Block Diagram Programming of Quantum Dot Sources and Infrared Photodetectors for Gamma Radiation Detection Through VisSim

Quantum dots (QDs) have attracted tremendous interest over the last few years for a large variety of applications ranging from optoelectronic through photocatalytic to biomedical, including applications as nanophosphors in light emitting diodes LEDs [1]. QDs have been suggested as scintillators for detection of alpha particles and gamma-rays [1-4]. Quantum dots offer an improvement on scintillator technology in that the size of the phosphorescent material would not be restrained by crystal growth. The dots would be suspended in a transparent matrix that could be as large as desired. Moreover, the output of the QDs is a function of their dimensions. Therefore, they could be produced to emit light at wavelengths suitable for detection by avalanche photodiodes. That offer higher quantum efficiencies than photomultiplier tubes. Therefore, the sensitivity of the scintillator detector is increased [5]. To our knowledge, still models describing QD sources as gamma detection are not devised yet. In this chapter, we report on the effects of gamma irradiation on the different properties of CdSe/ZnS QDs. These characteristics are optical gain, power, population inversion and photon density. Furthermore, a new semiconductor scintillator detector was studied in which high-energy gamma radiation produces electron-hole pairs in a direct-gap semiconductor material that subsequently undergo interband recombination, producing infrared light to be registered by a photo-detector [6]. Therefore, quantum dot infrared photodetectors (QDIPs) can be used for this purpose. This chapter presents a method to evaluate, study, and improve the performance of quantum dot sources and infrared photodetectors as gamma radiation detection. This chapter is organized as follows: Section 3.2 presents the basics of VisSim simulator. QD devices as a detector are illustrated in Section 3.3. The proposed models of both quantum dot devices are represented in Section 3.4. Discussion and results are summarized in Section 3.5.


Introduction
Quantum dots (QDs) have attracted tremendous interest over the last few years for a large variety of applications ranging from optoelectronic through photocatalytic to biomedical, including applications as nanophosphors in light emitting diodes LEDs [1].QDs have been suggested as scintillators for detection of alpha particles and gamma-rays [1][2][3][4].Quantum dots offer an improvement on scintillator technology in that the size of the phosphorescent material would not be restrained by crystal growth.The dots would be suspended in a transparent matrix that could be as large as desired.Moreover, the output of the QDs is a function of their dimensions.Therefore, they could be produced to emit light at wavelengths suitable for detection by avalanche photodiodes.That offer higher quantum efficiencies than photomultiplier tubes.Therefore, the sensitivity of the scintillator detector is increased [5].To our knowledge, still models describing QD sources as gamma detection are not devised yet.In this chapter, we report on the effects of gamma irradiation on the different properties of CdSe/ZnS QDs.These characteristics are optical gain, power, population inversion and photon density.Furthermore, a new semiconductor scintillator detector was studied in which high-energy gamma radiation produces electron-hole pairs in a direct-gap semiconductor material that subsequently undergo interband recombination, producing infrared light to be registered by a photo-detector [6].Therefore, quantum dot infrared photodetectors (QDIPs) can be used for this purpose.This chapter presents a method to evaluate, study, and improve the performance of quantum dot sources and infrared photodetectors as gamma radiation detection.This chapter is organized as follows: Section 3.2 presents the basics of VisSim simulator.QD devices as a detector are illustrated in Section 3.3.The proposed models of both quantum dot devices are represented in Section 3.4.Discussion and results are summarized in Section 3.5.

VisSim simulator
VisSim simulation is one of the most widely used environments in operations research and management science, and by all indications its popularity is on the increase.The goal of using VisSim modeling and analysis is to give an up-to-date treatment of all the important aspects of a simulation study, including modeling, simulation languages, validation, and output data analysis.However, most real world-systems are too complex to allow realistic models to be evaluated analytically, and these models must be studied by means of VisSim simulation.In VisSim we use a computer to evaluate a model numerically over a time period of interest, and data are gathered to estimate the desired true characteristics of the model.In addition we have tried to represent the operation of the QD sources and photodetectors in a manner understandable to a person having only a basic familiarity with its main behaviors such as optical gain, power, output photon densities, dark current, photocurrent, and detectivity.It can be a powerful supplement to traditional design techniques.
System engineering program such as Mathsoft's VisSim employ the Graphical User Interface (GUI) concept.In order to, display systems of differential equations as feedback systems.Additionally, if the relationships which compose the model are simple enough, it may be possible to use VisSim simulation model.Then, assume numerical integration using the methods of Laplace transforms for differential equations, hence the appearance of the symbols 1/S, to indicate integration.Though these packages integration is used because it is an inherently more stable numerical operation.The first step in converting from equation to block diagram form is thus to integrate both sides of differential equation.The operations of addition, multiplication, integration and so on are performed by blocks operators, as shown in the following models.Besides, reading the block diagram is from left to right.
The following are some possible reasons for the widespread popularity of the VisSim simulation [7-10]: 1. Most complex, real-world systems with stochastic elements cannot be accurately described by a mathematical model which can be evaluated analytically.Thus, VisSim simulation is often the main type of investigation possible.2. VisSim Simulation allows one to estimate the performance of an exciting system under some projected set of operation conditions.3. Alternative proposed system designs (or alternative operating policies for a single system) can be compared via VisSim simulation to see which best meets specified requirements.4. In VisSim simulation we can maintain much better control over experimental conditions than would generally be possible when experimenting with the system itself.5. VisSim Simulation allows us to study a system with along time frame, or alternatively to study the detailed workings of a system in expanded time.
Our goal in this chapter is to evaluate the performance of QDs devices by using VisSim environment along with the block diagram programming procedures.

QD devices as a detector
Quantum dots have been used in a wide variety of applications.A key advantage of these particles is that their optical properties depend predictably on size, which enables tuning of the emission wavelength [11].QD devices as a source and infrared photodetectors can be used to detect gamma radiation [2,4,6].Moreover, the ability of semiconductor quantum dots to convert alpha radiation into visible photons was demonstrated in [2].
In this chapter, we report on the scintillation of quantum dots sources and infrared photodetectors under gamma-ray irradiation.
Semiconductor scintillation gamma radiation detector based on QD will be discussed in which the gamma-ray absorbing semiconductor body is impregnated with multiple small direct gap semiconductor inclusions of band gap slightly narrower than that of the body.If the typical distance between them is smaller than the diffusion length of carriers in the body material, the photo-generated electrons and holes will recombine inside the impregnations and produce scintillating radiation to which the wide gap body is essentially transparent [6].Furthermore, the quantum dot lasers (QDLs) under gamma radiation is characterized by changes in threshold current, external slope efficiency and light output [12].
For infrared (IR) detection, most of QDIPs are based on vertical heterostructures consisting of two dimensional arrays of QDs separated by the barrier layers.The QD structures serving as the photodetector active region, where IR radiation is absorbed, are sandwiched between heavily doped emitter and collector contact layers.The active region can be either doped (with dopants of the same type as the contact layers) or undoped.Schematic view of vertical QDIPs device structures is in [13].The absorption of IR is associated with the electron intersubband transitions from bound states in QDs into continuum states above the barriers or into excited quasi-bound states near the barrier top.The bound-to-continuum transitions or bound-toquasi-bound transitions followe d b y f a s t e s c a p e i n t o t h e c o n t i n u u m r e s u l t i n t h e photoionization of QDs and the appearance of mobile electrons.Bound electrons accumulated in QDs can create a significant space charge in the active region.In this chapter, we extended the same physical characteristics to study QD devices under gamma radiation.

The proposed models of quantum dot devices 1.4.1 The proposed simulator of quantum dot laser under gamma radiation
Improved radiation detection using quantum dot semiconductor composites is demonstrated [4,14].The quantum confinement effects enabled the QDs to be used with a wide variety of detectors.The inorganic nanocrystalline quantum dots will be demonstrated as a powerful method in preparing scintillating devices.In gamma-ray detection, our first goal is to employ nanomaterials in the form of QD based mixed matrices to achieve scintillation output several times over that from NaI(Tl) crystals.Moreover, block diagram models are used to represent carrier densities in the Subbands, population inversion process, optical power, and gain.Our goal from this study is to obtain a device that has high performance with optimal operating conditions.

Proposed simulator of optical wavelength
This subsection introduces a useful block diagram model to predict effect of incident gamma radiation on quantum dot emission wavelength.
The QDs semiconductor composite is designed so that ionizing radiation produces excitations predominantly in the semiconductor QDs.These excitations are subsequently Förster-transferred to organic material.For scintillators, the composite material must be transparent to the emitted photon, and the large Stokes shift of the organic material is essential.For charge-collection devices the composite material must be trap free to allow efficient charge collection.Trap-free, conjugated organic materials are now available [4].Pure QDs solids are impractical radiation-detection materials because they are not transparent to their emission wavelength and have significant charge-carrier trapping.
If the peak photoluminescence (PL) photon emission energy, E PL , is always lower than the 1s-1s absorbance peak energy, E abs , by an energy shift (ΔE AP ~ -0.14 eV + 0.074 x E abs or ΔE AP ~0.025 eV for CdSe quantum dots when 2 eV < E abs < 2.5 eV), then the wavelength of the PL peak, PL , can be calculated as follows [15] where h, c, E g , X denote plank's constant, speed of light, energy gap, and X = 0.82x10 -7 eV-cm for CdSe, respectively.If all Cd precursors have been consumed, the average nanocrystal radius reaches the completion radius, R c , and PL emission occurs at a completion wavelength, c .where C 0 , N eff , and V m denote the original molar concentration of Cd in the batch (in moles cm -3 ), the effective number of spherical nanocrystals that would contain the number of moles of Cd that have been consumed, and the molar volume, respectively.Block diagram model that describe the effect of γ-energy on the emission wavelength is depicted in Fig. 3.1.

The models of quantum dot infrared photodetectors
A new scintillation-type semiconductor detector was studied in which high-energy radiation produces electron-hole pairs in a direct-gap semiconductor material that subsequently undergo interband recombination, producing infrared light to be registered by a QDIP.Scintillators are not normally made of semiconductor material.The key issue in implementing a semiconductor scintillator is how to make the material essentially transparent to its own infrared light.Consequently, that photons generated deep inside the semiconductor slab could reach its surface without tangible attenuation.
In this subsection, different treatments are applied to model the characteristics of QDIPs than that in [16][17] where q is the electron charge, ae is the dielectric constant of the material from which the QD is fabricated, are the QD form-factors in lateral (in the QD array plane) and transverse (growth) directions, respectively, x i and y j are the in-plane QD coordinates, z k = kL is the coordinate of the k th QD array (where k = 1, 2, 3, . . ., M and M is the number of the QD arrays in the QDIP), L is the transverse spacing between QDs and ρ D is the donor concentration in the active region.The form-factors correspond to the lateral and transverse sizes of QDs equal to a QD and l QD , respectively.
Moreover, block diagram model that describes the relation between dark current and structural parameters is implemented through VisSim as depicted in Fig. 3

Photocurrent density block diagram model of QDIP
We calculate the photocurrent density in QDIPs using a developed device model of [16].This model takes into account the space charge and the self-consistent electric potential in the QDIP active region, the activation character of the electron capture and its limitation by the Pauli principle, the thermionic electron emission from QDs and thermionic injection of electrons from the emitter contact into the QDIP active region, and the existence of the punctures between QDs.The developed model yields the photocurrent density in a QDIP as a function of its structural parameters.The photocurrent density of QDIP is given by [16][17] where J m is the maximum current density which can be supplied by the emitter contact.The average photocurrent density of QDIP is given by [16][17]  The specific detectivity, D, which is a measure of the signal-to-noise ratio of the device, used to characterize QDIPs [18].It was calculated from the noise density spectra and the peak responsivity [19].The detectivity of QDIP is determined by the following equation [20][21][22][23]; Moreover, block diagram model that describes the relation between detectivity and structural parameters is implemented through VisSim as illustrated in Fig. 3.4.

Results of QD sources
The main target of this subsection is to study the various parameters effects on quantum dot devices for gamma radiation detection.Block diagram model using VisSim environment is used for this purpose.Consequently, the current study assists on the fact that QD devices can be used for gamma radiation detection.The effect of incident gamma radiation on the emission wavelength is deeply studied.Moreover, the effect of QD parameters on the optical gain is investigated.The modal gain is determined by calculating the amplified spontaneous emission (ASE) power.We concluded that one of the main advantages of quantum dot (QD) is their wide wavelength range.Therefore, QD sources can be used as an efficient device for gamma detection.The emission wavelength against incident gamma energy at different N eff and V m is depicted in Figs.3.5, respectively.The wide range of emission wavelength is one of the main advantages of QD devices.However, the emission wavelength increases with the molar volume as shown in Fig. 3.5.From this study we are concluded that the emission wavelength of QD is wide.Therefore, QD can be used as an efficient device for gamma radiation detection.Furthermore, the intraband free-carrier absorption coefficient in doped semiconductors is roughly proportional to 2 , which translates into larger optical waveguide losses at the longer wavelengths.As seen in this figure, at the beginning the photocurrent is larger than the dark current because there is no thermionic emission of electron and the tunneling process of electron is so small.Then the dark current is sharply increased with the photocurrent, since more electrons are thermally emitted and losses of electrons are increased.results in increasing detectivity.With increasing Σ QD , the dark current is reduced and the unwanted noise becomes negligible.Hence detectivity is increased.As expected from Figs.

Energy (MeV)
3.11-3.12,a rapid decrease of the detectivity is observed with increasing both Σ D and the lateral sizes of QDs.

Fig. 3 . 1 .
Fig. 3.1.Block diagram model that describes the effect of incident gamma energy on emission wavelength.Growth of the average quantum dot radius can be written as [15] 1 3 0 3 4 m c eff CV R N       (3.3)

Figures 3 . 9 - 3 . 12 , 2 Σ
Figures 3.9-3.12,depicts the change of detectivity of QDIP against different parameters: temperature, Σ QD, Σ D, and a QD .As expected from Fig.3.9, a rapid decrease in detectivity occurs with the increase in a temperature due to contribution of thermal generation and increasing the dark current.From Fig.3.10, it is obvious that increasing quantum dot density

Fig. 3 . 7 .
Fig. 3.7.Dark current and biasing voltage results at different lateral characteristic size of quantum dot.

Fig. 3 . 8 .
Fig. 3.8.Dark current and photocurrent as a function of the biasing voltage at different quantum dot density of states.
[16]r gamma radiation.Furthermore, we will utilize a new block diagram model to consider the characteristics of a QDIP under dark and illumination condition.arethe in-plane indices of QDs, <N k > denotes average extra carrier number in the QDs and k is the index of the QD array.In this case, the distribution of the electric potential φ=φ(x,y,z) in the active region is governed by the Poisson equation[16]