Daniel J. Rivera
Impact in
- Catalysis top 1%
- Ammonia Synthesis and Nitrogen Reduction
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- Advanced Photocatalysis Techniques
- Electrocatalysts for Energy Conversion
- CO2 Reduction Techniques and Catalysts
Papers in
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- Ammonia Synthesis and Nitrogen Reduction 7
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- Catalytic Processes in Materials Science 2
- MXene and MAX Phase Materials 1
- Co-authors
- Christopher L. Muhich (7 shared papers)Srishti Gupta (2 shared papers)Guanhui Gao (2 shared papers)Feng-Yang Chen (1 shared paper)Zhenyu Wu (1 shared paper)Graham King (1 shared paper)David A. Cullen (1 shared paper)Peng Zhu (1 shared paper)
- Journals
- Small (1 paper)Surface Science (1 paper)Nature Nanotechnology (1 paper)Frontiers in Robotics and AI (1 paper)Nature Chemical Engineering (1 paper)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Daniel J. Rivera
7 papers receiving 979 citations
Daniel J. Rivera's Hit Papers
Peers
Comparison fields: 5 of 40
- Catalysis 858
- Renewable Energy, Sustainability and the Environment 657
- Computer Networks and Communications 396
- Organic Chemistry 171
- Materials Chemistry 253
Countries citing papers authored by Daniel J. Rivera
This map shows the geographic impact of Daniel J. Rivera'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 J. Rivera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel J. Rivera more than expected).
Fields of papers citing papers by Daniel J. Rivera
This network shows the impact of papers produced by Daniel J. Rivera. 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 J. Rivera. The network helps show where Daniel J. Rivera may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel J. Rivera, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Efficient conversion of low-concentration nitrate sources into ammonia on a Ru-dispersed Cu nanowire electrocatalyst Hit paper breakdown → | 2022 | 936 |
| 2 | 2025 | 18 | |
| 3 | 2018 | 13 | |
| 4 | 2024 | 8 | |
| 5 | 2023 | 7 | |
| 6 | 2023 | 7 | |
| 7 | 2024 | 1 | |
| 8 | 2025 | 0 |
About Daniel J. Rivera
Daniel J. Rivera is a scholar working on Catalysis, Materials Chemistry, Computer Networks and Communications, Renewable Energy, Sustainability and the Environment and Organic Chemistry, having authored 8 papers that have together received 990 indexed citations. Recurring topics across this work include Ammonia Synthesis and Nitrogen Reduction (7 papers), Advanced Photocatalysis Techniques (3 papers), Catalytic Processes in Materials Science (2 papers), Caching and Content Delivery (2 papers), Membrane Separation and Gas Transport (1 paper), MXene and MAX Phase Materials (1 paper), Nanomaterials for catalytic reactions (1 paper) and Muscle activation and electromyography studies (1 paper). The work is most often cited by research in Catalysis (858 citations), Renewable Energy, Sustainability and the Environment (657 citations), Computer Networks and Communications (396 citations), Organic Chemistry (171 citations) and Materials Chemistry (253 citations). Daniel J. Rivera has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Christopher L. Muhich, Srishti Gupta, Guanhui Gao, Feng-Yang Chen, Zhenyu Wu, Graham King, David A. Cullen, Peng Zhu, Debora Meira and Haotian Wang. Their work appears in journals such as Small, Surface Science, Nature Nanotechnology, Frontiers in Robotics and AI and Nature Chemical Engineering.
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.