Method of detecting an anomalous plasma event, and apparatus

Abstract

In certain embodiments, anomalous plasma events, including the formation of an electric arc within a semiconductor processing chamber, can be detected and mitigated. In several embodiments, a method may include detecting an optical signal emitted by plasma, converting the optical signal into a voltage signal, and forming an adjusted voltage signal. In response to a determination that a change associated with the adjusted voltage signal exceeds a threshold, the output power of an RF signal coupled to the chamber can be adjusted. This adjustment can mitigate the formation of anomalous plasma events occurring within the chamber.

Description

Abnormal plasma event detection method and semiconductor processing machine The present invention relates to the detection and mitigation of anomalous plasma events in semiconductor processing. Semiconductor processing often involves the use of plasma within the fabrication chamber. During these operations, an abnormal plasma event may occur in response to the electrical conditions used to generate the plasma. Abnormal plasma events can include, for example, arcing or other types of visible events resulting from discharges between two or more localized plasma regions within a process station. Abnormal plasma events can result in excessive heating and / or excessive current, which can damage the semiconductor wafer being processed. In some instances, abnormal plasma events can cause damage to the semiconductor process station. One embodiment may include a method for detecting an anomalous plasma event in a semiconductor processing chamber. This embodiment may include detecting an optical signal emitted by plasma in the semiconductor processing chamber, wherein the plasma is formed in response to an RF signal from an RF generator. The method may also include converting the optical signal into a voltage signal and adjusting the voltage signal to form an adjusted voltage signal. The method may further include determining whether a change associated with the adjusted voltage signal exceeds a threshold, and adjusting an output parameter of the RF signal from the RF generator based at least in part on the determination. In a specific embodiment, the method may include: adjusting the voltage signal to form the adjusted voltage signal by filtering the voltage signal with a low-pass filter. The operation of determining whether the change associated with the adjusted voltage exceeds a threshold value may include comparing the voltage signal to the change of the adjusted voltage signal. The step of adjusting the voltage signal to form the adjusted voltage signal may include applying an offset to the adjusted voltage signal. The step of adjusting the voltage signal to form the adjusted voltage signal may include taking a first derivative of the voltage signal. Adjusting the output parameter of the RF generator may include: reducing an output power of the RF generator from a first power level to a second power level. The method may further include: after reducing the output power of the RF generator from the first power level to the second power level, maintaining the output power of the RF generator at the second power level for a first period of time. The method may further include, after the maintaining step, increasing the output power of the RF generator from the second power level to the first power level for a second time period. The second power level may be a non-zero power level. Alternatively, the second power level may be zero. The method may further include determining a first amount by which to reduce RF power based at least in part on light intensity or process parameters within the semiconductor processing chamber, and reducing an output power level of the RF generator by the first amount, wherein the process parameters may include one or more process parameters selected from the group consisting of: DC power level, RF bias power level, station-to-station RF power variation, frequency tuning parameters, pressure, and temperature. In one or more embodiments, a semiconductor processing machine may include a semiconductor processing chamber. The semiconductor processing machine may include an RF generator configured to provide RF power to the semiconductor processing chamber to generate and maintain plasma. The semiconductor processing machine may also include a light detector configured to detect a light signal indicating that the plasma in the semiconductor processing chamber is emitting light. The light detector may be configured to convert the light signal into a voltage signal using a slope change detection unit. The semiconductor processing machine may also include receiving the voltage signal and adjusting the voltage signal to form an adjusted voltage signal. The semiconductor processing machine may be configured to determine whether a change associated with the adjusted voltage signal exceeds a threshold. In one embodiment, in response to the determination, the semiconductor processing machine may send a signal to the RF generator configured to cause an adjustment to the RF generator. In some embodiments, the semiconductor processing machine may further include a lens on the semiconductor processing chamber configured to allow light within the semiconductor processing chamber to pass through the lens. The semiconductor processing machine may also include a fiber optic cable interposed between the lens and the light detector and configured to transmit at least a portion of the light that passes through the lens to the light detector. The slope change detection unit of the semiconductor processing machine may further include a filter configured to filter the voltage signal to convert the voltage signal into the adjusted voltage signal. The semiconductor processing machine may also include a comparator configured to compare the change between the adjusted voltage signal and the voltage signal. The comparator of the semiconductor processing machine may include transistor-transistor logic (TTL) configured to send a TTL signal to the RF generator. The RF generator may be configured to reduce RF power from a first power level to a second power level in response to receiving the signal from the slope change detection unit. The slope change detection unit may include a differentiator configured to take a derivative of the voltage signal to convert the voltage signal into the adjusted voltage signal. The semiconductor processing machine may also include a comparator configured to determine whether a change in the adjusted voltage signal exceeds the threshold. The semiconductor processing machine may further include a fiber optic cable between the semiconductor processing chamber and the light detector configured to transmit light generated by plasma in the semiconductor processing chamber to the light detector. The light detector may be electrically connected to the RF generator, wherein the light signal from the semiconductor processing chamber is fed from the semiconductor processing chamber to the RF generator. The light detector and the slope change detection unit may be disposed outside the semiconductor processing chamber. Alternatively, the light detector and the slope change detection unit may be disposed between the semiconductor processing chamber and the RF generator. The light detector and the slope change detection unit may be disposed within the semiconductor processing chamber. In certain embodiments, a method for detecting an abnormal plasma event may include forming a plasma using a signal from an RF generator and detecting a fluctuating optical signal generated by the plasma. The detection method may include calculating a spectral density of the fluctuating optical signal and determining whether the spectral density of the fluctuating optical signal differs from one or more baseline spectral densities of a fluctuating optical signal generated by the plasma by a threshold amount. In certain embodiments, calculating the spectral density of the fluctuating optical signal may utilize a fast Fourier transform (FFT). The method may include determining the one or more baseline spectral densities of a fluctuating optical signal corresponding to the spectral density of a fluctuating optical signal generated by a plasma maintained under nominal conditions. The threshold value may correspond to one standard deviation relative to the spectral density of the fluctuating optical signal from the plasma maintained under nominal conditions. The threshold value may correspond to two standard deviations relative to the spectral density of the fluctuating optical signal from the plasma maintained under nominal conditions. The spectral density of the fluctuating optical signal may include determining the spectral density of the fluctuating optical signal at a frequency of approximately 400 kHz. Calculating the spectral density of the fluctuating optical signal may include determining the spectral density of the fluctuating optical signal at a frequency between approximately 400 kHz and approximately 4 MHz. Calculating the spectral density of the fluctuating optical signal may include determining the spectral density of the fluctuating optical signal at a complex frequency generated by one or more RF generators. In certain embodiments, an apparatus may include a signal processor configured to analyze an output signal from a light detector that receives an optical signal from a multi-station processing tool. The signal processor may be further configured to: detect a fluctuating optical signal generated by a plasma formed in a semiconductor processing chamber; calculate a spectral density of the fluctuating optical signal; and determine whether the spectral density of the fluctuating optical signal differs by a threshold amount from one or more baseline spectral densities of the fluctuating optical signal generated by the plasma. In certain embodiments, one or more baseline spectral densities of the fluctuating optical signal may correspond to spectral densities calculated when the plasma is maintained under nominal conditions. The threshold amount may correspond to one standard deviation relative to the spectral density of the fluctuating optical signal from the plasma maintained under nominal conditions. Alternatively, the threshold amount may correspond to two standard deviations relative to the spectral density of the fluctuating optical signal from the plasma maintained under nominal conditions. The spectral density of the fluctuating optical signal may be calculated when an RF signal having a frequency of approximately 400 kHz is coupled to the multi-station processing tool. The spectral density of the fluctuating optical signal may be calculated to determine the spectral density of the fluctuating optical signal at a frequency between 400 kHz and 4 MHz. The spectral density of the fluctuating optical signal may be calculated at a frequency of the RF signal coupled to the multi-station processing tool. In the following description, numerous specific details are described to provide a complete understanding of the embodiments. The disclosed embodiments may be practiced without some or all of these specific details. In other instances, well-known process operations are not described in detail to avoid unnecessarily obscuring the disclosed embodiments. Although the disclosed embodiments will be described in conjunction with these specific examples, it is understood that this is not intended to limit the disclosed embodiments. In this application, the terms "semiconductor wafer," "wafer," "substrate," "wafer substrate," and "semi-finished integrated circuit" are used interchangeably. One of ordinary skill in the art understands that the term "semi-finished integrated circuit" can refer to a silicon wafer during any of the many stages of integrated circuit manufacturing on the silicon wafer. Wafers or substrates used in the semiconductor device industry may have a diameter of 200 mm, or 300 mm, or 450 mm. The following embodiments assume that the present invention is implemented on a wafer. However, the present invention is not so limited. The workpiece may have a variety of shapes, sizes, and materials. In addition to semiconductor wafers, other workpieces that may utilize this invention include various objects, such as printed circuit boards, glass panels, and the like. Many semiconductor processes utilize plasma during one or more embodiments of processing. Plasma is typically generated within a processing chamber between two electrodes, one of which is connected to a radio frequency (RF) power source and the other to an RF ground. The RF power supplied to the electrodes may range from approximately 200 watts to approximately 3,000 watts. The frequency used to drive the plasma formation may include a high-frequency (HF) component, a low-frequency (LF) component, or both. The HF frequency may be approximately 13.56 MHz or approximately 27 MHz; the LF frequency may be between approximately 300-400 kHz. Other frequencies of high-frequency or low-frequency RF power may also be used, but "high" frequency generally refers to a signal frequency that is several orders of magnitude higher than "low" frequency, such as megahertz compared to kilohertz. One type of abnormal plasma event that can occur during plasma formation is a high voltage breakdown, "light up," or arcing within the processing chamber, for example, in the area surrounding a showerhead or substrate support structure such as an electrostatic chuck (ESC). Arcing or high voltage breakdown can occur under several circumstances when two structures that can serve as electrodes are separated by a gap. These circumstances generally depend on the voltage difference between the electrodes, the composition of the gas between the electrodes, the pressure of the gas between the electrodes, and the size of the separation between the electrodes. The interaction between these factors can be characterized by Paschen's law, which provides a high voltage breakdown voltage as a function of pressure, gap distance, and two gas-dependent parameters. The voltage required to initiate an abnormal plasma event, such as light up or arcing, can be called the "breakdown voltage" and is a function of, for example, the gas filling the volume between the two electrodes, the pressure of that gas, and the distance between the potential endpoints of the arc. This relationship is determined by Paschen's law, which states , where "V B ” is the breakdown voltage, “p” is the pressure, “d” is the distance, and “a” and “b” are empirically derived constants associated with the gas involved. FIG12 (Example 1200) depicts a Paschen curve for helium. The logarithmic vertical axis represents breakdown voltage (e.g., the voltage required to produce an arc or other type of anomalous plasma event) in volts, while the horizontal axis (also logarithmic) represents pressure multiplied by distance in Torr-cm. As shown in FIG12, the lowest, or minimum, breakdown voltage of approximately 150 V is at the lowest point of the Paschen curve, which occurs at approximately 4 Torr-cm. This characteristic establishes two regions where semiconductor processing can occur before reaching the lowest breakdown voltage—to the "left" of the lowest point of the curve and to the "right" of the lowest point of the curve. The vertical dashed line in FIG12 approximates the dividing line between these two sides. Some semiconductor processes utilize higher RF powers to reduce deposition times and increase substrate productivity. However, the use of higher RF powers may increase the risk of voltage breakdown, arcing, or other types of abnormal plasma events within the processing chamber. Such events can cause damage to the substrate, the electrodes (e.g., the showerhead or substrate support structure), and the chamber itself. Unacceptable damage to the substrate may result in substrate scraping and / or may cause damage to the electrodes. In addition, a damaged chamber may require lengthy, expensive, and / or extensive repairs of the electrodes (e.g., replacing the showerhead or susceptor), which may result in additional cost and additional downtime of the semiconductor processing chamber. Therefore, it is desirable to detect arcing or other types of abnormal plasma events within a processing chamber and subsequently mitigate such events. Many conventional abnormal plasma event detection techniques can result in missed and erroneous arc detections. For example, one conventional approach may include a voltage detection method that measures the RF voltage delivered to a driven electrode to generate the plasma and determines whether the voltage reaches or approaches a threshold voltage by a certain amount. If so, these systems assume that arcing may have occurred within the processing chamber. In response to detecting the threshold voltage, the RF power is reduced or completely shut down, thereby reducing the voltage within the processing chamber and preventing the occurrence of an abnormal plasma event. This threshold voltage is typically a predetermined value obtained through experimental measurements. However, this detection method has disadvantages, such as being limited to a single predetermined voltage threshold. Furthermore, this detection method can be difficult to implement because it can require computationally intensive, very fast voltage monitoring speeds and may not accurately reflect the instantaneous occurrence of an abnormal plasma event. This inability to accurately reflect the instantaneous occurrence of an abnormal plasma event may be due to a potential time shift between the occurrence of the arc event and the measured voltage. Furthermore, detection methods may be potentially insensitive to smaller arcing events, suffer from system noise, and may require significant time and experimentation to determine and optimize an appropriate threshold voltage. Threshold voltage detection methods may have other detection limitations. For example, these methods typically detect whether the measured voltage has increased above a specific threshold. However, if the RF drive signal comprises a time-varying voltage driven at various frequencies (e.g., a periodic waveform, such as a sinusoidal signal operating at 13.56 MHz), and the intensity of light emitted by the plasma may oscillate with a frequency component similar to the normal intensity of light emitted by the plasma in response to the RF signal at a nominal peak, then, if the threshold voltage is appropriately set, anomalous plasma events that cause additional light emission may be detectable. However, if the anomalous plasma event occurs between successive peaks of the plasma cycle, the anomalous plasma event may not be detected, particularly if the component in the detector output signal attributable to the anomalous plasma event has a smaller magnitude than the amplitude of the component in the detector output signal attributable to the RF signal. For example, assuming that the measured voltage of the detector output signal has a peak amplitude of 0.2 V with an average of 2 V due to the application of an RF drive signal, the voltage may increase to 2.2 V at the peak and then decrease to 1.8 V at the bottom (making the peak-to-peak value 0.4 V). If arcing occurs during cycling when the voltage peaks at 2.2 V, resulting in a 0.3 V increase in the detector output signal, the measured voltage will be 2.5 V, which is above the 2.4 V threshold (this threshold indicates the occurrence of arcing, as determined from experimental results). However, if arcing occurs during cycling when the voltage bottoms at 1.8 V, the measured voltage will be 2.1 V (1.8 V plus 0.3 V), which is below the 2.4 V threshold. The threshold in such systems cannot be set below the peak output signal magnitude produced by the application of a normal RF drive signal. Accordingly, this detection method may not be useful for detecting small voltage anomalous plasma events that occur during portions of an alternating (eg, sinusoidal) voltage cycle. Another similar technique may selectively monitor for anomalous plasma events. Here, similar to the method described above, a voltage is measured. However, the voltage may be derived from the output of a photodetector, which is configured to measure the intensity of light within the chamber and generate a voltage signal indicative of the light intensity. For example, plasma formed within the chamber may emit varying amounts of light depending on the plasma's behavior. The photodetector may thereby generate a voltage output signal representative of the intensity of the light emitted by the plasma. However, an arcing event may generate additional light, which causes a corresponding increase in the voltage generated by the photodetector. This voltage may then be monitored in the manner previously discussed for direct voltage monitoring. However, this technique suffers from many of the same drawbacks as the previously discussed direct voltage monitoring, particularly its insensitivity to small-intensity discharge events that may go undetected if they occur during a local minimum in the photodetector signal. Another limitation of these detection methods is that they may not detect abnormal plasma events that are smaller than the difference between the peak voltage and the threshold voltage. For example, the threshold voltage may shift beyond the peak voltage by a certain amount, so that the peak voltages, and / or small, insignificant voltage deviations, are not close to the threshold voltage and thus cause an alarm or other corrective action. However, harmful abnormal plasma events may occur at voltages lower than the shift between the peak voltage and the threshold. Accordingly, abnormal plasma events that are smaller than the difference between the peak voltage and the threshold voltage may not be detected. For example, if an abnormal plasma event of 0.15 V occurs at a peak voltage of 2.0 V, the measured voltage will be below the 2.2 V threshold and thus remain undetected and unmitigated. These conventional detection methods can also be undesirably sensitive to the parameter settings of the processes occurring within the processing chamber. For example, each time a process parameter is changed (e.g., RF power, RF frequency, gas species, chamber pressure, etc.), multiple new threshold voltages may be required in response to the modified process parameter's effect on, for example, the voltage threshold at which arcing occurs. Consequently, modifying parameter settings can require additional experimentation and optimization time, which can also result in undesirable downtime for the semiconductor processing tool. Thus, the present disclosure includes novel techniques and apparatus for detecting anomalous plasma events in semiconductor processing. Generally speaking, a plasma may emit light detectable by a light detector (e.g., a photosensor). The light emitted by the plasma may oscillate or fluctuate at various frequencies based on plasma parameters (e.g., chemical species, RF power parameters (voltage, etc.), RF frequency components (e.g., high-frequency components, low-frequency components, or both), etc.). Some exemplary plasma emission oscillation frequencies may be on the order of one cycle per tens of milliseconds, for example, approximately one cycle per 20 ms. In contrast, anomalous plasma events typically occur at a relatively fast, high frequency relative to other light emitted by the plasma; for example, on the order of one cycle per nanometer. The techniques discussed below exploit the differences between light energy fluctuations occurring during anomalous plasma event frequencies and light energy fluctuations occurring during nominal plasma operation. These differences can be exploited to identify anomalous plasma events. In some embodiments, because an anomalous plasma event, due to its higher frequency, may result in an abrupt (e.g., high-frequency) change in slope in the photodetector output signal, a change in slope at a particular moment in time can be determined. In other embodiments, the photodetector signal can be normalized by removing lower-frequency components of the signal, leaving only the higher-frequency components that may indicate an anomalous plasma event. In yet other embodiments, the photodetector signal can be subjected to, for example, Fourier analysis (e.g., fast Fourier transform) or other types of frequency spectrum analysis to determine the magnitude of the intensity of various frequency components. In particular embodiments, if the analyzed photodetector signal exhibits high-frequency components greater than a certain magnitude, then these frequency components may indicate an anomalous plasma event. These anomalous plasma event detection techniques may differ from conventional techniques, such as those described above, because, in certain embodiments, they consider the rate of change of the optical signal, unlike conventional techniques that rely solely on the magnitude of the detected signal. FIG1 depicts a first exemplary abnormal plasma event detection apparatus according to an embodiment 100. As shown, embodiment 100 includes a semiconductor processing chamber 102, a lens 104 (which may be omitted in some embodiments), a fiber optic cable 106 connected to lens 104 and a signal processor 108, and an RF generator 110. Semiconductor processing chamber 102 is discussed in more detail below, but can be used for any semiconductor process utilizing plasma, such as plasma-enhanced chemical vapor deposition (PECVD), atomic layer deposition (ALD), atomic layer etching (ALE), and the like. RF generator 110 is also discussed in more detail below and may include an LF power generator, an HF power generator, or both. Lens 104 is disposed within semiconductor processing chamber 102 to allow light generated within the chamber (including within any processing station within semiconductor processing chamber 102) to pass through lens 104 and, via fiber optic cable 106, to signal processor 108. Signal processor 108 may include a photodetector, such as photodetector 112 (which may include a photodiode), which may receive a light signal from semiconductor processing chamber 102 and convert the received light signal into a voltage signal. Photodetector 112 may include any other type of light detection electronics capable of detecting any number of photons of energy at various wavelengths of infrared, visible, and / or ultraviolet light, and may include, for example, a spectrometer. Signal processor 108 may also include a slope change detection unit 114 configured to receive a voltage signal from photodetector 112, as indicated by the dashed line between the photodetector and slope change detection unit 114. Signal processor 108 may further be configured to determine a change in the voltage signal from photodetector 112 and whether the change in the voltage signal indicates the occurrence of an abnormal plasma event within semiconductor processing chamber 102. In some embodiments, slope change detection unit 114 can compare the raw photodetector signal with a filtered version of the same signal to determine high-frequency changes between the raw and filtered signals. Comparison between the raw and filtered signals may allow for a determination that an anomalous plasma event has occurred. In some such embodiments, a signal having a high-frequency component resulting from an anomalous plasma event is compared to a signal lacking the high-frequency component (due to, for example, the use of a low-pass filter applied to the raw voltage signal). This comparison can allow for a determination of relative changes between the filtered and unfiltered versions of the signal. FIG2 depicts a first exemplary slope change detection unit according to embodiment 200. Here, photodetector 112 is shown along with a first exemplary slope change detection unit 214 surrounded by a dashed rectangle. A raw voltage signal 215 from photodetector 112 is branched and passed to a filter, which in some embodiments may include a buffer amplifier 216, a low-pass filter 218, and a feedback amplifier 220 having a threshold / enable signal 222. This filtered signal, along with the raw voltage signal 215, is then passed to a high-speed comparator 224. Buffer amplifier 216 is operable to isolate the raw analog data from low-pass filter 218 (which filters high-frequency signals), and threshold / enable signal 222 causes an offset in the filtered signal. In the embodiment of FIG2 , a high-speed comparator 224 operates to compare the raw photodetector voltage signal with the filtered photodetector voltage signal and determine whether a change has occurred between the signals. For example, the determination may be made as to whether the difference between the two signals at a given moment exceeds a threshold amount. In response to the difference between the filtered and unfiltered signals being greater than the threshold amount, this may indicate a slope change in the raw signal, thereby indicating an anomalous plasma event. In certain embodiments, a filtered signal, as discussed above, may be offset from the unfiltered signal by a specific offset amount, which may operate to avoid scenarios where the two signals may interfere with each other (unlikely due to an anomalous plasma event). High-speed comparator 224 may also include transistor-to-transistor logic (TTL) that may change output signal 226 from a first voltage to a second voltage in response to a detected change between the filtered and unfiltered signals being greater than a first threshold. Figures 3A and 3B depict waveforms representing an exemplary detection response of a slope change detection unit according to one embodiment. In Figure 3A (Example 300A), an analog raw photodetector voltage signal (305) is represented as a dashed line, the filtered and offset voltage signal (310) is represented as a dotted line, and the output TTL signal 315 is represented as a solid line. The vertical axis is scaled in volts, and the horizontal axis is scaled in time (in seconds). As shown, the detected plasma luminescence oscillates as a sinusoidal wave with an amplitude of approximately 0.2 V. In the example of Figure 3B, a detailed view of a portion of Figure 3A is depicted. Here, an abnormal plasma event has occurred, and because the high-frequency arc signal has been filtered out, the filtered signal remains constant. However, in this example, the abnormal plasma event corresponding to the arc has caused a change in the photodetector voltage signal. In this example, the change in the photodetector output voltage signal corresponds to an increase in the slope of the photodetector output voltage signal. In response to the comparison between the simulated raw photodetector voltage signal 305 and the filtered output signal 310 being offset by a first threshold (e.g., approximately 0 volts in FIG. 3B ), the high-speed comparator causes an output TTL signal 315 to change from approximately 0.2 V to approximately 3.8 V. As further shown in FIG. 3B (Example 300B), in response to the occurrence of an abnormal plasma event (e.g., an arc), the simulated raw photodetector voltage signal 305 changes again (e.g., decreases in slope). In response to the decrease in the slope of the simulated raw photodetector signal 305, such that the simulated raw photodetector signal 305 and the low-level signal 310 are no longer offset by a value greater than the first threshold, the high-speed comparator then causes the output TTL signal 315 to change from approximately 3.8 V back to approximately 0.2 V. FIG4 depicts an exemplary circuit capable of detecting an abnormal plasma event according to an embodiment 400. This circuit of embodiment 400 may represent an implementation of the signal processor 108 of FIG1 and the first exemplary slope change detection unit 214 of FIG2. In the embodiment of FIG4, the "analog photodetector input" may represent the photovoltage signal generated by the photodetector 112 of FIG2. In addition, the "threshold from the EIOC" (V 3) may represent a threshold / monitoring enable signal 222, which may be sent from an Ethernet input / output controller (EIOC) as part of a control program executed by the system controller 950 of FIG. 9 . Furthermore, the “buffer” of FIG. 4 may represent the buffer amplifier 216 of FIG. 2 . The feedback amplifier 220 (depicted as “Feedback Amplifier” in FIG. 4 ) converts the threshold (V 3) The signal is added (or summed) with the output signal from the buffer of FIG4. The output signal from the buffer of FIG4 is filtered by the combination of R1 / C1 / C2, which forms a low-pass filter corresponding to the low-pass filter 218 of FIG2. The output signal from the buffer of FIG4 is compared with the combined analog light detector input (V 2) and sine wave input (V 4) Signal Comparison. In response to comparing the sum of the combined analog photodetector input and the sine wave input with the output signal from the feedback amplifier, the comparator of FIG4 detects an anomalous plasma event. In certain embodiments, the anomalous plasma event is detected when the magnitude of the sum of the combined analog photodetector input and the sine wave is greater than the output signal from the feedback amplifier by a threshold value. While the functionality of the slope change detection unit in FIG. 2 can be implemented using the analog electronic circuit of FIG. 4 , in some other embodiments, the functionality of FIG. 2 can be implemented digitally, such as using a field programmable gate array (FPGA). In some other embodiments, the slope change detection unit can utilize a differentiator that is operable to take the derivative of a raw optical data signal (e.g., the optical data signal from photodetector 112) to determine whether a change in the slope of an output signal from the photodetector has occurred. The output signal from a differentiator can be proportional to the rate of change of an input signal voltage (e.g., the derivative with respect to time). The derivative of the raw optical data signal (e.g., from the photodetector) can be transmitted to the input port of a comparator (e.g., high-speed comparator 224). The high-speed comparator can compare the raw data signal with a threshold to determine whether the difference in the slope of the raw optical data signal exceeds the threshold. In some examples, the threshold sensitivity can be adjusted based on process variations during deposition to avoid false alarms. If the change exceeds the change threshold, the comparator 224 may again output a TTL signal at a second voltage having an increased magnitude relative to the first voltage. In some embodiments, the slope change detection unit may use a fast Fourier transform (FFT) to convert the raw photovoltage signal into the frequency domain. The signal represented in the frequency domain can be used to determine whether certain frequency components (e.g., those associated with arcing (or other abnormal plasma events)) are present at intensities greater than a specified threshold. In some embodiments, an output signal may be generated if an unexpected frequency response to an abnormal plasma event is detected (or detected at a level exceeding a threshold). In response to the detection of an abnormal plasma event, such as by generating a TTL signal, various reactions and actions may be taken, such as adjusting the RF power coupled to a processing chamber. In some instances, the adjustment may include reducing (or completely interrupting) the RF power (e.g., LF, HF, or both). In some such instances, after the magnitude of the RF power has been reduced to zero, the RF power may be increased back to its previous level after a period of time sufficient to allow arcing (or other abnormal plasma events within a processing chamber) to cease. This increase in RF power may correspond to a linear or nonlinear increase. In some other instances, the adjustment of the RF power may include reducing the RF power (e.g., LF, HF, or both) to a non-zero level for a period of time and then increasing the power to a level equivalent to the previous level. FIG5 shows a waveform 500 representing the RF power of a process station coupled to a chamber as a function of time. As shown in FIG5, time t1RF power (power supplied by RF generator 110 in FIG1 ) corresponds to power level P1. t1, in response to the detection of an abnormal plasma event, the RF power is reduced to power level P2 and maintained from time t1 to time A period of time t2. t2, the RF power is t2 and t3, the RF output power gradually increases (e.g., ramps) until the RF output power reaches level P1. In some embodiments, the RF power reduction may be a percentage reduction, such as a 10% or 30% reduction. However, it will be understood that the disclosed embodiments are not limited to these examples and are intended to encompass any percentage RF power reduction, such as 5%, 10%, 20%, 30%, etc. In some embodiments, a determination of the magnitude of a detected abnormal plasma event can be made, for example, by subtracting a low-pass filtered data point of a photodetector signal from a corresponding unfiltered data point to determine the intensity of the abnormal plasma event. Subtracting the low-pass filtered data point from the corresponding unfiltered data point can produce, for example, an estimate of the arcing intensity. This determination (or other determinations that provide some indication of the intensity of the abnormal plasma event) can, in some embodiments, be used to determine the extent of RF system adjustments in response to the abnormal plasma event. For example, if the detected abnormal plasma event has a decreasing magnitude, the system can cause the RF generator to switch to a lower power mode at a first level. However, if the magnitude of the detected RF event reaches some threshold magnitude, the system can cause the RF generator to switch to another lower power mode at a second level lower than the first level. In such systems, multiple power levels may be supported, where the supported power levels may correspond to different threshold magnitudes of the abnormal plasma event intensity. In these examples, the system can select a power level associated with a range of intensity magnitudes within which the detected arc event falls. FIG6A shows another waveform representing the RF power and output signals of the slope change detection unit according to embodiment 600A. As shown, the RF power output of the RF generator oscillates, and the output signal of the slope change detection unit corresponds to a relatively flat constant line. Upon a detected abnormal plasma event, the amplitude of the output signal of the slope change detection unit increases, and the RF power unit interrupts the RF power output signal. In some examples, the response time between the increase in the slope change detection unit signal and the adjustment in the RF power output can be as high as approximately 2 microseconds. In some embodiments where abnormal plasma events (e.g., arcing) occur above or below the edge of a semiconductor wafer, the arc intensity and process parameters can define the amount by which RF power should be reduced. For example, in some embodiments, high RF power produces a more dispersed RF plasma. Accordingly, reducing the RF power coupled to a process station can be used to localize the plasma to a region between electrodes. For example, in response to arcing at an edge of a semiconductor wafer, reducing RF power can reduce the plasma density at the wafer edge, thereby concentrating the generated plasma to a region between electrodes and closer to the center of the wafer. Reducing RF power can also reduce the voltage at the electrodes, thereby helping to reduce the occurrence of abnormal plasma events (e.g., arcing), even if such events occur near the center of the wafer (away from the edge). The intensity of the abnormal plasma event and process parameters can also be used to define the amount by which RF power should be reduced. For example, the higher the arc intensity, the greater the reduction in RF power. Additionally, for very low pressure processes, the plasma may be more dispersed compared to high pressure processes (for the same power, gases, and other parameters). Therefore, in these instances, the power may need to be lowered further to result in greater confinement of the plasma. Abnormal plasma event detection equipment, such as the apparatus described above, can be configured in alternative configurations. More specifically, the signal processor 108 can be located in various locations and can include various configurations. As described above, in FIG. 1 , the signal processor can be located in a different location than within the processing chamber, such as in a different portion of the tool. In some embodiments, an optical signal can be transmitted from a location within the processing chamber 102 to a light detector of the signal processor, such as via a fiber optic cable 106. FIG6B depicts a group of profiles representing the spectral density of optical energy fluctuations under nominal operating conditions within a process station according to one embodiment. The vertical axis of FIG6B indicates a measure of spectral density (e.g., a percentage of the total spectrum), while the logarithmically scaled horizontal axis of FIG6B indicates frequency. Thus, one profile in group of profiles 600B represents the spectral density of optical energy fluctuations in response to coupled RF power at frequencies of approximately 400 kHz (i.e., ±10%) and approximately 13.56 MHz (i.e., ±10%) during a predetermined time period. In the specific example of FIG6B , the spectral density of the optical energy fluctuations is displayed over four sampling periods, with each profile representing the spectral density of the optical energy fluctuations during one of the four sampling periods. Accordingly, in response to coupling RF power (e.g., including frequencies of 400 kHz and 13.56 MHz) into a processing chamber, the optical signal from the plasma may fluctuate or oscillate at a first peak corresponding to the 400 kHz fundamental frequency (±10%), as well as at harmonics of 400 kHz, such as approximately 800 kHz (±10%) and 1600 kHz (±10%). Furthermore, it can be appreciated that the spectral density of the fluctuating optical signal from the plasma varies only slightly at frequencies between approximately 100 kHz and approximately 50 MHz. For example, at a frequency of approximately 100 kHz, the spectral density of the optical signal generated by the plasma may range from approximately 0.8% to approximately 1.2% of the total spectrum of the fluctuating optical signal from the plasma. According to one embodiment 600C, FIG. 6C depicts a group of profiles representing the spectral density of optical energy fluctuations under nominal operating conditions within a process station, as well as a profile representing the spectral density of optical energy fluctuations when an anomalous plasma event occurs within the process station. Similar to FIG. 6B , the vertical axis of FIG. 6C indicates a measure of spectral density (e.g., a percentage of total optical energy), while the logarithmically scaled horizontal axis of FIG. 6C indicates frequency. One profile of the group of profiles 610 represents the spectral density of optical energy of a fluctuating plasma in response to coupling of RF power (e.g., 400 kHz and 13.56 MHz) to a processing chamber during a predetermined time period. In the specific example of FIG. 6C , the spectral density of optical energy fluctuations is displayed over three sampling periods, each corresponding to one of the profiles 610 . In response to coupling of RF power (e.g., 400 kHz and 13.56 MHz) to a processing chamber, an optical signal generated by a plasma may fluctuate or oscillate at a first peak frequency corresponding to a fundamental frequency of 400 kHz. The optical signal generated by the plasma may additionally fluctuate or oscillate at harmonics, such as approximately 800 kHz and (1600 kHz) 1.6 MHz. Additionally, it can be appreciated that the spectral density of each of the profiles 610 varies only slightly at frequencies between approximately 100 kHz and approximately 50 MHz. However, in addition to profile 610, FIG6C depicts profile 620, which represents the spectral density of optical energy fluctuations in response to an abnormal plasma event (e.g., an arc) occurring within a processing chamber. Thus, as shown in FIG6C , during an abnormal plasma event, the spectral density of the optical energy fluctuations increases significantly between approximately 600 kHz and approximately 3.6 MHz. In other embodiments, during an abnormal plasma event, the spectral density of the optical energy fluctuations may increase significantly over different frequency ranges, such as between approximately 400 kHz (±10%) and approximately 4 MHz (±10%). For example, at approximately 1 MHz (1000 kHz), the spectral density of profile 620 (which may be observed during an abnormal plasma event within the chamber) corresponds to a value of approximately 2%. This can be compared to the spectral density observed under nominal conditions (e.g., as indicated by profile 610), which corresponds to a value of approximately 1%. Thus, as shown in FIG. 6C , an anomalous plasma event (eg, as shown by profile 620 ) may be indicated by observing a significant increase in the spectral density of the plasma fluctuations between specific frequency ranges. In the specific example of FIG. 6C , an abnormal plasma event is indicated by observing or detecting an increase in spectral density of approximately 100% (e.g., from a spectral density of approximately 1% to a spectral density of approximately 2%) at a specific frequency or during a specific range of frequencies relative to nominal plasma conditions in a processing chamber at the specific frequency or frequency range. Additionally, such an increase in spectral density may be observed at frequencies between approximately 400 kHz (±10%) and 4 MHz (±10%), but it will be understood that the disclosed embodiments are not limited to these examples and may include spectral densities and / or spectral density profiles observed at other frequency ranges, such as frequencies below approximately 400 kHz and frequencies above approximately 4 MHz. Furthermore, in other embodiments, an abnormal plasma event may be indicated by a smaller increase in the spectral density of a fluctuating or oscillating signal from the plasma relative to nominal operating conditions. For example, in certain embodiments, an anomalous plasma event may be identified in response to an increase in spectral density of less than 100% (eg, 75%, 50%, etc.), and the disclosed embodiments are not limited to these examples and may include other increases in spectral density. In some embodiments, an anomalous plasma event can be identified in response to an increase in spectral density relative to the standard deviation of the spectral density observed under nominal operating conditions. Thus, in one example, an anomalous plasma event can be identified by first calculating the standard deviation of the spectral density for a group of profiles (e.g., profile 610) representing nominal (or baseline) plasma conditions. In another example, a moving average (and a moving standard deviation) can be calculated over a specific duration. In another example, a standard deviation can be calculated continuously using a time window that increases in size over time. The method used to calculate the standard deviation, or other statistical measure, can depend on the specific process being performed at a process station and can change during wafer processing. In response to calculating a standard deviation using a baseline spectral density, an anomalous plasma event can be identified in response to observing a fluctuating signal from a plasma, the fluctuating signal from the plasma being characterized by a spectral density profile having an amplitude that is, for example, one standard deviation greater than the calculated standard deviation (e.g., one standard deviation using a baseline on the spectral density). In another example, an anomalous plasma event can be identified in response to observing a spectral density profile having an amplitude that is two standard deviations greater than the calculated standard deviation (e.g., one standard deviation using a baseline spectral density). However, the disclosed embodiments are intended to include spectral density profiles that indicate an anomalous plasma event that differ by any number of standard deviations relative to the spectral density profile of the fluctuating signal from a plasma operating under nominal conditions. Returning briefly to FIG. 1 , in certain embodiments, signal processor 108 can be programmed to perform analysis on the raw output signal from photodetector 112 . In one or more of these embodiments, analysis of the output signal from photodetector 112 can be utilized to determine the spectral density of optical energy fluctuations under various operating conditions within a process station. Thus, referring to FIG. 6C , the profile of plasma energy fluctuations during a predetermined time period can be analyzed to determine the spectral density at various frequencies as a fraction or percentage of the total spectrum of optical energy fluctuations from a plasma source. In some examples, this analysis performed by signal processor 108 can involve performing a fast Fourier transform (FFT) on the output signal from photodetector 112 . After performing an FFT on the output signal from photodetector 112 during one or more predetermined time periods, the spectral density of the optical energy fluctuations can be plotted in a manner similar to FIG. 6B / 6C . In response to the analysis of the spectral density of the optical energy fluctuations, signal processor 108 can determine that an anomalous plasma event has occurred. In certain embodiments, an anomalous plasma event can be identified by detecting an increase in spectral density at a specific frequency of optical energy fluctuations (e.g., between approximately 400 kHz and approximately 4 MHz). An anomalous plasma event can be identified by observing a spectral density having an amplitude greater than a threshold value relative to the spectral density observed during nominal plasma conditions. In certain embodiments, for example, the threshold value can correspond to one or two standard deviations relative to the spectral density calculated during nominal plasma conditions. An anomalous plasma event can be identified by observing a spectral density having an amplitude different from one or two standard deviations relative to the spectral density calculated during nominal plasma conditions, but the disclosed embodiments are not limited to such examples. Furthermore, an anomalous plasma event can be identified by detecting an increase in spectral density at frequencies other than between approximately 400 kHz and approximately 4 MHz, but the disclosed embodiments are not limited to such examples. In fact, embodiments are intended to encompass the detection of spectral density within any range of oscillations or fluctuations of optical energy in a plasma. Figures 6D and 6E depict alternative configurations of the first exemplary abnormal plasma event detection apparatus of Figure 1 . In Figure 6D , abnormal plasma event detection apparatus 600D may not include a fiber optic cable. Instead, abnormal plasma event detection apparatus 600D may include a signal processing unit 608A disposed within or above processing chamber 602A, enabling a light detector to acquire an optical signal from the plasma within processing chamber 602A. The output signal from light detector 612A may be processed by a high-speed comparator 614A. The output signal from high-speed comparator 614A is then transmitted to RF generator 610A. In some embodiments, the apparatus may include a lens between processing chamber 602A and light detector 612A. In Figure 6E , abnormal plasma event detection apparatus 600E includes a lens 604B coupled to signal processing unit 608B, which is part of RF generator 610B, via fiber optic cable 606B. In these examples, light detector 612B may also be a component of RF generator 610B. In some of these examples, RF generator 610A may include a high-speed comparator 614B, eliminating the need for an additional high-speed comparator. An advantage of abnormal plasma event detection apparatus 600E is that noise near processing chamber 602B and signal processing unit 608B may not affect the signals generated and used by signal processing unit 608B. Various techniques can also be used to detect and mitigate arcing events within a processing chamber. FIG. 7A depicts a flow chart of a first exemplary technique for detecting and mitigating the effects of an anomalous plasma event, according to one embodiment 700A. The technique begins at 701, and at 703, an optical signal generated by fluctuating plasma light emission is detected. As described above, the plasma emits light of various wavelengths, and a photosensor or photodetector, such as photodetector 112, is configured to detect the light emitted by the plasma. Furthermore, at 705, that optical signal is converted to a voltage signal, and this conversion can be performed by the photosensor or photodetector. At 707, the voltage signal is adjusted to form an adjusted voltage signal. This adjustment can be based on any of the techniques described above, such as filtering and / or offsetting the raw photovoltage signal (as described with respect to FIG. 2 ), taking the derivative of the raw photovoltage signal, or using an FFT analysis of the raw photovoltage signal. In response to the raw photovoltage signal being adjusted, a determination is made 709 as to whether a change associated with the adjusted voltage signal exceeds a threshold. This determination can be any of the comparisons described above, such as comparing the filtered and / or offset voltage signal (i.e., the adjusted voltage signal) to the raw photovoltage signal to determine whether any change between the two signals exceeds the threshold. As described above, in some embodiments, a determination is made based on whether the change between these two signals exceeds a threshold, which can indicate arcing or other types of abnormal plasma events occurring within the processing chamber. In these embodiments (i.e., embodiments utilizing a filtered photovoltage signal), the determination is not based solely on changes in the filtered and / or offset signals themselves, but rather on changes in the raw voltage signal relative to the filtered and / or offset signals. For example, as shown in FIG3B , a change in the raw voltage signal relative to the filtered signal indicates the occurrence of an arc or other type of abnormal plasma event. In response to utilizing both of these signals, this comparison still results in a determination associated with the adjusted voltage signal. The threshold may be selected based on various parameters, such as the rate of change and the amount of change. In some other embodiments of 709, determining that an abnormal plasma event is occurring may be based on a change in the adjusted voltage signal relative to a threshold, such as using derivative and / or FFT techniques. Here, the determination may be based on a change in the adjusted voltage signal. For example, the output signal of the derivative technique may be directly related to the rate of change of the optical signal, such that the determination of the adjusted voltage signal may directly indicate the occurrence of an arc. If it is determined that the change associated with the adjusted voltage signal exceeds the threshold, mitigation actions may be taken at 711. These mitigation actions may include, as described above, adjusting output parameters of the RF generator, such as by reducing the RF power to a lower power level for a period of time and then ramping the RF power output back to the initial power level. Although not depicted in FIG. 7A , as described above, the technique may also include indicating that the determination at 709 causes a TTL signal to be generated and sent to the RF generator. In some embodiments, the RF generator is configured to receive the TTL signal and cause a response to one or more parameters of the RF generator, such as reducing the output power of the RF generator. Additional implementations of the technique may also include generating a plasma within the processing chamber by coupling RF power to the processing chamber prior to or concurrently with 703 . FIG7B depicts a flowchart illustrating a second exemplary technique for detecting and mitigating the effects of anomalous plasma events, according to an embodiment 700B. The technique begins at 751, and at 752, plasma is formed in response to a signal of sufficient amplitude from an RF generator. In some embodiments, an RF generator may, for example, generate signals at approximately 400 kHz (±10%) and approximately 13.56 MHz (±10%). It will be understood that the disclosed embodiments are not limited to these examples and may include various additional frequencies. At 754, a fluctuating optical signal generated by the plasma may be detected. Detection may be performed using a photosensor or optical detector. At 755, a signal processor may calculate the spectral density of the fluctuating optical signal. In certain embodiments, this calculation may occur while the plasma is operating under nominal conditions and may occur over a number of time periods. In certain embodiments, at 756, it may be determined whether the spectral density of the fluctuating optical signal differs from one or more previously calculated spectral densities of the fluctuating optical signal. However, in some other embodiments, 756 may include determining that the spectral density of the fluctuating optical signal differs from a baseline spectral density. In response to the spectral density of the fluctuating optical signal differing (possibly by a threshold amount) from a previously calculated spectral density, or any other type of baseline spectral density, the signal processor may indicate that an anomalous plasma event has occurred. In some embodiments, the semiconductor processing chamber may include two or more processing stations, as described below, and the light emission from each station may be monitored separately. For example, a processing chamber may include four processing stations, and each of these processing stations may utilize a separate light detector configured to detect light from the corresponding processing station. The apparatus and techniques described herein offer numerous advantages over conventional abnormal plasma event detection techniques. In some instances, these techniques allow for faster detection times and mitigation response times because optical signals can be processed using analog circuitry that can directly generate a signal to an RF generator (which can respond to that signal). The direct connection between the RF generator and the optical signal allows for fast, efficient response times. In contrast, conventional techniques may require sending the detected signal to a processor for analysis and another signal from the processor to the RF processor. Because some abnormal plasma events, such as arcs, can form rapidly, delays introduced by some conventional techniques can cause undesirable damage to wafers and / or other equipment. Additionally, as described above, these techniques and apparatus are capable of detecting small-scale abnormal plasma events that are not detectable by conventional methods. As mentioned above, the apparatus and techniques described herein are applicable to any semiconductor process that uses plasma, and any semiconductor processing chamber in which plasma is generated. Examples of such processes and apparatus are described below. Plasma-assisted chemical vapor deposition ( PECVD )equipment In some embodiments, the wafer processing equipment may include one or more PECVD process stations included in a process tool. The process tool may include the features described above with respect to Figures 6A and 6B, for example, along with other features described below. Figure 8 provides a block diagram of an exemplary apparatus that can be used to implement the disclosed embodiments. As shown, the reactor 800 of Figure 8 includes a process chamber 824, which houses the other components of the reactor and is used to contain the plasma generated by, for example, a capacitor-type system (including a showerhead 814 operating in conjunction with a grounded heater block 820). A high-frequency RF generator 804 (connected to a matching network 806) and a low-frequency RF generator 802 are connected to the showerhead 814. The power and frequency supplied by the matching network 806 are sufficient to generate the plasma from the process gas, for example, 400-700 W of total energy. In one embodiment of the present invention, both the HFRF generator and the LFRF generator may be used during deposition, while in some other embodiments, only the HFRF generator or the LFRF generator is used. In a typical process, the high-frequency RF component is generally between approximately 2 and 60 MHz; in at least one embodiment, the HF component is approximately 13.56 MHz. The low frequency LF components are generally between about 250-400 kHz. In some embodiments, the RF generator can be considered to have both an HF RF generator and a LF RF generator, and in some instances a matching network. Within the reactor, a wafer pedestal 818 supports a substrate 816. The pedestal typically includes a chuck, a fork, or lift pins for holding and transferring the substrate during and between deposition and / or plasma treatment reactions. The chuck can be an electronic chuck, a mechanical chuck, or various other types of chucks available for use in industry and / or research. The process gas system is introduced through inlet 812. Multiple source gas lines 810 are connected to manifold 808. These gases may or may not be premixed. Appropriate valving and mass flow control mechanisms are used to ensure that the correct gases are delivered during the deposition and post-deposition stages of the process. In instances where the chemical precursors are delivered in liquid form, liquid flow control mechanisms are used. The liquid system is then vaporized and mixed with other process gases during delivery within a manifold heated above its vaporization point before reaching the deposition chamber. Process gases exit chamber 824 through outlet 822. A vacuum pump 826 (e.g., one or more stages of mechanical dry pumps and / or turbomolecular pumps) typically draws the gases out and maintains a suitably low pressure within the reactor via a closed-loop controlled flow restriction element (e.g., a throttle valve or pendulum valve). The invention can be implemented on a multi-station or single-station tool. In a specific embodiment, a 300 mm Novellus Vector with a 4-station deposition solution TM 200 mm Sequel with 6-station deposition solution TM The machine is used. According to one embodiment 900, FIG9 shows a schematic diagram of an embodiment of a multi-station processing tool 900 having an inbound loadlock chamber 902 and an outbound loadlock chamber 904, either or both of which may utilize a remote plasma source. A robot 906 at atmospheric pressure is used to move wafers from a cassette loaded via a wafer cassette 908 into the inbound loadlock chamber 902 via an atmospheric port 910. A wafer is placed onto a pedestal 912 within the inbound loadlock chamber 902 by the robot 906, the atmospheric port 910 is closed, and the loadlock chamber is then evacuated. If the inbound loadlock chamber 902 utilizes a remote plasma source, the wafer may be exposed to the remote plasma treatment within the loadlock chamber prior to introduction into a processing chamber 914. Furthermore, the wafer may be heated within the inbound loadlock chamber 902 to remove moisture and adsorbed gases, for example. Next, a chamber transfer port 916 leading to the processing chamber 914 is opened, and another robot (not shown) places the wafer into the reactor onto a susceptor at a first station shown in the reactor for processing. Although the embodiment shown in FIG. 9 includes a load lock chamber, it will be appreciated that in some embodiments, the wafer may be directed into a processing station. The processing chamber 914 includes four processing stations, numbered 1 through 4 in the embodiment shown in FIG. Each station has a heated susceptor (shown as 918 for station 1) and gas line inlets. It will be appreciated that in some embodiments, each processing station may have different or multiple purposes. While the processing chamber 914 is shown as including four stations, it will be appreciated that a processing chamber according to the present disclosure may have any suitable number of stations. For example, in some embodiments, a processing chamber may have five or more stations, while in other embodiments, a processing chamber may have three or fewer stations. FIG9 also illustrates an embodiment of a wafer handling system 990 for transporting wafers within processing chamber 914. In some embodiments, wafer handling system 990 can transport wafers between various processing stations and / or between a processing station and a load lock chamber. It will be appreciated that any suitable wafer handling system can be used. Non-limiting examples include a wafer carousel and a wafer handling robot. FIG9 also illustrates an embodiment of a system controller 950 for controlling process conditions and hardware states of processing tool 900. System controller 950 can include one or more memory devices 956, one or more mass storage devices 954, and one or more processors 952. Processor 952 can include a CPU or computer, analog and / or digital input / output connections, a stepper motor controller board, and the like. Although not shown in FIG. 9 , the tool 900 may include any features of the reactor 800 , such as gases and piping for the aforementioned stations, and a vacuum pump. In some embodiments, the system controller 950 controls all activities of the processing tool 900. The system controller 950 executes system control software 958, which is stored in the mass storage device 954, loaded into the memory device 956, and executed by the processor 952. The system control software 958 may include instructions for controlling timing, gas mixtures, gas flow rates, chamber and / or station pressures, chamber and / or station temperatures, purge conditions and timing, wafer temperature, RF power levels, frequencies, substrate, susceptor, chuck, and / or susceptor positions, and other parameters of the specific process performed by the processing tool 900. The system control software 958 may be implemented in any suitable manner. For example, various process tool component subroutines or control objects may be written to control the operation of the process tool components used to perform various process tool processes. The system control software 958 may be coded in any suitable computer-readable programming language. In some embodiments, the system control software 958 may include input / output control (IOC) sequence instructions for controlling various of the aforementioned parameters. For example, a PECVD process may include one or more instructions for execution by the system controller 950. Instructions for setting process conditions for a PECVD process stage may be included in a corresponding PECVD recipe stage. In some embodiments, the PECVD recipe stages may be sequentially arranged so that all instructions for a PECVD process stage are executed concurrently with that process stage. Other computer software and / or programs stored in the mass storage device 954 and / or the memory device 956 associated with the system controller 950 may be used in some embodiments. Examples of programs or program segments used for this purpose include substrate positioning programs, process gas control programs, pressure control programs, heater control programs, and plasma control programs. The substrate positioning program may include program code for processing tool components used to load a substrate onto the pedestal 918 and control the spacing between the substrate and other components of the processing tool 900 . The process gas control program may include code for controlling gas composition and flow rates, and optionally for flowing gas into one or more process stations prior to deposition to stabilize the pressure within the process stations. The process gas control program may include code for controlling gas composition and flow rates within any of the disclosed ranges. The pressure control program may include code for controlling the pressure within the process station by, for example, adjusting the gas flow into the process station (e.g., a throttle valve in the process station exhaust system). The pressure control program may include code for maintaining the pressure within the process station within any of the disclosed pressure ranges. The heater control program may include code for controlling the current flowing to a heating element used to heat the substrate. Alternatively, the heater control program may control the delivery of a heat transfer gas (e.g., helium) to the substrate. The heater control program may include instructions for maintaining the substrate temperature within any of the disclosed ranges. The plasma control program may include code for setting the RF power level and frequency applied to the process electrodes in one or more process stations, such as using any of the RF power levels disclosed herein. The plasma control program may also include code for controlling the duration of each plasma exposure. In some embodiments, the system controller 950 may be part of or connected to a computer that is integrated with the system, connected to the system, otherwise networked to the system, or a combination thereof. For example, the controller may be in the "cloud" or part of a mainframe computer system in a wafer fab, which may allow remote access to wafer processing. The computer may allow remote access to the system to monitor the current progress of processing operations, review the history of past processing operations, examine trends or performance indicators from multiple processing operations, change parameters of the current process, set processing steps after the current process, or initiate new processes. In some examples, a remote computer (e.g., a server) may provide process recipes to the system via a network, such as a local area network (LAN) or the Internet. The remote computer may include a user interface that allows for the input or programming of parameters and / or settings, which are then transmitted from the remote computer to the system. In some examples, the system controller 950 receives instructions in the form of data that specifies parameters for various processing steps performed during one or more operations. It should be understood that the parameters can be specific to the type of process to be performed, as well as the type of tool to which the controller is configured to interface or control. Thus, as described above, the system controller 950 can be distributed, for example, by including one or more distributed controllers that are networked together and work toward a common purpose, such as the process and control described herein. An example of a distributed controller for this purpose can be one or more integrated circuits located on the chamber in communication with one or more remotely located integrated circuits (e.g., at the stage level or as part of a remote computer), which together control the process on the chamber. In some embodiments, there may be a user interface associated with the system controller 950. The user interface may include a display screen, a graphical software display of equipment and / or process conditions, and user input devices such as a pointing device, keyboard, touch screen, microphone, etc. In some embodiments, the parameters adjusted by system controller 950 may relate to process conditions. Non-limiting examples include process gas composition and flow rates, temperature, pressure, plasma conditions (e.g., RF power level, frequency, and exposure time), etc. These parameters may be provided to the user in the form of a recipe that can be entered via a user interface. Signals for monitoring the process can be provided from various process tool sensors via analog and / or digital input connections of the system controller 950. Signals for controlling the process can be output via analog and digital output connections of the processing tool 900. Non-limiting examples of process tool sensors that can be monitored include mass flow controllers, pressure sensors (e.g., manometers), thermocouples, and the like. Appropriately programmed feedback and control algorithms can be used with the data from these sensors to maintain process conditions. Any suitable chamber may be used to implement the disclosed embodiments. Exemplary deposition equipment includes, but is not limited to, equipment from the ALTUS® product family, the VECTOR® product family, and / or the SPEED® product family, each of which is available from Lam Research Corporation, Fremont, California, or various other commercially available processing systems. Two or more of the stations may perform the same function. Similarly, two or more stations may perform different functions. Each station may be designed or configured to perform a specific function / method as desired. PECVD deal with Many semiconductor fabrication processes use plasma-enhanced chemical vapor deposition ("PECVD") to deposit materials. In a typical PECVD reaction, a substrate is exposed to one or more volatile precursors, which react and / or decompose to produce the desired deposit on the substrate surface. The PECVD process generally begins by flowing one or more reactants into a reaction chamber. Reactant delivery can continue while the plasma is generated, exposing the substrate surface to the plasma, which causes deposition to occur on the substrate surface. This process continues until the desired film thickness is reached, after which the plasma is typically extinguished and the reactant flow terminated. Next, the reaction chamber can be purged and post-deposition steps can be performed. As described above, in some embodiments, the frequency used to drive plasma formation during PECVD may contain a high-frequency ("HF") component, a low-frequency ("LF") component, or both. The HF frequency may be approximately 13.56 MHz or approximately 27 MHz. The HF RF power used to drive plasma formation may be between approximately 200-3,000 W. These power levels represent the total power delivered, which may be divided among the multiple stations in a multi-station processing chamber. The plasma may be generated at a first power level, which may be any power within this range, such as 600 W for a single station or 2,400 W for a four-station processing chamber, resulting in 600 W for each of the four stations. The duration of the plasma exposure depends on the desired thickness of the deposited film. In some embodiments, pulsed PECVD methods may be used. These methods may involve pulsing the precursor and / or RF power levels. In some embodiments, the frequency used to drive plasma formation during PECVD may contain both LF and HF components. The LF frequency may be between about 300-400 kHz. The LF RF power used to drive plasma formation may be between about 200-2,500 W. Atomic layer deposition In some embodiments, a semiconductor process involves multiple film deposition cycles, each producing a "distinct" film thickness. Atomic layer deposition (ALD) is one such film deposition method, but any technique used to deposit thin layers of film in a repetitive, sequential manner can be considered to involve multiple deposition cycles, and the methods and apparatus disclosed herein can also be generally used to control film thickness during such multi-cycle deposition operations. As device and feature sizes continue to shrink in the semiconductor industry, and 3D device structures (e.g., Intel's three-gate transistor structure) become more prevalent in integrated circuit (IC) designs, the ability to deposit thin, conformal films (material films with uniform thickness relative to the shape of the underlying structure, even if non-planar) will become increasingly important. ALD (Analog Laser Deposition) is a film formation technique well-suited for conformal film deposition. This is because a single ALD cycle deposits only a single, thin layer of material, whose thickness is limited by the amount of one or more film precursor reactants that can adsorb on the substrate surface (i.e., forming an adsorption limiting layer) prior to the film-forming chemical reaction itself. Multiple "ALD cycles" can then be used to build up a film of the desired thickness, and because each layer is thin and conformal, the resulting film substantially conforms to the shape of the underlying device structure. In some embodiments, each ALD cycle includes the following steps: 1. Exposure of the substrate surface to a first precursor. 2. Purge of the reaction chamber in which the substrate is located. 3. Activation of the reaction on the substrate surface, typically using plasma and / or a second precursor. 4. Purge the reaction chamber in which the substrate is located. The duration of each ALD cycle is typically less than 25 seconds or less than 10 seconds. One or more plasma exposure steps in an ALD cycle may have a short duration, for example, less than 1 second. Due to the short duration, controlling plasma consistency can contribute to process uniformity. Variations in plasma impedance and delivered power are two factors that can affect process uniformity. Apparatus and methods are provided for controlling RF power used in multi-cycle deposition operations in a semiconductor tool having multiple processing stations sharing a common RF power source. The frequency of the RF power and the power applied to individual stations sharing a common RF power source are controlled. FIG10 illustrates a substrate processing apparatus for depositing films on semiconductor substrates according to one embodiment. The processing apparatus 1000 of FIG10 comprises a single processing chamber 1002 having a single substrate holder 1008 within an interior volume that can be maintained under vacuum by a vacuum pump 1018. A gas delivery system 1001 and a showerhead 1006 are also fluidically connected to the chamber to deliver, for example, film precursors, carrier and / or purge and / or process gases, secondary reactants, and the like. Equipment for generating a plasma within the processing chamber is also shown in FIG10 and will be described in greater detail below. The apparatus schematically depicted in FIG10 provides basic equipment for performing film deposition operations, such as chemical vapor deposition (CVD) or ALD, on semiconductor substrates. For simplicity, processing apparatus 100 is depicted as a standalone processing station having a processing chamber body for maintaining a low-pressure environment. However, it will be appreciated that multiple processing stations may be included in a common processing tool environment (e.g., within a common reaction chamber), as described herein. For example, FIG. 11 depicts an implementation of a multi-station processing tool, according to embodiment 1100. Furthermore, it will be appreciated that in some embodiments, one or more hardware parameters of processing apparatus 1000, including those discussed in detail above, may be programmatically adjusted by one or more system controllers. The processing apparatus 1000 is in fluid communication with a reactant delivery system 1001 for delivering process gases to a distribution showerhead 1006. The reactant delivery system 1001 includes a mixing vessel 1009 for mixing and / or conditioning process gases for delivery to the showerhead 1006. One or more mixing vessel inlet valves 1020 control the introduction of process gases into the mixing vessel 1009. Some reactants may be stored in liquid form prior to vaporization and subsequent delivery to processing chamber 1002. The embodiment of FIG10 includes a vaporization point 1003 for vaporizing the liquid reactants to be supplied to mixing vessel 1009. In some embodiments, vaporization point 1003 may be a heated liquid injection module. In some embodiments, vaporization point 1003 may be a heated vaporizer. In still other embodiments, vaporization point 1003 may be omitted from the processing station. In some embodiments, a liquid flow controller (LFC) may be provided upstream of the vaporization point 1003 to control the mass flow rate of the liquid used for vaporization and delivery to the processing chamber 1002 . The showerhead 1006 distributes process gases and / or reactants (e.g., film precursors) toward a substrate 1012 in a processing station. The flow of the process gases and / or reactants is controlled by one or more valves (e.g., valve 1020) upstream of the showerhead. In the embodiment shown in FIG10 , the substrate 1012 is positioned below the showerhead 1006 and is shown resting on a pedestal 1008. It will be appreciated that the showerhead 1006 can have any suitable shape and can have any suitable number and arrangement of ports for distributing process gases to the substrate 1012. Volume 1007 is located below showerhead 1006. In some embodiments, pedestal 1008 can be raised or lowered to expose substrate 1012 to volume 1007 and / or to change the volume of volume 1007. Optionally, pedestal 1008 can be lowered and / or raised during portions of a deposition process to modulate process pressure, reactant concentrations, etc. within volume 1007. In Figure 10 , showerhead 1006 and pedestal 1008 are electrically connected to RF power supply 1014 and matching network 1016 to provide power to the plasma. In some embodiments, plasma energy can be controlled by controlling one or more of process station pressure, gas concentration, RF source power, RF source frequency, and plasma power pulse timing (e.g., via a system controller with appropriate machine-readable instructions). For example, RF power supply 1014 and matching network 1016 can be operated at any suitable power to form a plasma with a desired radical species composition. Similarly, RF power supply 1014 can provide RF power at any suitable frequency. In some embodiments, the plasma can be monitored in situ using one or more plasma monitors. In one scenario, plasma power can be monitored using one or more voltage and current sensors (e.g., load sensors such as VI probes). Examples of such sensors include the MKS VI probes 4100 and 350. These sensors can measure voltage, current, and phase difference. In some embodiments, these sensors can be electrically connected to the RF power supply and can be located at or near the showerhead. In such embodiments, the impedance presented at the output port of the RF generator can represent the impedance of the plasma. In another scenario, the plasma density and / or process gas concentration can be measured using one or more optical emission spectroscopy (OES) sensors. In some embodiments, one or more plasma parameters can be programmably adjusted based on measurements from these in situ plasma monitors. For example, a load sensor can be used in a feedback loop to provide programmable control of the plasma power. It will be appreciated that in some embodiments, other monitors can be used to monitor plasma and other process characteristics. Such monitors may include, but are not limited to, infrared (IR) monitors, acoustic wave monitors, and pressure sensors. In some embodiments, the plasma may be controlled by an input / output control (IOC) sequence of instructions. In one example, instructions for setting the plasma conditions for the plasma activation phase may be included in a corresponding plasma activation recipe of a process recipe. In some instances, the process recipe phases may be arranged sequentially so that all instructions for a process are executed concurrently with that process. In some embodiments, instructions for setting one or more plasma parameters may be included in a recipe preceding a plasma process. For example, a first recipe may include: instructions for setting the flow rate of an inert (e.g., helium) and / or reactant gas; instructions for setting a plasma generator to a power set point; and a delay instruction for the first recipe. A second, subsequent recipe may include instructions for activating the plasma generator and a delay instruction for the second recipe phase. A third recipe may include instructions for deactivating the plasma generator and a delay instruction for the third recipe. It will be appreciated that these recipes may be further subdivided and / or repeated in any suitable manner within the scope of the present disclosure. In some deposition processes, plasma strikes last for durations on the order of several seconds or more. In some embodiments described herein, much shorter plasma strikes may be employed during a process cycle. These may be on the order of less than 50 milliseconds, with 25 milliseconds being a specific example. Such brief RF plasma strikes require rapid stabilization and adjustment of the plasma. To achieve rapid plasma stabilization and adjustment, the plasma generator may be configured using a two-step adjustment process comprising a coarse adjustment component and a fine adjustment component. In the coarse adjustment component, impedance matching may be preset to a specific impedance. The coarse adjustment component may be preset so that the impedance magnitude is, for example, 50 ohms. In some embodiments, the coarse adjustment component may be limited to adjustments that affect the impedance magnitude. In the fine adjustment component, the RF frequency may be allowed to float from a baseline frequency in an attempt to match the phase to a target value, such as a phase value of zero. Traditionally, high-frequency plasmas are generated at a frequency of approximately 13.56 MHz. In various embodiments disclosed herein, the frequency is allowed to float to a value different from this standard value in order to match the phase to the target value. In some embodiments, the fine-tuning element can be limited to adjustments that affect the impedance phase. By allowing the frequency to float while fixing the impedance to match the predetermined impedance, the plasma can stabilize more quickly. Very short plasma ignitions, such as those associated with ALD or atomic layer etch (ALE) cycles, can benefit from the rapid stabilization of the plasma. The first 1-2 milliseconds of a typical deposition cycle includes ignition of the plasma. After plasma ignition, fine tuning of the RF frequency is then performed to match the plasma phase to the target value. As described above, one or more process stations may be included in a multi-station substrate processing tool. FIG11 shows an exemplary multi-station substrate processing apparatus that may utilize plasma balancing hardware. Various performance improvements can be achieved by using a multi-station processing apparatus as shown in FIG11 with respect to both equipment cost and operating expenses. For example, a single vacuum pump can be used to establish a single high vacuum environment for all four process stations by evacuating exhaust gases for all four process stations, etc. Depending on the implementation, each process station may have its own dedicated showerhead for gas delivery, but may share the same gas delivery system. Similarly, certain elements of the plasma generator equipment may be shared between process stations (e.g., power supply), but depending on the implementation, certain implementations may be process station specific (e.g., if the showerhead is used to apply the plasma generating potential). Again, it is understood that such performance can be achieved to greater or lesser degrees by utilizing a greater or lesser number of process stations per processing chamber, such as 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16, or more, process stations per reaction chamber. The substrate processing apparatus of FIG9 can also be used to perform ALD processing. Here, a single substrate processing chamber 914 houses multiple substrate processing stations, each of which can be used to perform processing operations on a substrate held in a substrate holder at that processing station. In this particular embodiment, the multi-station substrate processing tool 900 is shown as having four processing stations 1, 2, 3, and 4. Other similar multi-station processing apparatuses may have more or fewer processing stations depending on the implementation and, for example, the desired degree of parallel wafer processing, size / space constraints, cost constraints, etc. In Figure 9, RF power is generated at an RF power system 913 and distributed to each of stations 1-4. The RF power system may include one or more RF power sources, such as a high-frequency (HFRF) and a low-frequency (LFRF) source, an impedance matching module, and filters. In some embodiments, the power source may be limited to only high-frequency or low-frequency sources. Unless otherwise described, the deposition process is assumed to use only high-frequency power. The distribution system of the RF power system is symmetrical with respect to the reactor and has high impedance. This symmetry and impedance result in approximately equal amounts of power being delivered to each station. Small variations in RF power (on the order of 5 to 15%) can result from tolerances in the distribution system components, station symmetry, temperature variations, and process conditions. Small differences in RF power can cause wafer-to-wafer non-uniformity in various film properties (e.g., composition, thickness, density, cross-linking, chemistry, reaction completion, stress, refractive index, dielectric constant, hardness, etch selectivity, stability, hermeticity, etc.). The ability to fine-tune plasma power at individual stations and dynamically respond to changing station conditions can reduce wafer-to-wafer non-uniformity. It is important to note that the methods and apparatus of this disclosure are not limited to multi-station reactors; the methods and apparatus disclosed herein are applicable to other RF power systems in which multiple processing zones share a common RF power source. System controller 950 can also be used to control process conditions and hardware states of processing tool 900 and its process stations to perform ALD. System controller 950 can provide machine-readable instructions for implementing deposition processes. These instructions can control various process parameters, such as DC power levels, RF bias power levels, station-to-station variation, such as RF power parameter variation, frequency tuning parameters, pressure, temperature, and the like. These instructions can control parameters to operate the in-situ deposition of film stacks according to the various embodiments described herein. FIG11 is a schematic diagram illustrating various components of an exemplary multi-station plasma reactor utilizing RF frequency tuning to share a common RF power source across multiple stations. As shown, an RF power source 1101 (which may be a high-frequency RF power source) is distributed to multiple stations 1151 via a distribution network 1121. The HFRF may have a frequency of approximately 2-60 MHz, or approximately 13.56 MHz. In other embodiments, a low-frequency RF power source may be used in addition to or in place of the high-frequency RF power source. The low-frequency RF power source may have a frequency of approximately 100 kHz to approximately 1 MHz, or approximately 400 kHz. Several commercially available RF power sources include the ability to tune the frequency of the RF power. Examples of such RF power sources include Advanced Engineer's Paramount series, MKS's SurePower series, Comdel's CB, CLX, and CDX series, and Huettinger's TruPlasma series. Power from the RF power source 1101 may be delivered via an impedance matching system that may include a fixed matching module 1103. In some embodiments including high-frequency and low-frequency RF power sources, a high-pass filter and / or a low-pass filter may also be present. Additionally, in some embodiments, power from the RF power source may be delivered via an automatic matching module. In embodiments including a low-frequency RF power source, either in addition to or in lieu of the high-frequency RF power source, the low-frequency power may be delivered via fixed or automatic matching components. In some embodiments, an automatic matching module may be used to match the RF power frequency to a set impedance of the plasma load. In other embodiments, a fixed matching module may be used that does not automatically match the RF power frequency to a set impedance of the plasma load. In the embodiment shown in FIG11 , RF power source 1101 is connected to a distribution network 1121. Distribution network 1121 distributes the RF power generated by RF power source 1101 to each of the plurality of stations 1151. Distribution network 1121 is connected to an RF regulator 1123 for each of the plurality of stations 1151. For each of the plurality of stations 1151, RF regulator 1123 is connected to a power parameter sensor 1133 located before showerhead 1153. Power parameter sensor 1133 can be any type of sensor previously disclosed, such as a load sensor or an OES sensor. RF power source 1101 can receive instructions from RF controller 1143 and vary the frequency of the RF power distributed to the stations. These instructions can be frequency adjustments based on impedance detected by one or more power parameter sensors 1133. In other embodiments, additional sensors can measure a final phase, which represents the plasma phase within each of the plurality of stations 1151. The RF controller 1143 can then vary the frequency of the RF power distributed to the station based on the final phase measured by the additional sensor. In some embodiments, the RF controller 1143 can include instructions, such as program code, to vary the frequency of the RF power so that the phase of the impedance is zero or near zero. In the embodiment shown in FIG11 , the RF controller 1143 can vary the frequency of the RF power from the RF power source 1101 upstream of the respective station. RF adjuster 1123 is controlled by RF controller 1143. RF controller 1143 can vary the RF power at each station by a predetermined amount based on measurements from sensor 1133 at each station 1151. In some embodiments, RF adjuster 1123 can be a variable capacitor. RF controller 1143 can control a stepper motor (not shown) that varies the capacitance of a variable capacitor. Other methods of varying capacitance can be used. For example, RF adjuster 1123 can also be a bank of capacitors with individual switches. RF power can be controlled by activating (turning on) a number of capacitors with specific values. For example, capacitors can be selected to add parallel capacitances of 1 pF, 2 pF, 4 pF, 8 pF, and 16 pF to the station. In this example, all combinations of active (activated) and inactive (unactivated) capacitors cover a range from 0 pF to 31 pF with a resolution of 1 pF. By selecting which capacitors to activate, the controller can vary the RF power for a station. Compared to using stepper motors to control variable capacitors, digital control can be faster, especially when a wide range of capacitances needs to be covered. Depending on the available space and the amount of control required, those skilled in the art can design an RF regulator using more than one capacitor to vary the RF power by several amounts. In other embodiments, RF adjuster 1123 may be a variable coil inductor. RF controller 1143 may control the variable coil inductor to affect the RF power delivered to the station. In some embodiments, RF adjusters are not limited to capacitors and inductors. In some embodiments, other RF adjusters 1123 may utilize different mechanisms to vary RF power, such as resonator circuits or resistor circuits. Sensor 1133 measures at least one RF power parameter. The measured RF power parameter can be voltage, current, impedance, phase, or load power. Commercially available probes can be used to measure the RF power parameter and provide the measurement value to the RF controller 1143. It is also possible to measure a non-RF parameter and use it as a source signal for the RF controller 1143. For example, light emission from the station plasma or substrate temperature sensors can measure station characteristics and feed them to the RF controller 1143. A light emission system can be installed near each station to collect light emitted by the station plasma. A substrate temperature sensor can use a remote infrared detection system constructed under a substrate. Sensor 1133 can also measure multiple RF power parameters, or multiple sensors can be used in some embodiments to measure multiple RF power parameters. In some embodiments, the RF regulator can be set to a fixed value or range of values ​​during a multi-step process (e.g., a multi-cycle ALD process). In such embodiments, little or no real-time sensing of RF power parameters and adjustment of RF power distribution between stations is required. Each station 1151 includes a showerhead 1153 operating in conjunction with a grounded pedestal 1157. The power and frequency supplied are sufficient to generate a plasma from the process gas, for example, in the range of about 50 W to about 6000 W per station. The power level may vary depending on the embodiment. RF power is connected to the station processing region via the showerhead 1153, and a plasma is generated or maintained when RF power is applied. The plasma causes material to be deposited onto the substrate by various mechanisms. For example, the plasma may cause the process gas to decompose and react with the substrate surface. In the embodiment shown, the RF current is grounded at the pedestal 1157, which is connected to ground 1131. In some other embodiments, the RF current may be grounded at a different location in the chamber, such as the showerhead. The plasma activation step of a multi-step deposition process with a short cycle duration can be brief. The duration of the plasma activation step can be approximately 150 milliseconds or less (e.g., approximately 50 milliseconds). Due to the short duration, controlling the plasma uniformity has an effect on process uniformity. Plasma balancing operations can be used to control the plasma uniformity. Although not shown in Figures 8-11 , any tool in these figures may include any features of any other tool, such as controller 950, and the controller may be configured to execute any instructions described herein for reactor 800. Furthermore, the chambers presented in embodiments 800, 900, and 1000 of Figures 8-10 , respectively, may be considered chamber 102 of Figure 1 and chambers 602A and 602B of Figures 6D and 6E , respectively. Furthermore, RF generators 110, 610A, and 610B may also be considered either or both of the HFRF and LFRF generators of Figures 8-11 . Unless the context of this disclosure clearly requires otherwise, throughout the claims, the terms "comprising," "including," and the like are to be interpreted in an inclusive sense and not in an exclusive or comprehensive sense; that is, in the sense of "including, but not limited to," as in the singular or plural sense. Terms used in the singular or plural also generally include the plural or singular, respectively. In addition, the terms "herein," "after," "above," "below," and similar terms refer to this application as a whole and not to any particular portion of this application. When the term "or" is used with reference to a list of two or more items, that term encompasses the following interpretations of the term: any one of the items in that list, all of the items in that list, and any combination of the items in that list. The term "embodiment" means an embodiment of the techniques and methods described herein, as well as physical objects that implement the structure and include the techniques and / or methods described herein. The terms "substantially," "approximately," and "about" are to be understood to include ±10% of the indicated amount. 102: Semiconductor processing chamber 104: Lens 106: Fiber optic cable 108: Signal processor 110: RF generator 112: Light detector 114: Slope change detection unit 214: Slope change detection unit 215: Raw voltage signal 216: Buffer amplifier 218: Low-pass filter 220: Feedback amplifier 222: Threshold / enable signal 224: High-speed comparator 226: Output signal 600D: Abnormal plasma event Detection device 600E: Abnormal plasma event detection device 602A: Processing chamber 602B: Processing chamber 604B: Lens 606B: Fiber optic cable 608A: Signal processing unit 608B: Signal processing unit 610A: RF generator 610B: RF generator 612A: Light detector 612B: Light detector 614A: High-speed comparator 614B: High-speed comparator 800: Reactor 802: Low-frequency RF generator Generator 804: High frequency RF generator 806: Matching network 808: Manifold 810: Source gas line 812: Inlet 814: Shower head 816: Substrate 818: Wafer pedestal 820: Heater block 822: Outlet 824: Processing chamber 826: Vacuum pump 900: Processing tool 902: Inbound load lock chamber 904: Outbound load lock chamber 906: Robot 908: Wafer cassette 910: Atmospheric port 912: Pedestal 91 3: RF Power System 914: Processing Chamber 916: Chamber Transfer Port 918: Pedestal 950: System Controller 952: Processor 954: Mass Storage Device 956: Memory Device 958: System Control Software 990: Wafer Handling System 1000: Processing Equipment 1001: Conveyor System 1002: Processing Chamber 1003: Vaporization Point 1006: Showerhead 1007: Volume 1008: Substrate Holder (Pedestal) 1009: Mixing Container 1014: RF Power Supply 1016: Matching Network 1018: Vacuum Pump 1020: Valve 1101: RF Power Source 1103: Matching Module 1121: Distribution Network 1123: RF Regulator 1131: Ground 1133: Power Parameter Sensor 1143: RF Controller 1151: Station 1153: Showerhead 1157: Pedestal Various embodiments disclosed herein are depicted by way of illustration and not limitation in the figures of the accompanying drawings in which like reference characters refer to similar elements. FIG. 1 depicts a first example of an abnormal plasma event detection apparatus. FIG. 2 depicts a first exemplary slope change detection unit capable of detecting abnormal plasma events. 3A and 3B depict waveforms representing exemplary detection responses of a slope change detection unit. FIG. 4 depicts a schematic diagram of an exemplary circuit capable of detecting an anomalous plasma event. FIG. 5 shows a waveform representing RF power coupled to a process station in a processing chamber as a function of time. FIG6A shows another waveform, which represents the RF power output and the signal output by the slope change detection unit. FIG. 6B depicts a set of contours representing the spectral density of light energy fluctuations under nominal operating conditions within a process station. 6C depicts a group of profiles representing spectral density of light energy fluctuations under nominal operating conditions within a process station, and a profile representing spectral density of light energy fluctuations when an abnormal plasma event occurs within a process station. 6D and 6E depict alternative configurations of the first exemplary abnormal plasma event detection apparatus of FIG. 1 . 7A depicts a flow chart of a first exemplary technique for detecting and mitigating the effects of an anomalous plasma event. FIG. 7B depicts a flow chart illustrating a second exemplary technique for detecting and mitigating the effects of abnormal plasma events. FIG8 provides a block diagram of an exemplary apparatus that may be used to implement the disclosed embodiments. FIG. 9 is a schematic diagram showing an embodiment of a multi-station processing tool. FIG. 10 shows a substrate processing apparatus for depositing a film on a semiconductor substrate. FIG. 11 depicts an embodiment of a multi-station processing tool. FIG12 depicts the Paschen curve for helium. 102: semiconductor processing chamber 104: Lens 106: Fiber optic cable 108:Signal Processor 110:RF generator 112: Light Detector 114: Slope change detection unit

Claims

1. A method for detecting abnormal plasma events, comprising: forming a plasma using a signal from an RF generator; detecting a fluctuating optical signal generated by the plasma; calculating the spectral density of the fluctuating optical signal; and determining that the spectral density of the fluctuating optical signal differs from one or more reference spectral densities of the fluctuating optical signal generated by the plasma by a threshold amount, wherein the step of calculating the spectral density of the fluctuating optical signal includes determining the spectral density of the fluctuating optical signal at a frequency of about 400 kHz or at a frequency between about 400 kHz and about 4 MHz.

2. The method for detecting abnormal plasma events as described in claim 1, wherein the step of calculating the spectral density of the fluctuating optical signal includes using a fast Fourier transform.

3. The abnormal plasma event detection method of claim 1, wherein the one or more reference spectral densities of the fluctuating optical signal correspond to the spectral density of a fluctuating optical signal generated by plasma maintained under nominal conditions.

4. The abnormal plasma event detection method of claim 3, wherein the threshold quantity is equivalent to at least one standard deviation relative to the spectral density of the optical signal from the fluctuation of the plasma maintained under nominal conditions.

5. The method for detecting abnormal plasma events as claimed in claim 1, wherein the step of calculating the spectral density of the wave's optical signal includes determining the spectral density of the wave's optical signal at a frequency of approximately 400 kHz.

6. The method for detecting abnormal plasma events as claimed in claim 1, wherein the step of calculating the spectral density of the fluctuating optical signal includes determining the spectral density of the fluctuating optical signal at a plurality of frequencies generated by one or more RF generators.

7. An apparatus comprising: a signal processor configured to analyze an output signal from a photodetector receiving an optical signal from a multistation processor, the signal processor further configured to: detect a fluctuating optical signal generated by plasma formed in a semiconductor processing chamber; calculate the spectral density of the fluctuating optical signal; and determine that the spectral density of the fluctuating optical signal differs from one or more reference spectral densities of the fluctuating optical signal generated by the plasma by a threshold amount, wherein the step of calculating the spectral density of the fluctuating optical signal includes determining the spectral density of the fluctuating optical signal at a frequency of about 400 kHz or at a frequency between about 400 kHz and about 4 MHz.

8. The apparatus of claim 7 further includes an RF generator configured to generate the plasma within the semiconductor processing chamber.

9. The apparatus of claim 7, wherein the one or more reference spectral densities of the fluctuating optical signal are equivalent to the spectral densities calculated when the plasma is maintained under nominal conditions.

10. The device of claim 9, wherein the threshold quantity corresponds to a standard deviation relative to the spectral density of the optical signal from the fluctuation of the plasma maintained under nominal conditions.

11. The device of claim 10, wherein the threshold quantity is equivalent to two standard deviations relative to the spectral density of the optical signal from the fluctuation of the plasma maintained under nominal conditions.

12. The apparatus of claim 11, wherein the spectral density of the fluctuating optical signal is calculated at a frequency of the RF signal coupled to the multistation processor.

13. The apparatus of claim 7, wherein the spectral density of the fluctuating optical signal is calculated using a fast Fourier transform.

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