Devin Daems

848 total citations
30 papers, 662 citations indexed

About

Devin Daems is a scholar working on Molecular Biology, Biomedical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Devin Daems has authored 30 papers receiving a total of 662 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 17 papers in Biomedical Engineering and 9 papers in Electrical and Electronic Engineering. Recurrent topics in Devin Daems's work include Advanced biosensing and bioanalysis techniques (12 papers), Biosensors and Analytical Detection (11 papers) and Electrochemical Analysis and Applications (7 papers). Devin Daems is often cited by papers focused on Advanced biosensing and bioanalysis techniques (12 papers), Biosensors and Analytical Detection (11 papers) and Electrochemical Analysis and Applications (7 papers). Devin Daems collaborates with scholars based in Belgium, United Kingdom and United States. Devin Daems's co-authors include Jeroen Lammertyn, Frans C. De Schryver, N. Boens, Dragana Spasić, Filip Delport, Karolien De Wael, Wolfgang Pfeifer, Barbara Saccà, L.J. Nagels and Guy Van Camp and has published in prestigious journals such as Analytical Chemistry, ACS Applied Materials & Interfaces and International Journal of Molecular Sciences.

In The Last Decade

Devin Daems

30 papers receiving 649 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Devin Daems Belgium 15 353 293 173 69 64 30 662
Magdalena Gębala Germany 18 668 1.9× 245 0.8× 167 1.0× 69 1.0× 36 0.6× 36 840
A. Tsargorodskaya United Kingdom 12 246 0.7× 162 0.6× 148 0.9× 56 0.8× 33 0.5× 23 515
Takahiko Nojima Japan 16 653 1.8× 289 1.0× 158 0.9× 50 0.7× 93 1.5× 59 923
Halina D. Inerowicz United States 14 308 0.9× 241 0.8× 92 0.5× 29 0.4× 149 2.3× 34 732
A. Ottova-Leitmannova United States 6 392 1.1× 125 0.4× 89 0.5× 70 1.0× 29 0.5× 9 560
Valérie Guieu France 15 479 1.4× 504 1.7× 107 0.6× 26 0.4× 58 0.9× 23 865
Mark J. Feldstein United States 12 566 1.6× 538 1.8× 185 1.1× 58 0.8× 88 1.4× 18 1.1k
Changsun Eun United States 13 281 0.8× 114 0.4× 69 0.4× 22 0.3× 33 0.5× 29 515
Susanne Witt Germany 11 533 1.5× 224 0.8× 248 1.4× 25 0.4× 80 1.3× 15 895
Joshua Salafsky United States 18 510 1.4× 137 0.5× 197 1.1× 30 0.4× 37 0.6× 29 1.0k

Countries citing papers authored by Devin Daems

Since Specialization
Citations

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

Fields of papers citing papers by Devin Daems

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Devin Daems

This figure shows the co-authorship network connecting the top 25 collaborators of Devin Daems. A scholar is included among the top collaborators of Devin Daems 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 Devin Daems. Devin Daems 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
1.
Carrignon, Simon, Paul J. Yaworsky, Xiutang Zhang, et al.. (2025). Assessing quantitative methods in archaeology via simulated datasets: The Archaeoriddle challenge. Concept, project and motivations. Journal of Archaeological Science. 177. 106179–106179. 2 indexed citations
2.
Bello, Valentina, Wouter Vandezande, Devin Daems, & Jeroen Lammertyn. (2023). A Dual-Region Fiber-Optic SPR Biosensor with Self-Referencing Compensation of Bulk Refractive Index and Temperature Effects. 1–1. 1 indexed citations
3.
4.
Echelpoel, Robin Van, et al.. (2022). Electrochemical methods for on-site multidrug detection at festivals. Sensors & Diagnostics. 1(4). 793–802. 11 indexed citations
5.
Vandezande, Wouter, et al.. (2021). Unraveling the effect of the aptamer complementary element on the performance of duplexed aptamers: a thermodynamic study. Analytical and Bioanalytical Chemistry. 413(19). 4739–4750. 9 indexed citations
6.
Echelpoel, Robin Van, Mats de Jong, Devin Daems, P. Van Espen, & Karolien De Wael. (2021). Unlocking the full potential of voltammetric data analysis: A novel peak recognition approach for (bio)analytical applications. Talanta. 233. 122605–122605. 17 indexed citations
7.
Jong, Mats de, et al.. (2020). Electrochemical analysis of speedball-like polydrug samples. The Analyst. 145(18). 6091–6096. 2 indexed citations
8.
Jong, Mats de, et al.. (2020). A Benzocaine‐Induced Local Near‐Surface pH Effect: Influence on the Accuracy of Voltammetric Cocaine Detection. Analysis & Sensing. 1(1). 54–62. 11 indexed citations
9.
Daems, Devin, et al.. (2020). Boosting biomolecular interactions through DNA origami nano-tailored biosensing interfaces. Journal of Materials Chemistry B. 8(16). 3606–3615. 16 indexed citations
10.
Adriaens, Ines, Tjebbe Huybrechts, Devin Daems, et al.. (2017). Mathematical characterization of the milk progesterone profile as a leg up to individualized monitoring of reproduction status in dairy cows. Theriogenology. 103. 44–51. 14 indexed citations
11.
Daems, Devin, Filip Delport, Ben Aernouts, et al.. (2016). Competitive inhibition assay for the detection of progesterone in dairy milk using a fiber optic SPR biosensor. Analytica Chimica Acta. 950. 1–6. 58 indexed citations
12.
Daems, Devin, Karel Knez, Filip Delport, Dragana Spasić, & Jeroen Lammertyn. (2016). Real-time PCR melting analysis with fiber optic SPR enables multiplex DNA identification of bacteria. The Analyst. 141(6). 1906–1911. 28 indexed citations
13.
Hamidi‐Asl, Ezat, Devin Daems, Karolien De Wael, Guy Van Camp, & L.J. Nagels. (2014). Concentration-Related Response Potentiometric Titrations To Study the Interaction of Small Molecules with Large Biomolecules. Analytical Chemistry. 86(24). 12243–12249. 11 indexed citations
14.
Daems, Devin, Alexander L.N. van Nuijs, Adrian Covaci, et al.. (2014). Potentiometric detection in UPLC as an easy alternative to determine cocaine in biological samples. Biomedical Chromatography. 29(7). 1124–1129. 7 indexed citations
15.
16.
Daems, Devin, Karolien De Wael, Kris Vissenberg, Guy Van Camp, & L.J. Nagels. (2013). Potentiometric sensors doped with biomolecules as a new approach to small molecule/biomolecule binding kinetics analysis. Biosensors and Bioelectronics. 54. 515–520. 13 indexed citations
17.
Wael, Karolien De, Devin Daems, Guy Van Camp, & L.J. Nagels. (2012). Use of Potentiometric Sensors To Study (Bio)molecular Interactions. Analytical Chemistry. 84(11). 4921–4927. 15 indexed citations
18.
Rouah‐Martin, Elsa, Jaytry Mehta, Bieke Van Dorst, et al.. (2012). Aptamer-Based Molecular Recognition of Lysergamine, Metergoline and Small Ergot Alkaloids. International Journal of Molecular Sciences. 13(12). 17138–17159. 16 indexed citations
19.
Daems, Devin, N. Boens, & Frans C. De Schryver. (1989). Fluorescence quenching with lindane in small unilamellar l,α-dimyristoylphosphatidylcholine vesicles. European Biophysics Journal. 17(1). 25–36. 9 indexed citations
20.

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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