van der Wiel, Wilfred G.

The rise of intelligent matter

Kaspar, C., Ravoo, B. J., van der Wiel, W. G., Wegner, S. V., & Pernice, W. H. P. (2021) · Nature

Advanced Memory and Neural ComputingAdvanced Materials and Mechanics

Cited by 526

Classification with a disordered dopant-atom network in silicon

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) · Nature

Advanced Memory and Neural ComputingNeural Networks and Applications

Cited by 95

A deep-learning approach to realizing functionality in nanoelectronic devices

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) · Nature Nanotechnology

Advancements in Semiconductor Devices and Circuit DesignQuantum and electron transport phenomena

Cited by 65

Hopping-Transport Mechanism for Reconfigurable Logic in Disordered Dopant Networks

Tertilt, H., Bakker, J., Becker, M., de Wilde, B., Klanberg, I., Geurts, B. J., van der Wiel, W. G., Heuer, A., & Bobbert, P. A. (2022) · Physical Review Applied

Advanced Memory and Neural ComputingAdvancements in Semiconductor Devices and Circuit Design

Cited by 8

Dopant network processing units as tuneable extreme learning machines

van de Ven, B., Alegre-Ibarra, U., Lemieszczuk, P. J., Bobbert, P. A., Ruiz Euler, H.-C., & van der Wiel, W. G. (2023) · Frontiers in Nanotechnology

Advanced Memory and Neural ComputingMachine Learning and ELM

Cited by 2