The Experts below are selected from a list of 95193 Experts worldwide ranked by ideXlab platform
Luigi Colalongo - One of the best experts on this subject based on the ideXlab platform.
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A Charge-Based OTFT Model for Circuit Simulation
IEEE Transactions on Electron Devices, 2009Co-Authors: Fabrizio Torricelli, Z.m. Kovacs-vajna, Luigi ColalongoAbstract:In this paper, a mathematical model for the dc/dynamic current of organic thin-film transistors is proposed. The model is based on the variable-range hopping transport theory, i.e., thermally activated tunneling of carriers between localized states, and the mathematical expression of the current is formulated by means of the channel accumulation charge. It accurately accounts for below-threshold, linear, and saturation operating conditions via a Single Formulation, and does not require the explicit definition of the threshold and saturation voltages. Basing on the charge control approach, the dc model is straightforwardly generalized to dynamic conditions; the resulting mathematical expressions are simple and suitable for CAD applications.
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A charge control analytical model for organic thin film transistors
Applied Physics Letters, 2008Co-Authors: Fabrizio Torricelli, Z.m. Kovacs-vajna, Luigi ColalongoAbstract:In this paper, a mathematical model for the dc current of organic thin film transistors is proposed. The model is based on the variable range hopping transport theory, while the mathematical expression of the current is formulated by means of the channel accumulation charge. It accurately accounts for below-threshold, linear, and saturation operating conditions via a Single Formulation and it does not require the explicit definition of the threshold and saturation voltages. Furthermore, thanks to the charge control approach, it is straightforwardly generalizable to dynamic behavior.
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Organic thin film transistors: a DC/dynamic analytical model
Solid-State Electronics, 2005Co-Authors: E. Calvetti, Luigi Colalongo, Z.m. Kovacs-vajnaAbstract:In this paper a new DC/dynamic analytical model for organic thin-film transistors (OTFTs) is presented. The model is based on the variable range hopping theory, i.e. thermally activated tunneling of carriers between localized states. It accurately accounts for below-threshold, linear, and saturation operating conditions via a Single Formulation. Furthermore, the model does not require the explicit definition of the threshold and saturation voltages as input parameters, which are rather ambiguously defined, and it is suitable for CAD applications.
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Organic thin film transistors: an analytical model for circuit simulation
2004 IEEE Region 10 Conference TENCON 2004., 1Co-Authors: E. Calvetti, Luigi Colalongo, Z.m.k. VajnaAbstract:In this paper a new DC and dynamic model for organic thin film transistors is presented. The model is based on the variable range hopping theory and the dynamic behavior of the organic thin film transistor has been derived following the charge control approach. The model accounts for all regions of operation via a Single Formulation, and it is suitable for the implementation in a circuit simulator as SPICE. Furthermore, a small-signal equivalent circuit is proposed.
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Organic thin film transistors: a DC model for circuit simulation
Proceedings of the 30th European Solid-State Circuits Conference (IEEE Cat. No.04EX850), 1Co-Authors: Luigi Colalongo, F. Romano, Z.m.k. VajnaAbstract:In this paper, a new analytical model for the DC current of organic thin-film transistors is presented. The model is based on the variable range hopping theory, i.e. thermally activated tunneling of carriers between localized states. It accurately accounts for below-threshold, linear and saturation operating conditions via a Single Formulation. Furthermore, the model does not require the explicit definition of the threshold and saturation voltages as input parameters, which are rather ambiguously defined. The model is also suitable for CAD applications.
Francesco Montomoli - One of the best experts on this subject based on the ideXlab platform.
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A Single Formulation for Uncertainty Propagation in Turbomachinery: SAMBA PC
Journal of Turbomachinery, 2017Co-Authors: Richard Ahlfeld, Francesco MontomoliAbstract:This work newly proposes an uncertainty quantification (UQ) method named sparse approximation of moment-based arbitrary polynomial chaos (SAMBA PC) that offers a Single solution to many current problems in turbomachinery applications. At the moment, every specific case is characterized by a variety of different input types such as histograms (from experimental data), normal probability density functions (PDFs) (design rules) or fat tailed PDFs (for rare events). Thus, the application of UQ requires the adaptation of ad hoc methods for each individual case. A second problem is that parametric PDFs have to be determined for all inputs. This is difficult if only few samples are available. In gas turbines, however, the collection of statistical information is difficult, expensive, and having scarce information is the norm. A third critical limitation is that if using nonintrusive polynomial chaos (NIPC) methods, the number of required simulations grows exponentially with increasing numbers of input uncertainties: the so-called “curse of dimensionality.” It is shown that the fitting of parametric PDFs to small data sets can lead to large bias and the direct use of the available data is more accurate. This is done by propagating uncertainty through several test functions and the computational fluid dynamics (CFD) simulation of a diffuser, highlighting the impact of different PDF fittings on the output. From the results, it is concluded that the direct propagation of the experimental data set is preferable to the fit of parametric distributions if data is scarce. Thus, the suggested method offers an alternative to the maximum entropy theorem to handle scarce data. SAMBA simplifies the mathematical procedure for many different input types by basing the polynomial expansion on moments. Its moment-based expansion automatically takes care of arbitrary combinations of different input data. It is also numerically efficient compared to other UQ implementations. The relationship between the number of random variables and number of simulation is linear (only 21 simulations for ten input random variables are required). It is shown in this paper that SAMBA's algorithm can propagate a high number of input distributions through a set of nonlinear analytic test functions. Doing this, the code needs a very small number of simulations and preserve a 5% error margin. SAMBA's flexibility to handle different forms of input distributions and a high number of input variables is shown on a low-pressure turbine (LPT) blade-based on H2 profile. The relative importance of manufacturing errors in different location of the blade is analyzed.
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A Single Formulation for Uncertainty Propagation in Turbomachinery: SAMBA PC
Volume 2C: Turbomachinery, 2016Co-Authors: Richard Ahlfeld, Francesco MontomoliAbstract:This work newly proposes an uncertainty quantification method named SAMBA PC (Sparse Approximation of Moment-Based Arbitrary Polynomial Chaos) that offers a Single solution to many current problems in turbomachinery applications. At the moment every specific case is characterized by a variety of different input types such as histograms (from experimental data), normal PDFs (design rules) or fat tailed PDFs (for rare events). Thus, the application of UQ requires the adaptation of ad hoc methods for each individual case. A second problem is that parametric PDFs have to be determined for all inputs. This is difficult if only few samples are available. In gas turbines, however, the collection of statistical information is difficult, expensive and having scarce information is the norm. A third critical limitation is that if using Non-Intrusive Polynomial Chaos methods the number of required simulations grows exponentially with increasing numbers of input uncertainties: the so-called ‘curse of dimensionality’. In this work it is shown that the fitting of parametric PDFs to small data sets can lead to large bias and the direct use of the available data is more accurate. This is done by propagating uncertainty through several test functions and the CFD simulation of a diffuser, highlighting the impact of different PDF fittings on the output. From the results it is concluded that the direct propagation of the experimental data set is preferable to the fit of parametric distributions if data is scarce. Thus, the suggested method offers an alternative to the maximum entropy theorem to handle scarce data. SAMBA simplifies the mathematical procedure for many different input types by basing the polynomial expansion on moments. Its moment-based expansion automatically takes care of arbitrary combinations of different input data. SAMBA is also numerically efficient compared to other UQ implementations. The relationship between the number of random variables and number of simulation is linear (only 21 simulations for 10 input random variables are required). It is shown that SAMBA’s algorithm can propagate a high number of input distributions through a set of nonlinear analytic test functions. Doing this the code needs a very small number of simulations and preserves a 5% error margin. SAMBA’s flexibility to handle different forms of input distributions and a high number of input variables is shown on a low pressure turbine blade based on H2 profile. The relative importance of manufacturing errors in different location of the blade is analyzed.
Richard Ahlfeld - One of the best experts on this subject based on the ideXlab platform.
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A Single Formulation for Uncertainty Propagation in Turbomachinery: SAMBA PC
Journal of Turbomachinery, 2017Co-Authors: Richard Ahlfeld, Francesco MontomoliAbstract:This work newly proposes an uncertainty quantification (UQ) method named sparse approximation of moment-based arbitrary polynomial chaos (SAMBA PC) that offers a Single solution to many current problems in turbomachinery applications. At the moment, every specific case is characterized by a variety of different input types such as histograms (from experimental data), normal probability density functions (PDFs) (design rules) or fat tailed PDFs (for rare events). Thus, the application of UQ requires the adaptation of ad hoc methods for each individual case. A second problem is that parametric PDFs have to be determined for all inputs. This is difficult if only few samples are available. In gas turbines, however, the collection of statistical information is difficult, expensive, and having scarce information is the norm. A third critical limitation is that if using nonintrusive polynomial chaos (NIPC) methods, the number of required simulations grows exponentially with increasing numbers of input uncertainties: the so-called “curse of dimensionality.” It is shown that the fitting of parametric PDFs to small data sets can lead to large bias and the direct use of the available data is more accurate. This is done by propagating uncertainty through several test functions and the computational fluid dynamics (CFD) simulation of a diffuser, highlighting the impact of different PDF fittings on the output. From the results, it is concluded that the direct propagation of the experimental data set is preferable to the fit of parametric distributions if data is scarce. Thus, the suggested method offers an alternative to the maximum entropy theorem to handle scarce data. SAMBA simplifies the mathematical procedure for many different input types by basing the polynomial expansion on moments. Its moment-based expansion automatically takes care of arbitrary combinations of different input data. It is also numerically efficient compared to other UQ implementations. The relationship between the number of random variables and number of simulation is linear (only 21 simulations for ten input random variables are required). It is shown in this paper that SAMBA's algorithm can propagate a high number of input distributions through a set of nonlinear analytic test functions. Doing this, the code needs a very small number of simulations and preserve a 5% error margin. SAMBA's flexibility to handle different forms of input distributions and a high number of input variables is shown on a low-pressure turbine (LPT) blade-based on H2 profile. The relative importance of manufacturing errors in different location of the blade is analyzed.
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A Single Formulation for Uncertainty Propagation in Turbomachinery: SAMBA PC
Volume 2C: Turbomachinery, 2016Co-Authors: Richard Ahlfeld, Francesco MontomoliAbstract:This work newly proposes an uncertainty quantification method named SAMBA PC (Sparse Approximation of Moment-Based Arbitrary Polynomial Chaos) that offers a Single solution to many current problems in turbomachinery applications. At the moment every specific case is characterized by a variety of different input types such as histograms (from experimental data), normal PDFs (design rules) or fat tailed PDFs (for rare events). Thus, the application of UQ requires the adaptation of ad hoc methods for each individual case. A second problem is that parametric PDFs have to be determined for all inputs. This is difficult if only few samples are available. In gas turbines, however, the collection of statistical information is difficult, expensive and having scarce information is the norm. A third critical limitation is that if using Non-Intrusive Polynomial Chaos methods the number of required simulations grows exponentially with increasing numbers of input uncertainties: the so-called ‘curse of dimensionality’. In this work it is shown that the fitting of parametric PDFs to small data sets can lead to large bias and the direct use of the available data is more accurate. This is done by propagating uncertainty through several test functions and the CFD simulation of a diffuser, highlighting the impact of different PDF fittings on the output. From the results it is concluded that the direct propagation of the experimental data set is preferable to the fit of parametric distributions if data is scarce. Thus, the suggested method offers an alternative to the maximum entropy theorem to handle scarce data. SAMBA simplifies the mathematical procedure for many different input types by basing the polynomial expansion on moments. Its moment-based expansion automatically takes care of arbitrary combinations of different input data. SAMBA is also numerically efficient compared to other UQ implementations. The relationship between the number of random variables and number of simulation is linear (only 21 simulations for 10 input random variables are required). It is shown that SAMBA’s algorithm can propagate a high number of input distributions through a set of nonlinear analytic test functions. Doing this the code needs a very small number of simulations and preserves a 5% error margin. SAMBA’s flexibility to handle different forms of input distributions and a high number of input variables is shown on a low pressure turbine blade based on H2 profile. The relative importance of manufacturing errors in different location of the blade is analyzed.
Fabrizio Torricelli - One of the best experts on this subject based on the ideXlab platform.
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A Charge-Based OTFT Model for Circuit Simulation
IEEE Transactions on Electron Devices, 2009Co-Authors: Fabrizio Torricelli, Z.m. Kovacs-vajna, Luigi ColalongoAbstract:In this paper, a mathematical model for the dc/dynamic current of organic thin-film transistors is proposed. The model is based on the variable-range hopping transport theory, i.e., thermally activated tunneling of carriers between localized states, and the mathematical expression of the current is formulated by means of the channel accumulation charge. It accurately accounts for below-threshold, linear, and saturation operating conditions via a Single Formulation, and does not require the explicit definition of the threshold and saturation voltages. Basing on the charge control approach, the dc model is straightforwardly generalized to dynamic conditions; the resulting mathematical expressions are simple and suitable for CAD applications.
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A charge control analytical model for organic thin film transistors
Applied Physics Letters, 2008Co-Authors: Fabrizio Torricelli, Z.m. Kovacs-vajna, Luigi ColalongoAbstract:In this paper, a mathematical model for the dc current of organic thin film transistors is proposed. The model is based on the variable range hopping transport theory, while the mathematical expression of the current is formulated by means of the channel accumulation charge. It accurately accounts for below-threshold, linear, and saturation operating conditions via a Single Formulation and it does not require the explicit definition of the threshold and saturation voltages. Furthermore, thanks to the charge control approach, it is straightforwardly generalizable to dynamic behavior.
Z.m. Kovacs-vajna - One of the best experts on this subject based on the ideXlab platform.
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A Charge-Based OTFT Model for Circuit Simulation
IEEE Transactions on Electron Devices, 2009Co-Authors: Fabrizio Torricelli, Z.m. Kovacs-vajna, Luigi ColalongoAbstract:In this paper, a mathematical model for the dc/dynamic current of organic thin-film transistors is proposed. The model is based on the variable-range hopping transport theory, i.e., thermally activated tunneling of carriers between localized states, and the mathematical expression of the current is formulated by means of the channel accumulation charge. It accurately accounts for below-threshold, linear, and saturation operating conditions via a Single Formulation, and does not require the explicit definition of the threshold and saturation voltages. Basing on the charge control approach, the dc model is straightforwardly generalized to dynamic conditions; the resulting mathematical expressions are simple and suitable for CAD applications.
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A charge control analytical model for organic thin film transistors
Applied Physics Letters, 2008Co-Authors: Fabrizio Torricelli, Z.m. Kovacs-vajna, Luigi ColalongoAbstract:In this paper, a mathematical model for the dc current of organic thin film transistors is proposed. The model is based on the variable range hopping transport theory, while the mathematical expression of the current is formulated by means of the channel accumulation charge. It accurately accounts for below-threshold, linear, and saturation operating conditions via a Single Formulation and it does not require the explicit definition of the threshold and saturation voltages. Furthermore, thanks to the charge control approach, it is straightforwardly generalizable to dynamic behavior.
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Organic thin film transistors: a DC/dynamic analytical model
Solid-State Electronics, 2005Co-Authors: E. Calvetti, Luigi Colalongo, Z.m. Kovacs-vajnaAbstract:In this paper a new DC/dynamic analytical model for organic thin-film transistors (OTFTs) is presented. The model is based on the variable range hopping theory, i.e. thermally activated tunneling of carriers between localized states. It accurately accounts for below-threshold, linear, and saturation operating conditions via a Single Formulation. Furthermore, the model does not require the explicit definition of the threshold and saturation voltages as input parameters, which are rather ambiguously defined, and it is suitable for CAD applications.
