Silvia Lacerda
About
In The Last Decade
Silvia Lacerda
6 papers receiving 379 citations
Peers
Comparison fields: 5 of 65
- Biomedical Engineering 186
- Materials Chemistry 143
- Molecular Biology 83
- Biomaterials 82
- Polymers and Plastics 79
Countries citing papers authored by Silvia Lacerda
This map shows the geographic impact of Silvia Lacerda'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 Silvia Lacerda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Silvia Lacerda more than expected).
Fields of papers citing papers by Silvia Lacerda
This network shows the impact of papers produced by Silvia Lacerda. 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 Silvia Lacerda. The network helps show where Silvia Lacerda may publish in the future.
Co-authorship network of co-authors of Silvia Lacerda
This figure shows the co-authorship network connecting the top 25 collaborators of Silvia Lacerda. A scholar is included among the top collaborators of Silvia Lacerda 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 Silvia Lacerda. Silvia Lacerda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 34 | |
| 2 | 81 | |
| 3 | 81 | |
| 4 | 45 | |
| 5 | 124 | |
| 6 | 21 |
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.