Shaochen Shi

1.3k citations
7 papers · 539 · 3 hit papers · h-index 7

Impact in

Papers in

Shaochen Shi

7 papers receiving 536 citations

Shaochen Shi's Hit Papers

A predictive machine learning force-field framework for liquid electrolyte development 2025 · 29 citations
290+1+2Years since publication50100150200250

Peers

Shaochen Shi
Comparison fields: 5 of 26
  • Automotive Engineering 237
  • Electrical and Electronic Engineering 494
  • Electronic, Optical and Magnetic Materials 49
  • Inorganic Chemistry 31
  • Materials Chemistry 96
Replace Yadong Ye with:
Yadong Ye China
Yuli Huang China
Anna Windmüller Germany
Yu Ou China
Zhenliang Mu China
Volker Hennige Austria
Kassie Nigus Shitaw Taiwan
Zaifa Wang China
Kangwoon Kim United States
Guochen Sun China
Shaochen Shi relative to Yadong Ye China Yadong Ye's profile →
Citations per field
00.5×1.5×
Yadong Ye · 1×
Citations per year

Countries citing papers authored by Shaochen Shi

Since Specialization
Citations

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

Fields of papers citing papers by Shaochen Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Shaochen Shi, 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 Shaochen Shi Line = papers co-authored together Shaochen Shi links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1
Hard-carbon-stabilized Li–Si anodes for high-performance all-solid-state Li-ion batteries
Hit paper breakdown →
2023252
2
Realizing long-cycling all-solid-state Li-In||TiS2 batteries using Li6+xMxAs1-xS5I (M=Si, Sn) sulfide solid electrolytes
Hit paper breakdown →
2023118
3 202265
4 202351
5
A predictive machine learning force-field framework for liquid electrolyte development
Hit paper breakdown →
202529
6 202418
7 20226

About Shaochen Shi

Shaochen Shi is a scholar working on Electrical and Electronic Engineering, Automotive Engineering, Spectroscopy, Inorganic Chemistry and Materials Chemistry, having authored 7 papers that have together received 539 indexed citations. Recurring topics across this work include Advanced Battery Materials and Technologies (6 papers), Advancements in Battery Materials (6 papers), Advanced battery technologies research (2 papers), Advanced Battery Technologies Research (2 papers), Advanced NMR Techniques and Applications (1 paper), Machine Learning in Materials Science (1 paper), Fuel Cells and Related Materials (1 paper) and Inorganic Chemistry and Materials (1 paper). The work is most often cited by research in Automotive Engineering (237 citations), Electrical and Electronic Engineering (494 citations), Electronic, Optical and Magnetic Materials (49 citations), Inorganic Chemistry (31 citations) and Materials Chemistry (96 citations). Shaochen Shi has collaborated with scholars based in China and United States. Frequent co-authors include Liquan Chen, Fan Wu, Hong Li, Wenlin Yan, Dengxu Wu, Pushun Lu, Yu Xia, Jiaze Lu, Zhenliang Mu and Yuli Huang. Their work appears in journals such as Advanced Functional Materials, Advanced Energy Materials, The Journal of Chemical Physics, Advanced Materials and Nature Communications.

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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