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.
A new recombination model for device simulation including tunneling
1992724 citationsG.A.M. Hurkx, D.B.M. Klaassen et al.IEEE Transactions on Electron Devicesprofile →
A unified mobility model for device simulation—I. Model equations and concentration dependence
Countries citing papers authored by D.B.M. Klaassen
Since
Specialization
Citations
This map shows the geographic impact of D.B.M. Klaassen'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 D.B.M. Klaassen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D.B.M. Klaassen more than expected).
This network shows the impact of papers produced by D.B.M. Klaassen. 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 D.B.M. Klaassen. The network helps show where D.B.M. Klaassen may publish in the future.
Co-authorship network of co-authors of D.B.M. Klaassen
This figure shows the co-authorship network connecting the top 25 collaborators of D.B.M. Klaassen.
A scholar is included among the top collaborators of D.B.M. Klaassen 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 D.B.M. Klaassen. D.B.M. Klaassen is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Cheng, Wei, Anne-Johan Annema, J.A. Croon, D.B.M. Klaassen, & Bram Nauta. (2008). A general weak nonlinearity model for LNAs. University of Twente Research Information. 54. 221–224.10 indexed citations
Aarts, A.C.T., R. van der Hout, J.C.J. Paasschens, et al.. (2006). New fundamental insights into capacitance modeling of laterally non-uniform MOS devices. TU/e Research Portal (Eindhoven University of Technology). 620.1 indexed citations
6.
Klaassen, D.B.M., R. van Langevelde, & A.J. Scholten. (2004). Compact CMOS Modelling for Advanced Analogue and RF Applications. IEICE Transactions on Electronics. 87(6). 854–866.6 indexed citations
7.
Havens, R.J., D.B.M. Klaassen, A.J. Scholten, et al.. (2003). Noise Modeling with MOS Model 11 for RF-CMOS Applications. TechConnect Briefs. 2(2003). 286–289.1 indexed citations
Tiemeijer, L.F., et al.. (1999). MOS Model 9 based Non-Quasi-Static Small-Signal Model for RF Circuit Design. European Solid-State Device Research Conference. 1. 652–655.1 indexed citations
10.
Klaassen, D.B.M., R. van Langevelde, A.J. Scholten, & L.F. Tiemeijer. (1999). Challenges in Compact Modelling of Future RF CMOS. European Solid-State Device Research Conference. 1. 95–102.3 indexed citations
11.
Montree, A.H., et al.. (1999). Limitations to Adaptive Back Bias Approach for Standby Power Reduction in deep sub-micron CMOS. European Solid-State Device Research Conference. 1. 580–583.6 indexed citations
12.
Bennebroek, Martijn, et al.. (1998). Layout Capacitance Extraction for Low-Power RF Circuitry in Silicon-On-Anything. European Solid-State Device Research Conference. 488–491.1 indexed citations
13.
Tiemeijer, L.F. & D.B.M. Klaassen. (1998). Geometry Scaling of the Substrate Loss of RF MOSFETs. European Solid-State Device Research Conference. 480–483.20 indexed citations
Slotboom, J.W., M.J. van Dort, G.A.M. Hurkx, et al.. (1993). Physical Modelling and Simulation of Advanced Si-devices - An Industrial Approach. European Solid-State Device Research Conference. 327–334.1 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.