D. T. Casey

10.5k total citations
91 papers, 1.8k citations indexed

About

D. T. Casey is a scholar working on Nuclear and High Energy Physics, Radiation and Mechanics of Materials. According to data from OpenAlex, D. T. Casey has authored 91 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Nuclear and High Energy Physics, 35 papers in Radiation and 32 papers in Mechanics of Materials. Recurrent topics in D. T. Casey's work include Laser-Plasma Interactions and Diagnostics (74 papers), Nuclear Physics and Applications (33 papers) and Laser-induced spectroscopy and plasma (28 papers). D. T. Casey is often cited by papers focused on Laser-Plasma Interactions and Diagnostics (74 papers), Nuclear Physics and Applications (33 papers) and Laser-induced spectroscopy and plasma (28 papers). D. T. Casey collaborates with scholars based in United States, United Kingdom and Austria. D. T. Casey's co-authors include R. D. Petrasso, J. A. Frenje, V. A. Smalyuk, O. L. Landen, D. S. Clark, T. C. Sangster, A. B. Zylstra, M. Gatu Johnson, F. H. Séguin and D. D. Meyerhofer and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Physical Review Letters.

In The Last Decade

D. T. Casey

85 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. T. Casey United States 25 1.5k 607 535 503 479 91 1.8k
A. B. Zylstra United States 24 1.3k 0.9× 577 1.0× 367 0.7× 489 1.0× 489 1.0× 104 1.6k
D. C. Wilson United States 25 1.3k 0.9× 577 1.0× 475 0.9× 721 1.4× 466 1.0× 118 2.0k
N. Izumi United States 25 1.6k 1.1× 783 1.3× 751 1.4× 556 1.1× 621 1.3× 138 2.0k
A. L. Kritcher United States 23 1.1k 0.8× 601 1.0× 280 0.5× 824 1.6× 734 1.5× 76 1.7k
T. Ma United States 21 1.2k 0.8× 693 1.1× 443 0.8× 703 1.4× 648 1.4× 115 1.7k
S. Le Pape United States 25 1.6k 1.0× 734 1.2× 464 0.9× 966 1.9× 752 1.6× 79 2.1k
A. S. Moore United States 20 900 0.6× 508 0.8× 264 0.5× 413 0.8× 273 0.6× 104 1.2k
O. S. Jones United States 28 2.1k 1.4× 1.2k 1.9× 293 0.5× 1.1k 2.1× 829 1.7× 94 2.6k
R. P. J. Town United States 27 1.9k 1.2× 1.0k 1.7× 244 0.5× 814 1.6× 706 1.5× 54 2.1k
A. G. MacPhee United States 27 1.4k 0.9× 812 1.3× 482 0.9× 1.1k 2.1× 377 0.8× 128 2.2k

Countries citing papers authored by D. T. Casey

Since Specialization
Citations

This map shows the geographic impact of D. T. Casey'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 D. T. Casey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. T. Casey more than expected).

Fields of papers citing papers by D. T. Casey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. T. Casey. 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 D. T. Casey. The network helps show where D. T. Casey may publish in the future.

Co-authorship network of co-authors of D. T. Casey

This figure shows the co-authorship network connecting the top 25 collaborators of D. T. Casey. A scholar is included among the top collaborators of D. T. Casey 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 D. T. Casey. D. T. Casey 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.
Spears, B. K., S. Brandon, D. T. Casey, et al.. (2025). Predicting fusion ignition at the National Ignition Facility with physics-informed deep learning. Science. 389(6761). 727–731. 2 indexed citations
2.
Adrian, P. J., B. Bachmann, D. T. Casey, et al.. (2025). Constraining the 3He +3He Gamow energy probed in high energy density plasmas at the National Ignition Facility. Physics of Plasmas. 32(2).
3.
Johnson, M. Gatu, J. H. Kunimune, G.P.A. Berg, et al.. (2024). The next-generation magnetic recoil spectrometer (MRSnext) on OMEGA and NIF for diagnosing ion temperature, yield, areal density, and alpha heating. Review of Scientific Instruments. 95(8). 2 indexed citations
4.
Adrian, P. J., R. M. Bionta, D. T. Casey, et al.. (2024). Diagnosing hot-spot symmetry in surrogate ignition experiments via secondary DT-neutron spectroscopy at the NIF. Physics of Plasmas. 31(8). 2 indexed citations
5.
Hurricane, O. A., D. A. Callahan, D. T. Casey, et al.. (2024). Energy Principles of Scientific Breakeven in an Inertial Fusion Experiment. Physical Review Letters. 132(6). 65103–65103. 36 indexed citations
6.
Kunimune, J. H., D. T. Casey, Bogdan Kustowski, et al.. (2024). 3D reconstruction of an inertial-confinement fusion implosion with neural networks using multiple heterogeneous data sources. Review of Scientific Instruments. 95(7). 2 indexed citations
7.
Dewald, E. L., D. S. Clark, D. T. Casey, et al.. (2022). Compensating cylindrical Hohlraum mode 4 asymmetry via capsule thickness tailoring and effects on implosions. Physics of Plasmas. 29(9). 2 indexed citations
8.
9.
Hartouni, E. P., R. M. Bionta, D. T. Casey, et al.. (2021). Interpolating individual line-of-sight neutron spectrometer measurements onto the “sky” at the National Ignition Facility (NIF). Review of Scientific Instruments. 92(4). 43512–43512. 4 indexed citations
10.
Izumi, N., D. T. Woods, N. B. Meezan, et al.. (2021). Low mode implosion symmetry sensitivity in low gas-fill NIF cylindrical hohlraums. Physics of Plasmas. 28(2). 9 indexed citations
11.
Callahan, D. A., O. A. Hurricane, A. L. Kritcher, et al.. (2020). A simple model to scope out parameter space for indirect drive designs on NIF. Physics of Plasmas. 27(7). 13 indexed citations
12.
Volegov, P. L., S. H. Batha, V. Geppert-Kleinrath, et al.. (2020). Density determination of the thermonuclear fuel region in inertial confinement fusion implosions. Journal of Applied Physics. 127(8). 19 indexed citations
13.
Clark, D. S., C. R. Weber, J. L. Milovich, et al.. (2019). Three-dimensional modeling and hydrodynamic scaling of National Ignition Facility implosions. Physics of Plasmas. 26(5). 63 indexed citations
14.
Berger, R. L., C. A. Thomas, K. L. Baker, et al.. (2019). Stimulated backscatter of laser light from BigFoot hohlraums on the National Ignition Facility. Physics of Plasmas. 26(1). 20 indexed citations
15.
Remington, B. A., Hyesook Park, D. T. Casey, et al.. (2018). Rayleigh–Taylor instabilities in high-energy density settings on the National Ignition Facility. Proceedings of the National Academy of Sciences. 116(37). 18233–18238. 83 indexed citations
16.
17.
Chen, Hui, T. Ma, R. Nora, et al.. (2017). On krypton-doped capsule implosion experiments at the National Ignition Facility. Physics of Plasmas. 24(7). 18 indexed citations
18.
Johnson, M. Gatu, J. A. Frenje, R. M. Bionta, et al.. (2016). High-resolution measurements of the DT neutron spectrum using new CD foils in the Magnetic Recoil neutron Spectrometer (MRS) on the National Ignition Facility. Review of Scientific Instruments. 87(11). 11D816–11D816. 7 indexed citations
19.
Ma, T., P. K. Patel, M. B. Schneider, et al.. (2016). Development of a krypton-doped gas symmetry capsule platform for x-ray spectroscopy of implosion cores on the NIF. Review of Scientific Instruments. 87(11). 11E327–11E327. 14 indexed citations
20.
Bionta, R. M., et al.. (2016). Fuel areal density distributions derived from nuclear scattering signatures. Bulletin of the American Physical Society. 2016.

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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