Sha Sha

1.1k citations
140 papers · 860 · h-index 15

Impact in

    • Fermentation and Sensory Analysis
    • Food Quality and Safety Studies
  • Biochemistry top 10%
    • Phytochemicals and Antioxidant Activities

Papers in

Sha Sha

120 papers receiving 836 citations

Peers

Sha Sha
Comparison fields: 5 of 148
  • Food Science 181
  • Biochemistry 56
  • Polymers and Plastics 79
  • Biomaterials 71
  • Sensory Systems 25
Replace Manuel Melgosa with:
Manuel Melgosa Spain
Qifan Wang China
Espen Olsen Norway
A. Domínguez-Pacheco Mexico
Yajing Li China
Hongjie Zhou China
B. Rigg United Kingdom
Roberto Alves Braga Brazil
Lingling Liu China
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Citations per field
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Citations per year

Countries citing papers authored by Sha Sha

Since Specialization
Citations

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

Fields of papers citing papers by Sha Sha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 140 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016140
2 201174
3 201761
4
A comparison of two models with Landsat data for estimating above ground grassland biomass in Inner Mongolia, China
200941
5 201526
6 202124
7 202123
8 201623
9 201921
10
An improved method for prediction of tomato photosynthetic rate based on WSN in greenhouse.
201619
11 201218
12 202217
13 201217
14
MP-WFRFT and Constellation Scrambling Based Physical Layer Security System
201614
15 202214
16 200913
17
nID-based Internet of Things and .Its Application in Airport Aviation Risk Management
201212
18 202412
19 202411
20 201311

About Sha Sha

Sha Sha is a scholar working on Materials Chemistry, Electrical and Electronic Engineering, Mechanical Engineering, Computational Mechanics and Computer Vision and Pattern Recognition, having authored 140 papers that have together received 860 indexed citations. Recurring topics across this work include Textile materials and evaluations (8 papers), 3D Shape Modeling and Analysis (7 papers), Magnesium Alloys: Properties and Applications (6 papers), Aluminum Alloys Composites Properties (6 papers), Supercapacitor Materials and Fabrication (5 papers), Advancements in Battery Materials (5 papers), Corrosion Behavior and Inhibition (5 papers) and Advanced Battery Materials and Technologies (4 papers). The work is most often cited by research in Food Science (181 citations), Biochemistry (56 citations), Polymers and Plastics (79 citations), Biomaterials (71 citations) and Sensory Systems (25 citations). Sha Sha has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Shuang Chen, Michael C. Qian, Yan Xu, Chengcheng Wang, Gaoming Jiang, Ying Kong, Jinrong Yang, Qi Gan, Jiangchao Qian and Changsheng Liu. Their work appears in journals such as Textile Research Journal, Metals and Materials International, Frontiers in Psychiatry, Materials and Journal of Affective Disorders.

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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