Isaac Tamblyn

2.4k citations
60 papers · 1.6k indexed · h-index 22
Topics
Machine Learning in Materials Science (25 papers)Advanced Chemical Physics Studies (12 papers)Electrocatalysts for Energy Conversion (6 papers)

In The Last Decade

Isaac Tamblyn

59 papers receiving 1.6k citations

Peers

Isaac Tamblyn
Comparison fields: 5 of 91
  • Materials Chemistry 761
  • Atomic and Molecular Physics, and Optics 681
  • Electrical and Electronic Engineering 363
  • Geophysics 238
  • Biomedical Engineering 146
Replace Mohan Chen with:
Mohan Chen China
Vikram Gavini United States
Franz Gähler Germany
John E. Pask United States
Andrew Canning United States
D. M. Deaven United States
Murilo L. Tiago United States
S. Alireza Ghasemi Switzerland
Richard J. Sadus Australia
Ralf Meyer Germany
Isaac Tamblyn relative to Mohan Chen China Mohan Chen's profile →
Citations per field
00.5×1.5×1.9×
Mohan Chen · 1×
Citations per year

Countries citing papers authored by Isaac Tamblyn

Since Specialization
Citations

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

Fields of papers citing papers by Isaac Tamblyn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Isaac Tamblyn

This figure shows the co-authorship network connecting the top 25 collaborators of Isaac Tamblyn. A scholar is included among the top collaborators of Isaac Tamblyn 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 Isaac Tamblyn. Isaac Tamblyn 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
#WorkIndexed citations
1 4
2 5
3 3
4 20
5 23
6 4
7 7
8 1
9 12
10 2
11 19
12 12
13
Adversarial Generation of Mesoscale Surfaces from Small-Scale Chemical Motifs
1
14 47
15 75
16 14
17 28
18 83
19 79
20 14

About Isaac Tamblyn

Isaac Tamblyn is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics and Catalysis, having authored 60 papers that have together received 1.6k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (25 papers), Advanced Chemical Physics Studies (12 papers) and Electrocatalysts for Energy Conversion (6 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (681 citations), Geophysics (238 citations) and Materials Chemistry (761 citations). Isaac Tamblyn has collaborated with scholars based in Canada, United States and Belgium. Frequent co-authors include Stanimir Bonev, Jeffrey B. Neaton, Kyle Mills, Kevin Ryczko, Stephen Whitelam, Jan Vorberger, Michael Spanner, Burkhard Militzer, Leeor Kronik and Nir Goldman. Their work appears in journals such as Physical Review Letters, Nature Communications and The Journal of Chemical Physics.

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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