includes six controlled variables {(CV( 1   a )-CV( 6   a )) that can be associated with the model  910 . Alternatively, a different number of different controlled variables may be associated with the first model  910 . In addition, a first set of exemplary equations  915  is shown that can be associated with the model  910 . Alternatively, other equations may be associated with the first model  910 . 
         [0165]    A second generalized model  920  is shown that can be associated with a metal-gate-etch (MGE) sequence and that includes a second set of MVs( 1   b - nb ), a second set of DVs( 1   b - nb ), and a second set of CVs( 1   b - nb ). A second set of exemplary MVs  921  is shown that includes eight manipulated variables {(MV( 1   b )-MV( 8   b )) that can be associated with the second model  920 . Alternatively, a different number of different manipulated variables may be associated with the second model  920 . A second set of exemplary DVs  922  is shown that includes six disturbance variables {(DV( 1   b )-DV( 6   b )) that can be associated with the second model  920 . Alternatively, a different number of different disturbance variables may be associated with the second model  920 . A second set of exemplary CVs  923  is shown that includes six controlled variables {(CV( 1   b )-CV( 6   b )) that can be associated with the second model  920 . Alternatively, a different number of different controlled variables may be associated with the second model  920 . In addition, a second set of exemplary equations  925  is shown that can be associated with the second model  920 . Alternatively, other equations may be associated with the second model  920 . 
         [0166]    One or more of the variables ( 911 ,  912 , or  913 ) associated with the first model  910  can be fed forward  930  to the second model  920 , and one or more of the variables ( 921 ,  922 , or  923 ) associated with the second model  920  can be fed back  935  to the first model  910 . 
         [0167]      FIG. 10  illustrates an exemplary flow diagram for a procedure for developing a Multi-Layer/Multi-Input/Multi-Output (MLMIMO) model in accordance with embodiments of the invention. In the illustrated embodiment, a procedure  1000  is shown having a number of steps. Alternatively, a different number of alternate steps may be used. 
         [0168]    In  1010 , one or more multi-layer processing sequences can be identified as candidates for a Multi-Layer/Multi-Input/Multi/Output modeling analysis procedure. In some examples, one or more MLMIMO models can be established to create one or more multi-layer metal-gate structures ( 601 ,  602 , and  603 ,  FIG. 6 ) and ( 701 ,  702 , and  703 ,  FIG. 7 ). 
         [0169]    In  1015 , a first set of controlled outputs variables (CVs) and the ranges associated with the CVs can be determined. One or more of the CVs can be specified by an end user or a customer. The CVs can include one or more critical dimensions (CDs) and/or one or more side wall angles associated with one or more of the multi-layer metal-gate structures ( 601 ,  602 , and  603 ,  FIG. 6 ) and ( 701 ,  702 , and  703 ,  FIG. 7 ). In some example, the multi-layer metal-gate structures ( 601 ,  602 , and  603 ,  FIG. 6 ) and ( 701 ,  702 , and  703 ,  FIG. 7 ) can be created using a Poly-Etch (PE) processing sequence and a metal-gate etch (MGE) processing sequence. For example, a metal-gate etch (MGE) sequence can be performed to create one or more metal-gate features in the gate stack, and different metal-gate etch sequences can be performed for pFET devices, nFET devices, Tri-gate devices, and FinFET devices. 
         [0170]    In  1020 , a first set of candidates can be determined for the manipulated variables (MVs) associated with the MLMIMO using one or more candidate recipes. The MVs can include WiW manipulated variables (WiW-MVs), and the WiW-MVs can include “fast” MVs that can be controlled while a wafer is being processed. The MVs can include W2W manipulated variables (W2W-MVs), and the W2W-MVs can include “slow” MVs that can be controlled when a wafer lot is being processed. The ranges for the MVs can be examined for each step in a candidate recipe. 
         [0171]    When a two-zone wafer holder with a fast response time is used, the center temperature and the edge temperature for the wafer holder can be used as (WiW-MVs) and can be changed on a step by step basis. When a RF source with a fast response time is used with a split upper electrode and power splitter, the center RF power and the edge RF power for the plasma can be used as (WiW-MVs) and can be changed on a step by step basis. When a low temperature chiller (−10 C) is used, there can be a larger temperature delta center to edge. In addition, pressure, time, and gas flows can be used as MVs. 
         [0172]    The disturbance variables (DVs) can include resist CD and SWA at the center and edge, the etch control layer CD and SWA at the center and edge, the layer thicknesses at the center and edge, the chemical and etch rate properties of the different layers, the maintenance events on chamber, the chamber-to-chamber data, and IM-to-IM data. 
         [0173]    In  1025 , Design of Experiment (DOE) procedures can be performed to analyze the MLMIMO model. Using physical analysis and engineering experience, DOE procedures can be performed to establish statistical models that can connect MVs with each CV. When the number of experiments increases, a more accurate model can be obtained, but at the expense of additional materials and time. Therefore, cost and availability can limit the number of DOE wafers. In order to reduce them as much as possible but also prevent inaccuracy, a well designed DOE is of key importance. The most critical factor for such a DOE is the format of the predicted model. One or more model types can be selected, ranges can be provided for the CVs and/or MVs, and statistical software, such as JMP® (a statistical software from the SAS Institute) can be used to establish one or more of the DOE tables). The DOE data can be used to establish a candidate MVs, CVs, and DVs that can be associated with a first poly-etch (P-E) sequence, and a metal-gate etch (MGE) sequence. In other analysis procedures, other MVs, DVs, and CVs can be used. In some embodiments, the chamber state data for the etching chambers and the IM chambers can be used as manipulated variables, Alternatively, the process modeling may assume that the chamber state is stable between wafers and/or lots. 
         [0174]    In some embodiments, the PE processing sequence can include an Si-ARC layer etching procedure, an etch-control layer (ECL) etching procedure, a TEOS layer etching procedure, a TEOS Over-Etch (OE) etching procedure, and an Ashing procedure. In addition, the metal-gate etch (MGE) processing sequence can include a “Break-Though” (BT) etching procedure, a main etch (ME) etching procedure, an Over-Etch (OE) etching procedure, a Titanium-Nitride (TiN) etching procedure, and a HK etching procedure. DOE data can be obtained for the P-E processing sequence and for the metal-gate etch (MGE) processing sequences. 
         [0175]    In  1030 , after performing the P-E sequences and the metal-gate etch sequences required to populate one or more DOE tables, nonlinear models with quadratic and interaction terms can be created by using a least squares technique and statistical software. In some models, terms can be deleted that have extremely small coefficients associated with them. 
         [0176]    In  1035 , one or more linear gain matrices (G) can be created using the DOE data. For example, 
         [0000]    
       
         
           
             
               λ 
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               ij 
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                       [ 
                       
                         
                           ∂ 
                           
                             CV 
                             i 
                           
                         
                         
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                             MV 
                             j 
                           
                         
                       
                       ] 
                     
                     
                       MV 
                       
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                     [ 
                     
                       
                         ∂ 
                         
                           CV 
                           i 
                         
                       
                       
                         ∂ 
                         
                           MV 
                           j 
                         
                       
                     
                     ] 
                   
                   
                     CV 
                     
                       k 
                       , 
                       
                         k 
                         ≠ 
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             = 
             
               
                 Gain 
                  
                 
                     
                 
                  
                 
                   ( 
                   
                     open 
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         [0177]    for i=1,2, . . . , n and j=1,2, . . . , n. The symbol (∂CV i /∂MV j ) MV  denotes a partial derivative that is evaluated with all of the manipulated variables except MV j  held constant, and this term is the open-loop gain between CV i  and MV j . In addition, the symbol (∂CV i /∂MV j ) CV  can be interpreted as a closed loop gain that indicates the effect of MV j  and CV i  when all of the control loops are closed. 
         [0178]    When a non-square matrix is obtained, some of the MVs or CVs may be eliminated to create a square matrix. In addition, when there are more MV&#39;s than CVs, the non-square matrix can be analyzed using a non-square RGA (NRGA). For example, 
         [0000]        NRGA=G {circle around (×)}( G   + ) T    
         [0179]    and the pseudo-inverse, G + , is used instead of the normal inverse, G −1 . NRGA provides several criteria for the selection of a square system, but their criteria are not always valid in some non-square systems, so all combinations of square pairing of subsystems might need considered. To compare one subsystem with others RGA pairing rules can be used as a metric. This creates sub combinations that can then be compared for best square matrix. 
         [0180]    In  1040 , one or more Relative Gain Arrays (RGA) can be calculated using one or more of the linear gain matrices (G). For example, when square matrices are used, 
         [0000]        RGA=G {circle around (×)}( G   −1 ) T    
         [0181]    where G is the gain matrix and G −1  is the inverse gain matrix. 
         [0182]    In  1045 , pairing rules in the RGA can be used to investigate the best combinations of MVs and CVs. RGA analysis can be used for measured model parameter selection, and CV-MV pairs can be selected such that their sum is closest to one. In addition, paring on negative elements can be avoided. In addition, the RGA analysis can be used to determine a number of candidate models and to identify the best case solution. When there are more CVs than MVs, RGA analysis can be used for selecting the most controllable CV (sensitivity analysis of CVs to MVs). 
         [0183]    In  1050 , the system stability and conditioning can be determined. For example, the Niederlinski Stability Theorem states that a closed loop system resulting from diagonal pairing is unstable if: 
         [0000]    
       
         
           
             NST 
             = 
             
               
                 
                   det 
                    
                   
                     ( 
                     G 
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                       i 
                       = 
                       1 
                     
                     n 
                   
                    
                   
                     g 
                     ii 
                   
                 
               
               &lt; 
               0 
             
           
         
       
     
         [0000]    where G is the gain matrix and g ii  is the diagonal elements of the gain matrix. The condition of the gain matrix (G) can be determined using the following: 
         [0000]      G=USV T    
         [0184]    where G, U, S, and V are matrices determined using singular value decomposition (SVD). In addition, a condition number (CN) can be determined using the ratio of the larger value to the smaller value in the S matrix. Additional information concerning the Niederlinski Theorem may be found in a book (ISBN 1852337761) entitled “Process Control: Theory and Applications” by Jean-Pierre Corriou which is incorporated herein in its entirety. For example, when CN is greater than fifty, the system is nearly singular and will have poor control performance. 
         [0185]    In  1055 , the MLMIMO model can be optimized using actual equipment and/or performance constraints. In some examples, the measurement locations can be examined and selected to optimize performance, the number of pre- and/or post measurement procedure can be established to optimize performance, the multi-chamber sequences can be examined to optimize throughput. The feedback can be optimized by tuning the EWMA filters. The time constants for the MVs can be determined, and their update frequency can be based on Lot-to-Lot (L2L), W2W, WiW, and process step values. In addition, process center points, CV center points, and MV center points can be examined to optimize performance. Historical data can be used to perform simulations. 
         [0186]    The wafers can include one or more layers that can include semiconductor material, carbon material, dielectric material, glass material, ceramic material, metallic material, oxidized material, mask material, or planarization material, or a combination thereof. 
         [0187]    In other embodiments, one or more wafers can be processed using a verified MLMIMO model and a verified processing sequence. When a verified MLMIMO model is used, one or more verified metal-gate structures can be created on a test wafer, and when the test wafer is examined, a test reference periodic structure can be used. During the examination, examination data can be obtained from the test reference periodic structure. A best estimate structure and associated best estimate data can be selected from the MLMIMO library that includes verified metal-gate structures and associated data. One or more differences can be calculated between the test reference periodic structure and the best estimate structure from the library, the differences can be compared to matching criteria, creation criteria, or product requirements, or any combination thereof. When matching criteria are used, the test reference periodic structure can be identified as a member of the MLMIMO library, and the test wafer can be identified as a reference “golden” wafer if the matching criteria are met or exceeded. When creation criteria are used, the test reference periodic structure can be identified as a new member of the MLMIMO library, and the test wafer can be identified as a verified reference wafer if the creation criteria are met. When product requirement data is used, the test reference periodic structure can be identified as a verified structure, and the test wafer can be identified as verified production wafer if one or more product requirements are met. Corrective actions can be applied if one or more of the criteria or product requirements are not met. MLMIMO-related confidence data and/or risk data can be established for the test reference structure using the test reference structure data and the best estimate structure data. For example, the MLMIMO evaluation library data can include goodness of fit (GOF) data, creation rules data, measurement data, inspection data, verification data, map data, confidence data, accuracy data, process data, or uniformity data, or any combination thereof. 
         [0188]    When metal-gate-related structures are produced and/or examined, accuracy and/or tolerance limits can be used. When these limits are not correct, refinement procedures can be performed. Alternatively, other procedures can be performed, other sites can be used, or other wafers can be used. When a refinement procedure is used, the refinement procedure can utilize bilinear refinement, Lagrange refinement, Cubic Spline refinement, Aitken refinement, weighted average refinement, multi-quadratic refinement, bi-cubic refinement, Turran refinement, wavelet refinement, Bessel&#39;s refinement, Everett refinement, finite-difference refinement, Gauss refinement, Hermite refinement, Newton&#39;s divided difference refinement, osculating refinement, or Thiele&#39;s refinement algorithm, or a combination thereof. 
         [0189]      FIG. 11  illustrates a simplified flow diagram of a procedure for using a Multi-Layer/Multi-Input/Multi-Output (MLMIMO) model in accordance with embodiments of the invention. 
         [0190]    In  1110 , a first set of patterned wafers and associated wafer data can be received by a processing system, and each patterned wafer can include a first patterned soft-mask layer and a plurality of additional layers. The first patterned soft-mask layer can include a plurality of gate-related soft-mask features and at least one first periodic evaluation structure. The wafer data can include real-time integrated metrology (IM) data for the at least one periodic structure in the first patterned soft-mask layer. 
         [0191]    In  1115 , a second set of patterned wafers can be created using a first multi-layer etch sequence, and the first multi-layer etch sequence can be configured to create a first intermediate pattern in a controlled masking layer by patterning a first set of the additional layers using the first patterned soft-mask layer. 
         [0192]    In  1120 , first simulation data can be determined for the first multi-layer etch sequence using a first Multi-Layer/Multi-Input/Multi-Output (MLMIMO) model for the first multi-layer etch sequence. The first MLMIMO model can include a first number (N a ) of first Controlled Variables (CV 1a , CV 2a , . . . CV Na ), a first number (M a ) of first Manipulated Variables (MV 1a , MV 2a , . . . MV Ma ), and a first number (L a ) of first Disturbance Variables (DV 1a , DV 2a , . . . DV La ), where (L a , M a , and N a ) are integers greater than one. 
         [0193]    In  1125 , a third set of patterned wafers can be created using a second multi-layer etch sequence, and the second multi-layer etch sequence can be configured to create a first pattern of metal-gate structures by patterning a second set of the additional layers using the first intermediate pattern in the controlled masking layer. 
         [0194]    In  1130 , second simulation data can be created for the second multi-layer etch sequence using a second MLMIMO model for the second multi-layer etch sequence. The second MLMIMO model can include a second number (N b ) of second Controlled Variables (CV 1b , CV 2b , . . . CV Nb ), a second number (M b ) of second Manipulated Variables (MV 1b , MV 2b , . . . MV Mb ), and a second number (L b ) of second Disturbance Variables (DV 1b , DV 2b , . . . DV Lb ), where (L b , M b , and N b ) are integers greater than one. 
         [0195]    In  1135 , evaluation data can be obtained for at least one of the third set of patterned wafers. 
         [0196]    In  1140 , a query can be performed to determine if the evaluation data is within one or more limits. When the evaluation data is within one or more of the limits, procedure  1100  can branch to  1145 . When the evaluation data is not within one or more of the limits, procedure  1100  can branch to  1150 . 
         [0197]    In  1145 , the third set of patterned wafers can be identified as verified wafers when the evaluation data is less than a first metal-gate limit. 
         [0198]    In  1150 , a corrective action can be performed when the evaluation data is not less than the first metal-gate limit. 
         [0199]      FIG. 12  illustrates a runtime flow diagram of a procedure for using a MLMIMO in accordance with embodiments of the invention. When data is collected, a number of wafers can be used and candidate disturbance variables can be identified. During data collection, the variations associated with one or more CVs can be minimized, and the collected data can be used for a simulation. The simulation can execute the same sequence as the gate etch process used in production. 
         [0200]    In  1210 , one or more wafers can be measured in an integrated metrology chamber and values for a first number (I) of disturbance variables D(I) can be obtained. In addition, other sensor data can be received and analyzed. The IM data can include CD and SWA data from multiple sites in a patterned masking layer on each incoming wafer. A second number (m) of manipulated variables MV(m) can be established. 
         [0201]    In some embodiments, the incoming disturbance variables related to wafer state can be measured by using an IM tool, and the IM data can include profile data, CD data, SWA data, and BARC film thickness data at multiple sites across the wafer. For example, 8-10 center sites can be selected that can represent the center of the wafer, and 8-10 edge sites at the same radius can be selected that represent the edge radial signature and that can be optimum for etch control. The same number of sites can be selected for each area of the wafer to give the same weighting of accuracy to all areas. Grating density and transistor type should be selected to correlate to the most critical chip level performance metric (such as P or N channel transistor type) because each of the transistor structures can have some variations that can be related to the etch profile control needs. 
         [0202]    The CD DV can be a critical DV and can have associated DVs that modify the measurement due to the mechanisms at work during the Poly-Etch (P-E) procedures. SWA can be a primary modifier that increases in sensitivity as the angle become less than ninety degrees, In addition, the middle CD can be used if it gives the most accurate correlation to the final CD. Middle CD performs the best in simple terms because it averages the variation of the top and bottom CD measurements. 
         [0203]    A second modifier of CD can be the BARC thickness variation across the wafer and water-to-wafer. BARC thickness can affect CD if the thickness is non-uniform because during the BARC etch the resist is continuing to be etched. A thinner BARC can give a shorter etch time, and thicker BARC can give a longer etch time, and a longer etch time will result in a smaller CD. Therefore, BARC non-uniformity can directly result in increased center to edge CD variation that will need to be modeled for control during the partial and final etch. 
         [0204]    The IM data can be obtained after a development procedure, and the IM data can be obtained using as IM unit in a Lithography subsystem, an IM unit in an Etch subsystem, or a standalone IM unit. 
         [0205]    In addition, sensor and state data can be used for DVs indicating a predicted plasma chamber state. For example, when lots (wafers) are being processed without using conditioning wafers, the chamber state can be affected by drift. Variations that contribute to chamber state feed forward DV can include events such as chamber cleans, parts replacements, chemical changes, idle time, conditioning wafers, chamber pause, manual adjustments, wafer material changes, and product density changes. 
         [0206]    In  1215 , the received data can be filtered and/or qualified. For example, the measurement DVs can be filtered using a box and whisker algorithm that eliminates sites that do not statically appear to be of the same population, and the remaining site can be averaged to represent the physical area of the wafer. 
         [0207]    In  1220 , one or more of the CVs can be calculated and CDs, SWAs, uniformity values, and/or profile changes can be determined for the poly-etch sequence. In some examples, a third number (N a ) of control variables can be established using the following: 
         [0000]        CV ( N   a )= f   Na   {MV (1 a ), . . .  MV ( Ma− 1),  MV ( Ma ),  DV (1 a ), . . .  DV ( La− 1),  DV ( La )}+offset Na    
         [0208]    where L a , M a , and N a  are integers that are greater than two. 
         [0209]    For example, when four CVs, six MVs, and four DVs have been identified, four non-linear models with higher order and interaction terms can be defined as: 
         [0000]        CV (1 a )= f   1a   {MV (1 a ),  MV (2 a ),  MV (3 a ),  MV (4 a ),  MV (5 a ),  MV (6 a ),  DV (1 a ),  DV (2 a ),  DV (3 a ),  DV (4 a )}+offset 1a    
         [0000]        CV (2 a )= f   2a   {MV (1 a ),  MV (2 a ),  MV (3 a ),  MV (4 a ),  MV (5 a ),  MV (6 a ),  DV (1 a ),  DV (2 a ),  DV (3 a ),  DV (4 a )}+offset 2a    
         [0000]        CV (3 a )= f   3a   {MV (1 a ),  MV (2 a ),  MV (3 a ),  MV (4 a ),  MV (5 a ),  MV (6 a ),  DV (1 a ),  DV (2 a ),  DV (3 a ),  DV (4 a )}+offset 3a    
         [0000]        CV (4 a )= f   4a   {MV (1 a ),  MV (2 a ),  MV (3 a ),  MV (4 a ),  MV (5 a ),  MV (6 a ),  DV (1 a ),  DV (2 a ),  DV (3 a ),  DV (4 a )}+offset 4a    
         [0210]    In addition, optimized process settings can be calculated using a quadratic objective function, and target deviation CVs can be defined as: 
         [0000]        t ( N   a )={ DV ( La }−target  CV ( N   a )} 
         [0211]    when Na=4 and La=4 the following equations can be obtained: 
         [0000]        t (1 a )={ DV (1 a }−target  CV (1 a )} 
         [0000]        t (2 a )={ DV (2 a }−target  CV (2 a )} 
         [0000]        t (3 a )={ DV (3 a }−target  CV (3 a )} 
         [0000]        t (4 a )={ DV (4 a }−target  CV (4 a )}. 
         [0212]    Using the models and the target terms, a first quadratic objective function that can be used for the nonlinear programming associated with the poly-etch sequence can be defined as: 
         [0000]    
       
         
           
             
               
                 
                   
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         [0213]    and when Na=4 the following simplified equation can be obtained 
         [0000]    
       
         
           
             
               
                 
                   
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         [0214]    and the w ja  are weighting factors. In addition, the manipulated variables MV(la) can have upper and lower limits that can be included as inequality constraints and when (la=4) the following can be established: 
         [0000]        a 1 ≦MV (1 a )≦ b 1 
         [0000]        c 1 ≦MV (2 a )≦ d 1 
         [0000]        e 1 ≦MV (3 a )≦ f 1 
         [0000]        g 1 ≦MV (4 a )≦ h 1  Eq. 2 
         [0215]    where a 1 −h 1  are constants that depend on the equipment constraints. The measured CD and SWA values can be used by the optimizer unit to calculate the MV, and the optimizer can determine the poly-etch recipe by minimizing Eq. (1a) with Eq. (2) using nonlinear programming. For example, the MATLAB optimization toolbox can be used for this simulation. 
         [0216]    In addition, one or more of the CVs can be calculated, and CDs, SWAs, uniformity values, and/or profile changes can be determined for the metal-gate-etch sequence. In some examples, a third number (Nb) of control variables can be established using the following: 
         [0000]        CV ( Nb )= f   Nb   {MV (1 b ), . . .  MV ( Mb− 1),  MV ( Mb ),  DV (1 b ), . . .  DV ( Lb− 1),  DV ( Lb )}+offset Nb    
         [0217]    where Lb, Mb, and Nb are integers that are greater than two. 
         [0218]    For example, when four CVs, six MVs, and four DVs have been identified, four non-linear models with higher order and interaction terms can be defined as: 
         [0000]        CV (1 b )= f   1b   {MV (1 b ),  MV (2 b ),  MV (3 b ),  MV (4 b ),  MV (5 b ),  MV (6 b ),  DV (1 b ),  DV (2 b ),  DV (3 b ),  DV (4 b )}+offset 1b    
         [0000]        CV (2 b )= f   2b   {MV (1 b ),  MV (2 b ),  MV (3 b ),  MV (4 b ),  MV (5 b ),  MV (6 b ),  DV (1 b ),  DV (2 b ),  DV (3 b ),  DV (4 b )}+offset 2b    
         [0000]        CV (3 b )= f   3b   {MV (1 b ),  MV (2 b ),  MV (3 b ),  MV (4 b ),  MV (5 b ),  MV (6 b ),  DV (1 b ),  DV (2 b ),  DV (3 b ),  DV (4 b )}+offset 3b    
         [0000]        CV (4 b )= f   4b   {MV (1 b ),  MV (2 b ),  MV (3 b ),  MV (4 b ),  MV (5 b ),  MV (6 b ),  DV (1 b ),  DV (2 b ),  DV (3 b ),  DV (4 b )}+offset 4b    
         [0219]    In  1225 , optimized process settings can be calculated using a quadratic objective function, and target deviation CVs can be defined as: 
         [0000]        t ( Nb )={ DV ( Lb }−target  CV ( Nb )} 
         [0220]    when Nb=4 and Lb=4 the following equations can be obtained: 
         [0000]        t (1 b )={ DV (1 b }−target  CV (1 b )} 
         [0000]        t (2 b )={ DV (2 b }−target  CV (2 b )} 
         [0000]        t (3 b )={ DV (3 b }−target  CV (3 b )} 
         [0000]        t (4 b )={ DV (4 b }−target  CV (4 b )}. 
         [0221]    Using the models and the target terms, a second quadratic objective function that can be used for the nonlinear programming associated with the metal-gate-etch sequence can be defined as: 
         [0000]    
       
         
           
             
               
                 
                   
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         [0222]    and when Nb=4 the following simplified equation can be obtained 
         [0000]    
       
         
           
             
               
                 
                   
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         [0223]    and the W jb  are weighting factors. In addition, the manipulated variables MV(lb) can have upper and lower limits that can be included as inequality constraints and when (lb=4) the following can be established: 
         [0000]        a 2 ≦MV (1 b )≦ b 2 
         [0000]        c 2 ≦MV (2 b )≦ d 2 
         [0000]        e 2 ≦MV (3 b )≦ f 2 
         [0000]        g 2 ≦MV (4 b )≦ h 2   Eq. 4 
         [0224]    where a 2 −h 2  are constants that depend on the equipment constraints. The measured CD and SWA values can be used by the optimizer unit to calculate the MV, and the optimizer can determine the metal-gate-etch recipe by minimizing Eq. (3a) with Eq. (4) using nonlinear programming. For example, the MATLAB optimization toolbox can be used for this simulation. 
         [0225]    In  1230 , process recipes can be defined for the poly-etch sequence and the metal-gate-etch sequence using one or more of the MVs established by the optimizer, and the process recipes can be adjusted using the new values for the MVs. Nonlinear optimization can be used to treat nonlinear relationships and constraints associated with etch processes to maximize performance of the poly-etch sequence and the metal-gate-etch sequence by adjusting the recipes after each run. 
         [0226]    The IM data can be fed forward to the optimizer to calculate the value of manipulated variables (MV). The nonlinear model formulas associated with each controlled variable (CV) can be used with each CV target value. A quadratic objective function can utilize weighting factors to prioritize each CV term in the objective function, and an optimizer in the MLMIMO can be used to determine etch recipe by minimizing or maximizing the objective function with the constraints of MVs using nonlinear programming. 
         [0227]    In  1235 , one or more of the wafers can be processed using the adjusted recipes. For example, the adjusted recipes can include optimized MVs from the optimizer for the poly-etch sequence and the metal-gate-etch sequence. 
         [0228]    In  1240 , measurement data can be obtained for one or more of the processed wafers. For example, measurements can be made at one or more sites on the wafer. The output CVs can be measured using the IM tool after the poly-etch sequence is performed and/or after the metal-gate-etch sequence is performed. 
         [0229]    In  1245 , the data obtained from the poly-etch sequence and/or the metal-gate-etch sequence can be filtered and/or qualified. 
         [0230]    In  1250 , a process error can be calculated for the poly-etch sequence and the metal-gate-etch sequence. For example, errors (actual outputs minus model outputs) can be calculated for each CV. 
         [0231]    In  1255 , feedback data items can be calculated for the poly-etch sequence and the metal-gate-etch sequence. For example, errors can be used to update the MLMIMO model CVs offsets using an exponentially weighted moving average (EWMA) filter. 
         [0232]    In  1260 , new model offsets can be updated for the poly-etch sequence and/or the metal-gate-etch sequence. These offset values can be provided to the optimizer unit to be used for compensating the disturbance for next run. This offset is used until a new update comes out. This procedure can be performed until the final wafer is processed. 
         [0233]    When send-ahead wafer are used, IM data can be obtained at intermediate points in the poly-etch sequence and the metal-gate-etch sequence. When new and/or additional measurement data, inspection data, and/or evaluation data is required, additional MLMIMO data can be obtained from one or more sites on the wafer. For example, measurement structures, such as periodic gratings, periodic arrays, and/or other periodic structures, on a wafer can be measured at one or more sites. 
         [0234]    In a first alternate embodiment, the first multi-layer etch sequence can further include: a1) transferring a first patterned to a first multi-zone temperature-controlled wafer holder in a first etching chamber using a transfer subsystem coupled to the first etching chamber, wherein the transfer subsystem is configured to prevent an oxide layer from forming on the first patterned during the transferring; a 2) performing a first etch procedure in the first multi-layer etch sequence wherein the first etch procedure is configured to create a first set of patterned layers using the first patterned soft-mask layer, the first set of patterned layers including an etched first hard mask layer having a plurality of first hard mask features, and an etched soft-mask layer having a plurality of etched soft mask features, wherein the first hard-mask layer comprises a silicone-containing anti-reflective coating (ARC) material; a 3) performing a second etch procedure in the first multi-layer etch sequence wherein the second etch procedure is configured to create a first intermediate pattern in a second set of patterned layers using the etched first hard mask layer, the second set of patterned layers including a re-etched first hard mask layer having a plurality of etched first hard mask features, and an etched gate-width control layer having a plurality of gate-width control features, wherein the first intermediate pattern includes at least one second periodic evaluation structure, wherein the gate-width control layer comprises a modified photoresist material; a4) obtaining first evaluation data for the first patterned using the at least one second periodic evaluation structure. 
         [0235]    In a second alternate embodiment, the first multi-layer etch sequence can further include: b1) transferring the first patterned to a second temperature-controlled wafer holder in a second etching chamber using the transfer subsystem coupled to the second etching chamber, wherein the transfer subsystem is configured to prevent an oxide layer from forming on the first patterned during the transferring, the first patterned being transferred after the first multi-layer etch sequence is identified as a verified multi-layer etch sequence; b2) performing a third etch procedure, wherein the third etch procedure is configured to create a second intermediate pattern in a third set of patterned layers using the re-etched first hard mask layer and/or the etched gate-width control layer, the third set of patterned layers including a re-etched gate-width control layer having a plurality of etched gate-width control features, an etched second hard-mask layer (titanium-nitride (TiN)) layer having a plurality of second hard mask features, an etched silicone-nitride (SiN) layer having a plurality of silicone-nitride (SiN) features, an etched amorphous silicone (a-Si) layer having a plurality of amorphous silicone (a-Si) features, and an etched second hard-mask (TEOS) layer having a plurality of second hard-mask features; b3) transferring the first patterned to a third temperature-controlled wafer holder in a first cleaning chamber using the transfer subsystem coupled to the first cleaning chamber, wherein the transfer subsystem is configured to prevent an oxide layer from forming on the first patterned during the transferring; b4) performing a first cleaning procedure in the second multi-layer etch sequence wherein a fourth set of patterned masking layers is created, wherein the fourth set of patterned masking layers comprises a cleaned second hard-mask (TEOS) layer having a plurality of cleaned second hard-mask features, a cleaned silicone-nitride (SiN) layer having a plurality of cleaned silicone-nitride (SiN) features, a cleaned amorphous silicone (a-Si) layer having a plurality of cleaned amorphous silicone (a-Si) features, a cleaned first hard-mask layer (titanium-nitride (TiN)) layer having a plurality of cleaned third hard mask features; b5) transferring the first patterned to a fourth temperature-controlled wafer holder in a fourth etching chamber using the transfer subsystem coupled to the fourth etching chamber, wherein the transfer subsystem is configured to prevent an oxide layer from forming on the first patterned during the transferring; b6) performing a fourth etch procedure in the second multi-layer etch sequence wherein the fourth etch procedure is configured to create a fourth intermediate pattern in a fourth set of patterned layers using the cleaned second hard-mask (TEOS) layer, the cleaned silicone-nitride (SiN) layer, the cleaned amorphous silicone (a-Si) layer, or the cleaned third hard-mask layer (titanium-nitride (TiN)) layer, or any combination thereof, the fourth set of patterned layers including a plurality of gate stacks, each gate stack comprising a metal-containing feature, a titanium-nitride (TiN) feature, an amorphous silicon feature, a silicone-nitride (SiN) feature and a TEOS feature; b7) obtaining additional evaluation data for the first patterned using at least one additional periodic evaluation structure, wherein the fourth intermediate pattern comprising the at least one additional periodic evaluation structure; b8) identifying the second multi-layer etch sequence as a second verified multi-layer etch sequence when the additional evaluation data is less than a first additional multi-etch limit; and b9) performing an additional corrective action when the additional evaluation data is not less than the first additional multi-etch limit. 
         [0236]    In a third alternate embodiment, the second multi-layer etch sequence can include: c1) transferring a first patterned in the second set of patterned wafers to a second temperature-controlled wafer holder in a second etching chamber using the transfer subsystem coupled to the second etching chamber, wherein the transfer subsystem is configured to prevent an oxide layer from forming on the first patterned during the transferring, the second multi-layer etch sequence being performed after the first multi-layer etch sequence is verified, the third etch procedure in the second multi-layer etch sequence, wherein the second set of patterned wafers comprises a plurality of partially-etched wafers; c2) performing a third etch procedure in the second multi-layer etch sequence etching a second set of the additional layers on the first partially-etched wafer using a third etch procedure in the second multi-layer etch sequence, the third etch procedure creating a third set of patterned masking layers by using the intermediate pattern in the second set of masking layers, wherein the second set of the additional layers comprise a TEOS layer, a silicone-nitride (SiN) layer, an amorphous silicon layer and a titanium-nitride (TiN) layer; c3) transferring the first patterned to a third temperature-controlled wafer holder in a first cleaning chamber using the transfer subsystem coupled to the first cleaning chamber, wherein the transfer subsystem is configured to prevent an oxide layer from forming on the first patterned during the transferring; c4) performing a first cleaning procedure wherein a fourth set of patterned masking layers is created; c5) transferring the first patterned to a fourth temperature-controlled wafer holder in a fourth etching chamber using the transfer subsystem coupled to the fourth etching chamber, wherein the transfer subsystem is configured to prevent an oxide layer from forming on the first patterned during the transferring; c6) performing a fourth etch procedure in the second multi-layer etch sequence, wherein the fourth etch procedure is configured to create a fifth set of patterned masking layers using the fourth set of patterned masking layers, the fifth set of patterned masking layers including a plurality of gate stacks, each gate stack comprising a metal-containing feature, a titanium-nitride (TiN) feature, an amorphous silicon feature, a silicone-nitride (SiN) feature and a TEOS feature; c7) obtaining additional evaluation data for the first patterned using at least one additional periodic evaluation structure; c8) identifying the second multi-layer etch sequence as a second verified multi-layer etch sequence when the additional evaluation data is less than a first additional multi-etch limit; and c9) performing an additional corrective action when the additional evaluation data is not less than the first additional multi-etch limit. 
         [0237]    In some embodiments, the historical and/or real-time data can include MLMIMO maps, wafer-related maps, process-related maps, damage-assessment maps, reference maps, measurement maps, prediction maps, risk maps, inspection maps, verification maps, evaluation maps, particle maps, and/or confidence map(s) for one or more wafers. In addition, some MLMIMO procedures may use wafer maps that can include one or more Goodness Of Fit (GOF) maps, one or more thickness maps, one or more gate-related maps, one or more Critical Dimension (CD) maps, one or more CD profile maps, one or more material related maps, one or more structure-related maps, one or more sidewall angle maps, one or more differential width maps, or a combination thereof. 
         [0238]    When wafer maps are created and/or modified, values may not be calculated and/or required for the entire wafer, and a wafer map may include data for one or more sites, one or more chip/dies, one or more different areas, and/or one or more differently shaped areas. For example, a processing chamber may have unique characteristics that may affect the quality of the processing results in certain areas of the wafer. In addition, a manufacturer may allow less accurate process and/or evaluation data for chips/dies in one or more regions of the wafer to maximize yield. When a value in a map is close to a limit, the confidence value may be lower than when the value in a map is not close to a limit. In addition, the accuracy values can be weighted for different chips/dies and/or different areas of the wafer. For example, a higher confidence weight can be assigned to the accuracy calculations and/or accuracy data associated with one or more of the previously used evaluation sites. 
         [0239]    In addition, process result, measurement, inspection, verification, evaluation, and/or prediction maps associated with one or more processes may be used to calculate a confidence map for a wafer. For example, values from another map may be used as weighting factors. 
         [0240]    Although only certain embodiments of this invention have been described in detail above, those skilled in the art will readily appreciate that many modifications are possible in the embodiments without materially departing from the novel teachings and advantages of this invention. Accordingly, all such modifications are intended to be included within the scope of this invention. 
         [0241]    Thus, the description is not intended to limit the invention and the configuration, operation, and behavior of the present invention has been described with the understanding that modifications and variations of the embodiments are possible, given the level of detail present herein. Accordingly, the preceding detailed description is not mean or intended to, in any way, limit the invention—rather the scope of the invention is defined by the appended claims.