Cobalt acceptor state in silicon: Temperature dependence of the energy level and capture cross section

1974 ◽  
Vol 9 (12) ◽  
pp. 5217-5221 ◽  
Author(s):  
Claude Penchina ◽  
John Moore
Keyword(s):  
Energy Level ◽  
Temperature Dependence ◽  
Cross Section ◽  
Capture Cross Section ◽  
Capture Cross ◽  
Acceptor State

scholarly journals Extracting bulk defect parameters in silicon wafers using machine learning models

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Yoann Buratti ◽  
Quoc Thong Le Gia ◽  
Josef Dick ◽  
Yan Zhu ◽  
Ziv Hameiri
Keyword(s):  
Machine Learning ◽  
Energy Level ◽  
Cross Section ◽  
Capture Cross Section ◽  
Complex Data ◽  
Capture Cross ◽  
Cross Section Ratio ◽  
Defect Energy ◽  
Section Ratio ◽  
The Impact

Abstract The performance of high-efficiency silicon solar cells is limited by the presence of bulk defects. Identification of these defects has the potential to improve cell performance and reliability. The impact of bulk defects on minority carrier lifetime is commonly measured using temperature- and injection-dependent lifetime spectroscopy and the defect parameters, such as its energy level and capture cross-section ratio, are usually extracted by fitting the Shockley-Read-Hall equation. We propose an alternative extraction approach by using machine learning trained on more than a million simulated lifetime curves, achieving coefficient of determinations between the true and predicted values of the defect parameters above 99%. In particular, random forest regressors, show that defect energy levels can be predicted with a high precision of ±0.02 eV, 87% of the time. The traditional approach of fitting to the Shockley-Read-Hall equation usually yields two sets of defect parameters, one in each half bandgap. The machine learning model is trained to predict the half bandgap location of the energy level, and successfully overcome the traditional approach’s limitation. The proposed approach is validated using experimental measurements, where the machine learning predicts defect energy level and capture cross-section ratio within the uncertainty range of the traditional fitting method. The successful application of machine learning in the context of bulk defect parameter extraction paves the way to more complex data-driven physical models which have the potential to overcome the limitation of traditional approaches and can be applied to other materials such as perovskite and thin film.

Behavior of Electron Traps Induced by Phosphidization and Nitridation of GaAs Surfaces

1998 ◽  
Vol 510 ◽  
Author(s):  
Satoshi Nozu ◽  
Koichiro Matsuda ◽  
Takashi Sugino
Keyword(s):  
Energy Level ◽  
Cross Section ◽  
Capture Cross Section ◽  
Conduction Band Edge ◽  
Capture Cross ◽  
Electron Traps ◽  
Plasma Treatments ◽  
Transient Spectroscopy ◽  
Capacitance Transient ◽  
Isothermal Capacitance Transient Spectroscopy

AbstractGaAs is treated with remote PH3 and N2 plasmas. Electron traps induced by plasma treatments are investigated by isothermal capacitance transient spectroscopy measurements. The EL2 trap is detected in the as-grown GaAs. The TP1 trap(Ec-0.26eV) is generated in GaAs phosphidized for 10min, while the TN1 trap(Ec-0.66eV) is induced in GaAs nitrided for 30min. It is found that the TP1 trap is changed to the another trap with an energy level as shallow as 0.16eV below the conduction band edge and a capture cross section as small as 1.8×10−21cm2 by treating with N2 plasma subsequently after PH3 plasma treatment.

Oxidation Induced ON1, ON2a/b Defects in 4H-SiC Characterized by DLTS

2014 ◽  
Vol 778-780 ◽  
pp. 281-284 ◽  
Author(s):  
Ian D. Booker ◽  
Hassan Abdalla ◽  
Louise Lilja ◽  
Jawad ul Hassan ◽  
Peder Bergman ◽  
...  
Keyword(s):  
Correlation Function ◽  
Energy Level ◽  
Electron Capture ◽  
Cross Section ◽  
Cross Sections ◽  
Capture Cross Section ◽  
Capture Cross ◽  
Electron Capture Cross Section ◽  
Pulse Measurement ◽  
Capture Cross Sections

The deep levels ON1and ON2a/bintroduced by oxidation into 4H-SiC are characterized via standard DLTS and via filling pulse dependent DLTS measurements. Separation of the closely spaced ON2a/bdefect is achieved by using a higher resolution correlation function (Gaver-Stehfest 4) and apparent energy level, apparent electron capture cross section and filling pulse measurement derived capture cross sections are given.

Al Implantation and Post Annealing Effects in n-Type 4H-SiC

2020 ◽  
Vol 15 (7) ◽  
pp. 777-782
Author(s):  
Woo-Young Son ◽  
Myeong-Cheol Shin ◽  
Michael Schweitz ◽  
Sang-Kwon Lee ◽  
Sang-Mo Koo
Keyword(s):  
Energy Level ◽  
Ion Implantation ◽  
Cross Section ◽  
Epitaxial Layer ◽  
Capture Cross Section ◽  
Deep Level ◽  
Capture Cross ◽  
Trap Concentration ◽  
Post Annealing ◽  
Measurement Results

We investigated the post annealing effect of Al implantation in n-type 4H-SiC by using deep level transient spectroscopy (DLTS). The Schottky contacts were deposited on n-type epitaxial layer on 4H-SiC substrates and the effect of Al-implantation on the structures has been examined with and without post-annealing process. n-type epitaxial layer on a 4H-SiC substrate was implanted with Al-ion at an energy of 300 keV and a dose of 1.0 × 1015 cm–2. The effect of annealing has been studied by annealing the structures at 1700 C after ion implantation. DLTS measurements were performed before and after ion implantation, in order to determine the characteristics and magnitudes of the resulting electrical defects. Based on the DLTS measurement results, typical Z1/2 peak of SiC is obtained in reference samples without implantation. Z1/2 of the non-annealed samples had an energy level of 0.831 eV. The energy level was found to be deeper after the implantation whereas the capture cross section is about 60 times smaller and the trap concentration increases by a factor of 10. In other words, the Al-ion implantation clearly influenced the electrical characteristics of the sample and consequently also the DLTS measurement results. After post-implantation annealing, a new shallow defect (I2Al-A) was identified (∼0.028 eV) with a capture cross section of 1.9 × 10–21 cm –2 and a trap concentration of 4.8 × 1015 cm–3.

Temperature dependence of electron-capture cross section of localized states ina−Si:H

1983 ◽  
Vol 27 (8) ◽  
pp. 5184-5187 ◽  
Author(s):  
H. Okushi ◽  
T. Takahama ◽  
Y. Tokumaru ◽  
S. Yamasaki ◽  
H. Oheda ◽  
...  
Keyword(s):  
Temperature Dependence ◽  
Electron Capture ◽  
Cross Section ◽  
Capture Cross Section ◽  
Localized States ◽  
Capture Cross ◽  
Electron Capture Cross Section
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