NASA Scientific and Technical Aerospace Reports

20040070924 NASA Marshall Space Flight Center, Huntsville, AL, USA
Ferroelectric Field Effect Transistor Model Using Partitioned Ferroelectric Layer and Partial Polarization
MacLeod, Todd C.; Ho, Fat D.; March 09, 2004; 1 pp.; In English; 16th International Symposium on Integrated Ferroelectrics,
8 Apr. 2004, Gyeonglu, Korea, Republic of
Contract(s)/Grant(s): 101-15-63; No Copyright; Avail: Other Sources; Abstract Only
A model of an n-channel ferroelectric field effect transistor has been developed based on both theoretical and empirical
data. The model is based on an existing model that incorporates partitioning of the ferroelectric layer to calculate the
polarization within the ferroelectric material. The model incorporates several new aspects that are useful to the user. It takes
into account the effect of a non-saturating gate voltage only partially polarizing the ferroelectric material based on the existing
remnant polarization. The model also incorporates the decay of the remnant polarization based on the time history of the FFET.
A gate pulse of a specific voltage; will not put the ferroelectric material into a single amount of polarization for that voltage,
but instead vary with previous state of the material and the time since the last change to the gate voltage. The model also
utilizes data from FFETs made from different types of ferroelectric materials to allow the user just to input the material being
used and not recreate the entire model. The model also allows the user to input the quality of the ferroelectric material being
used. The ferroelectric material quality can go from a theoretical perfect material with little loss and no decay to a less than
perfect material with remnant losses and decay. This model is designed to be used by people who need to predict the external
characteristics of a FFET before the time and expense of design and fabrication. It also allows the parametric evaluation of
quality of the ferroelectric film on the overall performance of the transistor.
Author
Ferroelectric Materials; Field Effect Transistors; Models; Fabrication
20040071065 Lockheed Martin Corp., Syracuse, NY, USA
Thermophotovoltaic Arrays for Electrical Power Generation
Nov. 2003; 14 pp.; In English
Report No.(s): DE2004-822278; LM-03K129; No Copyright; Avail: Department of Energy Information Bridge
Sarnoff has designed an integrated array of thermophotovoltaic (TPV) cells based on the In(Al)GaAsSb/GaSb materials
system. These arrays will be used in a system to generate electrical power from a radioisotope heat source that radiates at
temperatures from 700 to 1000 C. Two arrays sandwich the slab heat source and will be connected in series to build voltage.
Between the arrays and the heat source is a spectral control filter that transmits above-bandgap radiation and reflects
below-bandgap radiation. The goal is to generate 5 mW of electrical power at 3 V from a 700 C radiant source. Sarnoff is a
leader in antimonide-based TPV cell development. InGaAsSb cells with a bandgap of 0.53 eV have operated at system
conversion efficiencies greater than 17%. The system included a front-surface filter, and a 905 C radiation source. The cells
were grown via organo-metallic vapor-phase epitaxy. Sarnoff will bring this experience to bear on the proposed project. The
authors first describe array and cell architecture. They then present calculated results showing that about 80 mW of power can
be obtained from a 700 C radiator. Using a conservative array design, a 5-V output is possible.
NTIS
Photovoltaic Cells; Electric Power; Arrays
20040071095 Helsinki Univ. of Technology, Espoo, Finland
Artificial Neural Network Based RF-Model Generator-Version 0.2
Roos, J.; Sengor, N. S.; Pohjala, A.; 2003; 32 pp.; In English
Report No.(s): PB2004-105756; No Copyright; Avail: CASI; A03, Hardcopy
This report describes the development, implementation, and usage of an Artificial Neural Network (ANN) based
RF-model generator. Once the user has provided appropriate measurement or simulation data describing the behavior of an
RF component, the model generator trains the ANN, resulting in an S-parameter or equivalent-circuit model for the RF
component. The ANN-based RF-model generator has been implemented using the flexible input language of APLAC circuit
simulation and design tool. Therefore, the existing optimization methods of APLAC can be directly utilized in ANN training.
The final RF model obtained can be immediately used in any APLAC simulation.
NTIS
Neural Nets; Radio Frequencies
20040071100 Helsinki Univ. of Technology, Espoo, Finland
Parallel Processing in APLAC. Part A: DC and Transient Analyses
Honkala, M.; 2003; 26 pp.; In English
Report No.(s): PB2004-105755; No Copyright; Avail: CASI; A03, Hardcopy
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