Daniel Olds

1.7k citations
73 papers · 1.3k · h-index 20

Impact in

Papers in

    • X-ray Diffraction in Crystallography 14
    • Machine Learning in Materials Science 8
    • Nuclear materials and radiation effects 7
    • Nuclear Physics and Applications 9

Daniel Olds

70 papers receiving 1.3k citations

Peers

Daniel Olds
Comparison fields: 5 of 93
  • Materials Chemistry 706
  • Electronic, Optical and Magnetic Materials 185
  • Radiation 79
  • Structural Biology 11
  • Electrical and Electronic Engineering 413
Replace Zhimin Dai with:
Zhimin Dai China
Evgeny V. Podryabinkin Russia
Vicky Lynn Karen United States
Jacob W. Smith United States
Stephen W. T. Price United Kingdom
Antonis Vamvakeros United Kingdom
Brian Puchala United States
Markus Osenberg Germany
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Olds

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Olds

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Olds. 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 Daniel Olds. The network helps show where Daniel Olds may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Olds, 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 Daniel Olds Line = papers co-authored together Daniel Olds links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017157
2 202185
3 201768
4 202064
5 201963
6 201550
7 201846
8 202142
9 201640
10 201735
11 201834
12 202133
13 201829
14 202128
15 201526
16 202124
17 201923
18 202123
19 201423
20 201722

About Daniel Olds

Daniel Olds is a scholar working on Materials Chemistry, Radiation, Fluid Flow and Transfer Processes, Geophysics and Inorganic Chemistry, having authored 73 papers that have together received 1.3k indexed citations. Recurring topics across this work include X-ray Diffraction in Crystallography (14 papers), Advancements in Battery Materials (10 papers), Nuclear Physics and Applications (9 papers), Machine Learning in Materials Science (8 papers), Advanced battery technologies research (7 papers), Nuclear materials and radiation effects (7 papers), High-pressure geophysics and materials (7 papers) and Molten salt chemistry and electrochemical processes (6 papers). The work is most often cited by research in Materials Chemistry (706 citations), Electronic, Optical and Magnetic Materials (185 citations), Radiation (79 citations), Structural Biology (11 citations) and Electrical and Electronic Engineering (413 citations). Daniel Olds has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Katharine Lynn Page, Xiaowei Teng, Milinda Abeykoon, Gihan Kwon, Xiaoqiang Shan, Jue Liu, Jöerg C. Neuefeind, Peter F. Peterson, Geneva Laurita and Songi Han. Their work appears in journals such as Journal of Applied Crystallography, Review of Scientific Instruments, Chemistry of Materials, Acta Crystallographica Section A Foundations and Advances and Journal of the American Chemical Society.

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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