M. Lam

666 citations
14 papers · 494 · 1 hit paper · h-index 7

Impact in

Papers in

M. Lam

14 papers receiving 486 citations

M. Lam's Hit Papers

Silver-Based Plasmonic Nanoparticles for and Their Use in Biosensing 2019 · 349 citations
3490+2+4Years since publication100200300

Peers

M. Lam
Comparison fields: 5 of 89
  • Electronic, Optical and Magnetic Materials 141
  • Biomedical Engineering 225
  • Biomaterials 61
  • Surfaces, Coatings and Films 32
  • Materials Chemistry 200
Replace Andrey M. Zakharevich with:
Andrey M. Zakharevich Russia
Guansong Hu China
Aharon Gedanken Israel
Dandan Liu China
Agnese D’Agostino Italy
Aitor Urrutia Spain
Shuang Yang China
Yinghui Yang China
Aaron D. Strickland United States
Tan Liu China
M. Lam relative to Andrey M. Zakharevich Russia Andrey M. Zakharevich's profile →
Citations per field
00.5×1.5×
Andrey M. Zakharevich · 1×
Citations per year

Countries citing papers authored by M. Lam

Since Specialization
Citations

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

Fields of papers citing papers by M. Lam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside M. 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 M. Lam Line = papers co-authored together M. Lam links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1
Silver-Based Plasmonic Nanoparticles for and Their Use in Biosensing
Hit paper breakdown →
2019349
2 202078
3 202016
4 201610
5 20228
6 20178
7 20227
8 20225
9 20174
10
Maximising SAG mill throughput at Porgera gold mine by optimising blast fragmentation
20013
11 20232
12 20242
13 20211
14 20151

About M. Lam

M. Lam is a scholar working on Biomedical Engineering, Materials Chemistry, Industrial and Manufacturing Engineering, Surgery and Automotive Engineering, having authored 14 papers that have together received 494 indexed citations. Recurring topics across this work include Bone Tissue Engineering Materials (5 papers), Diverse Industrial Engineering Technologies (4 papers), Additive Manufacturing and 3D Printing Technologies (3 papers), Breast Implant and Reconstruction (2 papers), Metal Alloys Wear and Properties (2 papers), Microplastics and Plastic Pollution (2 papers), Metallurgy and Material Forming (2 papers) and Engineering and Environmental Studies (2 papers). The work is most often cited by research in Electronic, Optical and Magnetic Materials (141 citations), Biomedical Engineering (225 citations), Biomaterials (61 citations), Surfaces, Coatings and Films (32 citations) and Materials Chemistry (200 citations). M. Lam has collaborated with scholars based in France, Ukraine and Russia. Frequent co-authors include Gabriel Boitel‐Aullen, Alexis Loiseau, Michèle Salmain, Souhir Boujday, Céline Falentin‐Daudre, Véronique Migonney, Alexandre Serov, Vivien Moris, Vincent Humblot and Catherine Neuwirth. Their work appears in journals such as Journal of Biomedical Materials Research Part B Applied Biomaterials, Acta Biomaterialia, BMC Microbiology, Biophysical Chemistry and European Polymer Journal.

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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