Mark Barnell

8.8k citations
44 papers · 5.9k · 6 hit papers · h-index 20

Impact in

Papers in

Mark Barnell

41 papers receiving 5.8k citations

Mark Barnell's Hit Papers

Three-dimensional memristor circuits as complex neural networks 2020 · 280 citations
2800+3+6Years since publication50010001.5k

Peers

Mark Barnell
Comparison fields: 5 of 74
  • Cellular and Molecular Neuroscience 2.7k
  • Electrical and Electronic Engineering 5.7k
  • Polymers and Plastics 771
  • Cognitive Neuroscience 1.0k
  • Artificial Intelligence 926
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Citations per year

Countries citing papers authored by Mark Barnell

Since Specialization
Citations

This map shows the geographic impact of Mark Barnell's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mark Barnell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Barnell more than expected).

Fields of papers citing papers by Mark Barnell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark Barnell. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mark Barnell. The network helps show where Mark Barnell may publish in the future.

Co-authors

The 25 scholars most cited alongside Mark Barnell, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mark Barnell Line = papers co-authored together Mark Barnell links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing
Hit paper breakdown →
20161899
2
Analogue signal and image processing with large memristor crossbars
Hit paper breakdown →
2017986
3
Efficient and self-adaptive in-situ learning in multilayer memristor neural networks
Hit paper breakdown →
2018711
4 2017339
5
Anatomy of Ag/Hafnia‐Based Selectors with 1010 Nonlinearity
Hit paper breakdown →
2017324
6
Reinforcement learning with analogue memristor arrays
Hit paper breakdown →
2019289
7
Three-dimensional memristor circuits as complex neural networks
Hit paper breakdown →
2020280
8 2016219
9 2017190
10 2015120
11 201496
12 201781
13 201656
14 201841
15 201640
16 202039
17 202128
18 202222
19 201820
20 201819

About Mark Barnell

Mark Barnell is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Computer Vision and Pattern Recognition, Cognitive Neuroscience and Hardware and Architecture, having authored 44 papers that have together received 5.9k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (35 papers), Neuroscience and Neural Engineering (21 papers), Ferroelectric and Negative Capacitance Devices (21 papers), CCD and CMOS Imaging Sensors (7 papers), Photoreceptor and optogenetics research (6 papers), Advanced Neural Network Applications (4 papers), Neural dynamics and brain function (4 papers) and Physical Unclonable Functions (PUFs) and Hardware Security (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (2.7k citations), Electrical and Electronic Engineering (5.7k citations), Polymers and Plastics (771 citations), Cognitive Neuroscience (1.0k citations) and Artificial Intelligence (926 citations). Mark Barnell has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Qing Wu, J. Joshua Yang, Hao Jiang, Qiangfei Xia, Zhongrui Wang, Peng Lin, R. Stanley Williams, Ning Ge, John Paul Strachan and Miao Hu. Their work appears in journals such as Nature Communications, Nature Electronics, Advanced Materials, Nanoscale and Scientific Reports.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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