Predictive process design: a theoretical model of atomic layer deposition

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Abstract

We present a theoretical framework for the predictive design of atomic layer deposition (ALD). ALD is the leading process for the controlled deposition of thin films in a variety of technologies. For example, insulating alumina layers are fabricated by ALD for electroluminescent flat-screen displays and for node DRAM, and are under investigation as high-k dielectrics for the MOSFET gate. To develop and optimise an ALD process for a new material requires knowledge of the reaction mechanism. By combining structures computed at the quantum mechanical level and literature data from in situ experiments, we develop a quantitative model of the ALD reaction cycle for alumina deposition. We are thus able to identify the intrinsic limits on ALD growth and explain how the growth rate depends on process conditions.

Introduction

Atomic Layer Deposition (ALD) is a chemical vapour deposition technique, suitable for the slow and controlled growth of thin, conformal oxide films [1]. Gaseous precursors are admitted separately into the reactor in alternate pulses, chemisorbing individually onto the substrate, rather than reacting in the gas-phase. The reactor is purged with an inert gas between precursor pulses. Insulating layers of aluminium sesquioxide (alumina, Al2O3) are fabricated by ALD for electroluminescent flat-screen-displays [1], for node DRAM and for read/write thin film heads [2]. Despite its modest dielectric constant (k  9), the large band gap of alumina and the quality of its interface to silicon has made it a candidate for MOSFET gate dielectrics [3], possibly in combination with higher-k oxides.

Successful precursors for alumina ALD are trimethylaluminium, Al(CH3)3 or TMA, and water, H2O, which react to give solid alumina and methane:AlMe3(g)+3/2H2O(g)1/2Al2O3(s)+3CH4(g)

Various models for the mechanism of alumina ALD have been proposed [4], [5], [6] but definitive evidence for the surface intermediates is lacking. A previous computational study of alumina ALD considered the energetics of TMA hydrolysis, including activation energies, under the unhindered conditions of a cluster model, rather than at a realistic surface [7]. We therefore apply density functional theory (DFT) to models of the growing hydroxylated and methylated alumina surfaces, in order to investigate the atomic-scale structure and reactivity. The resulting mechanism allows us to establish the intrinsic limits to ALD growth.

In this work we develop a quantitative representation of the ALD reaction cycle: a phase portrait in the space of the chemical concentrations of reactive surface intermediates. The prototype reaction portrait is shown in Fig. 1. In each ALD pulse, the surface is saturated by precursor fragments (CH3 or H) that are reactive during the next pulse. The progress of the ALD process may therefore by plotted against the surface concentration, [CH3] or [H], of each reactive intermediate. The reaction portrait shows the net rate of precursor adsorption (horizontal and vertical lines) and of desorption of the CH4 by-product (diagonal lines) during each pulse. The Al2O3 growth rate is therefore proportional to the size (height or width) of the portrait (only surface species are shown on the portrait, so that there is no explicit representation of the growth of bulk Al2O3). In a successful pulse–purge–pulse–purge cycle leading to stoichiometric growth, there will be no accumulation of either CH3 or H on the surface, and the cycle will return to its starting point. The coverages are quoted without reference to actual surface structure—for example, it is not specified whether the H is present as Al–OH or as Al–OH2, or whether it penetrates into sub-surface layers.

We will adapt this general representation to the specific case of alumina ALD. First principles calculations are used in Section 2 to establish the coverage limits [Me], [H] and these are compared with literature data. The variation in surface intermediates with process conditions is considered in Section 3, looking in particular at how these change with temperature.

Section snippets

Method

The First Principles (FP) method is established as a reliable way to predict materials properties [8]. Self-consistent DFT within 3D-periodic boundary conditions is used to compute the ground state electronic structure. We employ the VASP package [9], [10], [11] and use a standard set of technical parameters, as follows: plane-wave basis <396 eV, ultrasoft pseudopotentials [12], gradient-corrected density functional PW91 [13], sparse sampling of reciprocal space [14], self-consistent

Optimum conditions

Bringing together the mechanistic data from Sections 2.2 Methyl coverage, 2.3 Hydroxyl coverage, a reaction portrait for optimum alumina ALD is proposed in Fig. 4. In this scheme, starting from the gibbsite-like hydroxylated substrate, one TMA molecule adsorbs per surface cell, two CH4 desorb and a surface covered with capping Al(CH3) is generated. The coverage of [Me] = 1 per cell corresponds to a coverage of 13 μmol m−2. During the H2O pulse and purge, 1.5 molecules per cell are needed to adsorb

Conclusion

A theoretical model is presented for the atomic-scale mechanism of alumina growth by atomic layer deposition from TMA and H2O precursors. First Principles density functional calculations are combined with literature data to determine the likely intermediates during the reaction cycle and their surface concentrations. This mechanistic information allows a quantitative portrait of the reaction to be sketched in the space of the coverage of intermediates. As well as giving an estimate of the

Acknowledgement

We are grateful for funding by the European Community under the “Information Society Technologies” Programme through the HIKE project, available from: <http://www.nmrc.ie/hike>.

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