David D. Landis
- Materials Chemistry top 5%
- Renewable Energy, Sustainability and the Environment top 2%
- Catalysis top 2%
- Electrical and Electronic Engineering top 10%
- Atomic and Molecular Physics, and Optics top 10%
- Co-authors
- Karsten W. JacobsenThomas BligaardJens K. NørskovAndreas MøgelhøjVivien PetzoldKeld T. LundgaardJess WellendorffSøren Dahl
- Topics
- Machine Learning in Materials Science (3 papers)Perovskite Materials and Applications (2 papers)Catalytic Processes in Materials Science (2 papers)
- Partner nations
- DenmarkUnited States
In The Last Decade
David D. Landis
7 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 75
- Materials Chemistry 1.5k
- Renewable Energy, Sustainability and the Environment 741
- Catalysis 542
- Electrical and Electronic Engineering 539
- Atomic and Molecular Physics, and Optics 242
Countries citing papers authored by David D. Landis
This map shows the geographic impact of David D. Landis'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 D. Landis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David D. Landis more than expected).
Fields of papers citing papers by David D. Landis
This network shows the impact of papers produced by David D. Landis. 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 D. Landis. The network helps show where David D. Landis may publish in the future.
Co-authorship network of co-authors of David D. Landis
This figure shows the co-authorship network connecting the top 25 collaborators of David D. Landis. A scholar is included among the top collaborators of David D. Landis 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 D. Landis. David D. Landis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 28 | |
| 3 | 164 | |
| 4 | 218 | |
| 5 | Density functionals for surface science: Exchange-correlation model development with Bayesian error estimationbreakdown → | 1225 |
| 6 | 344 | |
| 7 | 10 |
About David D. Landis
David D. Landis is a scholar working on Renewable Energy, Sustainability and the Environment, Statistics, Probability and Uncertainty and Materials Chemistry, having authored 7 papers that have together received 2.0k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (3 papers), Perovskite Materials and Applications (2 papers) and Catalytic Processes in Materials Science (2 papers). The work is most often cited by research in Catalysis (542 citations), Renewable Energy, Sustainability and the Environment (741 citations) and Materials Chemistry (1.5k citations). David D. Landis has collaborated with scholars based in Denmark and United States. Frequent co-authors include Karsten W. Jacobsen, Thomas Bligaard, Jens K. Nørskov, Andreas Møgelhøj, Vivien Petzold, Keld T. Lundgaard, Jess Wellendorff, Søren Dahl, Kristian S. Thygesen and Ivano E. Castelli. Their work appears in journals such as Energy & Environmental Science, Physical Review B and Topics in Catalysis.
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.