Determination of electron backscattering coefficient of beryllium by a high-precision Monte Carlo simulation

Hussain, Abrar; Yang, Liguang; Mao, Shifeng; Da, Bo; Tőkési, K.; Ding, Zejun

doi:10.1016/j.nme.2020.100862

Cited by 29 publications

(32 citation statements)

References 117 publications

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“…These problems are properly handled by another Monte Carlo model [98], CTMC-CHARG [114], where the 3D structures are constructed by using the finite triangle mesh (FTM) method and the trapping and recombination of the holes and the energy-exhausted electrons have been taken into account. FTM relies on placing a group of planar triangles tightly on the surface of the aimed structure, where the triangles are allowed to have different geometries and sizes, enabling the construction of very complex 3D structures [137][138][139][140][141].…”

Section: Sem Imagingmentioning

confidence: 99%

“…It is worth noting that the advantage owned by the Monte Carlo method over other theoretical methods in simulating the charging effect relies essentially on the fact that it can accurately trace electron transport in solid samples by including both incident electrons and cascade secondary electrons with the updated Monte Carlo model [ 72 , 97 , 98 ]. This is achieved at the cost of considerable computation time; for the CTMC-CHARG model simulation [ 114 ] with the self-consistent method the typical CPU time is about tens of hours on a parallel computer and the memory required is about several GB [ 98 ].…”

Section: Charging Effect Simulationmentioning

confidence: 99%

“…Though the Monte Carlo models mentioned above can be used to investigate the charging effect for 3D structures, they either cannot construct very complex structures or do not take the drift of the holes and the energy-exhausted electrons into account. These problems are properly handled by another Monte Carlo model [ 98 ], CTMC-CHARG [ 114 ], where the 3D structures are constructed by using the finite triangle mesh (FTM) method and the trapping and recombination of the holes and the energy-exhausted electrons have been taken into account. FTM relies on placing a group of planar triangles tightly on the surface of the aimed structure, where the triangles are allowed to have different geometries and sizes, enabling the construction of very complex 3D structures [ 137–141 ].…”

Section: Charging Effect Simulationmentioning

confidence: 99%

See 2 more Smart Citations

Charging effect induced by electron beam irradiation: a review

Ding

et al. 2021

Science and Technology of Advanced Materials

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Charging effect frequently occurs when characterizing nonconductive materials using electrons as probes and/or signals and can impede the acquisition of useful information about the material under investigation. It is not adequate to investigate it merely by experiments, but theoretical investigations, for which the Monte Carlo method is a suitable tool, are also necessary. In this paper we review Monte Carlo simulations and selected experiments, intending to provide general insight into the charging effects induced by electron beam irradiation. We will introduce categories of the charging effect, the theoretical framework that is adopted in Monte Carlo modeling of the charging effect and present some typical simulation results. At last, with the knowledge on charging effect imparted by the above contents, we will discuss the measures that can be used for minimizing it.

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Section: Sem Imagingmentioning

confidence: 99%

Section: Charging Effect Simulationmentioning

confidence: 99%

Section: Charging Effect Simulationmentioning

confidence: 99%

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Charging effect induced by electron beam irradiation: a review

Ding

et al. 2021

Science and Technology of Advanced Materials

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“…Model simulasi biasanya memperhitungkan keadaan sistem yang ditangkap melalui nilainilai variabel yang telah ditetapkan [4]. Simulasi sering digunakan dalam mempelajari atau menganalisis perilaku kerja dari suatu sistem atau proses oleh manajemen dalam menyelesaikan pekerjaannya [5]. Sehingga dapat disimpulkan bahwa simulasi merupakan program (software) komputer yang berfungsi untuk meniru perilaku sistem nyata.…”

Section: Pendahuluanunclassified

Monte Carlo Prediksi Tingkat Prevalensi Stunting Kabupaten Lima Puluh Kota Menggunakan Metode Monte Carlo

Zaimy¹,

Defit

Nurcahyo

2021

jidt

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Stunting merupakan kondisi gagal tumbuh pada anak balita (bayi di bawah lima tahun) akibat dari kekurangan gizi kronis sehingga anak terlalu pendek untuk usianya. Menurut data yang ada, angka prevalensi stunting di Kabupaten Lima Puluh Kota tahun 2020 cukup tinggi yakni sebesar 8,28%. Hal ini menjadi perhatian pemerintah pusat dengan menetapkan Kabupaten Lima Puluh Kota sebagai salah satu Kabupaten/Kota Lokasi Fokus Intervensi Penurunan Stunting Terintegrasi Secara Nasional. Hasil penelitian ini bertujuan untuk membantu Pemerintah Kabupaten Lima Puluh Kota dalam perencanaan konvergensi program/intervensi sebagai salah satu upaya percepatan pencegahan stunting dan menurunkan persentase balita stunting di Kabupaten Lima Puluh Kota. Data penelitian ini menggunakan angka prevalensi stunting dari tahun 2018 sampai tahun 2020 yang berasal dari data jumlah balita dan jumlah balita stunting dari 22 puskesmas yang berada di Kabupaten Lima Puluh Kota. Selanjutnya data tersebut diolah menggunakan metode Monte Carlo untuk memprediksi tingkat prevalensi stunting tahun 2021. Berdasarkan pengujian yang dilakukan menggunakan metode Monte Carlo, didapatkan hasil tingkat prediksi stunting yang tertinggi berada pada puskesmas Pakan Rabaa dan puskesmas Suliki dengan angka prevalensi stunting sebesar 11,70%. Adapun tingkat akurasi yang diperoleh sebesar 93,73 %. Metode Monte Carlo cocok digunakan untuk prediksi angka prevalensi stunting di Kabupaten Lima Puluh Kota dilihat dari tingkat akurasinya yang cukup tinggi dari hasil pengolahan data.

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“…Several authors have studies theoretically and experimental about the properties of backscattered electrons (BSE) and their depend on their coefficient (BSE coefficient η), angular distributions and their energy distributions. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Backscattered Electron (BSE) Detector for Variable Pressure SEM with Monte Carlo method

Hafsi¹,

Djemoui²,

Mansour³

et al. 2022

Advances in Intelligent Systems Research

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This work deals with The study of the energy and angular distributions of backscattered electrons (BSE) detected under vacuum and with pressure, which contribute to determining the appropriate place to put the BSE detector, we examine vacuum and air gas, the diameters of detector, we discuss its influence on the energy and angular distribution of BSE in the sample by Monte Carlo simulation to find the optimum experimental parameters needed for BSE imaging in VPSEM. For this aim, we have chosen: SiO2 as dielectric material and carbon for his lower atomic number in our results under vacuum shows that the limited geometry of the detector (detector radius) causes a great reduction of the BSE signal, The analyses demonstrate the location of a BSE detector relative to a sample surface will have a strong influence on its collection efficiency.

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Determination of electron backscattering coefficient of beryllium by a high-precision Monte Carlo simulation

Cited by 29 publications

References 117 publications

Charging effect induced by electron beam irradiation: a review

Charging effect induced by electron beam irradiation: a review

Monte Carlo Prediksi Tingkat Prevalensi Stunting Kabupaten Lima Puluh Kota Menggunakan Metode Monte Carlo

Optimization of Backscattered Electron (BSE) Detector for Variable Pressure SEM with Monte Carlo method

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