Carré

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

Full Professor of Nano Electronics, Director Center for Brain-Inspired Nano Systems (BRAINS)
EEMCS-EE-NE
Carré C1441
w.g.vanderwiel@utwente.nl
+31534892873
Business card

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)
Email: W.G.vanderWiel@utwente.nl

University of Twente Featured Scientist
Press photos

CURRICULUM VITAE

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 more than 125 journal articles receiving over 10,000 citations.  

EDUCATION

  • 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

1In the Netherlands, ‘cum laude’ is the only (and therefore highest) distinction for MSc and PhD degrees, and is only awarded to the top ~5% of the candidates. The predicates ‘summa cum laude’ and ‘magna cum laude’ do not exist in the Dutch system.

WORK EXPERIENCE

  • 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

PUBLICATIONS

>125 publications,
>8,250 citations, h-index: 32 (Web of Science, Nov 2022)
>12,200 citations, h-index: 39 (Google Scholar, Nov 2022)
Full list of publications

PATENTS

4 patents

OTHER SCIENTIFIC ACTIVITIES

  • 2022: Co-chair Workshop on Unconventional Computing, Erice (Italy)
  • 2022: Initiator and co-chair of Brainspiration 2022 (Enschede, NL)
  • 2021: Specialty Chief Editor Frontiers in Nanotechnology | Nanoelectronics
  • 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
  • 2005: Co-chair Gordon Research Conference on Quantum Information Science (Ventura, CA, USA)

GRANTS AND AWARDS

  • 2022-2027: EIC Pathfinder HYBRAIN (Horizon Europe, coordinator)
  • 2022-2025: Core-to-core Material Intelligence (JSPS, co-PI)
  • 2020-2024: Collaborative Research Centre Intelligent Matter (DFG, co-PI)
  • 2020: Take-off Grant (Dutch Science Council NWO, PI)
  • 2019: Program QUAKE, Dutch Science Council (NWO)
  • 2019: HTSM Grant NANO(AI)2 (Dutch Science Council NWO, PI)
  • 2018: Physics Projectruimte, Dutch Science Council (NWO)
  • 2017: NWA Startimpuls, Dutch Science Council (NWO)
  • 2016: UT in de media prijs 2015
  • 2015: Marie Curie Sklodowska ITN, European Commission
  • 201: HTSM Grant, Dutch Science Council (NWO)
  • 2015: Proof of Concept Grant (ERC, PI)
  • 2014: Proof of Concept Grant (ERC, PI)
  • 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

MEDIA

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

Organisations

Ancillary activities

  • Frontiers - www.frontiersin.orgSpecialty Chief Editor Frontiers in Nanotechnology | Nanoelectronics
  • Northwestern Polytechnical University, Xi’an, ChinaNPU Guest Professorship
  • ECsens b.v.Scientific Advisor to ECsens b.v.
  • Osaka UniversityPart-time lecturer
  • Westfälische Wilhelms Universität MünsterSecond membership Faculty of Physics WWU Münster
  • TU WienInternational Advisory Board ENROL

PUBLICATIONS

>130 publications, >8,750 citations
Web of Science: h-index 33 (October 2023)
Google Scholar:  h-index 41 (October 2023)
ORCID

Full list of publications

FEATURED PUBLICATIONS

Toward a formal theory for computing machines made out of whatever physics offers
H. Jaeger, B. Noheda and W.G. van der Wiel
Nat. Commun. 14, 4911 (2023)

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 
Nat. Nanotechnol. 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,
Science 289, 2105 (2000)

PATENTS

4 patents

RESEARCH INTERESTS

BRAIN-INSPIRED NANO SYSTEMS FOR ENERGY-EFFICIENT COMPUTING

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)

NANOELECTRONIC BIOSENSING

Spin-off company ECsens

Publications
Nano Letters 20, 820-828 (2020)

ACOUSTOELECTRONICS

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)   

HYBRID INORGANIC-ORGANIC ELECTRONICS

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)

COMPLEX-OXIDE ELECTRONICS

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)

Research profiles

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