Nature of impurity states in doped amorphous silicon

2000 ◽  
Vol 61 (15) ◽  
pp. 10206-10210 ◽  
Author(s):  
G. Allan ◽  
C. Delerue ◽  
M. Lannoo
Keyword(s):  
Amorphous Silicon ◽  
Impurity States

Nature of the Impurity States Arising from Transition Metals in Hydrogenated Amorphous Silicon

1989 ◽  
Vol 155 (2) ◽  
pp. K113-K118
Author(s):  
F. S. Nasredinov ◽  
M. M. Mezdrogina ◽  
P. P. Seregin ◽  
U. Zh. Abdumanapov ◽  
U. S. Tursunov
Keyword(s):  
Transition Metals ◽  
Amorphous Silicon ◽  
Hydrogenated Amorphous Silicon ◽  
Impurity States ◽  
Hydrogenated Amorphous

Gd-doping effects on properties of amorphous silicon films prepared by electron beam evaporations

1998 ◽  
Vol 13 (7) ◽  
pp. 1795-1798 ◽  
Author(s):  
Runjin Gan ◽  
Fengmin Liu ◽  
Li Qi ◽  
Jizheng Wang
Keyword(s):  
Electron Beam ◽  
Amorphous Silicon ◽  
Esr Spectra ◽  
Electron Beam Evaporation ◽  
Silicon Films ◽  
Impurity States ◽  
Doping Effects ◽  
Electron Beam Evaporation Technique ◽  
Spin Resonance ◽  
Evaporation Technique

Gd-doped amorphous silicon films have been prepared by the electron beam evaporation technique, employing the experimental methods of dc conductivity temperature properties, ESR (electron spin resonance) spectra, and optical band gap Eopt measurements. We have investigated the optical and electrical properties of the films. The results show that at 290 K < T < 330 K, hopping conduction in Gd impurity states near Fermi level is predominant, and at 330 K < T < 500 K extended state conduction dominates due to electrons exited from the impurity states. At a Gd concentration of about 1.0 at.% spin density Ns, peak-peak width ΔBpp and line-shape factor l of ESR spectra change their dependence on Gd contents. The optical gap of the films narrows with increasing Gd contents in the films from 1.68 eV to 0.42 eV. The results were explained on the basis of the partial compensation of Gd atoms for dangling bonds .

Machine learning reveals the complexity of dense amorphous silicon

Nature ◽  
2021 ◽  
Vol 589 (7840) ◽  
pp. 22-23
Author(s):  
Paul F. McMillan
Keyword(s):  
Machine Learning ◽  
Amorphous Silicon

Computer simulation study about the dependence of amorphous silicon photonic waveguides efficiency on the material quality

2020 ◽  
Vol 90 (3) ◽  
pp. 30502
Author(s):  
Alessandro Fantoni ◽  
João Costa ◽  
Paulo Lourenço ◽  
Manuela Vieira
Keyword(s):  
Amorphous Silicon ◽  
High Throughput Screening ◽  
Simulation Analysis ◽  
Low Cost ◽  
Deposition Process ◽  
Large Area ◽  
Sidewall Roughness ◽  
Sensing Applications ◽  
Fabrication Defects ◽  
The Impact

Amorphous silicon PECVD photonic integrated devices are promising candidates for low cost sensing applications. This manuscript reports a simulation analysis about the impact on the overall efficiency caused by the lithography imperfections in the deposition process. The tolerance to the fabrication defects of a photonic sensor based on surface plasmonic resonance is analysed. The simulations are performed with FDTD and BPM algorithms. The device is a plasmonic interferometer composed by an a-Si:H waveguide covered by a thin gold layer. The sensing analysis is performed by equally splitting the input light into two arms, allowing the sensor to be calibrated by its reference arm. Two different 1 × 2 power splitter configurations are presented: a directional coupler and a multimode interference splitter. The waveguide sidewall roughness is considered as the major negative effect caused by deposition imperfections. The simulation results show that plasmonic effects can be excited in the interferometric waveguide structure, allowing a sensing device with enough sensitivity to support the functioning of a bio sensor for high throughput screening. In addition, the good tolerance to the waveguide wall roughness, points out the PECVD deposition technique as reliable method for the overall sensor system to be produced in a low-cost system. The large area deposition of photonics structures, allowed by the PECVD method, can be explored to design a multiplexed system for analysis of multiple biomarkers to further increase the tolerance to fabrication defects.

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