A. K. McNamara

4.8k total citations · 1 hit paper
46 papers, 3.4k citations indexed

About

A. K. McNamara is a scholar working on Geophysics, Astronomy and Astrophysics and Atmospheric Science. According to data from OpenAlex, A. K. McNamara has authored 46 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Geophysics, 4 papers in Astronomy and Astrophysics and 3 papers in Atmospheric Science. Recurrent topics in A. K. McNamara's work include Geological and Geochemical Analysis (37 papers), High-pressure geophysics and materials (36 papers) and earthquake and tectonic studies (33 papers). A. K. McNamara is often cited by papers focused on Geological and Geochemical Analysis (37 papers), High-pressure geophysics and materials (36 papers) and earthquake and tectonic studies (33 papers). A. K. McNamara collaborates with scholars based in United States, United Kingdom and Germany. A. K. McNamara's co-authors include Edward J. Garnero, Shijie Zhong, Mingming Li, Peter E. van Keken, Sang‐Heon Shim, Jeroen Ritsema, A. L. Bull, Shun-ichiro Karato, Sebastian Rost and Michael Gurnis and has published in prestigious journals such as Nature, Science and Nature Communications.

In The Last Decade

A. K. McNamara

45 papers receiving 3.3k citations

Hit Papers

Continent-sized anomalous... 2016 2026 2019 2022 2016 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
A. K. McNamara United States 30 3.1k 209 171 151 84 46 3.4k
Frédéric Deschamps Taiwan 29 2.3k 0.7× 240 1.1× 170 1.0× 416 2.8× 72 0.9× 83 2.7k
Arwen Deuss United Kingdom 31 3.4k 1.1× 206 1.0× 105 0.6× 61 0.4× 36 0.4× 75 3.6k
U. Faul United States 34 3.3k 1.1× 54 0.3× 135 0.8× 252 1.7× 249 3.0× 54 3.6k
Yozo Hamano Japan 25 1.1k 0.3× 655 3.1× 478 2.8× 211 1.4× 49 0.6× 90 1.6k
Eh Tan United States 17 1.3k 0.4× 111 0.5× 91 0.5× 116 0.8× 50 0.6× 38 1.5k
J. A. Tyburczy United States 25 1.4k 0.5× 61 0.3× 134 0.8× 469 3.1× 108 1.3× 45 1.9k
Maxim Ballmer United Kingdom 25 1.6k 0.5× 61 0.3× 143 0.8× 277 1.8× 39 0.5× 60 1.8k
V. Lekić United States 29 2.8k 0.9× 148 0.7× 203 1.2× 380 2.5× 48 0.6× 75 3.0k
K. Tsuno United States 19 1.4k 0.4× 93 0.4× 128 0.7× 569 3.8× 75 0.9× 26 1.7k
Sebastian Rost United Kingdom 26 2.4k 0.8× 102 0.5× 109 0.6× 52 0.3× 40 0.5× 72 2.6k

Countries citing papers authored by A. K. McNamara

Since Specialization
Citations

This map shows the geographic impact of A. K. McNamara'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 A. K. McNamara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. K. McNamara more than expected).

Fields of papers citing papers by A. K. McNamara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. K. McNamara. 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 A. K. McNamara. The network helps show where A. K. McNamara may publish in the future.

Co-authorship network of co-authors of A. K. McNamara

This figure shows the co-authorship network connecting the top 25 collaborators of A. K. McNamara. A scholar is included among the top collaborators of A. K. McNamara 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 A. K. McNamara. A. K. McNamara is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
McNamara, A. K., et al.. (2025). How increased intrinsic viscosity of lower mantle compositional reservoirs affects their spatial and morphological stability. Earth and Planetary Science Letters. 662. 119393–119393. 1 indexed citations
2.
Munuera, Jose, Cian Gabbett, Joseph Neilson, et al.. (2025). Quantifying the Influence of Nanosheet Aspect Ratio on Network Morphology and Junction Resistance in Solution-Processed Nanosheet Networks. ACS Nano. 19(37). 33118–33133. 1 indexed citations
3.
McNamara, A. K., et al.. (2019). Dynamical investigation of a thickening ice-shell: Implications for the icy moon Europa. Icarus. 329. 251–269. 17 indexed citations
4.
Garnero, Edward J., et al.. (2017). Intermittent and lateral varying ULVZ structure at the northeastern margin of the Pacific LLSVP. Journal of Geophysical Research Solid Earth. 122(2). 1198–1220. 31 indexed citations
5.
Li, Mingming, A. K. McNamara, & Edward J. Garnero. (2014). Chemical complexity of hotspots caused by cycling oceanic crust through mantle reservoirs. Nature Geoscience. 7(5). 366–370. 132 indexed citations
6.
McNamara, A. K., et al.. (2013). Three dimensional morphology and dynamics of ultra-low velocity zones. AGUFM. 2013. 1 indexed citations
7.
Li, Mingming & A. K. McNamara. (2013). The difficulty for subducted oceanic crust to accumulate at the Earth's core‐mantle boundary. Journal of Geophysical Research Solid Earth. 118(4). 1807–1816. 64 indexed citations
8.
Cottaar, Sanne, et al.. (2012). Forward modeling the perovskite-postperovskite transition in seismically anisotropic models beneath a slab. AGU Fall Meeting Abstracts. 2012.
9.
McNamara, A. K., Edward J. Garnero, & Sebastian Rost. (2010). Tracking deep mantle reservoirs with ultra-low velocity zones. Earth and Planetary Science Letters. 299(1-2). 1–9. 181 indexed citations
10.
Bull, A. L., A. K. McNamara, & Jeroen Ritsema. (2009). Synthetic tomography of plume clusters and thermochemical piles. Earth and Planetary Science Letters. 278(3-4). 152–162. 103 indexed citations
11.
McNamara, A. K., et al.. (2008). Dynamics of the Ultra Low Velocity Zone. AGUFM. 2008. 2 indexed citations
12.
McNamara, A. K., et al.. (2007). Toward understanding Ultra Low Velocity Zone dynamics. AGU Fall Meeting Abstracts. 2007. 1 indexed citations
13.
Ritsema, Jeroen, A. K. McNamara, & A. L. Bull. (2007). Tomographic filtering of geodynamic models: Implications for model interpretation and large‐scale mantle structure. Journal of Geophysical Research Atmospheres. 112(B1). 80 indexed citations
14.
Rost, Sebastian, et al.. (2005). Detection of Subducted Lithosphere in the Midmantle From Asymmetric PP Reflections. AGU Fall Meeting Abstracts. 2005. 1 indexed citations
15.
McNamara, A. K. & Shijie Zhong. (2005). Thermochemical structures beneath Africa and the Pacific Ocean. Nature. 437(7062). 1136–1139. 361 indexed citations
16.
McNamara, A. K. & Shijie Zhong. (2004). The influence of thermochemical convection on the fixity of mantle plumes. Earth and Planetary Science Letters. 222(2). 485–500. 41 indexed citations
17.
Zhong, Shijie, J. H. Roberts, & A. K. McNamara. (2004). On the Dynamic Origin of the Crustal Dichotomy and Its Implications for early Mars Evolution. 76. 1 indexed citations
18.
McNamara, A. K., Peter E. van Keken, & Shun‐ichiro Karato. (2003). Development of finite strain in the convecting lower mantle and its implications for seismic anisotropy. Journal of Geophysical Research Atmospheres. 108(B5). 51 indexed citations
19.
McNamara, A. K., Peter E. van Keken, & Shun-ichiro Karato. (2002). Development of anisotropic structure in the Earth's lower mantle by solid-state convection. Nature. 416(6878). 310–314. 122 indexed citations
20.
McNamara, A. K., Conall Mac Niocaill, Ben A. van der Pluijm, & Rob Van der Voo. (2001). West African proximity of the Avalon terrane in the latest Precambrian. Geological Society of America Bulletin. 113(9). 1161–1170. 58 indexed citations

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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