Betavoltaic study of a GaN p-i-n structure grown by metal-organic vapour phase epitaxy with a Ni-63 source

Kuruoğlu, Neslihan Ayarcı; Özdemi̇r, Orhan; Bozkurt, Kutsal

doi:10.1016/j.tsf.2017.07.033

Cited by 22 publications

(5 citation statements)

References 26 publications

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“…Previous studies on the conversion of 63 Ni beta particle energy into electricity by means of GaN-based p-n junctions reported output powers from 23 pW to 0.57 nW [2][3][4][5]. Note that, in practice, the power output is typically lower than theor etical expectations, which are often above 2 nW [6].…”

Section: Introductionmentioning

confidence: 94%

Modeling, design, fabrication and experimentation of a GaN-based,⁶³Ni betavoltaic battery

Munson¹,

Gaimard²,

Merghem³

et al. 2017

J. Phys. D: Appl. Phys.

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GaN is a durable, radiation hard and wide-bandgap semiconductor material, making it ideal for usage with betavoltaic batteries. This paper describes the design, fabrication and experimental testing of 1 cm 2 GaN-based betavoltaic batteries (that achieve an output power of 2.23 nW) along with a full model that accurately simulates the device performance which is the highest to date (to the best of our knowledge) for GaN-based devices with a 63 Ni source.

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Section: Introductionmentioning

confidence: 94%

Modeling, design, fabrication and experimentation of a GaN-based,⁶³Ni betavoltaic battery

Munson¹,

Gaimard²,

Merghem³

et al. 2017

J. Phys. D: Appl. Phys.

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“…As follows from Equations ( 13) and ( 15), the J 0 increase leads to a decrease in both V oc and FF, thus to additional decreasing the cell efficiency. Experimental studies in the most cases also gave for V oc in GaN and 4H-SiC converters values about or below 1 V [84][85][86][87]. Even when measured V oc values were as high as 1.5-2.1 V [38,88,89], FF is rather small (0.5-0.6) that decreases the converter efficiency.…”

Section: Calculation Of Betavoltaic Cell Output Parametersmentioning

confidence: 99%

Prediction of Betavoltaic Battery Parameters

Yakimov

2023

Energies

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The approaches for predicting output parameters of betavoltaic batteries are reviewed. The need to develop a strategy for predicting these parameters with sufficient accuracy for the optimization of betavoltaic cell design without using the simple trial and error approach is discussed. The strengths and weaknesses of previously proposed approaches for the prediction are considered. Possible reasons for the difference between the calculated and measured parameters are analyzed. The depth dependencies of beta particles deposited energy for Si, SiC, GaN, and Ga2O3 and 20% purity 63Ni and titanium tritide as radioisotope sources are simulated using the Monte Carlo algorithm taking into account the full beta energy spectrum, the isotropic angular distribution of emitted electrons and the self-absorption inside the radioisotope source for homogeneously distributed emitting points. The maximum short circuit current densities for the same semiconductors and radioisotope sources are calculated. The methodology allowing the prediction of betavoltaic cell output parameters with accuracy no worse than 30% is described. The results of experimental and theoretical investigations of the temperature dependence of betavoltaic cell output parameters are briefly discussed. The radiation damage by electrons with the subthreshold energy and the need to develop models for its prediction is considered.

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“…GaN-based diodes have been widely used in ultraviolet light detection [1], high energy particle detection [2,3], preparation of nuclear batteries [4][5][6][7] because of their high radiation damage threshold, wide direct bandgap, high breakdown filed (3 × 10 7 V m −1 ) [6], and high electron mobility [8]. Generally, increasing the active area of the diodes is beneficial to increasing the output power of the diodes in the energy conversion system [9].…”

Section: Introductionmentioning

confidence: 99%

Analysis of surface morphology at leakage current sources on large-area GaN-based p-i-n diodes

Yang,

Liu

et al. 2023

Semicond. Sci. Technol.

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This paper investigated the relationship between the leakage current of 8 GaN-based diodes with the large size of 8×8 2 under reverse bias and their responsivity, and it was found that reducing leakage current is an important way to improve the conversion effective of diodes. Leakage analysis was performed separately for two sizes of diodes. The location of the leakage was found by emission microscope, and the morphology of the leakage point was analyzed using a focus ion beam and a scanning electron microscope. It was found that structural defects, which may be caused by drops of impurities during material growth, can form large leakage channels.

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Betavoltaic study of a GaN p-i-n structure grown by metal-organic vapour phase epitaxy with a Ni-63 source

Cited by 22 publications

References 26 publications

Modeling, design, fabrication and experimentation of a GaN-based,⁶³Ni betavoltaic battery

Modeling, design, fabrication and experimentation of a GaN-based,⁶³Ni betavoltaic battery

Prediction of Betavoltaic Battery Parameters

Analysis of surface morphology at leakage current sources on large-area GaN-based p-i-n diodes

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Betavoltaic study of a GaN p-i-n structure grown by metal-organic vapour phase epitaxy with a Ni-63 source

Cited by 22 publications

References 26 publications

Modeling, design, fabrication and experimentation of a GaN-based,63Ni betavoltaic battery

Modeling, design, fabrication and experimentation of a GaN-based,63Ni betavoltaic battery

Prediction of Betavoltaic Battery Parameters

Analysis of surface morphology at leakage current sources on large-area GaN-based p-i-n diodes

Contact Info

Product

Resources

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Modeling, design, fabrication and experimentation of a GaN-based,⁶³Ni betavoltaic battery

Modeling, design, fabrication and experimentation of a GaN-based,⁶³Ni betavoltaic battery