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Mendeley readers
Attention Score in Context
| Title |
Microstructure and dynamics of vacancy-induced nanofilamentary switching network in donor doped SrTiO3−x memristors
|
|---|---|
| Published in |
Nanotechnology, November 2016
|
| DOI | 10.1088/0957-4484/27/50/505210 |
| Pubmed ID | |
| Authors |
Hussein Nili, Taimur Ahmed, Sumeet Walia, Rajesh Ramanathan, Ahmad Esmaielzadeh Kandjani, Sergey Rubanov, Jeeson Kim, Omid Kavehei, Vipul Bansal, Madhu Bhaskaran, Sharath Sriram |
| Abstract |
Donor doping of perovskite oxides has emerged as an attractive technique to create high performance and low energy non-volatile analog memories. Here, we examine the origins of improved switching performance and stable multi-state resistive switching in Nb-doped oxygen-deficient amorphous SrTiO3 (Nb:a-STO x ) metal-insulator-metal (MIM) devices. We probe the impact of substitutional dopants (i.e., Nb) in modulating the electronic structure and subsequent switching performance. Temperature stability and bias/time dependence of the switching behavior are used to ascertain the role of substitutional dopants and highlight their utility to modulate volatile and non-volatile behavior in a-STO x devices for adaptive and neuromorphic applications. We utilized a combination of transmission electron microscopy, photoluminescence emission properties, interfacial compositional evaluation, and activation energy measurements to investigate the microstructure of the nanofilamentary network responsible for switching. These results provide important insights into understanding mechanisms that govern the performance of donor-doped perovskite oxide-based memristive devices. |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 3% |
| Unknown | 28 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 17% |
| Student > Master | 4 | 14% |
| Student > Ph. D. Student | 3 | 10% |
| Professor > Associate Professor | 2 | 7% |
| Professor | 2 | 7% |
| Other | 5 | 17% |
| Unknown | 8 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Materials Science | 6 | 21% |
| Engineering | 5 | 17% |
| Physics and Astronomy | 3 | 10% |
| Chemistry | 2 | 7% |
| Unspecified | 1 | 3% |
| Other | 2 | 7% |
| Unknown | 10 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 December 2016.
All research outputs
#18,483,671
of 22,903,988 outputs
Outputs from Nanotechnology
#3,387
of 4,529 outputs
Outputs of similar age
#302,681
of 415,686 outputs
Outputs of similar age from Nanotechnology
#60
of 88 outputs
Altmetric has tracked 22,903,988 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,529 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 415,686 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 88 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.