The Experts below are selected from a list of 69753 Experts worldwide ranked by ideXlab platform
Pingsha Dong - One of the best experts on this subject based on the ideXlab platform.
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a selectively coupled shear localization model for friction stir welding Process Window estimation
International Journal of Machine Tools & Manufacture, 2017Co-Authors: Xianjun Pei, Pingsha DongAbstract:Abstract This paper presents a novel computational procedure specifically aimed at gaining modeling capabilities for estimating friction stir welding (FSW) Process Window. The proposed model first combines a three-dimensional (3D) transient heating effects with a one-dimensional (1D) shear localization Process leading to shear band development within one pin revolution. The resulting shear band width is then compared with the minimum material flow layer thickness required for satisfying both mass conservation and velocity continuity conditions in a two-dimensional (2D) planar material flow around the tool pin. If the shear band width formed within one pin revolution is equal or larger than the minimum material flow layer thickness, conditions for developing a quality weld prevail. Otherwise, conditions for developing various forms of weld defects can be identified, depending upon shear localization behavior predicted. Specifically, the proposed model is shown capable of elucidating some of the major defect formation mechanisms observed in experiments, such as “lack of fill”, “abnormal stirring”, “surface galling”, and “excessive flash”, etc. As a result, the selectively-coupled shear localization model enables a theoretical estimation of FSW Process Window typically represented as a regime of welding speed and stir tool rotation speed combination for a given application, within which acceptable weld quality should be expected. Its application in FSW Process Window estimation is demonstrated by considering three types of aluminum alloys. In all cases, good agreements are achieved between model-estimated and experimentally-determined Process Windows. In addition, the proposed model also enables a theoretical estimation of optimum welding parameters within an established Process Window, e.g., for achieving maximum welding speed while maintaining good weld quality.
Xianjun Pei - One of the best experts on this subject based on the ideXlab platform.
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a selectively coupled shear localization model for friction stir welding Process Window estimation
International Journal of Machine Tools & Manufacture, 2017Co-Authors: Xianjun Pei, Pingsha DongAbstract:Abstract This paper presents a novel computational procedure specifically aimed at gaining modeling capabilities for estimating friction stir welding (FSW) Process Window. The proposed model first combines a three-dimensional (3D) transient heating effects with a one-dimensional (1D) shear localization Process leading to shear band development within one pin revolution. The resulting shear band width is then compared with the minimum material flow layer thickness required for satisfying both mass conservation and velocity continuity conditions in a two-dimensional (2D) planar material flow around the tool pin. If the shear band width formed within one pin revolution is equal or larger than the minimum material flow layer thickness, conditions for developing a quality weld prevail. Otherwise, conditions for developing various forms of weld defects can be identified, depending upon shear localization behavior predicted. Specifically, the proposed model is shown capable of elucidating some of the major defect formation mechanisms observed in experiments, such as “lack of fill”, “abnormal stirring”, “surface galling”, and “excessive flash”, etc. As a result, the selectively-coupled shear localization model enables a theoretical estimation of FSW Process Window typically represented as a regime of welding speed and stir tool rotation speed combination for a given application, within which acceptable weld quality should be expected. Its application in FSW Process Window estimation is demonstrated by considering three types of aluminum alloys. In all cases, good agreements are achieved between model-estimated and experimentally-determined Process Windows. In addition, the proposed model also enables a theoretical estimation of optimum welding parameters within an established Process Window, e.g., for achieving maximum welding speed while maintaining good weld quality.
Shih-chin Gong - One of the best experts on this subject based on the ideXlab platform.
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Effects of pressure sensor dimensions on Process Window of membrane thickness
Sensors and Actuators A-physical, 2004Co-Authors: Shih-chin GongAbstract:In some applications the purchase price of the pressure sensor can be prime consideration in the pressure sensor selection Process. It is important to design a pressure sensor with a competitive price. The low-cost pressure sensor requires minimum dimensions of pressure sensor, while maintains allowed Process Window in fabrication. The cost of pressure sensor depends on pressure sensor size and Process yield. In order to design low-cost pressure sensors, it is necessary to understand the Process Window. The membrane thickness of pressure sensor is a key parameter in fabrication. The Process Window of membrane thickness refers to the amount of variability that a Process can tolerate while producing results that are acceptable. A smaller Process Window of membrane thickness has tighter acceptable variations of membrane thickness, and the suitable Process Window size is demanded in mass production. The effects of pressure sensor dimensions on the Process Window of the membrane thickness were studied in this paper. High-sensitivity pressure sensors have high resolution, small burst pressure, and small Process Window. The effect of the doping concentrations of resistors on the Process Window is also included. To decrease the temperature effect, the doping concentration of resistors was increased. The increasing doping concentration of the resistor will decrease the Process Window significantly.
Masayuki Nogami - One of the best experts on this subject based on the ideXlab platform.
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Process Window for the synthesis of ag wires through polyol Process
Materials Chemistry and Physics, 2009Co-Authors: Yuchieh Lu, Kansen Chou, Masayuki NogamiAbstract:Abstract A Process Window for the synthesis of Ag wires through the polyol Process was established, in which long and uniform size of silver wires is obtained. The formation of decahedral seeds (leading to the formation of wires) is in competition with ordinary seeds (becoming spherical colloids) and heterogeneous nucleation and deposition on vessel walls. All of the various Processes are in turn influenced by the supply rate of silver from reduction reactions. Adding silver nuclei before the reduction reaction could effectively decrease the wire diameter.
Kevin Lucas - One of the best experts on this subject based on the ideXlab platform.
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Hybrid resist model to enhance continuous Process Window model for OPC
Photomask and Next-Generation Lithography Mask Technology XV, 2008Co-Authors: Qiaolin Zhang, Kevin LucasAbstract:As the semiconductor industry enters the 45nm node and beyond, the tolerable lithography Process Window significantly shrinks due to the decreasing k 1 factor and increasing lens NA required to meet product shrink goals. The usable depth of focus at the 45nm node for critical layer is less than 200nm and for the 32nm node it will approach 100nm. Consequently, Process Window aware Optical Proximity Correction (OPC) and Lithography Rule Check (LRC) become crucial to ensure the robustness of OPC to focus and dose variation. An accurately calibrated continuous Process Window model is the corner stone for successful Process variation aware OPC and LRC. For ease of use, this calibrated model should be a continuous function of defocus and dose and able to interpolate and extrapolate in the usable Process Window. Lithographic proximity effects have an optical component and a resist component. As state of the art OPC simulation tool is capable of precise and fast optical simulation, however its treatment of chemical amplified resist effects is relatively crude and does not capture the complex behavior during acid & quencher reaction, diffusion and development. This in turn causes difficulties for a continuous Process Window model where the resist component plays an important role. We proposed a hybrid resist model, which is a superposition of a traditional OPC chemical amplified resist model and a first order resist bias model. Using Synopsys' OPC modeling software package-ProGen, we incorporated this hybrid resist model into the continuous Process Window (PW) modeling module, and very good model calibration performance was achieved.
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Continuous Process Window modeling for Process variation aware OPC and lithography verification
Design for Manufacturability through Design-Process Integration II, 2008Co-Authors: Qiaolin Zhang, Yunqiang Zhang, Qiliang Yan, Kevin LucasAbstract:As the semiconductor industry moves to the 45nm node and beyond, the tolerable lithography Process Window significantly shrinks due to the combined use of high NA and low k 1 factor. This is exacerbated by the fact that the usable depth of focus at 45nm node for critical layer is 200nm or less. Traditional Optical Proximity Correction (OPC) only computes the optimal pattern layout to optimize its patterning at nominal Process condition (nominal defocus and nominal exposure dose) according to an OPC model calibrated at this nominal condition, and this may put the post-OPC layout at nonnegligible patterning risk due to the inevitable Process variation (defocus and dose variations). With a little sacrifice at the nominal condition, Process variation aware OPC can greatly enhance the robustness of post-OPC layout patterning in the presence of defocus and dose variation. There is also an increasing demand for through Process Window lithography verification for post-OPC circuit layout. The corner stone for successful Process variation aware OPC and lithography verification is an accurately calibrated continuous Process Window model which is a continuous function of defocus and dose. This calibrated model needs to be able to interpolate and extrapolate in the usable Process Window. Based on Synopsys' OPC modeling software package ProGen, we developed and implemented a novel methodology for continuous Process Window (PW) model, which has two continuous adjustable Process parameters: defocus and dose. The calibration of this continuous PW model was performed in a single calibration Process using silicon measurement at nominal condition and off-focus-off-dose conditions which are sparsely sampled within the measured entire focus exposure matrix (FEM). The silicon data at the off-focus-off-dose conditions not used for model calibration was utilized to validate the accuracy and stability of PW model during model interpolation and extrapolation. We demonstrated this novel continuous PW modeling approach can achieve very good performance both at nominal condition and at interpolated or extrapolated off-focus-off-dose conditions.
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Process Window OPC verification: dry versus immersion lithography for the 65nm node
Optical Microlithography XIX, 2006Co-Authors: Amandine Borjon, Kevin Lucas, Jerome Belledent, Yorick Trouiller, Christophe Couderc, Frank Sundermann, Jean-christophe Urbani, Yves Rody, Christian Gardin, F. FoussadierAbstract:Ensuring robust patterning after OPC is becoming more and more difficult due to the continuous reduction of layout dimensions and diminishing Process Windows associated with each successive lithographic generation. Lithographers must guarantee high imaging fidelity throughout the entire range of normal Process variations. To verify the printability of a design across Process Window, compact optical models similar to those used for standard OPC are used. These models are calibrated from experimental data measured at the limits of the Process Window. They are then applied to the design to predict potential printing failures. This approach has been widely used for dry lithography. With the emergence of immersion lithography in production in the IC industry, the predictability of this approach has to be validated on this new lithographic Process. In this paper, a comparison between the dry lithography Process model and the immersion lithography Process model is presented for the Poly layer at 65 nm node patterning. Examples of specific failure predictions obtained separately with the two Processes are compared with experimental results. A comparison in terms of Process performance will also be a part of this study.
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Process Window OPC Verification: Dry versus Immersion Lithography for the 65 nm node
2006Co-Authors: Amandine Borjon, Kevin Lucas, Jerome Belledent, Yorick Trouiller, Christophe Couderc, Frank Sundermann, Jean-christophe Urbani, Yves Rody, Christian Gardin, F. FoussadierAbstract:Ensuring robust patterning after OPC is becoming more and more difficult due to the continuous reduction of layout dimensions and diminishing Process Windows associated with each successive lithographic generation. Lithographers must guarantee high imaging fidelity throughout the entire range of normal Process variations. To verify the printability of a design across Process Window, compact optical models similar to those used for standard OPC are used. These models are calibrated from experimental data measured at the limits of the Process Window. They are then applied to the design to predict potential printing failures. This approach has been widely used for dry lithography. With the emergence of immersion lithography in production in the IC industry, the predictability of this approach has to be validated on this new lithographic Process. In this paper, a comparison between the dry lithography Process model and the immersion lithography Process model is presented for the Poly layer at 65 nm node patterning. Examples of specific failure predictions obtained separately with the two Processes are compared with experimental results. A comparison in terms of Process performance will also be a part of this study.
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High Accuracy 65nm OPC Verification: Full Process Window Model vs. Critical Failure ORC
2005Co-Authors: Amandine Borjon, Kevin Lucas, Shumay Shang, Jerome Belledent, Christophe Couderc, Yves Rody, Olivier Toublan, Corinne Miramond, Kyle Patterson, Frank SundermannAbstract:It is becoming more and more difficult to ensure robust patterning after OPC due to the continuous reduction of layout dimensions and diminishing Process Windows associated with each successive lithographic generation. Lithographers must guarantee high imaging fidelity throughout the entire range of normal Process variations. The techniques of Mask Rule Checking (MRC) and Optical Rule Checking (ORC) have become mandatory tools for ensuring that OPC delivers robust patterning. However the first method relies on geometrical checks and the second one is based on a model built at best Process conditions. Thus those techniques do not have the ability to address all potential printing errors throughout the Process Window (PW). To address this issue, a technique known as Critical Failure ORC (CFORC) was introduced that uses optical parameters from aerial image simulations. In CFORC, a numerical model is used to correlate these optical parameters with experimental data taken throughout the Process Window to predict printing errors. This method has proven its efficiency for detecting potential printing issues through the entire Process Window [1]. However this analytical method is based on optical parameters extracted via an optical model built at single Process conditions. It is reasonable to expect that a verification method involving optical models built from several points throughout PW would provide more accurate predictions of printing errors for complex features. To verify this approach, compact optical models similar to those used for standard OPC were built and calibrated with experimental data measured at the PW limits. This model is then applied to various test patterns to predict potential printing errors. In this paper, a comparison between these two approaches is presented for the poly layer at 65 nm node patterning. Examples of specific failure predictions obtained separately with the two techniques are compared with experimental results. The details of implementing these two techniques on full product layouts are also included in this study.
