Qiuling Tao

819 total citations · 1 hit paper
11 papers, 624 citations indexed

About

Qiuling Tao is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Mechanical Engineering. According to data from OpenAlex, Qiuling Tao has authored 11 papers receiving a total of 624 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Electrical and Electronic Engineering, 6 papers in Materials Chemistry and 5 papers in Mechanical Engineering. Recurrent topics in Qiuling Tao's work include Perovskite Materials and Applications (6 papers), Machine Learning in Materials Science (4 papers) and High Temperature Alloys and Creep (4 papers). Qiuling Tao is often cited by papers focused on Perovskite Materials and Applications (6 papers), Machine Learning in Materials Science (4 papers) and High Temperature Alloys and Creep (4 papers). Qiuling Tao collaborates with scholars based in China, Japan and Hong Kong. Qiuling Tao's co-authors include Minjie Li, Wencong Lu, Pengcheng Xu, Tian Lu, Sheng Ye, Long Li, Xue Yang, Long Li, Shilin Zhang and Pengcheng Xu and has published in prestigious journals such as The Journal of Physical Chemistry C, The Journal of Physical Chemistry Letters and Journal of Material Science and Technology.

In The Last Decade

Qiuling Tao

11 papers receiving 611 citations

Hit Papers

align trajectories

What are hit papers?

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.

Machine learning for perovskite materials design and discovery

2021 351 citations Qiuling Tao, Pengcheng Xu et al. npj Computational Materials profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Qiuling Tao China	7	480	338	104	59	55	11	624
Arunkumar Chitteth Rajan South Korea	9	512 1.1×	206 0.6×	77 0.7×	29 0.5×	133 2.4×	10	657
Junfei Cai China	15	322 0.7×	337 1.0×	79 0.8×	14 0.2×	27 0.5×	41	608
Jake Graser United States	7	428 0.9×	195 0.6×	46 0.4×	23 0.4×	55 1.0×	8	600
Haoyang Luo China	12	417 0.9×	276 0.8×	100 1.0×	27 0.5×	66 1.2×	21	649
Hyunsoo Park South Korea	13	392 0.8×	174 0.5×	57 0.5×	18 0.3×	62 1.1×	26	604
Mariya Layurova United States	5	379 0.8×	391 1.2×	47 0.5×	71 1.2×	25 0.5×	8	497
Kameel Abdel‐Latif United States	11	436 0.9×	281 0.8×	38 0.4×	21 0.4×	251 4.6×	13	672
Yuyang Sun China	8	311 0.6×	269 0.8×	126 1.2×	125 2.1×	48 0.9×	11	490
Edirisuriya M. Dilanga Siriwardane United States	15	495 1.0×	199 0.6×	40 0.4×	10 0.2×	50 0.9×	30	580
Brenna M. Gibbons United States	7	315 0.7×	149 0.4×	169 1.6×	14 0.2×	34 0.6×	9	465

Countries citing papers authored by Qiuling Tao

Since Specialization

Citations

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

Fields of papers citing papers by Qiuling Tao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qiuling Tao

This figure shows the co-authorship network connecting the top 25 collaborators of Qiuling Tao. A scholar is included among the top collaborators of Qiuling Tao 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 Qiuling Tao. Qiuling Tao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

1.

Tao, Qiuling, Longke Bao, Rongpei Shi, et al.. (2025). Enhanced extrapolative machine learning for designing high‐performance multi‐principal‐element superalloys. Rare Metals. 44(10). 7859–7875. 2 indexed citations

2.

Tao, Qiuling, Zhou Li, Longke Bao, et al.. (2025). Accelerated design and property validation of L12-strengthened Co-Ni-Cr-Al-Cu-Ti high-entropy superalloys based on unsupervised and supervised learning. Journal of Material Science and Technology. 259. 162–172. 1 indexed citations

3.

Tao, Qiuling, Longke Bao, Yuefei Zhou, et al.. (2025). Transforming machine learning model knowledge into material insights for multi-principal-element superalloy phase design. npj Computational Materials. 11(1). 3 indexed citations

4.

Tao, Qiuling, Jinxin Yu, Xue Jia, et al.. (2025). Machine learning strategies for small sample size in materials science. Science China Materials. 68(2). 387–405. 8 indexed citations

5.

Yu, Jinxin, Longke Bao, Qiuling Tao, et al.. (2023). Predicting atomic structure and mechanical properties in quinary L12-Strengthened cobalt-based superalloys using machine learning-driven first-principles calculations. Materials Today Communications. 38. 107774–107774. 5 indexed citations

6.

Yang, Xue, Long Li, Qiuling Tao, Wencong Lu, & Minjie Li. (2021). Rapid discovery of narrow bandgap oxide double perovskites using machine learning. Computational Materials Science. 196. 110528–110528. 45 indexed citations

7.

Li, Long, Qiuling Tao, Pengcheng Xu, et al.. (2021). Studies on the regularity of perovskite formation via machine learning. Computational Materials Science. 199. 110712–110712. 26 indexed citations

8.

Tao, Qiuling, Tian Lu, Long Li, et al.. (2021). Multiobjective Stepwise Design Strategy-Assisted Design of High-Performance Perovskite Oxide Photocatalysts. The Journal of Physical Chemistry C. 125(38). 21141–21150. 16 indexed citations

9.

Tao, Qiuling, Pengcheng Xu, Minjie Li, & Wencong Lu. (2021). Machine learning for perovskite materials design and discovery. npj Computational Materials. 7(1). 351 indexed citations breakdown →

10.

Zhang, Shilin, Tian Lu, Pengcheng Xu, et al.. (2021). Predicting the Formability of Hybrid Organic–Inorganic Perovskites via an Interpretable Machine Learning Strategy. The Journal of Physical Chemistry Letters. 12(31). 7423–7430. 56 indexed citations

11.

Tao, Qiuling, Tian Lu, Sheng Ye, et al.. (2021). Machine learning aided design of perovskite oxide materials for photocatalytic water splitting. Journal of Energy Chemistry. 60. 351–359. 111 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.

Explore authors with similar magnitude of impact