Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Gold nanoparticles in delivery applications☆
20082.2k citationsPallab Ghosh, Gang Han et al.Advanced Drug Delivery Reviewsprofile →
This map shows the geographic impact of Gang Han'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 Gang Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gang Han more than expected).
This network shows the impact of papers produced by Gang Han. 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 Gang Han. The network helps show where Gang Han may publish in the future.
Co-authorship network of co-authors of Gang Han
This figure shows the co-authorship network connecting the top 25 collaborators of Gang Han.
A scholar is included among the top collaborators of Gang Han 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 Gang Han. Gang Han is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
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.