Self-limited etching for atomic scale surface engineering of metals: understanding and design

University Of California-Los Angeles, Los Angeles CA

Investigators

Abstract

All solids are terminated by a surface. To control the composition and structure of a surface, chemically selective and spatially accurate modification processes with atomic-level precision are required. This is particularly true for the semiconductor industry where device feature sizes have entered the single-digit nanometer scale. To enable the fabrication of future nanodevices, this project seeks to develop methods to selectively and directionally etch industrially significant metals. Traditionally, metal etching and patterning has been performed by expositing the surface to an acid. However, such an approach cannot be used for nanofabrication because of its poor selectivity, non-directionality, and poor etch-depth control. Plasma etch processes constitute a significant improvement in directional control, but these processes can suffer from metal redeposition. Atomic layer etching (ALE) offers a promising alternative. ALE is a two-step self-limiting cyclic process where the metal surface is first modified by a plasma process and then is exposed to a precursor that selectively etches the modified surface. While having the potential to address all the aforementioned drawbacks of etch processes, a thorough understanding of the plasma and surface reaction mechanisms for important metals such as Ni and Cu is needed. This proposal seeks to fill this knowledge gap with a comprehensive computational chemistry approach. The project integrates research and training of Ph.D. and undergraduate students at the frontier of theoretical modeling and surface engineering process design and discovery. These students will be well prepared by the broad training on electronic structure calculations, algorithms of artificial intelligence and data science, surface chemistry experiments, and understanding of experimental data, capabilities, and limitations. This computational/experimental research program focuses on developing atomic layer etch (ALE) processes for the layer-by-layer removal of metal films. The reactive ALE process to be modelled starts with a metal surface modification step under plasma conditions to convert surface metal atoms to a surface compound that, when exposed to an etching agent, forms volatile metal-complexes that desorb, exposing the etched metal surface. The modification step will be modelled using molecular dynamics (MD) simulations with neural network potentials (NNPs), considering realistic initial kinetic energy for the trajectories. The NNP parameters will be identified using a training data set generated using density functional theory (DFT) based calculations. The results of plasma modification machine-learning MD simulations will be verified with surface modification experiments in an Inductively Coupled Plasma (ICP) chamber. For the etching reaction step, a thermodynamic database of energy will first be constructed as a function of etchant, substrate, modifiers, and process conditions. The thermodynamic database will be used to propose feasible etching chemistries. For experimentally validated cases, a detailed computational mechanistic exploration of reaction elementary steps for the etching reaction will determine the size of kinetic barriers for key low-energy pathways. Collectively, this methodology will result in an enhanced understanding of self-limiting surface reactions as well as the definition of optimal reactants to accurately engineer metallic surfaces. Educational and outreach activities supported by this program include partnering with the UCLA Center for Excellence in Engineering and Diversity (CEED) to identify top underrepresented minority (URM) students to work on this program (undergraduate student in the first year and high-school student in the second year). Informal science communication will be performed using the educational portals, such as Atomic Scale Design Network (ASDN.net) and NanoHUB (nanohub.org). The research team will create educational pages that bring forth the novel concepts and ideas in the field of atomic scale surface engineering. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.