Microwave frequency small‐signal equivalent circuit parameter extraction for AlInN/GaN MOSHEMT

This article presents an accurate and efficient extraction procedure for microwave frequency small‐signal equivalent circuit parameters of AlInN/GaN metal‐oxide‐semiconductor high electron mobility transistor (MOSHEMT). The parameter extraction technique is based on the combination of conventional and optimization methods using the computer‐aided modeling approach. The S‐, Y‐, and Z‐ parameters of the model are extracted from extensive dynamic AC simulation of the proposed device. From the extracted Y‐ and Z‐ parameters the pad capacitances, parasitic inductances and resistances are extracted by operating the device at low and high frequency pinch‐off condition depending upon requirement. Then, the intrinsic elements are extracted quasi analytically by de‐embedding the extrinsic parameters. S‐parameter simulation of the developed small‐signal equivalent circuit model is carried out and is compared with TCAD device simulation results to validate the model. The gradient based optimization approach is used to optimize the small‐signal parameters to minimize the error between developed SSEC model and device simulation based s‐parameters. The microwave characteristics of optimized SSEC model is carried out (f_T = 169 GHz and f_max = 182 GHz) and compared with experimental data available from literature to validate the model.     

Bayesian inference‐based small‐signal modeling technique for GaN HEMTs

A new modeling methodology for gallium nitride (GaN) high‐electron‐mobility transistors (HEMTs) based on Bayesian inference theory, a core method of machine learning, is presented in this article. Gaussian distribution kernel functions are utilized for the Bayesian‐based modeling technique. A new small‐signal model of a GaN HEMT device is proposed based on combining a machine learning technique with a conventional equivalent circuit model topology. This new modeling approach takes advantage of machine learning methods while retaining the physical interpretation inherent in the equivalent circuit topology. The new small‐signal model is tested and validated in this article, and excellent agreement is obtained between the extracted model and the experimental data in the form of dc I–V curves and S‐parameters. This verification is carried out on an 8 × 125 μm GaN HEMT with a 0.25 μm gate feature size, over a wide range of operating conditions. The dc I–V curves from an artificial neural network (ANN) model are also provided and compared with the proposed new model, with the latter displaying a more accurate prediction benefiting, in particular, from the absence of overfitting that may be observed in the ANN‐derived I–V curves.     

Blue‐to‐red electroluminescence from organic light‐emitting field‐effect transistor using various organic semiconductor materials

Abstract— We succeeded in observing visible bright electroluminescence from blue to red in an organic field‐effect‐transistor structure. In particular, tetraphenylpyrene (TPPy) demonstrated a high photoluminescence efficiency of φ_PL ～ 70% and a maximum electroluminescence efficiency of η_EL ～ 10^?2%. The electroluminescence efficiency (ηEL) was enhanced by using a short source‐to‐drain channel length (L_SD < 1 μm). In addition, doping the TPPy layer with highly fluorescent rubrene molecules led to an #PL of ～100% and a maximum ηEL of 0.8%.     

Machine learning technique based extremely broadband small‐signal behavioral model for InP DHBTs

A novel modeling methodology for indium phosphide (InP) double heterojunction bipolar transistors (DHBTs) based on the theory of Bayesian inference, a well‐known method from the field of machine learning, is presented in this article. An extremely broadband small‐signal behavioral model, from 200 MHz to 325 GHz, is built, tested, and validated in this work, with excellent agreement obtained between the extracted model and the experimental data in the form of S‐parameters. A single finger InP DHBT device, with emitter size of 0.5 × 5 μm² exhibiting an ft of over 550 GHz, is used in the verification example. Taking advantage of regression techniques based on machine learning concepts, the proposed black‐box behavioral model can more accurately predict the behavior of the device compared with the traditional equivalent circuit modeling method. Several sets of measured vs modeled data are shown, indicating the efficacy of the method.     

Investigation on the non‐quasi‐static effect implementation for millimeter‐wave FET models

The present article analyzes in detail different intrinsic small‐signal models for transistors. Particular attention is devoted to the non‐quasi‐static effects, which play a crucial role at microwave and millimeter‐wave frequencies. The advantages and disadvantages of these different equivalent circuit topologies are analyzed from both theoretical and experimental standpoints. This study clearly proves that best choice among these model representations depends on the specific device technology besides the investigated frequency range. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010.     

Direct extraction method of HEMT switch small‐signal model with multiparasitic capacitive current path

It has been found that the analytical extraction methods cannot be applied to the usual test structure of the switch high electron‐mobility transistor (HEMT) with a large‐value gate grounded resistor. The significant effect of the precise multicapacitive current path on switch model precision has also been found. The multicapacitive current path here is different from the seemingly similar hypothesis proposed for the distributed parasitic effects at high frequencies (eg, D‐band). In fact, for switch based HEMT, it is important to distinguish between the capacitive current paths accurately even at relatively low frequencies. Due to the existing of the large gate resistance, the usual capacitance mix decreases the accuracy of the switch model significantly. Thus an analytical method has been developed to calculate parasitic capacitances (the capacitance to ground and the interelectrode capacitance) through full‐wave electromagnetic analysis. For practical applications and further verification, the whole HEMT switch small‐signal models and the direct extraction methods are presented. The simulated results fit well with the measurements up to 40 GHz.     

Effect of guard‐ring on the DC and high‐frequency performance of deep‐submicrometer metal oxide semiconductor field effect transistor

The influence of guard‐ring (GR) on the direct current (DC) and high‐frequency performance of deep‐submicrometer metal oxide semiconductor field effect transistors (MOSFETs) is investigated in this study. MOSFETs with four different GRs are fabricated using 90 nm complementary metal oxide semiconductor (CMOS) process, and a detailed comparative study on their device performances is performed. A united DC and small signal equivalent circuit model that takes into the effect of GR is developed. A set of simple, but efficient formulas provide a bidirectional bridge for the S parameters transformation between devices with different GRs. The corresponding model parameters for MOSFETs with different GRs are determined from S parameter on‐wafer measurement up to 40 GHz. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:259–267, 2014.     

Complete parasitic‐capacitance‐shell extraction of high‐frequency switch‐HEMT equivalent‐circuit model

This paper presents a new solution to a particular problem of high electron‐mobility transistor (HEMT) equivalent‐circuit modeling, that is, complete parasitic‐capacitance‐shell extraction of high‐frequency single‐gate and dual‐gate switch‐based HEMTs, which is very important to the accuracy of high‐frequency HEMT switch models, but not important in the conventional common‐source HEMT modeling for amplifier‐applications. A full‐wave electromagnetic (EM) analysis based method is proposed to analytically extract the complete parasitic‐capacitance‐shell of single‐gate and dual‐gate switch‐based HEMTs. All the 6 parasitic capacitances of the single‐gate switch‐based HEMT and all the 10 parasitic capacitances of the dual‐gate switch‐based HEMT are extracted by linear equations. No resistance parameter is needed to calculate the capacitance‐to‐ground and the interelectrode‐capacitance, and for the first time, all the 10 parasitic capacitances of the dual‐gate switch‐based HEMT are completely considered and analytically extracted. Then, a consistent and systematic modeling procedure of single‐gate and dual‐gate switch‐based HEMT is verified. With the complete parasitic‐capacitance‐shells extracted, the accurate intrinsic model of the single‐gate HEMT can be directly embedded into the parasitic‐shell of the dual‐gate HEMT. The predicted scattering parameters of the single‐gate and dual‐gate series switches fit well with the measurements up to 40 GHz, and accurate linear scalability are also found.     

Hybrid small‐signal model parameter extraction of GaN HEMTs on Si and SiC substrates based on global optimization

This article presents efficient parameters extraction procedure applied to GaN High electron mobility transistor (HEMT) on Si and SiC substrates. The method depends on combined technique of direct and optimization‐based to extract the elements of small‐signal equivalent circuit model (SSECM) for GaN‐on‐Si HEMT. The same model has been also applied to GaN‐on‐SiC substrate to evaluate the effect of the substrates on the model parameters. The quality of extraction was evaluated by means of S‐parameter fitting at pinch‐off and active bias conditions.     

A HEMT large‐signal model for use in the design of microwave switching circuits

The nonlinear sources of switch‐HEMTs have been well analyzed by using the measured data. The small signal intrinsic capacitances (under both positive and negative V _ds operation) have been extracted by an extended small signal model. one‐dimension capacitance model has been effectively applied to model the small signal incremental capacitances directly extracted from the key operation region, which has also automatically taken into account the surface trapping effects. A new capacitance model has been effectively proposed to well fit the key nonlinear source (the deep subthreshold capacitance) of switch‐HEMTs. Simple switching function and additional voltage dependence have been applied to model the wide linear‐region (from high‐ V _gs region to deep subthreshold region) of channel current. On/off state small signal insertion loss, small signal isolation, weak harmonics, and power carrying capabilities are accurately predicted by the large signal model. The model shows very good convergence of circuit simulation. Meanwhile, the simple equations and distinguishing among the capacitances accurately make the scaling rules simple and accurate.