Tamara Husch

666 citations
17 papers · 528 indexed · h-index 13

Tamara Husch

17 papers receiving 525 citations

Peers

Tamara Husch
Comparison fields: 5 of 61
  • Catalysis 80
  • Physical and Theoretical Chemistry 60
  • Electronic, Optical and Magnetic Materials 107
  • Automotive Engineering 67
  • Computational Theory and Mathematics 68
Replace Chien‐Pin Chou with:
Chien‐Pin Chou Taiwan
Shulu Feng United States
Nuno M. Garrido Portugal
Е. Yu. Tyunina Russia
Florian Dommert Germany
Muhamad Abdulkadir Martoprawiro Indonesia
Jingbai Li United States
Jeff Lengyel United States
Maximilian Kubillus Germany
R. Vasanthi India
Tamara Husch relative to Chien‐Pin Chou Taiwan Chien‐Pin Chou's profile →
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Citations per year

Countries citing papers authored by Tamara Husch

Since Specialization
Citations

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

Fields of papers citing papers by Tamara Husch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

17 of 17 papers shown
#Work
1 202111
2 202138
3 202017
4 201859
5 20189
6 20181
7 201823
8 201719
9 201727
10 201712
11 201657
12 201615
13 201632
14 201655
15 201537
16 201568
17 201448

About Tamara Husch

Tamara Husch is a scholar working on Physical and Theoretical Chemistry, Catalysis, Renewable Energy, Sustainability and the Environment, Spectroscopy and Organic Chemistry, having authored 17 papers that have together received 528 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (6 papers), Advanced Battery Materials and Technologies (4 papers), Crystallography and molecular interactions (4 papers), Advancements in Battery Materials (3 papers), Advanced Chemical Physics Studies (3 papers), Asymmetric Synthesis and Catalysis (2 papers), Molecular Sensors and Ion Detection (2 papers) and Conducting polymers and applications (2 papers). The work is most often cited by research in Catalysis (80 citations), Physical and Theoretical Chemistry (60 citations), Electronic, Optical and Magnetic Materials (107 citations), Automotive Engineering (67 citations) and Computational Theory and Mathematics (68 citations). Tamara Husch has collaborated with scholars based in Switzerland, Germany and United States. Frequent co-authors include Markus Reiher, Martin Korth, Andrea Balducci, Christoph Schütter, Leon Freitag, Jonny Proppe, Gregor N. C. Simm, Cornelius Gropp, Nils Trapp and Thomas F. Miller. Their work appears in journals such as Journal of the American Chemical Society, The Journal of Physical Chemistry C, Physical Chemistry Chemical Physics, The Journal of Chemical Physics and Journal of Chemical Theory and Computation.

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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