We present a comprehensive, up-to-date compilation of band parameters for the technologically important III–V zinc blende and wurtzite compound semiconductors: GaAs, GaSb, GaP, GaN, AlAs, AlSb, AlP, AlN, InAs, InSb, InP, and InN, along with their ternary and quaternary alloys. Based on a review of the existing literature, complete and consistent parameter sets are given for all materials. Emphasizing the quantities required for band structure calculations, we tabulate the direct and indirect energy gaps, spin-orbit, and crystal-field splittings, alloy bowing parameters, effective masses for electrons, heavy, light, and split-off holes, Luttinger parameters, interband momentum matrix elements, and deformation potentials, including temperature and alloy-composition dependences where available. Heterostructure band offsets are also given, on an absolute scale that allows any material to be aligned relative to any other.

Band parameters for III–V compound semiconductors and their alloys

This paper gives the 2010 self-consistent set of values of the basic constants and conversion factors of physics and chemistry recommended by the Committee on Data for Science and Technology (CODATA) for international use. The 2010 adjustment takes into account the data considered in the 2006 adjustment as well as the data that became available from 1 January 2007, after the closing date of that adjustment, until 31 December 2010, the closing date of the new adjustment. Further, it describes in detail the adjustment of the values of the constants, including the selection of the final set of input data based on the results of least-squares analyses. The 2010 set replaces the previously recommended 2006 CODATA set and may also be found on the World Wide Web at physics.nist.gov/constants.

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CODATA Recommended Values of the Fundamental Physical Constants: 2006

To improve the use of lithium-ion batteries in electric vehicle (EV) applications, evaluations and comparisons of different equivalent circuit models are presented in this paper. Based on an analysis of the traditional lithium-ion battery equivalent circuit models such as the Rint, RC, Thevenin and PNGV models, an improved Thevenin model, named dual polarization (DP) model, is put forward by adding an extra RC to simulate the electrochemical polarization and concentration polarization separately. The model parameters are identified with a genetic algorithm, which is used to find the optimal time constant of the model, and the experimental data from a Hybrid Pulse Power Characterization (HPPC) test on a LiMn2O4 battery module. Evaluations on the five models are carried out from the point of view of the dynamic performance and the state of charge (SoC) estimation. The dynamic performances of the five models are obtained by conducting the Dynamic Stress Test (DST) and the accuracy of SoC estimation with the Robust Extended Kalman Filter (REKF) approach is determined by performing a Federal Urban Driving Schedules (FUDS) experiment. By comparison, the DP model has the best dynamic performance and provides the most accurate SoC estimation. Finally, sensitivity of the different SoC initial values is investigated based on the accuracy of SoC estimation with the REKF approach based on the DP model. It is clear that the errors resulting from the SoC initial value are significantly reduced and the true SoC is convergent within an acceptable error.

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Evaluation of Lithium-Ion Battery Equivalent Circuit Models for State of Charge Estimation by an Experimental Approach

Pharmacological sodium nitrate supplementation has been reported to reduce the O2 cost of submaximal exercise in humans. In this study, we hypothesized that dietary supplementation with inorganic n...

/pdf/dietary-nitrate-supplementation-reduces-the-o2-cost-of-low-x1v5si1jxj.pdf

Dietary nitrate supplementation reduces the O2 cost of low-intensity exercise and enhances tolerance to high-intensity exercise in humans

This paper presents a method for modeling and estimation of the state of charge (SOC) of lithium-ion (Li-Ion) batteries using neural networks (NNs) and the extended Kalman filter (EKF). The NN is trained offline using the data collected from the battery-charging process. This network finds the model needed in the state-space equations of the EKF, where the state variables are the battery terminal voltage at the previous sample and the SOC at the present sample. Furthermore, the covariance matrix for the process noise in the EKF is estimated adaptively. The proposed method is implemented on a Li-Ion battery to estimate online the actual SOC of the battery. Experimental results show a good estimation of the SOC and fast convergence of the EKF state variables.

State-of-Charge Estimation for Lithium-Ion Batteries Using Neural Networks and EKF

The properties of InGaAs‐InP single quantum wells have been studied by using the photoluminescence technique. Samples were grown by atmospheric pressure metalorganic vapor phase epitaxy. The photoluminescence of nominally undoped quantum wells is studied as a function of temperature and excitation power. The role of an excitonic process in 4‐K radiative recombinations is pointed out. The best linewidth obtained for a 140‐A well is 4.5 meV, fairly close to the limit imposed by alloy fluctuations in the InGaAs thick layers. Radiative recombination is more and more efficient with decreasing well thickness and higher than in InGaAs bulk material.

Photoluminescence investigation of InGaAs‐InP quantum wells

The control system is connected to a rechargeable battery (110) having charge phases alternating with discharge phases in a charge discharge cycles, The system includes neural networks formed from microprocessors (160) and memory zones(170). A first neural network (NN1) is arranged to collect, at the start of a discharge phase in a charge/ discharge cycle, a group of operating parameters called first parameters (WjA) and to receive as input a predetermined value for a critical step discharge voltage (VTH). The network is arranged to produce a predictive output calculated for the instant (tTH) when the battery reaches the critical step (VTH) corresponding to the end of the discharge phase, The system has also: second and third neural networks (NN2,NN3), connected to the first (NN1), which are arranged to receive as input, at an initial instant, of the aforesaid discharge phase, 1 - a battery voltage value, called the initial voltage (Vo), a variation value for this initial voltage of ( delta Vo) after a short time lapse from the instant of the initial voltage and 2 - a value (No) for a number of initial discharge/charge cycles of the battery, to be carried out prior to the aforesaid discharge phase. The neural networks are arranged to provide as output, at the instant of the discharge phase, where the initial values are available, a set of approximate operating parameters corresponding to a correction (WjC) which are added so as to provide the first set of operating parameters (WjA) to be input to the first network (NN1).

System for controlling the charge/discharge cycles of a rechargeable battery and host device including an intelligent battery

The quantum Hall effect (QHE) samples fabricated by LEP according to specifications intended to optimize their usefulness in metrology are described. Their measured characteristics, notably carrier density, carrier mobility at zero magnetic field, dependence of the quantized resistance on temperature, measuring current, and the quality of electrical contacts, are reported. >

Report on a joint BIPM-EUROMET project for the fabrication of QHE samples by the LEP

High-density selective placement methods for carbon nanotubes

A PIN photodiode having a low leakage current comprises a substrate (10) of indium phosphide (InP) which is n 30 doped and on whose first surface is formed a layer (11) of indium phosphide (InP) which is n - doped and on which is disposed a MESA structure formed by a layer (b 12) of gallium indium arsenide (InGaAs) which is n - doped and is moreover constituted by a layer (13, 113, 213) of the p + type formed at the surface, at the edges and along the circumference of the MESA structure. The structure further comprises a metallic contact (22) formed on the second surface of the substrate and an ohmic contact (21) formed on a part of the p + layer. The invention is characterized in that the n - doping of the layer of indium phosphide (InP) (11) is chosen to be lower than the n - doping of the layer of gallium indium arsenide (InGaAs) (12), and in that the ohmic contact (21) is formed on a part (213) of the p + zone located in the layer of indium phosphide (InP) (11) along the circumference of the MESA structure.

Jean-Noel Patillon

Papers

Photoluminescence investigation of InGaAs‐InP quantum wells

System for controlling the charge/discharge cycles of a rechargeable battery and host device including an intelligent battery

Report on a joint BIPM-EUROMET project for the fabrication of QHE samples by the LEP

High-density selective placement methods for carbon nanotubes

PIN photodiode having a low leakage current