silicon interface
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Nanomaterials ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 43
Author(s):  
Andrea G. Marrani ◽  
Alessandro Motta ◽  
Francesco Amato ◽  
Ricardo Schrebler ◽  
Robertino Zanoni ◽  
...  

The wafer-scale integration of graphene is of great importance in view of its numerous applications proposed or underway. A good graphene–silicon interface requires the fine control of several parameters and may turn into a high-cost material, suitable for the most advanced applications. Procedures that can be of great use for a wide range of applications are already available, but others are to be found, in order to modulate the offer of different types of materials, at different levels of sophistication and use. We have been exploring different electrochemical approaches over the last 5 years, starting from graphene oxide and resulting in graphene deposited on silicon-oriented surfaces, with the aim of understanding the reactions leading to the re-establishment of the graphene network. Here, we report how a proper choice of both the chemical environment and electrochemical conditions can lead to a more controlled and tunable graphene–Si(111) interface. This can also lead to a deeper understanding of the electrochemical reactions involved in the evolution of graphene oxide to graphene under electrochemical reduction. Results from XPS, the most suitable tool to follow the presence and fate of functional groups at the graphene surface, are reported, together with electrochemical and Raman findings.


Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3068
Author(s):  
Gerardo Saggese ◽  
Antonio Giuseppe Maria Strollo

High-density microelectrode arrays allow the neuroscientist to study a wider neurons population, however, this causes an increase of communication bandwidth. Given the limited resources available for an implantable silicon interface, an on-fly data reduction is mandatory to stay within the power/area constraints. This can be accomplished by implementing a spike detector aiming at sending only the useful information about spikes. We show that the novel non-linear energy operator called ASO in combination with a simple but robust noise estimate, achieves a good trade-off between performance and consumption. The features of the investigated technique make it a good candidate for implantable BMIs. Our proposal is tested both on synthetic and real datasets providing a good sensibility at low SNR. We also provide a 1024-channels VLSI implementation using a Random-Access Memory composed by latches to reduce as much as possible the power consumptions. The final architecture occupies an area of 2.3 mm2, dissipating 3.6 µW per channels. The comparison with the state of art shows that our proposal finds a place among other methods presented in literature, certifying its suitability for BMIs.


2021 ◽  
Vol 551 ◽  
pp. 149461
Author(s):  
Holger Fiedler ◽  
Jérôme Leveneur ◽  
Mitchell Nancarrow ◽  
David R.G. Mitchell ◽  
John Kennedy

2021 ◽  
Vol 1841 (1) ◽  
pp. 012003
Author(s):  
J Dulanto ◽  
M A Sevillano-Bendezú ◽  
R Grieseler ◽  
J A Guerra ◽  
L Korte ◽  
...  

2020 ◽  
Vol 102 (24) ◽  
Author(s):  
J. Courtin ◽  
S. Tricot ◽  
G. Delhaye ◽  
P. Turban ◽  
B. Lépine ◽  
...  

2020 ◽  
Vol 82 (5) ◽  
pp. 522-528
Author(s):  
N. E. Esipova ◽  
A. I. Rusanov ◽  
V. D. Sobolev

2020 ◽  
Vol 7 (20) ◽  
pp. 2000957
Author(s):  
Jakub Holovský ◽  
Silvia Martín De Nicolás ◽  
Stefaan De Wolf ◽  
Christophe Ballif

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