Expertise
Engineering & Materials Science
# Atoms
# Deep Learning
# Doping (Additives)
# Nanoelectronics
# Neural Networks
# Silicon
Mathematics
# Gradient Descent
Physics & Astronomy
# Learning
Organisations
Publications
Recent
van de Ven, B. (2022).
Classification using Dopant Network Processing Units. University of Twente.
https://doi.org/10.3990/1.9789036553735
Boon, M. N.
, Ruiz Euler, H-C.
, Chen, T.
, van de Ven, B.
, Alegre Ibarra, U.
, Bobbert, P. A.
, & van der Wiel, W. G. (2021).
Gradient Descent in Materio. Manuscript submitted for publication.
https://doi.org/10.48550/arXiv.2105.11233
Ruiz Euler, H-C.
, Alegre Ibarra, U.
, van de Ven, B.
, Broersma, H.
, Bobbert, P. A.
, & van der Wiel, W. G. (2021).
Dopant Network Processing Units: Towards Efficient Neural-network Emulators with High-capacity Nanoelectronic Nodes.
Neuromorphic Computing and Engineering,
1(2), [024002].
https://doi.org/10.1088/2634-4386/ac1a7f
Sousa de Almeida, A. J.
, Marquez Seco, A., van de Berg, T.
, van de Ven, B.
, Amitonov, S.
, & Zwanenburg, F. A. (2020).
Ambipolar charge sensing of few-charge quantum dots.
Physical review B: Covering condensed matter and materials physics,
101(20), [201301].
https://doi.org/10.1103/PhysRevB.101.201301
Chen, T., van Gelder, J.
, van de Ven, B.
, Amitonov, S. V., de Wilde, B.
, Ruiz Euler, H-C.
, Broersma, H.
, Bobbert, P. A.
, Zwanenburg, F. A.
, & van der Wiel, W. G. (2020).
Classification with a disordered dopant-atom network in silicon.
Nature,
577, 341-345.
https://doi.org/10.1038/s41586-019-1901-0
Ruiz Euler, H-C.
, Boon, M. N., Wildeboer, J. T.
, van de Ven, B.
, Chen, T.
, Broersma, H.
, Bobbert, P. A.
, & van der Wiel, W. G. (2020).
A deep learning approach to realize funtionality in nanoelectronic devices.
Nature nanotechnology,
15, 992-998.
https://doi.org/10.1038/s41565-020-00779-y
Ruiz, H-C.
, Alegre Ibarra, U.
, van de Ven, B.
, Broersma, H.
, Bobbert, P. A.
, & van der Wiel, W. G. (2020).
Dopant Network Processing Units: Towards Efficient Neural-network Emulators with High-capacity Nanoelectronic Nodes. ArXiv.
https://arxiv.org/abs/2007.12371
Contact Details
Visiting Address
University of Twente
Drienerlolaan 5
7522 NB Enschede
The Netherlands
Mailing Address
University of Twente
P.O. Box 217
7500 AE Enschede
The Netherlands