D. Train

636 citations
29 papers · 530 · h-index 10

Impact in

Papers in

D. Train

26 papers receiving 485 citations

Peers

D. Train
Comparison fields: 5 of 78
  • Pharmaceutical Science 186
  • Fluid Flow and Transfer Processes 41
  • Analytical Chemistry 63
  • Mechanical Engineering 184
  • Computational Mechanics 94
Replace Kimio Kawakita with:
Kimio Kawakita Japan
Laila J. Jallo United States
Harona Diarra France
Josefina Nordström Sweden
Abderrahim Michrafy France
Ilgaz Akseli United States
Jon Hilden United States
Juan G. Osorio United States
Maxx Capece United States
A.C. Bentham United Kingdom
D. Train relative to Kimio Kawakita Japan Kimio Kawakita's profile →
Citations per field
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Kimio Kawakita · 1×
Citations per year

Countries citing papers authored by D. Train

Since Specialization
Citations

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

Fields of papers citing papers by D. Train

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside D. Train, 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 D. Train Line = papers co-authored together D. Train links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1956143
2 1958138
3
Transmission forces through a powder mass during the process of pelleting
195783
4 196019
5 196019
6 198519
7 196513
8 196013
9 196512
10 198312
11 19749
12 19749
13 19658
14 19778
15 19754
16 19884
17 19793
18 19732
19 19762
20 19832

About D. Train

D. Train is a scholar working on Electrical and Electronic Engineering, Materials Chemistry, Mechanical Engineering, Control and Systems Engineering and Mechanics of Materials, having authored 29 papers that have together received 530 indexed citations. Recurring topics across this work include High voltage insulation and dielectric phenomena (12 papers), Powder Metallurgy Techniques and Materials (9 papers), Power Transformer Diagnostics and Insulation (9 papers), Thermal Analysis in Power Transmission (5 papers), Advanced materials and composites (4 papers), Metallurgy and Material Forming (3 papers), Injection Molding Process and Properties (2 papers) and Electrostatic Discharge in Electronics (2 papers). The work is most often cited by research in Pharmaceutical Science (186 citations), Fluid Flow and Transfer Processes (41 citations), Analytical Chemistry (63 citations), Mechanical Engineering (184 citations) and Computational Mechanics (94 citations). D. Train has collaborated with scholars based in Canada, United Kingdom and Mexico. Frequent co-authors include John A. Hersey, Chris Lewis, Ryszard Malewski, E. So, N.G. Trinh, H. Anis, Daniel Dupont, E Shotton, A. Chamberland and A. J. Evans. Their work appears in journals such as Journal of Pharmacy and Pharmacology, IEEE Transactions on Power Delivery, Nature, Powder Metallurgy and IEEE Power Engineering Review.

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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