Xiaoting Zhong

446 citations
10 papers · 311 · 1 hit paper · h-index 6

Impact in

    • Hydrogen embrittlement and corrosion behaviors in metals
    • Machine Learning in Materials Science
    • Microstructure and mechanical properties
    • Electronic and Structural Properties of Oxides

Papers in

Xiaoting Zhong

8 papers receiving 299 citations

Xiaoting Zhong's Hit Papers

Explainable machine learning in materials science 2022 · 214 citations
2140+1+2Years since publication50100150200

Peers

Xiaoting Zhong
Comparison fields: 5 of 83
  • Metals and Alloys 16
  • Materials Chemistry 177
  • Mechanical Engineering 84
  • Computational Theory and Mathematics 28
  • Health Informatics 2
Replace Fang Ren with:
Fang Ren United States
Ruho Kondo Japan
Qidong Liu China
Nima H. Siboni Germany
Dongbo Dai China
M.L. Bouazizi Tunisia
Jiang Guo China
He Zhao United States
Xiaoting Zhong relative to Fang Ren United States Fang Ren's profile →
Citations per field
00.5×
Fang Ren · 1×
Citations per year

Countries citing papers authored by Xiaoting Zhong

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoting Zhong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaoting Zhong, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiaoting Zhong Line = papers co-authored together Xiaoting Zhong links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
Explainable machine learning in materials science
Hit paper breakdown →
2022214
2 201646
3 202114
4 201913
5 201811
6 20188
7 20224
8 20221
9 20190
10 20250

About Xiaoting Zhong

Xiaoting Zhong is a scholar working on Materials Chemistry, Structural Biology, Statistical and Nonlinear Physics, Artificial Intelligence and Management Science and Operations Research, having authored 10 papers that have together received 311 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (4 papers), Microstructure and mechanical properties (3 papers), Advanced Electron Microscopy Techniques and Applications (3 papers), Complex Network Analysis Techniques (2 papers), Electron and X-Ray Spectroscopy Techniques (2 papers), Innovation Diffusion and Forecasting (2 papers), Opinion Dynamics and Social Influence (2 papers) and Computational Drug Discovery Methods (1 paper). The work is most often cited by research in Metals and Alloys (16 citations), Materials Chemistry (177 citations), Mechanical Engineering (84 citations), Computational Theory and Mathematics (28 citations) and Health Informatics (2 citations). Xiaoting Zhong has collaborated with scholars based in United States, China and Australia. Frequent co-authors include T. Yong-Jin Han, Brian Gallagher, Anna M. Hiszpanski, Shusen Liu, Bhavya Kailkhura, Gregory S. Rohrer, David J. Rowenhorst, Hossein Beladi, Shen J. Dillon and Herbert M. Miller. Their work appears in journals such as npj Computational Materials, Acta Materialia, ACS Omega, Microscopy and Microanalysis and Journal of the American Ceramic Society.

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.

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