Tammo van der Heide

1.8k total citations
17 papers, 532 citations indexed

About

Tammo van der Heide is a scholar working on Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering and Materials Chemistry. According to data from OpenAlex, Tammo van der Heide has authored 17 papers receiving a total of 532 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Atomic and Molecular Physics, and Optics, 5 papers in Electrical and Electronic Engineering and 5 papers in Materials Chemistry. Recurrent topics in Tammo van der Heide's work include Machine Learning in Materials Science (3 papers), Molecular Junctions and Nanostructures (3 papers) and Advanced Chemical Physics Studies (3 papers). Tammo van der Heide is often cited by papers focused on Machine Learning in Materials Science (3 papers), Molecular Junctions and Nanostructures (3 papers) and Advanced Chemical Physics Studies (3 papers). Tammo van der Heide collaborates with scholars based in Germany, China and Netherlands. Tammo van der Heide's co-authors include A.V. Stoupakova, K. Rønning, Geir Birger Larssen, E. Henriksen, Alf Ryseth, H.M. Bjørnseth, Bálint Aradi, Thomas Frauenheim, Wenbo Sun and Elizabeth Santos and has published in prestigious journals such as The EMBO Journal, Molecular Microbiology and Biological reviews/Biological reviews of the Cambridge Philosophical Society.

In The Last Decade

Tammo van der Heide

13 papers receiving 511 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Tammo van der Heide Germany	8	239	212	127	122	72	17	532
Xiaoli Wu China	16	212 0.9×	54 0.3×	25 0.2×	35 0.3×	61 0.8×	63	709
Anders Ahlberg Sweden	12	63 0.3×	81 0.4×	120 0.9×	15 0.1×	106 1.5×	26	587
Youyi Yu China	10	60 0.3×	105 0.5×	70 0.6×	37 0.3×	134 1.9×	17	566
C. L. Thompson United States	11	156 0.7×	46 0.2×	45 0.4×	32 0.3×	19 0.3×	22	438
Chenhui Liu China	10	50 0.2×	16 0.1×	54 0.4×	54 0.4×	100 1.4×	23	401
Young-Gyun Kim South Korea	13	82 0.3×	27 0.1×	78 0.6×	136 1.1×	9 0.1×	29	408
J.K.C. Hessels Netherlands	8	162 0.7×	85 0.4×	225 1.8×	34 0.3×	3 0.0×	8	560
Satoshi Omori Japan	21	32 0.1×	86 0.4×	302 2.4×	11 0.1×	858 11.9×	44	1.4k
Tianqi Zhou China	13	176 0.7×	63 0.3×	30 0.2×	26 0.2×	155 2.2×	52	484

Countries citing papers authored by Tammo van der Heide

Since Specialization

Citations

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

Fields of papers citing papers by Tammo van der Heide

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tammo van der Heide. 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 Tammo van der Heide. The network helps show where Tammo van der Heide may publish in the future.

Co-authorship network of co-authors of Tammo van der Heide

This figure shows the co-authorship network connecting the top 25 collaborators of Tammo van der Heide. A scholar is included among the top collaborators of Tammo van der Heide 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 Tammo van der Heide. Tammo van der Heide is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Bouma, Tjeerd J., et al.. (2025). A review of the historic and present ecological role of aquatic and shoreline wood, from forest to deep sea. Biological reviews/Biological reviews of the Cambridge Philosophical Society.

Sun, Wenbo, Tammo van der Heide, Van‐Quan Vuong, et al.. (2025). Hybrid Functional DFTB Parametrizations for Modeling Organic Photovoltaic Systems. Journal of Chemical Theory and Computation. 21(10). 5103–5117.

Jiang, Junke, Tammo van der Heide, Arnaud Fihey, et al.. (2025). Flexible and efficient semiempirical DFTB parameters for electronic structure prediction of 3D, 2D iodide perovskites and heterostructures. Physical Review Materials. 9(2).

Heide, Tammo van der, B. Hourahine, Bálint Aradi, Thomas Frauenheim, & Thomas A. Niehaus. (2024). Phonon-induced band gap renormalization by dielectric dependent global hybrid density functional tight binding. Physical review. B.. 109(24). 3 indexed citations

Santos, Elizabeth, Bálint Aradi, Tammo van der Heide, & Wolfgang Schmickler. (2024). Free energy curves for the Volmer reaction obtained from molecular dynamics simulation based on quantum chemistry. Journal of Electroanalytical Chemistry. 954. 118044–118044. 8 indexed citations

Zhugayevych, Andriy, et al.. (2023). Benchmark Data Set of Crystalline Organic Semiconductors. Journal of Chemical Theory and Computation. 19(22). 8481–8490. 7 indexed citations

Quaino, Paola, José Luís Núñez, Bálint Aradi, et al.. (2023). Why DFT‐Based Tight Binding Gives a Better Representation of the Potential at Metal‐Solution Interfaces than DFT Does. ChemElectroChem. 10(20). 5 indexed citations

Wu, Xiaoyan, Tammo van der Heide, Shi‐Zheng Wen, et al.. (2023). Molecular dynamics study of plasmon-mediated chemical transformations. Chemical Science. 14(18). 4714–4723. 9 indexed citations

Sun, Wenbo, et al.. (2023). Machine Learning Enhanced DFTB Method for Periodic Systems: Learning from Electronic Density of States. Journal of Chemical Theory and Computation. 19(13). 3877–3888. 14 indexed citations

10.

Heide, Tammo van der, Bálint Aradi, B. Hourahine, Thomas Frauenheim, & Thomas A. Niehaus. (2023). Hybrid functionals for periodic systems in the density functional tight-binding method. Physical Review Materials. 7(6). 6 indexed citations

11.

Heide, Tammo van der, Jolla Kullgren, Peter Broqvist, et al.. (2022). Fortnet, a software package for training Behler-Parrinello neural networks. Computer Physics Communications. 284. 108580–108580. 5 indexed citations

12.

Henriksen, E., Alf Ryseth, Geir Birger Larssen, et al.. (2011). Chapter 10 Tectonostratigraphy of the greater Barents Sea: implications for petroleum systems. Geological Society London Memoirs. 35(1). 163–195. 135 indexed citations

13.

Henriksen, E., H.M. Bjørnseth, Tammo van der Heide, et al.. (2011). Chapter 17 Uplift and erosion of the greater Barents Sea: impact on prospectivity and petroleum systems. Geological Society London Memoirs. 35(1). 271–281. 180 indexed citations

14.

Heide, Tammo van der, et al.. (2007). Zeegrasmitigaties Oosterschelde. Proeven met verplaatsen van klein zeegras Zostera noltii in de Oosterschelde: mitigatiemaatregel bij toekomstige dijkwerkzaamheden.

15.

Heide, Tammo van der. (2001). On the osmotic signal and osmosensing mechanism of an ABC transport system for glycine betaine. The EMBO Journal. 20(24). 7022–7032. 147 indexed citations

16.

Poolman, B., Fang Ge, Robert H. Friesen, et al.. (2000). Amplified gene expression in gram-positive bacteria, and membrane reconstitution of purified membrane transport proteins. University of Groningen research database (University of Groningen / Centre for Information Technology). 3 indexed citations

17.

Heide, Tammo van der, et al.. (1995). Expression of the gltP gene of Escherichia coli in a glutamate transport‐deficient mutant of Rhodobacter sphaeroides restores chemotaxis to glutamate. Molecular Microbiology. 18(4). 641–647. 10 indexed citations

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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