Accurate Empirical Model Research Articles

Large-signal modeling of SOI MESFETs

It has been demonstrated that sub-micron metal–semiconductor field-effect transistors (MESFETs) can be fabricated using a commercial 3.5 V silicon-on-insulator (SOI) CMOS foundry with no changes to the CMOS process flow. The SOI MESFETs demonstrate excellent RF capabilities and can operate at voltages that are at least 3X higher than the MOSFET breakdown voltage. If the high voltage capability is to be exploited in radio frequency integrated circuits it is important to develop an accurate empirical model of the device. This paper presents the SPICE model development of the SOI MESFET. A measurement-based approach is used to customize a commercially available, large-signal TOM3 MESFET model. Using the TOM3 model, an SOI MESFET Colpitts oscillator operating at 1.5 GHz has been simulated with an output swing of 7 V to illustrate the high voltage RF applications of the device.

Simulation of hydrogen plasma with cluster multi-range interpolation

In the present work, we use the recently developed cluster multi-range interpolation (CMRI) (Valuev 2005 Comput. Phys. Commun. 169 60) of interaction potentials to simulate hydrogen plasma using molecular dynamics (MD). The interpolation is based on variational mixing of cluster connectivity within a given system of electrons and ions described by coordinates of the particles. The use of potential interpolation based on connectivity allows us to treat the collisions of small numbers of particles (up to two ions and three electrons together) by more accurate empirical models and treat such processes as ionization or molecule formation by means of MD simulation on single-valued smooth approximate N-particle potential energy surfaces. The construction of the scheme and the results of equilibrium MD simulations are discussed. Energy spectra and particle pair correlation functions are compared between the current CMRI model and two classical models with pair pseudopotentials.

A hybrid adaptive time-delay neural network model for multi-step-ahead prediction of sunspot activity

The availability of accurate empirical models for multi-step-ahead (MS) prediction is desirable in many areas. Some ANN technologies, such as multiple-neural network, time-delay neural network (TDNN), and adaptive time-delay neural network (ATNN), have proven successful in addressing various complicated problems. The purpose of this study was to investigate the applicability of neural network MS predictive models. Motivated by the above-mentioned technologies, we proposed a hybrid neural network model, which integrated characteristics decomposition units, and a dynamic spline interpolation unit into the multiple ATNNs. Inside the net, the regular and certain information were extracted to ATNN, while both time delays and weights were dynamically adapted. The yearly average of the sunspots, which has been considered by geophysicists, environment scientists, and climatologists as a complicated non-linear system, was selected to test the hybrid model. Comparative results were presented between a traditional MS predictive model based on TDNN and the proposed model. Validation studies indicated that the proposed model is quite effective in MS prediction, especially for single-factor time series.

Empirical model generation techniques for planar microwave components using electromagnetic linear regression models

Accurate and efficient empirical model generation techniques of microwave devices, for a large range of geometric and material parameters opportunely chosen, are presented. The empirical models are based on multiple linear regression approach, which compensates the error between an initial inaccurate empirical model and an electromagnetic (EM) full-wave solver (or measurement data). The aim of these techniques is to generate accurate empirical models, which are computationally very efficient with respect to any EM technique. These simple models could be integrated in a toolbox of any commercially available computed-aided design tools for RF/microwave circuits. Comparisons with artificial neural networks and linear-regression-based models are listed and discussed for the dispersion of a microstrip transmission line propagating the quasi-TEM mode and a microwave tunable phase shifter propagating the even mode.

Enhanced empirical large-signal model for HBTs with performance comparable with physics-based models

An accurate empirical large-signal model for an heterojunction bipolar transistor (HBT) is given. In the DC mode, thermal-dependent physics-based relations for Kirk and avalanche effects are included to improve the accuracy of the model. In the small-signal mode, in addition to the distribution of the base resistance and base collector junction, the model captures the variation of various AC parameters with both bias voltage and bias current over the entire forward-bias region and a wide range of signal frequencies. DC parameter extraction is easily carried out using suitable optimisation codes on the measured I/sub c/-V/sub ce/ curves and Gummel plots, whereas the AC parameters are determined from multibias S-parameter measurements. To assess the validity and the accuracy of the proposed model the empirical large-signal model is constructed for a 2/spl times/25 /spl mu/m/sup 2/ emitter-area transistor and compared with measurements in DC, small-signal and large-signal modes. The model is further tested by comparing it with the physics-based and well-established VBIC model. It is found that, despite its reduced complexity, the enhanced empirical model gives better agreement with measurements than the VBIC model in all modes of operation.

Optimal and sub-optimal Loop Filter Responses for Continuous-Time ΔΣ Modulators

This paper describes a comprehensive analysis of the stability of continuous-time low-pass or band-pass ΔΣ modulators. This analysis is based on a fully S-domain approach which considers the modulator as a feedback control system with gain and phase margins. Theoretical responses for both the optimal filter and a sub-optimal one are derived using a mathematical formalism close to well-known boundary elements methods. A very accurate empirical model has also been developed and, for each case (optimal and sub-optimal), normalized sets of curves allowing to extract the maximum achievable loop gain for a given loop configuration. High achievable gains were found even in the case of ΔΣ modulators involving large delays (several clock times).

Empirical prediction of smoke production in the ISO Room Corner Fire Test by use of ISO Cone Calorimeter Fire Test data

The combustion conditions in the ISO Room Corner Fire Test make it possible to predict full scale smoke production by use of prediction models and bench scale fire test data procured by the ISO Cone Calorimeter Fire Test. The full scale smoke production is governed by the type of material burning only if the rate of heat release is less than 400–600 kW. For higher rates of heat release, the smoke production is more governed by the combustion conditions. The influence of the combustion conditions on the full scale smoke production reduces the possibilities of smoke prediction to materials causing flashover within 10 min in the ISO Room Corner Fire Test. The smoke to heat ratio SQ (m2MJ) was used to compare smoke production between the scales. In general, the comparison revealed that the smoke yield was significantly less in full scale than in bench scale, especially for the plastics. Plastics do yield more smoke than wood based materials in both scales, but the differences in full scale are not as extreme as indicated by the bench scale smoke data. No simple correlations between the scales seem to exist. Multiple regression studies on empirical smoke prediction models show that bench scale fire parameters can be used to predict full scale fire performance. A quite accurate empirical smoke prediction model is presented for the group of materials which caused flashover within 10 min. The model predicts the full scale rate of smoke production at a rate of heat release of 400 kW. The presented results might be used to assess the fire safety hazard of visible smoke, but benchmarks of smoke hazard do not seem to exist. Thus further studies and agreement on safety levels and principles are needed for general visibility analysis concerning fire safety engineering purposes. Copyright © 1999 John Wiley & Sons, Ltd.

About a Conjunction between Electrical and Optical Phenomena in p‐Type Heavily Doped Silicon at Room Temperature

AbstractThe conjunction between electrical and optical phenomena in p‐type heavily doped silicon at room temperature is investigated, based on our accurate empirical models for the band‐gap narrowing, apparent band‐gap narrowing, and unperturbed Fermi energy shift. The numerical results of optical band gap, reduced interacting Fermi energy, and reduced interacting density‐of‐valence band states effective mass are presented and compared with other theoretical results and experiments. It is concluded that, taking into account the unperturbed Fermi energy shift effect, the values of band‐gap narrowing, obtained from electrical and optical phenomena, are found to be the same, removing the disagreements or discrepancies in theoretical and experimental values of band‐gap narrowing existing so far in the literature.

A new methodology to produce accurate empirical models for VLSI MOSFETs

A procedure for deriving a set of piecewise continuous orthogonal functions capable of representing a wide range of experimental data of VLSI MOSFETs from simple analytical device models is presented. In addition, the conditions required to obtain continuous functions are given by evaluating a function of data and fitting parameters, called “entropy”. Finally, a new methodology to produce accurate empirical models as continuous functions of all the empirical parameters and bias voltages is proposed. As an example, an advanced HCMOS process is considered.

SO 2 dosages in an urban area

Five winter-semesters of data of SO 2 concentration at three sites in the urban area of Milan were analyzed to generate statistics of dosage which describe the dosage distributions, the temporal structure, the dependence upon concentration thresholds and the six-month-average concentration. By considering the joint distributions of dosages and their durations it is found that the basic ambiguity between dosages and their durations can be resolved since for each dosage value only a limited range of durations is observed. It is also found that the six-month-average concentration has a dominating role on the statistics of dosages; previous works have reported a similar influence on concentration statistics, durations and extreme values. For most of the statistics it has been possible to develop simple and accurate empirical models.