Spatially-Modulated Silicon Interface Energetics via Hydrogen Plasma-Assisted Atomic Layer Deposition of Ultrathin Alumina
Alex Henning, Johannes D. Bartl, Lukas Wolz, Maximilian Christis,, Felix Rauh, Michele Bissolo, Theresa Gr\"unleitner, Johanna Eichhorn, Patrick, Zeller, Matteo Amati, Luca Gregoratti, Jonathan J. Finley, Bernhard Rieger,, Martin Stutzmann, Ian D. Sharp

TL;DR
This paper introduces a novel atomic layer deposition method using hydrogen plasma to create ultrathin, patterned alumina coatings on silicon, enabling precise control of surface charge and interface energetics for semiconductor applications.
Contribution
The study demonstrates a new ALD process with hydrogen plasma that achieves sub-nanometer, patterned alumina layers on silicon, allowing for spatial modulation of interface properties.
Findings
Achieved sub-nanometer thick, continuous AlOx layers on silicon.
Created lateral AlOx/SiO2 interfaces with 0.3 nm step height.
Introduced fixed negative charges enabling surface potential modulation.
Abstract
Atomic layer deposition (ALD) is a key technique for the continued scaling of semiconductor devices, which increasingly relies on reproducible and scalable processes for interface manipulation of 3D structured surfaces on the atomic scale. While ALD allows the synthesis of conformal films at low temperature with utmost control over the thickness, atomically-defined closed coatings and surface modifications are still extremely difficult to achieve because of three-dimensional growth during nucleation. Here, we present a route towards sub-nanometer thin and continuous aluminum oxide (AlOx) coatings on silicon (Si) substrates for the spatial control of the surface charge density and interface energetics. We use trimethylaluminum (TMA) in combination with remote hydrogen plasma instead of a gas-phase oxidant for the transformation of silicon oxide into alumina (AlOx). During the initial ALD…
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Taxonomy
TopicsSemiconductor materials and devices · Electronic and Structural Properties of Oxides · Advanced Memory and Neural Computing
