scholarly journals Simulation and Optimization Design of SiC-Based PN Betavoltaic Microbattery Using Tritium Source

Crystals ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 105
Author(s):  
Zhang Lin
Keyword(s):  
Monte Carlo ◽  
Conversion Efficiency ◽  
Ionization Energy ◽  
Doping Concentration ◽  
Energy Deposition ◽  
Surface Recombination ◽  
Material Surface ◽  
Simulation And Optimization ◽  
Output Characteristics ◽  
Recombination Effect

In this paper, the Monte Carlo method and numerical model are used to build the electrical model of a SiC-based betavoltaic microbattery using a 3H source, and the influences of structural parameters and the surface recombination effect on the output characteristics of the SiC PN battery are simulated. According to Monte Carlo calculations based on the energy spectrum of the 3H source, the ionization energy deposition approaches the exponential distribution along the depth direction, and most of the 22rs are concentrated near the material surface. The ionization energy deposition data is converted into non-equilibrium carrier information for the numerical simulation of the battery’s output characteristics. The simulation results show that the conversion efficiency of the battery rises first, and then decreases with the increase of the doping concentration of the N region. This is because the N region-doping affects the depletion region width and the built-in electrical potential at the same time. After considering the surface recombination effect, the conversion efficiency decreased significantly. Thinning the thickness of or moderately reducing the doping concentration of the P region will weaken the surface recombination effect.

Research on Characteristics of the Photovoltaic Cells Integrated on Chip

2014 ◽  
Vol 525 ◽  
pp. 287-291
Author(s):  
Li Xian Xiao ◽  
Yong Tai He ◽  
Yue Hong Peng ◽  
Jin Hao Liu
Keyword(s):  
Conversion Efficiency ◽  
Doping Concentration ◽  
Photovoltaic Cells ◽  
Influence Factors ◽  
Device Layer ◽  
Fabrication Technology ◽  
Junction Depth ◽  
On Chip ◽  
Substrate Doping ◽  
Emitter Junction

The influence factors of Photovoltaic (PV) cells characteristics integrated on chip were analyzed based on the fabrication process and the structure of the PV cells and CMOS devices. The results show the substrate doping concentration, the emitter doping concentration, the emitter junction depth and the thickness of device layer directly determine the conversion efficiency, open voltage and the light-generated current of photovoltaic cells. In the emitter doping concentration range of 1×1019/cm3 to 1×1021/cm3 and the substrate doping concentration range of 1.0×1015/cm3 to 1.0×1017/cm3, the Photovoltaic cells have batter conversion characteristics. The PV cells were designed based on the analysis results in PC1D, and the conversion efficiency is 9.43%. The Photovoltaic cells and the CMOS devices have batter fabrication technology compatibility integrated on chip.

Estimation of Nanometer-Sized EB Patterning Using Energy Deposition Distribution in Monte Carlo Simulation

2011 ◽  
Vol 497 ◽  
pp. 127-132 ◽  
Author(s):  
Hui Zhang ◽  
Takuro Tamura ◽  
You Yin ◽  
Sumio Hosaka
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Electron Beam ◽  
Energy Distribution ◽  
Electron Energy ◽  
Electron Beam Lithography ◽  
Energy Deposition ◽  
Si Substrate ◽  
Positive Resist

We have studied on theoretical electron energy deposition in thin resist layer on Si substrate for electron beam lithography. We made Monte Carlo simulation to calculate the energy distribution and to consider formation of nanometer sized pattern regarding electron energy, resist thickness and resist type. The energy distribution in 100 nm-thick resist on Si substrate were calculated for small pattern. The calculations show that 4 nm-wide pattern will be formed when resist thickness is less than 30 nm. Furthermore, a negative resist is more suitable than positive resist by the estimation of a shape of the energy distribution.

GaN Radiation Detection Research Based on Monte Carlo Method

2014 ◽  
Vol 668-669 ◽  
pp. 1011-1014
Author(s):  
Yang Liu ◽  
Guo Zheng Zhu ◽  
Zhen Ni Xing
Keyword(s):  
Monte Carlo ◽  
Energy Deposition ◽  
Detection Efficiency ◽  
Hadron Collider ◽  
Radiation Detection ◽  
Radiation Energy ◽  
Radiation Detectors ◽  
Detection Mechanism ◽  
Radiation Beam ◽  
The Impact

Gallium nitride (GaN) is the third generation of semiconductor material; it has a large band gap, high thermal conductivity, low dielectric constant, high drift speed, etc. Radiation detectors based on GaN material have small volume, high radiation resistance, and fast response, can be used to replace the existing Large Hadron Collider vertex detector and track detector. Energy deposition characteristic of GaN detectors to radiation beam is an important factor for detection efficiency, and there are many factors that affect the energy deposition characteristics of the detector, like the detection mechanism, the impact of material properties, the type of incident ray, radiation energy, and many other factors. This paper studies the physical properties of GaN detector by calculation based on Monte Carlo simulation. Energy deposition characteristics are discussed respectively for incident γ-ray with different energy, in the front-end and back-end add PTFE material. The results of our study present the theoretical properties of GaN radiation detectors.

scholarly journals Modelling a Segmented Skutterudite-Based Thermoelectric Generator to Achieve Maximum Conversion Efficiency

2020 ◽  
Vol 10 (1) ◽  
pp. 408
Author(s):  
Aminu Yusuf ◽  
Sedat Ballikaya
Keyword(s):  
Temperature Gradient ◽  
Conversion Efficiency ◽  
Thermoelectric Generator ◽  
Mass Scale ◽  
Open Circuit ◽  
Scale Production ◽  
Compatibility Factor ◽  
Output Characteristics ◽  
Te Material ◽  
P Type

Thermoelectric generator (TEG) modules generally have a low conversion efficiency. Among the reasons for the lower conversion efficiency is thermoelectric (TE) material mismatch. Hence, it is imperative to carefully select the TE material and optimize the design before any mass-scale production of the modules. Here, with the help of Comsol-Multiphysics (5.3) software, TE materials were carefully selected and the design was optimized to achieve a higher conversion efficiency. An initial module simulation (32 couples) of unsegmented skutterudite Ba0.1Yb0.2Fe0.1Co3.9Sb12 (n-type) and Ce0.5Yb0.5Fe3.25Co0.75Sb12 (p-type) TE materials was carried out. At the temperature gradient T∆ = 500 K, a maximum simulated conversion efficiency of 9.2% and a calculated efficiency of 10% were obtained. In optimization via segmentation, the selection of TE materials, considering compatibility factor (s) and ZT, was carefully done. On the cold side, Bi2Te3 (n-type) and Sb2Te3 (p-type) TE materials were added as part of the segmentation, and at the same temperature gradient, an open circuit voltage of 6.2 V matched a load output power of 45 W, and a maximum simulated conversion efficiency of 15.7% and a calculated efficiency of 17.2% were achieved. A significant increase in the output characteristics of the module shows that the segmentation is effective. The TEG shows promising output characteristics.

scholarly journals Radiation Dosimetry of Inhaled Radioactive Aerosols: CFPD and MCNP Transport Simulations of Radionuclides in the Lung

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Khaled Talaat ◽  
Jinxiang Xi ◽  
Phoenix Baldez ◽  
Adam Hecht
Keyword(s):  
Monte Carlo ◽  
Respiratory Tract ◽  
Radiation Dosimetry ◽  
Energy Deposition ◽  
Radiation Transport ◽  
The Body ◽  
Lung Model ◽  
Whole Body ◽  
Upper Airways ◽  
Radioactive Aerosols

AbstractDespite extensive efforts in studying radioactive aerosols, including the transmission of radionuclides in different chemical matrices throughout the body, the internal organ-specific radiation dose due to inhaled radioactive aerosols has largely relied on experimental deposition data and simplified human phantoms. Computational fluid-particle dynamics (CFPD) has proven to be a reliable tool in characterizing aerosol transport in the upper airways, while Monte Carlo based radiation codes allow accurate simulation of radiation transport. The objective of this study is to numerically assess the radiation dosimetry due to particles decaying in the respiratory tract from environmental radioactive exposures by coupling CFPD with Monte Carlo N-Particle code, version 6 (MCNP6). A physiologically realistic mouth-lung model extending to the bifurcation generation G9 was used to simulate airflow and particle transport within the respiratory tract. Polydisperse aerosols with different distributions were considered, and deposition distribution of the inhaled aerosols on the internal airway walls was quantified. The deposition mapping of radioactive aerosols was then registered to the respiratory tract of an image-based whole-body adult male model (VIP-Man) to simulate radiation transport and energy deposition. Computer codes were developed for geometry visualization, spatial normalization, and source card definition in MCNP6. Spatial distributions of internal radiation dosimetry were compared for different radionuclides (131I, 134,137Cs, 90Sr-90Y, 103Ru and 239,240Pu) in terms of the radiation fluence, energy deposition density, and dose per decay.

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