Magnus So

518 total citations
42 papers, 401 citations indexed

About

Magnus So is a scholar working on Electrical and Electronic Engineering, Automotive Engineering and Renewable Energy, Sustainability and the Environment. According to data from OpenAlex, Magnus So has authored 42 papers receiving a total of 401 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Electrical and Electronic Engineering, 14 papers in Automotive Engineering and 13 papers in Renewable Energy, Sustainability and the Environment. Recurrent topics in Magnus So's work include Fuel Cells and Related Materials (15 papers), Advancements in Battery Materials (14 papers) and Advanced Battery Technologies Research (14 papers). Magnus So is often cited by papers focused on Fuel Cells and Related Materials (15 papers), Advancements in Battery Materials (14 papers) and Advanced Battery Technologies Research (14 papers). Magnus So collaborates with scholars based in Japan, China and Algeria. Magnus So's co-authors include Gen Inoue, Yoshifumi Tsuge, Tomohiro Ohnishi, Shota Ishikawa, Mitsuharu Terashima, Hidenari Yasui, Rajeev Goel, Naoki Kimura, Sakae Takenaka and John J. Engel and has published in prestigious journals such as SHILAP Revista de lepidopterología, Advanced Functional Materials and Journal of The Electrochemical Society.

In The Last Decade

Magnus So

39 papers receiving 386 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Magnus So Japan 12 309 176 96 84 26 42 401
Shu Yuan China 12 500 1.6× 340 1.9× 80 0.8× 139 1.7× 49 1.9× 25 620
Guofu Ren China 10 252 0.8× 187 1.1× 26 0.3× 96 1.1× 79 3.0× 14 336
Mayank Sabharwal Canada 14 480 1.6× 309 1.8× 59 0.6× 169 2.0× 86 3.3× 29 559
Peter Wilde Germany 7 361 1.2× 284 1.6× 39 0.4× 114 1.4× 65 2.5× 7 384
P.V. Suresh India 8 297 1.0× 125 0.7× 46 0.5× 38 0.5× 56 2.2× 11 366
Mrittunjoy Sarker United States 10 287 0.9× 234 1.3× 35 0.4× 83 1.0× 74 2.8× 23 312
Xiaoning Jia China 9 377 1.2× 237 1.3× 105 1.1× 83 1.0× 50 1.9× 10 453
Congfan Zhao China 9 339 1.1× 227 1.3× 59 0.6× 93 1.1× 33 1.3× 15 428
Michael Brodmann Germany 11 313 1.0× 179 1.0× 68 0.7× 125 1.5× 29 1.1× 26 420
Hüseyin KAHRAMAN Türkiye 7 329 1.1× 241 1.4× 70 0.7× 121 1.4× 72 2.8× 12 389

Countries citing papers authored by Magnus So

Since Specialization
Citations

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

Fields of papers citing papers by Magnus So

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Magnus So

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

All Works

20 of 20 papers shown
1.
2.
So, Magnus, et al.. (2025). Optimization of catalyst layers for polymer electrolyte membrane fuel cells using heterogeneous modeling and machine learning frameworks. Journal of Power Sources. 652. 237421–237421. 1 indexed citations
3.
So, Magnus, et al.. (2025). Electrodeposited nickel selenide thin film on carbon paper as an efficient binder-free anode for sodium-ion batteries. Journal of Energy Storage. 132. 117861–117861.
4.
So, Magnus, et al.. (2025). Porosity and tortuosity dynamics and their impact on lithium-ion battery performance with different separator structures. Journal of Power Sources. 647. 237278–237278. 6 indexed citations
5.
6.
Belhadj, M., Gaurav Goel, K. N. Singh, et al.. (2025). CFD Optimization of Disinfection Performance in Wastewater Treatment: A Case Study of Baffled Airlift Reactor Design Implementation in an Ozonation Tank. ACS ES&T Water. 5(2). 965–975. 4 indexed citations
7.
So, Magnus, et al.. (2024). Mechanism of Internal Crack Formation in All-Solid-State Batteries Due to Expansion and Shrinkage and Its Effects. ECS Meeting Abstracts. MA2024-02(67). 4416–4416. 1 indexed citations
8.
So, Magnus, et al.. (2023). Comparison of Different Carbon Supports By Simulation of Agglomeration in Polymer Electrolyte Fuel Cell Catalyst Ink. ECS Meeting Abstracts. MA2023-02(37). 1730–1730. 1 indexed citations
9.
Liu, Xuanchen, Magnus So, Shota Ishikawa, et al.. (2022). 3D generation and reconstruction of the fuel cell catalyst layer using 2D images based on deep learning. SHILAP Revista de lepidopterología. 14. 100084–100084. 12 indexed citations
10.
Inoue, Gen, et al.. (2022). Design of porous metal collector via bubble template-assisted electrochemical deposition using numerical simulation. Chemical Engineering Journal Advances. 10. 100266–100266. 3 indexed citations
11.
Ishikawa, Shota, Xuanchen Liu, Magnus So, et al.. (2022). Simulation to estimate the correlation of porous structure properties of secondary batteries determined through machine learning. SHILAP Revista de lepidopterología. 15. 100094–100094. 8 indexed citations
12.
Inoue, Gen, et al.. (2022). Microscale simulations of reaction and mass transport in cathode catalyst layer of polymer electrolyte fuel cell. International Journal of Hydrogen Energy. 47(25). 12665–12683. 16 indexed citations
13.
So, Magnus, et al.. (2021). Effect of mold pressure on compaction and ion conductivity of all-solid-state batteries revealed by the discrete element method. Journal of Power Sources. 508. 230344–230344. 35 indexed citations
14.
So, Magnus, et al.. (2020). Evaluation of Effect of Volume Expansion on Cell Performance of All-Solid-State Batteries with 1D Simulation. ECS Meeting Abstracts. MA2020-02(5). 909–909. 1 indexed citations
15.
So, Magnus, et al.. (2020). A Particle Based Ionomer Attachment Model for a Fuel Cell Catalyst Layer. Journal of The Electrochemical Society. 167(1). 13544–13544. 18 indexed citations
16.
Inoue, Gen, et al.. (2019). Simulation of carbon black aggregate and evaluation of ionomer structure on carbon in catalyst layer of polymer electrolyte fuel cell. Journal of Power Sources. 439. 227060–227060. 48 indexed citations
17.
Ohnishi, Tomohiro, et al.. (2019). Improvement of cell performance in catalyst layers with silica-coated Pt/carbon catalysts for polymer electrolyte fuel cells. International Journal of Hydrogen Energy. 45(3). 1867–1877. 25 indexed citations
18.
So, Magnus, et al.. (2019). The effect of solvent and ionomer on agglomeration in fuel cell catalyst inks: Simulation by the Discrete Element Method. International Journal of Hydrogen Energy. 44(54). 28984–28995. 47 indexed citations
19.
Ohnishi, Tomohiro, Magnus So, Sakae Takenaka, Yoshifumi Tsuge, & Gen Inoue. (2018). Performance of Carbon-Supported Pt Nanoparticles Covered by Silica Layers with Low Ionomer in Polymer Electrolyte Fuel Cells. ECS Transactions. 86(13). 453–460. 3 indexed citations
20.
So, Magnus, et al.. (2014). Modelling clogging and biofilm detachment in sponge carrier media. Water Science & Technology. 69(6). 1298–1303. 6 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.

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