China
Africa
Explore chapters and articles related to this topic
Detectors and Focal Planes
Published in Monroe Schlessinger, Infrared Technology Fundamentals, 2019
In the previous section we provided the expression for the signal current. It remains to define a similar expression for the detector noise. Noise in photodetectors has various components that have been defined [12] and are summarized in Table 4. The primary sources of noise are the generation-recombination noise (g-r noise) caused by the statistical nature of the charge carrier generation and recombination process and the Johnson, or thermal, noise. As shown in Ref. 1, the noise currents of photo-voltaic and photo-conductive detectors have the form () In2=Uq[qηϕBAG2+Id(v)+KTqR]Δf
Nature of Light
Published in George K. Knopf, Kenji Uchino, Light Driven Micromachines, 2018
From a material’s perspective, a detailed understanding of the photoconductive behavior of a semiconductor material can be obtained by looking at the distribution of electronic states in the material and on carrier generation and recombination processes from the dependence on factors such as the exciting photon energy, the intensity of the illumination, or the ambient temperature (Kasap and Capper 2006). Experimental techniques involving either steady-state currents under constant illumination or transient methods that exploit pulsed excitation can be used to study the electronic density of states and recombination processes. The results of these experimental investigations can then be used to determine the optical absorption coefficients or concentrations and distributions of defects in the material. Extensive details about the process and experimental methods can be found in a variety of textbooks and handbooks.
Nanostructured Semiconducting Polymer Inorganic Hybrid Composites for Opto-Electronic Applications
Published in Mahmood Aliofkhazraei, Advances in Nanostructured Composites, 2019
Sudha J. Devaki, Rajaraman Ramakrishnan
Hierarchical structure of ZnO and TiO2 are widely used as active materials in DSSCs and photocatalytic application. In DSSCs, the major restricting problem of improving the higher conversion efficiencies is a dynamic competition between the charge carrier generation and recombination of photoexcited carriers (Law et al. 2005, Paulose et al. 2006). One dimensional nanostructures are able to provide a direct pathway for the rapid collection of photogenerated electrons and thus reduce the degree of charge recombination. However, such one dimensional nanostructures seem to have insufficient internal surface area which limits their energy conversion efficiency at a relatively low level, for example, 1.5% for ZnO nanowires and 4.7% for titania nanotubes (Nishimura et al. 2003, Halaoui et al. 2005). Another way to increase the light harvesting capability of the photo electrode films is utilizing optical enhancement effects. This can be achieved by means of light scattering via introducing scattering particles into the photo electrode film (Zhang et al. 2009, Chou et al. 2007). The following criteria are essential for improving the power conversion efficiency of solar cell. It should allow the complete light absorption in the spectral range of the dye, increase the light scattering of the absorbing layer for enhancing the time spent by light inside the sensitized film and improving light absorption, and inhibition of back electron transfer between the conducting layer at the anode and the electrolyte (Guillen et al. 2013, Zhang et al. 2008). Figures 10(a and b) show the hierarchical structure of ZnO and the effect of light scattering and photon localization within a film consisting of submicrometer sized aggregates.
Exploring p-channel TFET for Optimum Cavity-Length Window in Detecting a Wide Variety of Protein-Molecules with the Effect of Their Position Dependent Variability on Sensitivity
Published in IETE Technical Review, 2021
Sanu Gayen, Suchismita Tewari, Avik Chattopadhyay
The entire analysis of the proposed pTFET-BS device is carried out by SILVACO ATLAS, a 2D numerical device simulator [23]. In order to consider the spatial change in the energy band profile, the nonlocal band-to-band tunneling (BTBT) model is invoked in our simulation, along with Shockley–Read–Hall (SRH) and Auger models to capture the essence of carrier generation and recombination. To capture the effects due to high doping concentration, band gap narrowing model is incorporated. Additionally, to incorporate, the temperature-, field (both lateral and longitudinal)-, and concentration-dependency in carrier mobility, Lombardi CVT mobility model has been invoked. Throughout the simulation Fermi–Dirac (FD) statistics is used.
A 2D channel potential modelling of symmetric double-gate MOSFET at onset of threshold condition
Published in International Journal of Electronics Letters, 2021
It is found from our threshold voltage model (23) that threshold voltage reduces with the reduction of L, i.e. threshold voltage roll-off which is a significant SCE occurring in the devices as also found in Figure 6. For different Vds values, the simulated curve for surface potential and centre electrostatic potential resemble the curve generated from our model equation. With the increase of Vds, the curves each for surface and centre electrostatic potential show an upward shift which imply the presence of DIBL. It can be observed from figures that at higher channel length values, the surface potential distribution remains almost flat at the centre of the channel region. As channel length decreases, the surface potential is no more flat which implies that in short channel devices the surface potential is greatly affected by source/drain bias. For a doped device, mobility degradation effect needs to be considered as it happens due to random dopant fluctuation. In the simulation of our device, Philips Unified Mobility Model is used to consider the impact of mobility degradation. Besides this, field-dependent (including velocity saturation and transverse field dependence) mobility models and bandgap narrowing models are also included for simulation. Doping-dependent Shockley–Read–Hall recombination model is used to include carrier generation and recombination process in the channel region. In our work, the device is modelled based on classical theory. Therefore, to compare accurately the model results with numerical simulation, the device is run using drift-diffusion model selected as transport model in the device simulator. Quantum confinement effects are ignored as it becomes significant for channel thickness less than 5 nm (Trivedi & Fossum, 2005). We have considered the fixed charges present in source/drain depletion width in deriving our channel potential model.