David Clases

1.4k total citations
62 papers, 997 citations indexed

About

David Clases is a scholar working on Analytical Chemistry, Spectroscopy and Health, Toxicology and Mutagenesis. According to data from OpenAlex, David Clases has authored 62 papers receiving a total of 997 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Analytical Chemistry, 14 papers in Spectroscopy and 10 papers in Health, Toxicology and Mutagenesis. Recurrent topics in David Clases's work include Analytical chemistry methods development (21 papers), Mass Spectrometry Techniques and Applications (12 papers) and Mercury impact and mitigation studies (7 papers). David Clases is often cited by papers focused on Analytical chemistry methods development (21 papers), Mass Spectrometry Techniques and Applications (12 papers) and Mercury impact and mitigation studies (7 papers). David Clases collaborates with scholars based in Austria, Australia and Germany. David Clases's co-authors include Raquel González de Vega, Philip Doble, David Bishop, Thomas E. Lockwood, Uwe Kärst, Dominic J. Hare, Michael Sperling, Xiaoxue Xu, Samantha Goyen and Lukas Schlatt and has published in prestigious journals such as Chemical Reviews, Analytical Chemistry and The Science of The Total Environment.

In The Last Decade

David Clases

54 papers receiving 989 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Clases Austria 20 358 238 191 153 141 62 997
Lanlan Jin China 21 582 1.6× 199 0.8× 233 1.2× 87 0.6× 90 0.6× 60 1.3k
Nanjing Zhao China 19 418 1.2× 125 0.5× 204 1.1× 106 0.7× 124 0.9× 123 1.1k
E. García-Ruiz Spain 27 795 2.2× 260 1.1× 190 1.0× 199 1.3× 162 1.1× 48 1.6k
Owen T. Butler United Kingdom 21 464 1.3× 249 1.0× 258 1.4× 147 1.0× 61 0.4× 44 1.0k
C. Derrick Quarles United States 19 496 1.4× 226 0.9× 240 1.3× 85 0.6× 61 0.4× 51 955
Tomáš Vaculovič Czechia 21 278 0.8× 124 0.5× 116 0.6× 148 1.0× 169 1.2× 104 1.4k
Lee L. Yu United States 19 225 0.6× 80 0.3× 209 1.1× 77 0.5× 107 0.8× 51 923
Olga Borovinskaya Switzerland 18 411 1.1× 203 0.9× 145 0.8× 71 0.5× 226 1.6× 26 1.1k
Björn Meermann Germany 24 431 1.2× 217 0.9× 422 2.2× 197 1.3× 261 1.9× 73 1.7k
Hongtao Zheng China 27 1.1k 3.1× 514 2.2× 360 1.9× 77 0.5× 86 0.6× 53 1.5k

Countries citing papers authored by David Clases

Since Specialization
Citations

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

Fields of papers citing papers by David Clases

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Clases

This figure shows the co-authorship network connecting the top 25 collaborators of David Clases. A scholar is included among the top collaborators of David Clases 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 David Clases. David Clases 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
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Lockwood, Thomas E., Raquel González de Vega, Lukas Schlatt, & David Clases. (2025). Accurate thresholding using a compound-Poisson-lognormal lookup table and parameters recovered from standard single particle ICP-TOFMS data. Journal of Analytical Atomic Spectrometry. 40(10). 2633–2640.
3.
Kronenberg, Katharina, Nassim Ghaffari‐Tabrizi‐Wizsy, Dalial Freitak, et al.. (2025). Exploring high-dimensional LA-ICP-TOFMS data with uniform manifold approximation and projection (UMAP). Journal of Analytical Atomic Spectrometry. 40(12). 3473–3484.
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Chowdari, Ramesh Kumar, et al.. (2025). Hierarchical hollow-microspheres of nickel-copper bimetallic catalyst for the highly selective hydrodeoxygenation of guaiacol to cyclohexanol. Chemical Engineering Journal Advances. 24. 100875–100875. 1 indexed citations
6.
7.
Vega, Raquel González de, Etienne Skrzypek, Brigid A. McKenna, et al.. (2024). Investigating how H2S can alter the interactions between Hg0 and corroded steel surfaces to guide future decommissioning projects. Journal of Hazardous Materials. 480. 136025–136025. 2 indexed citations
8.
Lockwood, Thomas E., et al.. (2024). AF 4 -MALS-SP ICP-ToF-MS analysis gives insight into nature of HgSe nanoparticles formed by cetaceans. Environmental Science Nano. 11(5). 1883–1890. 4 indexed citations
9.
Vega, Raquel González de, Tatiane de Andrade Maranhão, Natalia P. Ivleva, et al.. (2024). Studying the degradation of bulk PTFE into microparticlesviaSP ICP-MS: a systematically developed method for the detection of F-containing particles. Journal of Analytical Atomic Spectrometry. 39(8). 2030–2037. 6 indexed citations
10.
Clases, David, Noemí Eiró, Luis O. González, et al.. (2024). Quantitative distribution of essential elements and non-essential metals in breast cancer tissues by LA-ICP-TOF–MS. Analytical and Bioanalytical Chemistry. 417(2). 361–371. 1 indexed citations
11.
Lockwood, Thomas E., Raquel González de Vega, Zhiye Du, et al.. (2023). Strategies to enhance figures of merit in ICP-ToF-MS. Journal of Analytical Atomic Spectrometry. 39(1). 227–234. 19 indexed citations
12.
Clases, David, Raquel González de Vega, John Parnell, & Jörg Feldmann. (2023). Fluorine mapping via LA-ICP-MS/MS: a proof of concept for biological and geological specimens. Journal of Analytical Atomic Spectrometry. 38(8). 1661–1667. 6 indexed citations
13.
Vega, Raquel González de, et al.. (2023). Non-target analysis and characterisation of nanoparticles in spirits via single particle ICP-TOF-MS. Journal of Analytical Atomic Spectrometry. 38(12). 2656–2663. 16 indexed citations
14.
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Clases, David. (2023). Swimming against the current – sacrificing unit mass resolution in ICP-MS to improve figures of merit. Journal of Analytical Atomic Spectrometry. 38(12). 2518–2527. 2 indexed citations
16.
Vega, Raquel González de, David Clases, Bliss A. Cunningham, et al.. (2023). Spatial distribution of trace metals and associated transport proteins during bacterial infection. Analytical and Bioanalytical Chemistry. 416(11). 2783–2796. 1 indexed citations
17.
Maleknia, Simin D., David Clases, Andrew I. Minett, et al.. (2022). Immunoaffinity extraction followed by enzymatic digestion for the isolation and identification of proteins employing automated μSPE reactors and mass spectrometry. Analytical and Bioanalytical Chemistry. 415(18). 4173–4184. 3 indexed citations
18.
Camp, Emma F., Matthew R. Nitschke, David Clases, et al.. (2022). Micronutrient content drives elementome variability amongst the Symbiodiniaceae. BMC Plant Biology. 22(1). 184–184. 15 indexed citations
19.
Du, Ziqing, Abhishek Gupta, Christian Clarke, et al.. (2020). Porous Upconversion Nanostructures as Bimodal Biomedical Imaging Contrast Agents. The Journal of Physical Chemistry C. 124(22). 12168–12174. 23 indexed citations
20.
Hermann, Sven, Gerald Kehr, David Clases, et al.. (2017). Harnessing the Maltodextrin Transport Mechanism for Targeted Bacterial Imaging: Structural Requirements for Improved in vivo Stability in Tracer Design. ChemMedChem. 13(3). 241–250. 42 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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