Daniel Wheeler

4.3k total citations
71 papers, 3.6k citations indexed

About

Daniel Wheeler is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Electronic, Optical and Magnetic Materials. According to data from OpenAlex, Daniel Wheeler has authored 71 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Electrical and Electronic Engineering, 30 papers in Materials Chemistry and 15 papers in Electronic, Optical and Magnetic Materials. Recurrent topics in Daniel Wheeler's work include Electrodeposition and Electroless Coatings (28 papers), Corrosion Behavior and Inhibition (16 papers) and Copper Interconnects and Reliability (14 papers). Daniel Wheeler is often cited by papers focused on Electrodeposition and Electroless Coatings (28 papers), Corrosion Behavior and Inhibition (16 papers) and Copper Interconnects and Reliability (14 papers). Daniel Wheeler collaborates with scholars based in United States, United Kingdom and Australia. Daniel Wheeler's co-authors include D. Josell, Thomas P. Moffat, D. Josell, T. P. Moffat, James A. Warren, William Huber, Jonathan E. Guyer, Monica D. Edelstein, S.-K. Kim and C. Witt and has published in prestigious journals such as Physical Review Letters, Journal of Applied Physics and Journal of The Electrochemical Society.

In The Last Decade

Daniel Wheeler

68 papers receiving 3.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Wheeler United States 28 2.6k 1.5k 884 597 498 71 3.6k
Masanori Hara Japan 42 3.4k 1.3× 3.3k 2.2× 444 0.5× 275 0.5× 444 0.9× 348 6.2k
Michel Rosso France 34 3.9k 1.5× 864 0.6× 265 0.3× 339 0.6× 382 0.8× 90 5.2k
A. Otto Germany 26 1.6k 0.6× 631 0.4× 873 1.0× 208 0.3× 1.3k 2.5× 110 4.2k
Guowei Li China 34 1.3k 0.5× 1.7k 1.2× 449 0.5× 172 0.3× 585 1.2× 132 3.9k
Gang Zhao China 47 3.5k 1.3× 2.4k 1.6× 1.2k 1.3× 206 0.3× 999 2.0× 205 5.8k
Xinjun Wang China 29 1.3k 0.5× 1.7k 1.1× 1.2k 1.3× 74 0.1× 712 1.4× 116 3.3k
Peter J. Hesketh United States 33 1.9k 0.7× 935 0.6× 281 0.3× 210 0.4× 842 1.7× 166 3.9k
Herbert Hutter Austria 30 1.2k 0.4× 2.3k 1.5× 728 0.8× 78 0.1× 200 0.4× 222 3.5k
Arnulf Latz Germany 43 3.7k 1.4× 1.8k 1.2× 582 0.7× 85 0.1× 419 0.8× 197 5.6k
Zhigang Li China 29 811 0.3× 1.1k 0.7× 946 1.1× 100 0.2× 254 0.5× 105 2.7k

Countries citing papers authored by Daniel Wheeler

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Wheeler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Wheeler

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Wheeler. A scholar is included among the top collaborators of Daniel Wheeler 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 Daniel Wheeler. Daniel Wheeler 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.
Ganapathysubramanian, Baskar, et al.. (2024). Active learning for regression of structure–property mapping: the importance of sampling and representation. Digital Discovery. 3(10). 1997–2009. 4 indexed citations
2.
Wheeler, Daniel, et al.. (2022). How important is microstructural feature selection for data-driven structure-property mapping?. MRS Communications. 12(1). 95–103. 9 indexed citations
3.
Wheeler, Daniel, Trevor Keller, Stephen DeWitt, et al.. (2019). PFHub: The Phase-Field Community Hub. Journal of Open Research Software. 7(1). 29–29. 9 indexed citations
4.
Wheeler, Daniel, et al.. (2017). Materials Knowledge Systems in Python - A Data Science Framework for Accelerated Development of Hierarchical Materials | NIST. JOM. 1 indexed citations
5.
Wheeler, Daniel, et al.. (2017). Materials Knowledge Systems in Python—a Data Science Framework for Accelerated Development of Hierarchical Materials. Integrating materials and manufacturing innovation. 6(1). 36–53. 83 indexed citations
6.
Wheeler, Daniel, et al.. (2017). Microstructure-based knowledge systems for capturing process-structure evolution linkages.. Acta Materialia. 21. 2 indexed citations
7.
Josell, D., Daniel Wheeler, & Thomas P. Moffat. (2012). Modeling Extreme Bottom-Up Filling of Through Silicon Vias. Journal of The Electrochemical Society. 159(10). D570–D576. 95 indexed citations
8.
Schwalbach, Edwin J., Stephen H. Davis, Peter W. Voorhees, Daniel Wheeler, & James A. Warren. (2011). Liquid droplet dynamics and complex morphologies in vapor–liquid–solid nanowire growth. Journal of materials research/Pratt's guide to venture capital sources. 26(17). 2186–2198. 15 indexed citations
9.
Wheeler, Daniel, James A. Warren, & W. J. Boettinger. (2010). Modeling the early stages of reactive wetting. Physical Review E. 82(5). 51601–51601. 29 indexed citations
10.
Saylor, David M., Jonathan E. Guyer, Daniel Wheeler, & James A. Warren. (2010). Predicting microstructure development during casting of drug-eluting coatings. Acta Biomaterialia. 7(2). 604–613. 11 indexed citations
11.
Moffat, Thomas P., Daniel Wheeler, & D. Josell. (2008). Superconformal Film Growth: Mechanism and Quantification. ECS Transactions. 13(2). 129–137. 10 indexed citations
12.
Moffat, Thomas P., Daniel Wheeler, S.-K. Kim, & D. Josell. (2007). Curvature enhanced adsorbate coverage mechanism for bottom-up superfilling and bump control in damascene processing. Electrochimica Acta. 53(1). 145–154. 142 indexed citations
13.
Wheeler, Daniel, Jonathan E. Guyer, & James A. Warren. (2005). FiPy: A Finite Volume PDE Solver Using Python. International Journal of Web Services Research. 8 indexed citations
14.
Moffat, Thomas P., Daniel Wheeler, & D. Josell. (2004). Electrodeposition of Copper in the SPS-PEG-Cl Additive System. Journal of The Electrochemical Society. 151(4). C262–C262. 313 indexed citations
15.
Josell, D., et al.. (2003). Interconnect Fabrication by Superconformal Iodine-Catalyzed Chemical Vapor. Journal of The Electrochemical Society. 150(5). 1 indexed citations
16.
Baker, B. C., et al.. (2003). Superconformal Electrodeposition of Silver from a KAg(CN)[sub 2]-KCN-KSeCN Electrolyte. Journal of The Electrochemical Society. 150(2). C61–C61. 52 indexed citations
17.
Josell, D., Thomas P. Moffat, & Daniel Wheeler. (2002). Numerical Simulation of Superconformal Electrodeposition Using the Level Set Method. TechConnect Briefs. 2(2002). 348–351. 3 indexed citations
18.
Bailey, C., Huiqing Lu, & Daniel Wheeler. (2002). Predicting the movement of voids in solder bumps and subsequent reliability [flip chip assembly]. 97–102. 4 indexed citations
19.
Josell, D., Daniel Wheeler, William Huber, & T. P. Moffat. (2001). Superconformal Electrodeposition in Submicron Features. Physical Review Letters. 87(1). 16102–16102. 153 indexed citations
20.
Loy, Douglas A., et al.. (1999). Maleimide Functionalized Siloxane Resins. MRS Proceedings. 576. 6 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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