Alwin Daus

1.9k citations
61 papers · 1.5k · h-index 19

Impact in

Papers in

    • Advanced Memory and Neural Computing 19
    • Thin-Film Transistor Technologies 19
    • Semiconductor materials and devices 13
    • Perovskite Materials and Applications 12
    • Chalcogenide Semiconductor Thin Films 9
    • 2D Materials and Applications 17

Alwin Daus

58 papers receiving 1.5k citations

Peers

Alwin Daus
Comparison fields: 5 of 72
  • Polymers and Plastics 311
  • Electrical and Electronic Engineering 1.0k
  • Materials Chemistry 724
  • Biomedical Engineering 560
  • Bioengineering 56
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Citations per field
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Citations per year

Countries citing papers authored by Alwin Daus

Since Specialization
Citations

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

Fields of papers citing papers by Alwin Daus

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017215
2 2021158
3 2021128
4 2022113
5 202269
6 201866
7 201666
8 201863
9 201760
10 201854
11 201541
12 201737
13 201734
14 202334
15 202333
16 201626
17 202321
18 201820
19 202218
20 202317

About Alwin Daus

Alwin Daus is a scholar working on Electrical and Electronic Engineering, Materials Chemistry, Biomedical Engineering, Polymers and Plastics and Atomic and Molecular Physics, and Optics, having authored 61 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (19 papers), Thin-Film Transistor Technologies (19 papers), 2D Materials and Applications (17 papers), Semiconductor materials and devices (13 papers), Perovskite Materials and Applications (12 papers), Transition Metal Oxide Nanomaterials (10 papers), Advanced Sensor and Energy Harvesting Materials (10 papers) and Chalcogenide Semiconductor Thin Films (9 papers). The work is most often cited by research in Polymers and Plastics (311 citations), Electrical and Electronic Engineering (1.0k citations), Materials Chemistry (724 citations), Biomedical Engineering (560 citations) and Bioengineering (56 citations). Alwin Daus has collaborated with scholars based in United States, Germany and Switzerland. Frequent co-authors include Eric Pop, Giuseppe Cantarella, Gerhard Tröster, Stefan Knobelspies, Giovanni A. Salvatore, Luisa Petti, Niko Münzenrieder, Christian Vogt, Lars Büthe and Ryan W. Grady. Their work appears in journals such as IEEE Electron Device Letters, Nano Letters, Advanced Functional Materials, Advanced Electronic Materials and ACS Applied Materials & Interfaces.

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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