CN103065991B - The detection method of the repeated defects of semiconductor device - Google Patents
The detection method of the repeated defects of semiconductor device Download PDFInfo
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- CN103065991B CN103065991B CN201210451665.5A CN201210451665A CN103065991B CN 103065991 B CN103065991 B CN 103065991B CN 201210451665 A CN201210451665 A CN 201210451665A CN 103065991 B CN103065991 B CN 103065991B
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Abstract
A detection method for the repeated defects of semiconductor device, comprising: step S1: fixed point scanning; Set up fixed point scanning formula, and choose the interior zone of repetitive in module to be tested, the Minimum Area that can scan using described electron beam flaw scanner as scanning element region, and is set as defect and be detected, takes electron microscope collection of illustrative plates; Step S2: GTG sample collection; GTG analysis is carried out to electron microscope collection of illustrative plates described in step S1, obtains typical gray-scale distribution and gray-scale distribution interval thereof, and define standard gray scale interval; Step S3: abnormal semiconductor device forecast.The standard gray scale interval that the present invention collects data and described normal semiconductor device by the GTG that electron beam flaw scanner obtains compares, can effectively forecast abnormal semiconductor device, and the repeated defects realized ion implantation technology produces effectively is monitored, and then be process window optimization and on-line monitoring supplying method opinion, provide safeguard with Yield lmproved for semiconductor manufactures online.
Description
Technical field
The present invention relates to technical field of semiconductor device, particularly relate to a kind of detection method of repeated defects of semiconductor device.
Background technology
Ion implantor is one of implantation equipment of most critical during semiconductor device manufactures, is a kind of by guiding impurity to inject semiconductor wafer, thus changes the equipment of wafer conductivity.The performance quality of quality to semiconductor device that semiconductor ion injects plays critical effect.
Along with the development of integrated circuit technology and critical size scaled, such as when below 55nm accomplished by device, the control of ion implantation is even more important.Numerous factors all produces great impact by performance of semiconductor device, and described factor includes but not limited to dosage and the ion concentration of injecting ion, the degree of depth of ion implantation, and ion self diffusion etc.In addition, due to the particularity of ion implantation self, if ion implantation technology generation deviation, online scanner is difficult to monitor by traditional scan mode and analysis means.
Refer to Fig. 8, Figure 8 shows that the repeated defects schematic diagram in semiconductor device.Enumerate ground, if consistent angular deviation appears in ion implantation, thus form shadow effect, time serious, a line or multirow off-grade metal oxide device 19 will be occurred in grade metal oxide device 18.But, due to its all indiscriminate appearance in all repetitives, namely occur in the mode of repeated defects, even scanning machine electron beam flaw scanner, this situation can not be detected.
Therefore for prior art Problems existing, this case designer is by means of being engaged in the industry experience for many years, and active research improves, so there has been the detection method of the repeated defects of a kind of semiconductor device of the present invention.
Summary of the invention
The present invention be directed in prior art, the indiscriminate appearance of repeated defects of traditional semiconductor device, and the detection method that defect provides a kind of repeated defects of semiconductor device such as cannot to detect.
In order to solve the problem, the invention provides a kind of detection method of repeated defects of semiconductor device, the detection method of the repeated defects of described semiconductor device comprises:
Perform step S1: fixed point scanning; Described fixed point scanning comprises further, applying electronic harness defects scanner sets up fixed point scanning formula in the metal connecting layer of the semiconductor device adopting normal process, and choose the interior zone of repetitive in module to be tested, the Minimum Area that can scan using described electron beam flaw scanner is as scanning element region, described scanning element region is set as defect by formula and is detected, and takes electron microscope collection of illustrative plates;
Perform step S2: GTG sample collection; Described GTG sample collection comprises further, GTG analysis is carried out to the electron microscope collection of illustrative plates in the scanning element region described in step S1, the typical gray-scale distribution and the gray-scale distribution thereof that obtain normal semiconductor device are interval, and define the standard gray scale interval that described gray-scale distribution interval is described normal semiconductor device;
Perform step S3: the abnormal semiconductor device forecast with repeated defects; The GTG that described electron beam flaw scanner analyzes semiconductor device to be tested collects data, is forecast by the semiconductor device differing from described standard gray scale interval as real defect.
Alternatively, described scanning element region is 512 × 512 pixels.
Alternatively, the semiconductor device of described employing normal process is the ideal component without repeated defects, i.e. normal semiconductor device.
Alternatively, described electron beam flaw scanner has sensitiveness to ion beam mutation doping.
Alternatively, described scanning element region is the non-borderline region of repetitive.
Alternatively, described standard gray scale interval is 50 ~ 100, and what differ from described standard gray scale interval is abnormal semiconductor device.
Alternatively, the GTG interval of described abnormal semiconductor device is 130 ~ 190.
In sum, the standard gray scale interval that the present invention collects data and described normal semiconductor device by the GTG that electron beam flaw scanner obtains compares, can effectively forecast abnormal semiconductor device, and the repeated defects realized ion implantation technology produces effectively is monitored, and then be process window optimization and on-line monitoring supplying method opinion, provide safeguard with Yield lmproved for semiconductor manufactures online.
Accompanying drawing explanation
Figure 1 shows that the flow chart of the detection method of the repeated defects of semiconductor device of the present invention;
Figure 2 shows that electron beam flaw scanner is to ion beam mutation doping sensitiveness schematic diagram;
Figure 3 shows that the schematic diagram that electron beam flaw scanner scanning area is selected;
Fig. 4 (a) is depicted as the repetitive schematic diagram of normal semiconductor device;
Fig. 4 (b) is depicted as the typical gray-scale distribution figure of normal semiconductor device;
Figure 5 shows that the interval schematic diagram of the standard gray scale of normal semiconductor device;
Fig. 6 (a) is depicted as the repetitive schematic diagram of abnormal semiconductor device;
Fig. 6 (b) is depicted as the gray-scale distribution figure of abnormal semiconductor device;
Figure 7 shows that the interval schematic diagram of the GTG of abnormal semiconductor device;
Figure 8 shows that the repeated defects schematic diagram in semiconductor device.
Embodiment
By describe in detail the invention technology contents, structural feature, reached object and effect, coordinate accompanying drawing to be described in detail below in conjunction with embodiment.
Refer to Fig. 1, Figure 1 shows that the flow chart of the detection method of the repeated defects of semiconductor device of the present invention.The detection method of the repeated defects of described semiconductor device, comprises the following steps:
Perform step S1: fixed point scanning; Particularly, described fixed point scanning comprises further, applying electronic harness defects scanner sets up fixed point scanning formula in the metal connecting layer of the semiconductor device adopting normal process, and choose the interior zone of repetitive in module to be tested, the Minimum Area that can scan using described electron beam flaw scanner is as scanning element region, described scanning element region is set as defect by formula and is detected, and takes electron microscope collection of illustrative plates.Wherein, described scanning element region preferably 512 × 512 pixels.The semiconductor device of described employing normal process is the ideal component without repeated defects, i.e. normal semiconductor device.
Perform step S2: GTG sample collection; Particularly, described GTG sample collection comprises further, GTG analysis is carried out to the electron microscope collection of illustrative plates in the scanning element region described in step S1, the typical gray-scale distribution and the gray-scale distribution thereof that obtain normal semiconductor device are interval, and define the standard gray scale interval that described gray-scale distribution interval is described normal semiconductor device.
Perform step S3: the abnormal semiconductor device forecast with repeated defects.Particularly, the GTG that described electron beam flaw scanner analyzes semiconductor device to be tested collects data, is forecast by the semiconductor device differing from described standard gray scale interval as real defect.
As the specific embodiment of the present invention, in the present invention, described electron beam flaw scanner has sensitiveness to ion beam mutation doping.That is, when the dosage in ion beam implantation process or injection condition change or deviation time, the image gray-scale level data that described electron beam flaw scanner obtains can change thereupon.As shown in Figure 2, Figure 2 shows that electron beam flaw scanner is to ion beam mutation doping sensitiveness schematic diagram.Significantly, described p-type doped region 11 has different luma data from described N-shaped doped region 12.
Nonrestrictively enumerate, the detection method of the repeated defects of described semiconductor device, comprises the following steps:
Perform step S1: fixed point scanning; Particularly, refer to Fig. 3, Figure 3 shows that the schematic diagram that electron beam flaw scanner scanning area is selected.Described fixed point scanning comprises further, applying electronic harness defects scanner sets up fixed point scanning formula in the metal connecting layer of the semiconductor device adopting normal process, and choose the interior zone of repetitive 13 in module to be tested, the Minimum Area that can scan using described electron beam flaw scanner is as scanning element region 14, described scanning element region 14 is set as defect by formula and is detected, and takes electron microscope collection of illustrative plates.
Wherein, described scanning element region 14 preferably 512 × 512 pixel regions.The semiconductor device of described employing normal process is the ideal component without repeated defects, i.e. normal semiconductor device.In the present invention, preferably, described scanning element region 14 is the non-borderline region of repetitive 13.Therefore when the repeated defects carrying out semiconductor device detects, the borderline region 15 selecting described repetitive 13 should be avoided in described scanning element region 14.
Perform step S2: GTG sample collection; Particularly, refer to Fig. 4 (a), Fig. 4 (b), and Fig. 5, Fig. 4 (a) are depicted as the repetitive schematic diagram of normal semiconductor device.Fig. 4 (b) is depicted as the typical gray-scale distribution figure of normal semiconductor device.Figure 5 shows that the interval schematic diagram of the standard gray scale of normal semiconductor device.Described GTG sample collection comprises further, GTG analysis is carried out to the electron microscope collection of illustrative plates in the scanning element region 14 described in step S1, the typical gray-scale distribution and the gray-scale distribution thereof that obtain normal semiconductor device are interval, and define the standard gray scale interval 16 that described gray-scale distribution interval is described normal semiconductor device.In the present invention, enumerate without limitation, described standard gray scale interval 16 is 50 ~ 100.
Perform step S3: the abnormal semiconductor device forecast with repeated defects.Particularly, refer to Fig. 6 (a), Fig. 6 (b), and Fig. 7, Fig. 6 (a) are depicted as the repetitive schematic diagram of abnormal semiconductor device.Fig. 6 (b) is depicted as the gray-scale distribution figure of abnormal semiconductor device.Figure 7 shows that the interval schematic diagram of the GTG of abnormal semiconductor device.Significantly, the GTG that described electron beam flaw scanner analyzes semiconductor device to be tested collects data, and the GTG interval 17 obtaining described abnormal semiconductor device is 130 ~ 190, therefore the semiconductor device differing from described standard gray scale interval 50 ~ 100 is forecast as real defect.
In sum, the standard gray scale interval that the present invention collects data and described normal semiconductor device by the GTG that electron beam flaw scanner obtains compares, can effectively forecast abnormal semiconductor device, and the repeated defects realized ion implantation technology produces effectively is monitored, and then be process window optimization and on-line monitoring supplying method opinion, provide safeguard with Yield lmproved for semiconductor manufactures online.
Those skilled in the art all should be appreciated that, without departing from the spirit or scope of the present invention, can carry out various modifications and variations to the present invention.Thus, if when any amendment or modification fall in the protection range of appended claims and equivalent, think that these amendment and modification are contained in the present invention.
Claims (6)
1. a detection method for the repeated defects of semiconductor device, is characterized in that, described method comprises:
Perform step S1: fixed point scanning; Described fixed point scanning comprises further, applying electronic harness defects scanner sets up fixed point scanning formula in the metal connecting layer of the semiconductor device adopting normal process, and choose the interior zone of repetitive in module to be tested, the Minimum Area that can scan using described electron beam flaw scanner is as scanning element region, described scanning element region is set as defect by formula and is detected, and takes electron microscope collection of illustrative plates;
Perform step S2: GTG sample collection; Described GTG sample collection comprises further, GTG analysis is carried out to the electron microscope collection of illustrative plates in the scanning element region described in step S1, the typical gray-scale distribution and the gray-scale distribution thereof that obtain normal semiconductor device are interval, and define the standard gray scale interval that described gray-scale distribution interval is described normal semiconductor device;
Perform step S3: the abnormal semiconductor device forecast with repeated defects; The GTG that described electron beam flaw scanner analyzes semiconductor device to be tested collects data, is forecast by the semiconductor device differing from described standard gray scale interval as real defect;
Wherein, described electron beam flaw scanner to ion beam mutation doping there is sensitiveness, when the dosage in ion beam implantation process or injection condition change or deviation time, the image gray-scale level data that described electron beam flaw scanner obtains can change thereupon.
2. the detection method of the repeated defects of semiconductor device as claimed in claim 1, it is characterized in that, described scanning element region is 512 × 512 pixels.
3. the detection method of the repeated defects of semiconductor device as claimed in claim 1, it is characterized in that, the semiconductor device of described employing normal process is the ideal component without repeated defects, i.e. normal semiconductor device.
4. the detection method of the repeated defects of semiconductor device as claimed in claim 1, it is characterized in that, described scanning element region is the non-borderline region of repetitive.
5. the detection method of the repeated defects of semiconductor device as claimed in claim 1, it is characterized in that, described standard gray scale interval is 50 ~ 100, and what differ from described standard gray scale interval is abnormal semiconductor device.
6. the detection method of the repeated defects of semiconductor device as claimed in claim 5, it is characterized in that, the GTG interval of described abnormal semiconductor device is 130 ~ 190.
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| CN103500720B (en) * | 2013-09-30 | 2016-10-26 | 上海华力微电子有限公司 | Electron beam flaw scanner matching degree test structure and method of testing |
| CN104157586B (en) * | 2014-08-08 | 2017-03-08 | 上海华力微电子有限公司 | The method being accurately positioned the repetitive structure defect that analysis electron beam defects detection finds |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US20030076989A1 (en) * | 2001-10-24 | 2003-04-24 | Maayah Kais Jameel | Automated repetitive array microstructure defect inspection |
| CN102412168A (en) * | 2011-11-30 | 2012-04-11 | 上海华力微电子有限公司 | Wafer defect defection method and system |
| CN102735688A (en) * | 2012-06-20 | 2012-10-17 | 上海华力微电子有限公司 | Defect detection method |
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| US8094924B2 (en) * | 2008-12-15 | 2012-01-10 | Hermes-Microvision, Inc. | E-beam defect review system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US20030076989A1 (en) * | 2001-10-24 | 2003-04-24 | Maayah Kais Jameel | Automated repetitive array microstructure defect inspection |
| CN102412168A (en) * | 2011-11-30 | 2012-04-11 | 上海华力微电子有限公司 | Wafer defect defection method and system |
| CN102735688A (en) * | 2012-06-20 | 2012-10-17 | 上海华力微电子有限公司 | Defect detection method |
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