A method for identifying process batch information of commercial VDMOS devices

Abstract

The present invention relates to a method for identifying process batch information of commercial VDMOS devices, which comprises device parameter testing, batch data statistical analysis, and the establishment of sensitive batch parameters. The main factor affecting the process batch identification of commercial VDMOS devices is that minor fluctuations in the manufacturing process lead to differences in the electrical parameters of devices between different batches and within batches. By conducting parameter testing experiments on two batches of devices and comparing the distributions of the two batches on the same coordinate axis based on a data statistical analysis method, a mapping relationship between device parameters and process batch information identification is established, ultimately obtaining electrical parameters sensitive to device process batch information identification.

Description

Technical Field

[0001] The invention relates to a method for identifying process batch information of a commercial VDMOS device, and belongs to the field of microelectronic device testing. Background Art

[0002] Commercial VDMOS (Vertical Double-diffused MOSFET) devices feature high input impedance, high current gain, excellent noise margin, and low conduction losses. They also have a negative temperature coefficient and are immune to secondary breakdown effects such as thermoelectric breakdown and tunneling breakdown, making them widely used in power supply systems. However, subtle variations in temperature distribution, impurity diffusion, and implantation during device manufacturing processes, both within and between batches, can lead to fluctuations and inconsistencies in electrical parameters between devices within and across batches. This can cause dynamic voltage imbalances, increased losses, and failures in devices and related circuit modules, impacting the stability and reliability of power supply modules.

[0003] The identification of process batch information for commercial VDMOS devices in both conventional and special functional environments has been widely researched. Most factories use scanning acoustic microscopes and X-rays to identify and screen the reliability of plastic-encapsulated devices. A small number of research institutions use initial noise values ​​and tracking the preferential nucleation of V-type epitaxial defects and stacking dislocations formed by screw dislocations in N+ doped substrates to identify process batch information for MOS devices. All of the above methods have certain costs and technical difficulties, and are difficult to be widely applied. Electrical parameters sensitive to process batches have not been established. Existing guidance documents have principled requirements for process batch identification and low-cost evaluation technologies for commercial VDMOS devices, but lack technical details.

[0004] This paper proposes a method for identifying process batch information for commercial VDMOS devices. It includes device parameter testing methods, batch data statistical analysis methods, and sensitive batch parameter identification methods. Combined, these methods enable this assessment technique to be simple to operate and time-efficient, resulting in a wide range of applications. It can be used to mitigate the risks of frequent VDMOS process technology line changes and insufficient traceability in the market. Summary of the Invention

[0005] The present invention aims to provide a method for identifying process batch information of commercial VDMOS devices, which method comprises device parameter testing, batch data statistical analysis and the establishment of sensitive batch parameters. The main factor affecting the process batch identification of commercial VDMOS devices due to uncontrollable errors is that slight fluctuations in the process manufacturing process will lead to differences in the electrical parameters of devices in different batches and within batches. By carrying out parameter testing experiments on two batches of devices, based on the data statistical analysis method, the distribution of the two batches is compared on the same coordinate axis, and a mapping relationship between device parameters and process batch information identification is established, and finally the electrical parameters sensitive to the device process batch information identification are obtained.

[0006] The present invention provides a method for identifying process batch information of commercial VDMOS devices. The method comprises device parameter testing, batch data statistical analysis, and establishment of sensitive batch parameters. The specific operation is performed according to the following steps:

[0007] Device parameter test:

[0008] a. Transfer characteristic curves of two batches of commercial N-channel VDMOS devices tested at room temperature I DS -V GS , extract the maximum transconductance, threshold voltage, and subthreshold swing of the device through the transfer characteristic curve, and test the capacitance-voltage characteristic curve C of the device OSS -V DS Curve, the output capacitance is extracted from the capacitance-voltage characteristic curve, and the on-resistance and forward voltage drop are directly tested. All qualified devices from the two batches are used as test samples and numbered.

[0009] Batch data statistical analysis:

[0010] b. Based on the parameter data measured from the two batches of devices in step a, statistically analyze the distribution pattern of the same parameter of the two batches of devices, select the same parameter of the first and second batches of devices as the horizontal axis, and the device frequency as the vertical axis, and draw a normal distribution histogram within the same coordinate axis. The device frequency is represented by the distribution of the histogram, the mean is represented by the peak of the normal curve, the value of the distance from the mean is used to represent the device frequency, and the flatness or slenderness of the curve is used to represent the degree of dispersion or concentration of the data distribution. After batch data statistics, the distribution of the two batches of devices is distinguished under the same parameter characterization conditions;

[0011] Sensitive batch parameters established:

[0012] c. By comparing the fluctuation and batch correlation, as well as the peak and batch correlation of the normal distribution graphs of the two batches of devices characterized by the same electrical parameters in step b, and then comparing the distributions of the two batches of devices characterized by the electrical parameters and the electrical parameters, a mapping relationship between device parameters and process batch information identification is established to determine the sensitivity of device parameters to process batch information.

[0013] The method for identifying process batch information of commercial VDMOS devices disclosed in the present invention has the following beneficial effects:

[0014] This method and steps enable initial testing in a conventional environment. Guided by the principles and technical details of the evaluation technology, it reduces the cost and technical difficulty of device screening and batch identification, and obtains electrical parameters sensitive to process batches. This establishes a method for identifying process batch information for commercial VDMOS devices, addressing the risks of frequent device process technology line changes and insufficient traceability in the market.

[0015] The above description is only an overview of the technical solution of this application. In order to more clearly understand the technical means of this application and implement it in accordance with the contents of the specification, the following is an embodiment of this application and is described in detail with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The maximum transconductance (G MMAX ) Normal distribution histogram of initial value test;

[0017] Figure 2 is the threshold voltage of the two batches of devices in the present invention (V TH ) Normal distribution histogram of initial value test;

[0018] Figure 3 The normal distribution histogram of the initial subthreshold swing (SS) value test of two batches of devices of the present invention is as follows;

[0019] Figure 4 is the output capacitance of the two batches of devices in the present invention (C OSS ) Normal distribution histogram of initial value test;

[0020] Figure 5 The on-resistance (R DS(ON) ) Normal distribution histogram of initial value test;

[0021] Figure 6 is the forward voltage drop of the two batches of devices in the present invention (V SD ) Normal distribution histogram of the initial value test. DETAILED DESCRIPTION

[0022] Example

[0023] The present invention provides a method for identifying process batch information of commercial VDMOS devices. The method comprises a device parameter testing method, a batch data statistical analysis method, and a sensitive batch parameter establishment method. The specific operation is performed according to the following steps:

[0024] Device parameter test:

[0025] a. Transfer characteristic curves of two batches of commercial N-channel VDMOS devices tested at room temperature I DS -V GS , extract the maximum transconductance (G MMAX ), threshold voltage (V TH ), subthreshold swing (SS), and at the same time, the capacitance-voltage characteristic curve (C OSS -V DS curve), output capacitance (C OSS ) is directly extracted from the capacitance-voltage characteristic curve and the on-resistance (R DS(ON) ) and forward voltage drop (V SD );

[0026] To ensure the integrity and statistical nature of the batch device data, all qualified devices from the first and second batches were used as test samples;

[0027] Batch data statistical analysis:

[0028] b. Based on the parameter data measured from the two batches of devices in step a, statistically analyze the distribution patterns of the two batches of devices under the same parameter. Select the same parameter of the first and second batches of devices as the abscissa and the device frequency as the ordinate. Draw a normal distribution histogram within the same coordinate axis. The device frequency is represented by the distribution of the histogram, and the mean is represented by the peak of the normal curve. The normal distribution histograms of the first and second batches of devices are green and red, respectively.

[0029] Sensitive batch parameters established:

[0030] c. Observe the correlation between the fluctuation and batch, and the peak value and batch of the normal distribution diagram of the two batches of devices characterized in step b under the same electrical parameters, and then compare the distribution of the two batches of devices characterized by different electrical parameters such as maximum transconductance, threshold voltage, subthreshold swing, output capacitance, on-resistance and forward voltage drop, and establish a mapping relationship between device parameters and process batch information identification, so as to determine the sensitivity of device parameters to process batch information. The maximum transconductance of the first and second batches of devices are distributed in the range of 0S-0.05S and 0S-0.6S respectively, with peak values ​​of about 0.02S and 0.23S, and the overlap rate is about 8.33%; the threshold voltage of the first and second batches of devices are distributed in the range of 2.7V-2.95V and 2.3V-2.75V respectively, with peak values ​​of about 2.77V and 2.48V, and the overlap rate is about 7.69%; the subthreshold swing range is 0. The interval distribution is 0.25mv / dec-0.275mv / dec, 0.24mv / dec-0.275mv / dec, with peak values ​​of about 0.267mv / dec and 0.253mv / dec, and the overlap rate is about 50%; the output capacitance interval distribution is 1023pF-1038pF, 1026pF-1042pF, with peak values ​​of about 1031pF and 1036pF. , the overlap rate is about 63.16%; the on-resistance intervals are 3.9mΩ-4.3mΩ and 3.75mΩ-4.05mΩ, with peak values ​​of about 4.07mΩ and 3.88mΩ, and the overlap rate is about 27.27%; while the forward voltage drop is distributed in the intervals of 0.845V-0.865V and 0.815V-0.84V, with peak values ​​of about 0.852V and 0.828V, and the overlap rate is 0%; see Table 1

[0031] Table 1 Batch identification of device parameters and process batch information

[0032]

[0033] It can be seen that the maximum transconductance, threshold voltage, subthreshold swing, output capacitance, and on-resistance interval distributions of the two batches of devices have a certain overlap, but the peak values ​​do not overlap, which can better distinguish the process batch information of the devices.

[0034] The forward voltage drop's range of fluctuations and peak-to-peak overlap can clearly distinguish device batches. Compared to other electrical parameters, the forward voltage drop's normal curve is taller and more concentrated, making it more sensitive to batch information.

[0035] The above examples merely illustrate the implementation of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application, particularly with regard to the protection of the forward voltage drop, the most sensitive parameter in process batch identification for VDMOS devices.

Claims

1. A method for identifying process batch information of commercial VDMOS devices, characterized in that This method consists of device parameter testing, batch data statistical analysis, and sensitive batch parameter establishment. The specific operations are as follows: Device parameter test: a. Transfer characteristic curves of two batches of commercial N-channel VDMOS devices tested at room temperature I DS -V GS , extract the maximum transconductance, threshold voltage, and subthreshold swing of the device through the transfer characteristic curve, and test the capacitance-voltage characteristic curve C of the device OSS -V DS Curve, the output capacitance is extracted from the capacitance-voltage characteristic curve, and the on-resistance and forward voltage drop are directly tested. All qualified devices from the two batches are used as test samples and numbered. Batch data statistical analysis: b. Based on the parameter data measured from the two batches of devices in step a, statistically analyze the distribution pattern of the same parameter of the two batches of devices, select the same parameter of the first and second batches of devices as the horizontal axis, and the device frequency as the vertical axis, and draw a normal distribution histogram within the same coordinate axis. The device frequency is represented by the distribution of the histogram, the mean is represented by the peak of the normal curve, the value of the distance from the mean is used to represent the device frequency, and the flatness or slenderness of the curve is used to represent the degree of dispersion or concentration of the data distribution. After batch data statistics, the distribution of the two batches of devices is distinguished under the same parameter characterization conditions; Sensitive batch parameters established: c. By comparing the fluctuation and batch correlation, as well as the peak and batch correlation of the normal distribution graphs of the two batches of devices characterized by the same electrical parameters in step b, and then comparing the distributions of the two batches of devices characterized by the electrical parameters and the electrical parameters, a mapping relationship between device parameters and process batch information identification is established to determine the sensitivity of device parameters to process batch information.

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