Authors
S. A. Dagesyan, S. Yu. Ryzhenkova, I. V. Sapkov, D. E. Presnov, A. S. Trifonov, V. A. Krupenin & O. V. Snigirev

Moscow University Physics Bulletin, 75, 4, 331-335 (2020)

Abstract
In this work, we present a nanoscale solid state structure, which is a 3D-array of tunnel-coupled arsenic dopants in silicon with a system of metallic electrodes leading to them. The structures of eight metal electrodes were fabricated on the inhomogeneously in depth doped with arsenic silicon surface, four of which converge to a region 50 nm in diameter, and four to a region of 200 nm. After removal of a thin highly conducting upper silicon layer, single-electron transport in an array (reservoir) of arsenic impurity atoms located between the electrodes is demonstrated. The Coulomb blockade was ∼100 mV at a temperature of 4.2 K. The proposed structure can be used as a reservoir neural network, where single impurity atoms act as neurons, and electrodes will act as input and output terminals of the device, and also be used to configure the neural network. The operating temperature of such devices can be significantly increased due to the relatively small effective size of impurity arsenic atoms in silicon (3–5 nm).