Stephen Lam

915 citations
24 papers · 671 indexed · h-index 13

Stephen Lam

23 papers receiving 652 citations

Peers

Stephen Lam
Comparison fields: 5 of 53
  • Fluid Flow and Transfer Processes 226
  • Materials Chemistry 490
  • Inorganic Chemistry 91
  • Aerospace Engineering 156
  • Mechanical Engineering 179
Replace Raluca O. Scarlat with:
Raluca O. Scarlat United States
K. Ananthasivan India
Koji Kitano Japan
H.S. Kamath India
František Šimko Slovakia
Charles E. Wicks United States
Nicole Roux France
Xian Shi United States
Hongjie Xu China
Penghui Yang China
Stephen Lam relative to Raluca O. Scarlat United States Raluca O. Scarlat's profile →
Citations per field
00.5×1.5×
Raluca O. Scarlat · 1×
Citations per year

Countries citing papers authored by Stephen Lam

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Lam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20242
3 20245
4 20249
5 20241
6 202210
7 202235
8 202215
9 202179
10 202123
11 202143
12 202161
13
A neural network interatomic potential for molten NaCl
20201
14 201932
15 201912
16 201822
17 2018126
18 20179
19 201715
20 201781

About Stephen Lam

Stephen Lam is a scholar working on Fluid Flow and Transfer Processes, Inorganic Chemistry, Materials Chemistry, Catalysis and Radiation, having authored 24 papers that have together received 671 indexed citations. Recurring topics across this work include Molten salt chemistry and electrochemical processes (11 papers), Fusion materials and technologies (8 papers), Machine Learning in Materials Science (7 papers), Inorganic Fluorides and Related Compounds (6 papers), Nuclear Materials and Properties (6 papers), Nuclear reactor physics and engineering (4 papers), X-ray Diffraction in Crystallography (4 papers) and Graphite, nuclear technology, radiation studies (2 papers). The work is most often cited by research in Fluid Flow and Transfer Processes (226 citations), Materials Chemistry (490 citations), Inorganic Chemistry (91 citations), Aerospace Engineering (156 citations) and Mechanical Engineering (179 citations). Stephen Lam has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Charles Forsberg, R. G. Ballinger, Ming Hu, Alejandro Rodriguez, Ju Li, Qing‐Jie Li, Raluca O. Scarlat, Guiqiu Zheng, Boris Khaykovich and James R. Keiser. Their work appears in journals such as Journal of Nuclear Materials, Nuclear Technology, ACS Applied Materials & Interfaces, Fusion Science & Technology and Physical Review Materials.

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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