Model-based predictive control of thermal processing

Details Model-based predictive control of thermal processing Model-based predictive control of thermal processing

2000-06-27

2002-04-16

Paschall, Mark (Department: 3742)

Electric heating

Heating devices

With power supply and voltage or current regulation or...

C219S483000, C219S486000, C392S416000, 36

Reexamination Certificate

active

06373033

ABSTRACT:

BACKGROUND OF THE INVENTION
1. Field of the Invention
The invention relates to automatic feedback control of thermal processing. In particular, the invention pertains to model-based predictive temperature control of thermal process reactors such as used in semiconductor processing.
2. Description of the Related Art
Until recently, most of the high temperature processing necessary for integrated circuit fabrication was performed in hot-wall, resistance-heated batch reactors. Controlling the wafer temperature uniformity (within-wafer, point-to-point) in these reactors was generally not considered an issue, because the reactors were substantially isothermal. The down-boat (wafer-to-wafer) temperature uniformity could be controlled effectively by dividing the cylindrical heating coil into several zones, each with its own temperature sensor controller and power supply. The outer zones were typically adjusted to compensate for heat losses at the furnace ends. Independent, single-loop, off-the-shelf PID controllers suffice for these purposes. The trend to larger wafer diameters, the demanding uniformity requirements for ULSI applications, and the demands for reduced thermal budget all led to an increased use of single-wafer process reactors. For commercially feasible throughput, it is highly desirable to minimize the process cycle time by heating substantially only the wafer and its immediate environment. In many cases, single-wafer reactors are of the cold-wall or warm-wall type, in which quartz or stainless steel process chambers are water or air cooled. Under such circumstances, the system is no longer isothermal and temperature uniformity control becomes an issue of considerable concern and technical difficulty. A recent technical review of the field is provided in “Rapid Thermal Processing Systems: A Review with Emphasis on Temperature Control,” F. Roozeboom, N. Parekh,
J. Voc. Sci. Technol.
B 8(6), 1249-1259, 1990.
Specific physical process characteristics serve to exemplify the need for precise temperature uniformity. Homo-epitaxial deposition of silicon should be performed in a manner which minimizes crystalline growth defects, such as lattice slip. Such defects are induced by thermal gradients in the wafer during high temperature processing, becoming more sensitive to gradients as temperature increases. For example, while gradients of about 100° C. across an 8-inch wafer may be tolerable at a process temperature of 900° C., respective gradients of only 2-3° C. are allowable at process temperatures of 1100° C. There is some experimental evidence to indicate that gradients of approximately 10° C. may be tolerable for a few seconds. The deposition of polycrystalline silicon (polysilicon) typically takes place at 600-700° C. where as a rule of thumb a 2% uniformity degradation is incurred for every degree of temperature gradient. Moreover, in heterodeposition processes such as polysilicon deposition, multiple reflections and optical interference within the deposited overlayers can give rise to emissive or absorptive changes with overlayer thickness, exacerbating the problem of maintaining temperature uniformity (J. C. Liao, T. I. Kamins, “Power Absorption During Polysilicon Deposition in a Lamp-Heated CVD Reactor, J. Appld. Phys., 67(8), 3848-3852 (1990)). Furthermore, patterned layers can also lead to variations in light absorption across the wafer, creating local temperature gradients. (P. Vandenabeele, K. Maex, “Temperature Non-Uniformities During Rapid Thermal Processing of Patterned Wafers,”
Rapid Thermal Processing
SPIE, Vol. 1189, pp. 84-103, 1989).
The aforementioned factors complicating the control system design are not only manifest for rapid thermal chemical vapor deposition (RTCVD) systems, but apply to thermal processing (TP) systems in general, where the need for precise process control is balanced by the demand for minimal process cycle times. The generally short process cycle times and fast dynamics of the single-wafer systems render dynamic control of temperature uniformity a necessity of considerable technical difficulty. The radiant heating systems used for rapid wafer heating comprise either arc lamps or banks of linear tungsten-halogen lamps divided into several independently-controllable heating zones. The wafer itself, in principle, represents a complex thermal system whose interaction with the radiant energy is inherently nonlinear. Furthermore, since the requirements for power distribution over the wafer are different for dynamic compared to steady-state uniformity, it does not suffice to deduce the required power settings from a wafer temperature measurement at a single point. In general, multiple sensors are required to measure and maintain a uniform temperature distribution over the wafer. These considerations render temperature control an essentially multi-input, multi-output (MIMO) or multivariable problem. Due to the large interaction between zones inherently present in radially heated systems, the conventional control techniques, for example, using single-loop, coupled or master-slave type PID control, cannot be expected to provide thermal process reactor systems with the required control specifications for all operating conditions. Conventional PID control techniques are susceptible to lag, overshoot and instability at the desirable process rates, and therefore become limiting factors in single-wafer process reactors. Thus, there is a clear need in electronic materials processing for systems which can maintain precise, dynamic multivariant control while providing commercially viable wafer throughput.
The foregoing discussion has clearly outlined the need for effective uniformity control in thermal process reactors using a multivariable approach. This view is endorsed by many authors. See, for instance, several contributions in the
Rapid Thermal and Integrated Processing Symposium,
ed. J. C. Gelpey, et al.,
Mater. Res. Soc. Symp. Proc.,
Vol. 224, 1991. In particular, articles by Moslehi et al. (pp. 143-156), Apte, et al. (pp. 209-214), and Norman et al. (pp. 177-183), discuss various aspects of multivariable temperature control. Several attempts to develop models for RTP and RTCVD systems are reported in the literature. Two examples, Norman and Gyurcsik, et al., developed different models, both using a first-principles approach, and applied the models to uniformity optimization (S. A. Norman, “Optimization of Wafer Temperature Uniformity in Rapid Thermal Processing Systems,”
0
ISL Tech. Rep. No. 91-SAN-1, Subm. to IEEE Trous. on Electron Devices, 1991; R. S. Gyurcsik, T. J. Riley, R. Y. Sorrel, “A Model for Rapid Thermal Processing: Achieving Uniformity Through Lamp Control,” IEEE Trans. on Semicon. Manf., Vol. 4(1), 1991). The model of Norman (1991) consists of two components. The first component models the (two-dimensional) heat balance of the wafer and is used to compute the steady-state wafer temperature profile for a given heat flux from the lamps. The second component models the heat flux from the lamps as a function of the individual lamp powers. A least-squares method is used to fit a quadratic relationship between the desired temperature at discrete radial positions on the wafer and the flux density due to the lamps. Next, the lamp model is used to determine optimal relative power settings for the lamps that approximate the required flux. This method only applies to the uniformity control in steady-state, i.e., constant input. However, Norman, et al. (1991), consider not only the steady-state optimization problem, but also the problem of designing an optimal trajectory. For this purpose the dynamic model is a finite-difference approximation to the one-dimensional heat equation, including the effects of conduction in the wafer, convective heat loss from the wafer, and radiative transfer. A minimax solution is chosen for the steady-state uniformity optimization and trajectory following.
Dynamic system modeling is an essential ingredient of predictive control laws, which provide the fundamental structure for a unique class of conte

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