prof.dr.ir. W.G. van der Wiel (Wilfred)

Full Professor of Nano Electronics, Director Center for Brain-Inspired Nano Systems (BRAINS)

About Me

Given names:                       Wilfred Gerard
Academic titles:                  Prof. Dr. MSc.
Birth date and place:           28 May 1975, Gouda, The Netherlands
Present function:                 Professor of NanoElectronics and Director of Center for
                                              Brain-Inspired Nano Systems (BRAINS)
                                              E: W.G.vanderWiel@utwente.nl

University of Twente Featured Scientist
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Wilfred G. van der Wiel (Gouda, 1975) is full professor of Nanoelectronics and director of the BRAINS Center for Brain-Inspired Nano Systems at the University of Twente, The Netherlands. He holds a second professorship at the Institute of Physics of the Westfälische Wilhelms Universität Münster, Germany. His research focuses on unconventional electronics for efficient information processing. Van der Wiel is a pioneer in Material Learning at the nanoscale, realizing computational functionality and artificial intelligence in designless nanomaterial substrates through principles analogous to Machine Learning. He is author of 120 journal articles receiving 7,500 citations.  


1998-2002           PhD Applied Physics (cum laude1), Delft University of Technology, The                              Netherlands; NTT Basic Research Labs. Japan
1993-1997           MSc Applied Physics (cum laude1), Delft University of Technology, The                              Netherlands

1Highest distinction in the Netherlands academic system awarded to ~5% of candidates


2018-present       Director Center for Brain-Inspired Nano Systems (BRAINS)
2009-present       Full Professor and Chair, University of Twente
2007-2009           Associate Professor, University of Twente
2005-2007           Research Program Leader, University of Twente, The Netherlands
2002-2005           PostDoc and JST Sakigake Fellow, University of Tokyo, Japan


>125 publications, >7,500 citations, h-index: 30 (Web of Science)

Full list of publications


4 patents


2020-present      International advisor for WISE-SSS program, Tokyo Institute of                                           Technology, Tokyo, Japan
2020-present      Member External Advisory Board, Research Center for Neuromorphic
                           AI Hardware, Kyushu Institute of Technology, Japan
2019-present      Visiting Professor in the Institute of Physics, Westfälische-Wilhelms-                                 Universität Münster
2018-present      Member External Advisory Panel Groningen Cognitive Systems and                                   Materials Center, University of Groningen, The Netherlands
2016-present      Member Advisory Editorial Board Journal of Science: Adv. Materials
                           and Devices
2014 - 2016        Member Executive Committee of the Global Young Academy (GYA)
2012-2017          Member Global Young Academy (GYA)
2007 - 2012        Member Young Academy (DJA), Royal Netherlands Academy of Art
                           and Sciences


2020                   Take-off Grant, Dutch Science Council (NWO)
2019                   Program Quake, Dutch Science Council (NWO)
2019                   HTSM Grant, Dutch Science Council (NWO)
2018                   Physics Projectruimte, Dutch Science Council (NWO)
2017                   NWA Startimpuls, Dutch Science Council (NWO)
UT in de media prijs 2015
2015                   Marie Curie Sklodowska ITN, European Commission
2015                   HTSM Grant, Dutch Science Council (NWO)
2015                   ERC Proof of Concept Grant
2014                   ERC Proof of Concept Grant
2014                   FOM Projectruimte, Dutch Science Council (NWO)
2014                   Program DESCO, Dutch Science Council (NWO)
2013                   World Economic Forum Outstanding Young Scientist Award
2013                   STW Valorization Grant I, Dutch Science Council (NWO)
2012                   FETOPEN Nascence, FP7 European Commission
2009                   ERC Starting Grant
2009                   NanoSci-E+, European Commission
2009                   Program Inter-phase, Dutch Science Council (NWO)
2009                   NWO nano (2x), Dutch Science Council (NWO)
2008                   STW Open Technologie Programma, Dutch Science Council (NWO)
2006                   NWO Vidi Grant, Dutch Science Council (NWO)
2002                   JST Pioneer (Sakigake) Fellowship


2021                   NEMO - Gouden nanodeeltjes imiteren hersencellen
2021                   Trouw - Het ideaal ligt in de armen van de octopus
2021                   De Ingenieur - Breincomputer
2020                   Financieel Dagblad - De machine wordt menselijker
2020                   Tweakers - De hersenen als voorbeeld: Neuromorfische Informatica
2020                   Tubantia - Miljoenen voor samenwerking UT met Universiteit Münster
2020                   Physics World - Electrically tuneable network learns fast
2020                   Introduction to BRAINS
2019                   Omroep MAX - Het eeuwige leven van Jan Mulder
2018                   Nieuwsuur - Is de dood straks een keuze?
2017                   UT Magazine - Smarter than our brain
2016                   Studium Generale - Darwin on a chip
2015                   Financieel Dagblad - Het brein als inspiratiebron
2015                   New Scientist - Grains of gold shine at computing
2015                   de Volkskrant - Nanolabyrinth uit Twente lijkt op menselijk brein
2015                   Tubantia - Geloof in de wetenschap
2014                   de Volkskrant - Chips kunnen nauwelijks kleiner. En nu?
2012                   Between Nano and Nature
2011                   BNR Nieuwsradio - Denktank 
2009                   Tubantia - Europees geld voor onderzoek nanotechnologie


For more info about Wilfred van der Wiel on the 'Featured Scientists' page, click below:

Ancillary Activities

  • Westfälische Wilhelms Universität Münster
    Second membership Faculty of Physics WWU Münster
  • ECsens b.v.
    Scientific Advisor to ECsens b.v.
  • Tokyo Institute of Technology, Tokyo, Japan
    International advisor for WISE-SSS program, Tokyo Institute of Technology, Tokyo, Japan
  • Research Center for Neuromorphic AI Hardware, Kyushu Institute of Technology, Japan
    Member External Advisory Board, Research Center for Neuromorphic AI Hardware, Kyushu Institute of Technology, Japan
  • Frontiers - www.frontiersin.org
    Specialty Chief Editor Frontiers in Nanotechnology | Nanoelectronics
  • Northwestern Polytechnical University, Xi’an, China
    NPU Guest Professorship
  • ECsens b.v.
    Scientific Advisor to ECsens b.v.
  • Osaka University
    Part-time lecturer



>125 publications, >7,500 citations
Web of Science: h-index 30 (November 2021)
Google Scholar:  h-index 37 (November 2021)

Full list of publications


A deep-learning approach to realizing functionality in nanoelectronic devices
Hans-Christian Ruiz Euler, Marcus N. Boon, Jochem T. Wildeboer, Bram van de Ven, Tao Chen, Hajo Broersma, Peter A. Bobbert and Wilfred G. van der Wiel 
Nature Nanotechnology 15, 992-998 (2020)

Electrochemical Detection of Tumor-Derived Extracellular Vesicles on Nanointerdigitated Electrodes 
D. G. Mathew, P. Beekman, S. G. Lemay, H. Zuilhof, S. le Gac, W. G. van der Wiel 
Nano Letters 20, 820-828 (2020)

Classification with a disordered dopant-atom network in silicon 
T. Chen, J. van Gelder, B. van de Ven, S. Amitonov, B. de Wilde, H.-C. Ruiz-Euler, 
H. J. Broersma, P. A. Bobbert, F. A. Zwanenburg, W. G. van der Wiel 
Nature 577, 341-345 (2020) 

Bottom-Up Single-Electron Transistors
K. S. Makarenko, Z. H. Liu, M. P. de Jong, F. A. Zwanenburg, J. Huskens,
W. G. van der Wiel

Adv. Mater. 29, 1702920 (2017)

Evolution of a Designless Nanoparticle Network into Reconfigurable Boolean Logic
S. K. Bose, C. P. Lawrence, Z. Liu, K. S. Makarenko, R. M. J. van Damme, H. J. Broersma and W. G. van der Wiel 
Nature Nanotechnology 10, 1048 (2015)

Tunable Doping of a Metal with Molecular Spins
T. Gang, M. D. Yilmaz, D. Ataç, S.K. Bose, E. Strambini, A. H. Velders, M. P. de Jong,
J. Huskens and W. G. van der Wiel 
Nature Nanotechnology 
7, 232 (2012)

Electron transport through double quantum dots
W. G. van der Wiel, S. De Franceschi, J.M. Elzerman, T. Fujisawa, S. Tarucha and
L. P. Kouwenhoven,
Rev. Mod. Phys. 
75, 1 (2003)

The Kondo Effect in the Unitary Limit 
W. G. van der Wiel, S. De Franceschi, T. Fujisawa, J. M. Elzerman, S. Tarucha and
L. P. Kouwenhoven,
289, 2105 (2000)


4 patents



Digital computing has dramatically changed our society. Despite its undeniable success, its technical progress is slowing down and facing physical and economical limits. Moreover, the energy consumption of digital IT is rapidly increasing to an unsustainable level. In order to overcome the limitations of digital computing – particularly, but not exclusively for machine-learning tasks – our group has been exploring the intrinsic physical properties of disordered, nanoscale networks. We have shown that such nonlinear systems can be trained to perform logic operations and canonical machine-learning tasks with potentially very high energy efficiency and small footprint.

Natural and man-made information processing systems differ greatly. Evolution has resulted in living systems that utilize whatever physical properties are exploitable to enhance the fitness for survival. Nature thereby exploits the emergent properties and massive parallelism of highly interconnected networks of locally active components. Man-made computers, however, are based on circuits of functional units, following rigid design rules. In conventional (classical) computational paradigms, potentially exploitable physical processes to solve a problem, are possibly left out. In our research, we manipulate physical systems using the principle of Material Learning, to take full advantage of the computational power of nanomaterial networks.

We have shown that a designless network of gold nanoparticles can be evolved into Boolean logic gates [1]. Later we demonstrated that the above principle is generic and can be demonstrated in other material systems as well, at much higher temperatures. By exploiting the nonlinearity of a nanoscale network of boron dopants in silicon (Si:B networks), we can significantly facilitate (nonlinear) classification [2]. We map a limited number of input data to a new, high-dimensional feature space, in which the data become linearly separable. Using a convolutional neural network approach, it becomes possible to use our device for handwritten digit recognition.

We also show that our Si:B network can be well described by a deep neural network, which allows for applying standard machine learning techniques in finding functionality [3]. We argue that this approach can be helpful in optimizing complex (quantum) nanoelectronic devices in general.

[1] Nature Nanotechnology 10, 1048 (2015) 
[2] Nature 577, 341-345 (2020)
[3] Nature Nanotechnology (2020)




Spin-off company ECsens

Nano Letters 20, 820-828 (2020)



The oscillating (piezo-)electric fields accompanying surface acoustic waves (SAWs) are able to transport charge carriers in semiconductor nanostructures, where the SAW wavelength can be of the same order as the device size [1]. In our research, we apply nano imprint lithography (NIL) to define high-frequency (> 1 GHz) interdigitated transducers (IDTs) to electrically excite SAWs in a piezoelectric substrate [2,3]. In particular, we demonstrate acoustic transport of photo-generated electron-hole pairs in GaAs/AlGaAs core/shell nanowires on top of a LiNbO3 substrate [4]. The wavelength of the acoustic modulation is smaller than the nanowire length. This allows for transporting the electrons and holes in a spatially separated fashion along the nanowire with a well-defined acoustic velocity towards indium doped recombination centers, where light is detected. Spatially resolved photoluminescence measurements indicate a relative transport efficiency of ~60%. By depositing a piezoelectric layer [3], acoustro-electronic transport experiments in non-piezoelectronic semiconductors like silicon is in reach.

[1] Phys. Rev. Lett. 96, 136807 (2006)
[2] Nanotechnology 23 315303 (2012)
[3] Appl. Phys. Lett. 102, 013112 (2013)
[4] Nanotechnology 25, 135204 (2014)

Applied Physics Letters 116, 011601 (2020)
Journal of Applied Physics 127, 214901 (2020)
Journal of Physics D: Applied Physics 53, 335301 (2020)   



Where conventional electronics makes use mainly of top-down fabrication technology, the introduction of molecular materials paves the way for bottom-up fabrication as well (self-assembly). Hybrid electronic devices benefit from the strong aspects of both fabrication methods. In this research line we take advantage of all these characteristics of hybrid electronic devices to carry out experiments in a largely unexplored area of fundamental and broad scientific interest.

The conduction mechanism in organic (molecular) materials often differs drastically from that in their inorganic (crystalline) counterparts, and still many aspects remain to be understood. A very important and critical issue is the understanding of electronic phenomena at the interface between inorganic and molecular materials, as they usually play a dominant role in the overall properties.

Nature Nanotechnology 7, 232 (2012)
Adv. Mater. 29, 1702920 (2017)
Angew. Chem. Int. Ed. 57, 11465 (2018)
Advanced Electronic Materials 5, 1900041 (2019)



Appl. Phys. Lett. 103, 201603 (2013)
Phys. Rev. Lett. 118, 106401 (2017)
Phys. Rev. B 97, 245113 (2018)
Applied Physics Letters 116, 011601 (2020)
Journal of Applied Physics 127, 214901 (2020)
Journal of Physics D: Applied Physics 53, 335301 (2020)
Physical Review Letters 124, 017702 (2020) 
2020 IEEE 33rd International Conference on Microelectronic Test Structures (ICMTS)

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Courses Academic Year  2021/2022

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses Academic Year  2020/2021

Contact Details

Visiting Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Carré (building no. 15), room C1441
Hallenweg 23
7522NH  Enschede
The Netherlands

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Mailing Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Carré  C1441
P.O. Box 217
7500 AE Enschede
The Netherlands

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