Searching the Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

Chalcogen passivation: an in-situ method to manipulate the morphology and electrical property of GaAs nanowires.

Zai-Xing Yang | Yanxue Yin | Jiamin Sun | Luozhen Bian | Ning Han | Ziyao Zhou | Lei Shu | Fengyun Wang | Yunfa Chen | Aimin Song | Johnny C Ho
Scientific reports | 2018

Recently, owing to the large surface-area-to-volume ratio of nanowires (NWs), manipulation of their surface states becomes technologically important and being investigated for various applications. Here, an in-situ surfactant-assisted chemical vapor deposition is developed with various chalcogens (e.g. S, Se and Te) as the passivators to enhance the NW growth and to manipulate the controllable p-n conductivity switching of fabricated NW devices. Due to the optimal size effect and electronegativity matching, Se is observed to provide the best NW surface passivation in diminishing the space charge depletion effect induced by the oxide shell and yielding the less p-type (i.e. inversion) or even insulating conductivity, as compared with S delivering the intense p-type conductivity for thin NWs with the diameter of ~30 nm. Te does not only provide the surface passivation, but also dopes the NW surface into n-type conductivity by donating electrons. All of the results can be extended to other kinds of NWs with similar surface effects, resulting in careful device design considerations with appropriate surface passivation for achieving the optimal NW device performances.

Pubmed ID: 29720609

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

None found

Associated grants

None

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


GAAS (tool)

RRID:SCR_008967

An integrated software framework for efficient management, analysis and visualization of large amounts of gene expression data across replicated experiments.

View all literature mentions