Home
Products
Services
Industries
Research
Company

Metal-Organic Chemical Vapor Deposition (MOCVD)

MOCVD of BSTO Thin Films

The team of SC Solutions, Stanford University, and ATMI (Danbury, CT) has developed chemical mechanisms, reactor-scale models and control strategies for MOCVD of Barium Strontium Titanate/Oxide (BSTO) thin-films. There is considerable interest in polycrystalline BSTO films because they exhibit low dielectric losses and tunable dielectric constants that make them very useful for a wide range of applications.

Our approach has involved concurrent ab initio research into the chemical mechanisms for oxide formation using quantum chemistry calculations, together with reactor-scale modeling of transport properties and chemical kinetics. Prior to this work, no studies had been undertaken to determine the decomposition mechanism from a fundamental standpoint. This integrated approach has enabled realistic simulations of BSTO deposition, the results of which compare favorably with experimental data. The model was subsequently used for development of a control architecture for realizing deposition with enhanced oxide uniformity and accurate stoichiometries. Additionally, the model was used to study ways in which minor chamber modifications would enhance deposition uniformity.

The reactor-scale simulations, used to determine both reactor design as well as process optimization, require kinetic and transport properties of the barium, strontium and titanium beta-diketonate precursors and their decomposition products. These are generally not known, however there is some experimental data of the overall rate of film growth and several mechanisms for film deposition have been proposed.

We have used quantum chemical methods to study the decomposition mechanisms of beta-diketonate precursors and found that decomposition is likely to begin with the cleavage of M-O bonds. The M-O bond in the monodentate ligand is considerably strengthened after the other M-O bond (of the same ring) is broken due to the charge donation of the oxygen into empty metal d states. The co-polymerization model found in the literature assumed that Ba(dpm)2 and Sr(dpm)2 copolymerize preferentially with TiO(dpm)2. Our calculations have shown that Ti (OH)2-O-M and Ti(OH)2-O2-M where M= Sr or Ba, dimers are indeed stable and energetically favored over the homogeneous dimers.

SC Solutions has developed reactor-scale models developed for studying species transport and chemical kinetics within the reactor. A popular software platform, CFD-ACETM, was used for developing the models. Both two-dimensional (2D) and three dimensional (3D) models were developed. However, the 2D model was considered sufficiently accurate for most of the simulations of this nominally axisymmetric reactor. The model incorporates all the essential physics, and the kinetics models and transport properties were based on the DFT studies and data from the literature. The deposition rates and uniformities obtained from the simulations were similar to those obtained on the ATMI's reactor. The model was used to perform 'what-if' experiments for testing sensitivity of deposition uniformity and precursor utilization. The model was used to recommend minor modifications to the ATMI reactor for better uniformity, as well as developing a run-to-run controller.

Model-Based Control for BSTO MOCVD

The primary objective is to obtain a uniformly distributed BSTO deposition of desired thickness and stoichiometry on a wafer, with little variation from wafer-to-wafer. Thickness non-uniformity is primarily caused by species depletion and by temperature non-uniformity on the wafer at lower temperatures. Stoichiometry non-uniformity may be caused by unequal diffusivities of the gas-phase intermediates and fluctuations or drifts in the precursor supply.

The inputs available to control deposition are the flow rate and/or pressure of the carrier gas, the temperature of the susceptor, and the concentration of the precursor gases. The outputs that are measured are the flow rates of carrier gas (in-situ), susceptor temperatures measured using thermocouples (in-situ), and the deposition thickness (ex-situ). The wafer temperature may or may not be measured using a pyrometer, or has to be modeled from the susceptor temperature. The expected sources of noise and disturbances include measurement noise on all measurements, random fluctuations in flow rate, random fluctuations in precursor concentration, and drifts in wafer and susceptor temperatures. The control problem is to obtain deposition thickness with desired deposition uniformity using the available control inputs and measured outputs, in the face of the expected noise and disturbances. The physical model described in the previous section approximates the static global behavior of the MOCVD reactor, and is used in the controller design.

Although the deposition process as a function of control inputs can be considered as a static system, all disturbances are dynamic, which implies that dynamic "slave" controllers are needed locally to obtain tight regulation at the desired operating points, as shown in the figure below. The control structure shows both dynamic controllers using in-situ sensing as well as a run-to-run controller employing ex-situ sensors. The vaporizers are controlled by local (inner-loop) controllers, there are in-situ temperature sensors measuring substrate temperature corresponding to substrate (segmented) heaters, and metrology is employed to measure wafer properties of interest (deposition thickness and uniformity, stoichiometry). Integral control and (notch) filtering possibly extended with some phase compensation should give tight regulation. For this design, it is preferable to have (low-complexity) dynamic models available that relate measured outputs to manipulated inputs and disturbances/noise.

bstocontrol
Schematic of Control Structure for BSTO MOCVD

Run-to-run Control for BSTO MOCVD

Run-to-run control has been shown to be an excellent means to achieve desired film properties. Here, the values of the nominal operating set-points (called recipe variables) are adjusted after one run of the process based on ex-situ measurements of wafer properties before processing the next wafer. SC Solutions has developed a model-based run-to-run controller for BSTO thin film manufacturing.

MOCVD of High Temperature Superconducting Thin Films

SC Solutions, in partnership with MIT, developed techniques and tools for modeling, model-order reduction and control of MOCVD of YBCO (yttrium barium copper oxide) high temperature superconducting (HTS) thin-films. This was one of the first such modeling efforts for HTS manufacturing. As further example of SC Solutions' CVD modeling capabilities, some results for a 2D reactor using a seven-step finite-rate kinetics model are shown below.

mocvd5

mocvd6

Gas velocities in a 2D version of Thomas Swan MOCVD reactor (vertical dimensions exaggerated).

Temperature contours for same flow. The 50 m diameter wafer sits 175 mm from the left end of reactor.

mocvd7

mocvd8

Precursor mass fraction at mid-height along reactor.

Oxide mass fractions in the vertical direction at the wafer center.

YBCO deposition rate uniformity with wafer rotating. Operating conditions are as follows: the gas mixture of precursors, oxygen, nitrogen, and argon enter the reactor at a pressure of 10 torr with velocity 2 m/s and temperature 513 K. Inlet mole fractions are: O2 = 0.44, N2 = 0.47, Ar = 0.088, Y(dpm)3 = 2.72X10-5, (Ba(dpm)2)4 = 4.41X10-5, Cu(dpm)2 = 2.35X10-5. The wafer (and the chamber walls) are kept at a temperature of 1073 K.

mocvd9

This work was funded by a DARPA contract and administerd by ONR.

Related Projects

Related Publications

Copyright © 2010 SC Solutions, Inc.