György Vas

3.2k total citations · 1 hit paper
16 papers, 2.1k citations indexed

About

György Vas is a scholar working on Spectroscopy, Analytical Chemistry and Health, Toxicology and Mutagenesis. According to data from OpenAlex, György Vas has authored 16 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Spectroscopy, 7 papers in Analytical Chemistry and 4 papers in Health, Toxicology and Mutagenesis. Recurrent topics in György Vas's work include Analytical chemistry methods development (6 papers), Mass Spectrometry Techniques and Applications (5 papers) and Atmospheric chemistry and aerosols (4 papers). György Vas is often cited by papers focused on Analytical chemistry methods development (6 papers), Mass Spectrometry Techniques and Applications (5 papers) and Atmospheric chemistry and aerosols (4 papers). György Vas collaborates with scholars based in United States, Belgium and Hungary. György Vas's co-authors include Károly Vékey, Magda Claeys, Reinhilde Vermeylen, Willy Maenhaut, V. A. Pashynska, Paulo Artaxo, Meinrat O. Andreae, Jan Cafmeyer, Wu Wang and Bim Graham and has published in prestigious journals such as Science, Journal of Clinical Investigation and Analytical Chemistry.

In The Last Decade

György Vas

15 papers receiving 2.0k citations

Hit Papers

Formation of Secondary Or... 2004 2026 2011 2018 2004 250 500 750 1000
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Formation of Secondary Organic Aerosols Through Photooxidation of Isoprene
    2004 1.2k citations Magda Claeys, Bim Graham et al. Science profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
György Vas 1.3k 843 492 273 249 16 2.1k
Bo Larsen 667 0.5× 941 1.1× 140 0.3× 392 1.4× 141 0.6× 34 1.9k
E. Kleist 1.9k 1.5× 1.5k 1.8× 720 1.5× 179 0.7× 732 2.9× 45 3.0k
Jarí N. Cardoso 413 0.3× 427 0.5× 241 0.5× 136 0.5× 89 0.4× 73 1.5k
M. Judith Charles 559 0.4× 1.5k 1.8× 169 0.3× 275 1.0× 54 0.2× 57 2.3k
Jevgeni Parshintsev 369 0.3× 322 0.4× 98 0.2× 232 0.8× 65 0.3× 41 1.2k
Luciano Lepri 433 0.3× 880 1.0× 89 0.2× 648 2.4× 81 0.3× 109 2.2k
José Ruiz‐Jiménez 259 0.2× 276 0.3× 101 0.2× 291 1.1× 224 0.9× 70 1.8k
Mona Shahgholi 790 0.6× 545 0.6× 188 0.4× 161 0.6× 50 0.2× 26 1.3k
Rafał Szmigielski 2.1k 1.6× 1.5k 1.7× 405 0.8× 161 0.6× 102 0.4× 58 2.4k
István Gebefügi 268 0.2× 506 0.6× 65 0.1× 182 0.7× 107 0.4× 48 1.3k

Countries citing papers authored by György Vas

Since Specialization
Citations

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

Fields of papers citing papers by György Vas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of György Vas

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

All Works

16 of 16 papers shown
1.
Szabo, Drew, Travis M. Falconer, Christine M. Fisher, et al.. (2024). Online and Offline Prioritization of Chemicals of Interest in Suspect Screening and Non-targeted Screening with High-Resolution Mass Spectrometry. Analytical Chemistry. 96(9). 3707–3716. 15 indexed citations
2.
Norwood, Daniel L., et al.. (2022). Impact of the GC-MS Injection Solvent and the Analyte Concentration on Relative Responses for common Extractables. 4(1). e22002–e22002. 3 indexed citations
3.
4.
Armstrong, Barbara L., et al.. (2012). Stir bar sorptive extraction combined with GC–MS/MS for determination of low level leachable components from implantable medical devices. Journal of Pharmaceutical and Biomedical Analysis. 74. 162–170. 19 indexed citations
5.
6.
Wang, Xiande, et al.. (2012). Molecular imaging of drug‐eluting coronary stents: method development, optimization and selected applications. Journal of Mass Spectrometry. 47(2). 155–162. 14 indexed citations
7.
Claeys, Magda, Ivan Kourtchev, V. A. Pashynska, et al.. (2010). Polar organic marker compounds in atmospheric aerosols during the LBA-SMOCC 2002 biomass burning experiment in Rondônia, Brazil: sources and source processes, time series, diel variations and size distributions. Atmospheric chemistry and physics. 10(19). 9319–9331. 77 indexed citations
8.
Hanczko, Robert, David Fernández, Edward Doherty, et al.. (2009). Prevention of hepatocarcinogenesis and increased susceptibility to acetaminophen-induced liver failure in transaldolase-deficient mice by N-acetylcysteine. Journal of Clinical Investigation. 119(6). 1546–1557. 71 indexed citations
9.
Vas, György, et al.. (2008). Investigation of mass-balance issue in e-beam sterilized paclitaxel eluting coronary stents by SPME/GC–MS. Journal of Pharmaceutical and Biomedical Analysis. 48(3). 568–572. 4 indexed citations
10.
Vas, György, et al.. (2006). Study of transaldolase deficiency in urine samples by capillary LC‐MS/MS. Journal of Mass Spectrometry. 41(4). 463–469. 20 indexed citations
11.
Vas, György & Károly Vékey. (2004). Solid‐phase microextraction: a powerful sample preparation tool prior to mass spectrometric analysis. Journal of Mass Spectrometry. 39(3). 233–254. 446 indexed citations
12.
Wang, Wu, György Vas, R. Dommisse, Kristof T. J. Loones, & Magda Claeys. (2004). Fragmentation study of diastereoisomeric 2‐methyltetrols, oxidation products of isoprene, as their trimethylsilyl ethers, using gas chromatography/ion trap mass spectrometry. Rapid Communications in Mass Spectrometry. 18(16). 1787–1797. 30 indexed citations
13.
Claeys, Magda, Bim Graham, György Vas, et al.. (2004). Formation of Secondary Organic Aerosols Through Photooxidation of Isoprene. Science. 303(5661). 1173–1176. 1179 indexed citations breakdown →
14.
Pashynska, V. A., Reinhilde Vermeylen, György Vas, Willy Maenhaut, & Magda Claeys. (2002). Development of a gas chromatographic/ion trap mass spectrometric method for the determination of levoglucosan and saccharidic compounds in atmospheric aerosols. Application to urban aerosols. Journal of Mass Spectrometry. 37(12). 1249–1257. 152 indexed citations
15.
Szilágyi, Zoltán, et al.. (1996). Investigation of Macromolecules in Wines by Matrix-assisted Laser Desorption/Ionization Time-of-flight Mass Spectrometry. Rapid Communications in Mass Spectrometry. 10(9). 1141–1143. 11 indexed citations
16.
Vas, György, Károly Vékey, Gábor Czira, et al.. (1993). Characterization of melanins by pyrolysis/gas chromatography/mass spectrometry. Rapid Communications in Mass Spectrometry. 7(10). 870–873. 7 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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