Retrieving the electronic properties of silicon nanocrystals embedded in a dielectric matrix by low-loss EELS

Nanoscale ◽  
2014 ◽  
Vol 6 (24) ◽  
pp. 14971-14983 ◽  
Author(s):  
Alberto Eljarrat ◽  
Lluís López-Conesa ◽  
Julian López-Vidrier ◽  
Sergi Hernández ◽  
Blas Garrido ◽  
...  

A novel approach to disentangle the electronic features corresponding to pure Si-NCs from their surrounding dielectric material.

2012 ◽  
Vol 116 (6) ◽  
pp. 3988-3994 ◽  
Author(s):  
Estrella Ramos ◽  
B. Marel Monroy ◽  
Juan Carlos Alonso ◽  
Luis E. Sansores ◽  
Roberto Salcedo ◽  
...  

2007 ◽  
Vol 994 ◽  
Author(s):  
Rinaldo Trotta ◽  
Antonio Polimeni ◽  
Marco Felici ◽  
Giorgio Pettinari ◽  
Mario Capizzi ◽  
...  

AbstractThe capability of hydrogen to passivate nitrogen in dilute nitrides is exploited to in-plane engineer the electronic properties of Ga(AsN)/GaAs heterostructures. Two methods are presented: i) by deposition of hydrogen-opaque metallic masks on Ga(AsN) and subsequent hydrogen irradiation, we artificially create zones of the crystal having the band gap of untreated Ga(AsN) surrounded by GaAs-like barriers; ii) by employing an intense (∼100 nA) and narrow (∼100 nm) beam of electrons, we dissociate the complexes formed by N and H in a spatially delimited part of a hydrogenated Ga(AsN) sample. As a consequence, in the spatial regions irradiated by the electron beam, hydrogenated Ga(AsN) recovers the smaller energy gap it had before hydrogen implantation.


2019 ◽  
Vol 69 (5) ◽  
pp. 464-468
Author(s):  
Mandar K. Bivalkar ◽  
Bambam Kumar ◽  
Dharmendra Singh

Low dielectric materials referred as weak targets are very difficult to detect behind the wall in through wall imaging (TWI) due to strong reflections from wall. TWI Experimental data collected for low dielectric target behind the wall and transceiver on another side of the wall. Recently several researchers are using low-rank approximation (LRA) for reduction of random noise in the various data. Explore the possibilities of using LRA for TWI data for improving the detection of low dielectric material. A novel approach using modification of LRA with exploiting the noise subspace in singular value decomposition (SVD) to detect weak target behind the wall is introduced. LRA consider data has low rank in f-x domain for noisy data, local windows are implemented in LRA approach to satisfy the principle assumptions required by the LRA algorithm itself. Decomposed TWI data in the noise space of the SVD to detect the weak target adaptively. Results for modified LRA for detection of weak target behind the wall are very encouraging over LRA.


2012 ◽  
Vol 95 (11) ◽  
pp. 3363-3365 ◽  
Author(s):  
Qingwei Liao ◽  
Lingxia Li ◽  
Xiang Ren ◽  
Xiaoxu Yu ◽  
Dong Guo ◽  
...  

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