Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Intrinsic Response of Graphene Vapor Sensors
2009822 citationsYaping Dan, Ye Lu et al.Nano Lettersprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Nicholas Kybert
Since
Specialization
Citations
This map shows the geographic impact of Nicholas Kybert'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 Nicholas Kybert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas Kybert more than expected).
This network shows the impact of papers produced by Nicholas Kybert. 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 Nicholas Kybert. The network helps show where Nicholas Kybert may publish in the future.
Co-authorship network of co-authors of Nicholas Kybert
This figure shows the co-authorship network connecting the top 25 collaborators of Nicholas Kybert.
A scholar is included among the top collaborators of Nicholas Kybert based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Nicholas Kybert. Nicholas Kybert is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kybert, Nicholas, et al.. (2016). Detection of the Odor Signature of Ovarian Cancer using DNA-Decorated Carbon Nanotube Field Effect Transistor Arrays. Bulletin of the American Physical Society. 2016.1 indexed citations
Naylor, Carl H., et al.. (2015). Seeded Growth of Highly Crystalline Molybdenum Disulphide Monolayers at Controlled Locations. Bulletin of the American Physical Society. 2015.2 indexed citations
Kybert, Nicholas. (2015). Nano-Bio Hybrid Electronic Sensors for Chemical Detection and Disease Diagnostics. Scholarly Commons (University of Pennsylvania).1 indexed citations
7.
Kybert, Nicholas. (2015). Nano-bio hybrid sensors for chemical detection and disease diagnostics. Scholarly Commons (University of Pennsylvania).
Kybert, Nicholas, Gang Han, Mitchell Lerner, & A. T. Charlie Johnson. (2013). Scalable Arrays of DNA-decorated Graphene Chemical Vapor Sensors. Bulletin of the American Physical Society. 2013.1 indexed citations
11.
Lerner, Mitchell, et al.. (2013). Toward Quantifying the Electrostatic Transduction Mechanism in Carbon Nanotube Biomolecular Sensors. Bulletin of the American Physical Society. 2013.3 indexed citations
Lu, Ye, Brett Goldsmith, Nicholas Kybert, & A. T. Charlie Johnson. (2010). DNA-decorated graphene chemical sensors. Applied Physics Letters. 97(8).174 indexed citations
Dan, Yaping, Ye Lu, Nicholas Kybert, Zhengtang Luo, & A. T. Charlie Johnson. (2009). Intrinsic Response of Graphene Vapor Sensors. Nano Letters. 9(4). 1472–1475.822 indexed citations breakdown →
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.