David J Barnes

2.6k total citations
54 papers, 1.8k citations indexed

About

David J Barnes is a scholar working on Astronomy and Astrophysics, Instrumentation and Nuclear and High Energy Physics. According to data from OpenAlex, David J Barnes has authored 54 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Astronomy and Astrophysics, 26 papers in Instrumentation and 6 papers in Nuclear and High Energy Physics. Recurrent topics in David J Barnes's work include Galaxies: Formation, Evolution, Phenomena (40 papers), Astronomy and Astrophysical Research (26 papers) and Astrophysical Phenomena and Observations (10 papers). David J Barnes is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (40 papers), Astronomy and Astrophysical Research (26 papers) and Astrophysical Phenomena and Observations (10 papers). David J Barnes collaborates with scholars based in United Kingdom, United States and Netherlands. David J Barnes's co-authors include Scott T. Kay, Joop Schaye, Yannick M Bahé, Ian G. McCarthy, Claudio Dalla Vecchia, P. Thomas, R. G. Bower, Adrian Jenkins, Matthieu Schaller and Tom Theuns and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, Wear and Journal of Cereal Science.

In The Last Decade

David J Barnes

53 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David J Barnes United Kingdom 25 1.5k 802 295 84 74 54 1.8k
N. G. Douglas Australia 16 618 0.4× 372 0.5× 53 0.2× 1 0.0× 32 0.4× 40 827
Paul Harding United States 28 2.0k 1.4× 1.0k 1.3× 142 0.5× 26 0.4× 67 2.2k
Andrew C. Phillips United States 22 2.1k 1.4× 1.3k 1.6× 150 0.5× 75 1.0× 32 2.1k
L. M. Young United States 22 1.3k 0.9× 470 0.6× 143 0.5× 22 0.3× 43 1.5k
Ji Wang United States 16 624 0.4× 211 0.3× 22 0.1× 4 0.0× 3 0.0× 74 844
Julien Carron Switzerland 16 684 0.5× 117 0.1× 201 0.7× 41 0.6× 52 901
E. R. Carrasco Chile 15 656 0.4× 292 0.4× 103 0.3× 19 0.3× 55 739
H. Lux United Kingdom 18 577 0.4× 298 0.4× 499 1.7× 32 0.4× 39 1.1k
Abdurrouf Indonesia 10 826 0.6× 421 0.5× 54 0.2× 1 0.0× 19 0.3× 41 980
J. Varela Spain 25 1.7k 1.1× 1.2k 1.5× 150 0.5× 58 0.8× 73 1.9k

Countries citing papers authored by David J Barnes

Since Specialization
Citations

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

Fields of papers citing papers by David J Barnes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J Barnes. 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 David J Barnes. The network helps show where David J Barnes may publish in the future.

Co-authorship network of co-authors of David J Barnes

This figure shows the co-authorship network connecting the top 25 collaborators of David J Barnes. A scholar is included among the top collaborators of David J Barnes 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 David J Barnes. David J Barnes 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.
Anbajagane, Dhayaa, A. E. Evrard, Arya Farahi, et al.. (2020). Stellar property statistics of massive haloes from cosmological hydrodynamics simulations: common kernel shapes. Monthly Notices of the Royal Astronomical Society. 495(1). 686–704. 22 indexed citations
2.
Lim, Seunghwan, D. Scott, Arif Babul, et al.. (2020). Is there enough star formation in simulated protoclusters?. Monthly Notices of the Royal Astronomical Society. 501(2). 1803–1822. 20 indexed citations
3.
Barnes, David J, Rahul Kannan, Mark Vogelsberger, & Federico Marinacci. (2020). Radiative AGN feedback on a moving mesh: The impact of the galactic disc and dust physics on outflow properties. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 13 indexed citations
4.
Su, Yuanyuan, Yanbin Zhang, Gongbo Liang, et al.. (2020). A deep learning view of the census of galaxy clusters in IllustrisTNG. Monthly Notices of the Royal Astronomical Society. 498(4). 5620–5628. 19 indexed citations
5.
He, Qiuhan, Hongyu Li, Ran Li, et al.. (2020). Constraining the inner density slope of massive galaxy clusters. Monthly Notices of the Royal Astronomical Society. 496(4). 4717–4733. 20 indexed citations
6.
Wang, Yunchong, Mark Vogelsberger, D. Xu, et al.. (2019). Early-type galaxy density profiles from IllustrisTNG – I. Galaxy correlations and the impact of baryons. Monthly Notices of the Royal Astronomical Society. 491(4). 5188–5215. 37 indexed citations
7.
Lovell, Mark R., David J Barnes, Yannick M Bahé, et al.. (2019). The signal of decaying dark matter with hydrodynamical simulations. Monthly Notices of the Royal Astronomical Society. 485(3). 4071–4089. 7 indexed citations
8.
Wang, Yunchong, Mark Vogelsberger, D. Xu, et al.. (2019). Early-type galaxy density profiles from IllustrisTNG – II. Evolutionary trend of the total density profile. Monthly Notices of the Royal Astronomical Society. 490(4). 5722–5738. 24 indexed citations
9.
Barnes, David J, Rahul Kannan, Mark Vogelsberger, et al.. (2019). Enhancing AGN efficiency and cool-core formation with anisotropic thermal conduction. Monthly Notices of the Royal Astronomical Society. 488(3). 3003–3013. 26 indexed citations
10.
Kay, Scott T., et al.. (2019). An application of machine learning techniques to galaxy cluster mass estimation using the MACSIS simulations. Monthly Notices of the Royal Astronomical Society. 484(2). 1526–1537. 28 indexed citations
11.
Lagos, Claudia del P., Joop Schaye, Yannick M Bahé, et al.. (2018). The connection between mass, environment, and slow rotation in simulated galaxies. Monthly Notices of the Royal Astronomical Society. 476(4). 4327–4345. 63 indexed citations
12.
Vecchia, Claudio Dalla, et al.. (2018). The evolution of the luminosity function faint end of cluster galaxies in the Cluster-EAGLE simulation. Proceedings of the International Astronomical Union. 14(S344). 495–497.
13.
Barnes, David J, Mark Vogelsberger, Rahul Kannan, et al.. (2018). A census of cool-core galaxy clusters in IllustrisTNG. Monthly Notices of the Royal Astronomical Society. 481(2). 1809–1831. 67 indexed citations
14.
Barnes, David J, Alvina Y L On, Kinwah Wu, & Daisuke Kawata. (2018). SPMHD simulations of structure formation. Monthly Notices of the Royal Astronomical Society. 476(3). 2890–2904. 9 indexed citations
15.
Barnes, David J, et al.. (2016). The impact of baryons on massive galaxy clusters: halo structure and cluster mass estimates. Monthly Notices of the Royal Astronomical Society. 465(3). 3361–3378. 74 indexed citations
16.
Barnes, David J, et al.. (2016). The redshift evolution of massive galaxy clusters in the MACSIS simulations. Monthly Notices of the Royal Astronomical Society. 465(1). 213–233. 93 indexed citations
17.
Kawata, Daisuke, Takashi Okamoto, B. K. Gibson, David J Barnes, & Renyue Cen. (2012). Calibrating an updated smoothed particle hydrodynamics scheme within gcd+. Monthly Notices of the Royal Astronomical Society. 428(3). 1968–1979. 36 indexed citations
18.
Barnes, David J & Junia V. Melo. (2003). Management of chronic myeloid leukemia: Targets for molecular therapy. Seminars in Hematology. 40(1). 34–49. 4 indexed citations
19.
Barbenel, J.C., David J Barnes, & Gordon Lowe. (1986). The prediction of high shear whole blood viscosity. Clinical Hemorheology and Microcirculation. 6(5). 405–412. 2 indexed citations
20.
Barnes, David J, et al.. (1975). The effect of temperature and environment on the friction of some well characterized refractory surfaces. Wear. 31(1). 63–76. 7 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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