defect detection in si-wafer

INSTITUTE OF PHYSICS PUBLISHING MEASUREMENT SCIENCE AND TECHNOLOGY

Meas. Sci. Technol. 15 (2004) 35–43 PII: S0957-0233(04)65357-4

Defect detection in unpolished Si wafersby digital shearographyGanesha Udupa1, B K A Ngoi1, H C Freddy Goh2 and M N Yusoff1

1 Precision Engineering and Nanotechnology Centre, School of Mechanical and ProductionEngineering, Nanyang Technological University, Nanyang Avenue, 639798, Singapore2 International Semiconductors Products Pte. Ltd, 629013, Singapore

Received 24 June 2003, in final form 9 September 2003, accepted forpublication 16 September 2003Published 14 October 2003Online at stacks.iop.org/MST/15/35 (DOI: 10.1088/0957-0233/15/1/005)

AbstractDefects in silicon wafers have been of great scientific and technologicalinterest since before the earliest days of the silicon transistor. Recentlymuch attention has been focused on crystal originated pits on the polishedsurface of the wafer. These defects have been shown to contribute to gatedielectric breakdown. The present work relates to surface and/or subsurfacedefect inspection systems for semiconductor industries and particularly to aninspection system for defects such as swirl defects and groups of particles inunpolished silicon wafers before the wafer reclamation and/or the waferfabrication process using a digital shearography technique. The methoddescribed here relates specifically to semiconductor wafers, but may begeneralized to any other samples. In the present work, surface or subsurfacedefects are detected and evaluated by stressing the silicon wafer whilelooking for defect-induced anomalies in a fringe pattern, generated by theinterference of two speckle patterns, in the CCD camera and digital imageprocessing.

Keywords: COPs, digital shearography, semiconductor defect detection

(Some figures in this article are in colour only in the electronic version)

1. Introduction

Silicon wafers are widely used in the semiconductor andmicroelectronics industries. With this material, there isan immense need to obtain a defect-free highly polishedsurface for improved yield and performance of the micro-components. The current practice in the semiconductorindustry is to inspect the wafers for any surface defects onlyat the end of the final polishing stage. At this stage, thesubsurface defects are visible (as they have been exposed bypolishing) as minute spots forming spiral rings or ‘swirls’.These subsurface defects, which cannot be detected beforethe reclamation process or wafer fabrication process, causea high wafer rejection rate at the end of the finishing stage.Unfortunately, there is no instrument currently available toinspect the ‘prime’/‘test’ wafers at the subsurface level beforewafer fabrication/reclamation.

Several techniques such as x-ray, atomic force mi-croscopy, scanning tunnelling microscopy, scanning electronmicroscopy, and acoustic scanning electron microscopy have

been utilized for the surface defect characterization [1]. How-ever, in the semiconductor industry, the main challenge lies inthe characterization of subsurface as well as surface defects.There has been very little research work in the characterizationof subsurface defects in Si wafers.

Optical interferometric techniques have been used for non-destructive testing (NDT) of objects. Two of these techniquesare electronic speckle pattern interferometry (ESPI) andspeckle shearing interferometry, also known as shearography.These techniques have been used to detect hidden defectsin aircraft parts, turbine blades, space vehicles, automobilesand many other products [2]. Shearography is a laseroptical method, which is suited for either NDT or forstrain analysis. In contrast to holography, which measuressurface displacements, shearography measures derivativesof surface displacements. Since strains are functions ofdisplacement derivatives, shearography allows strains to bedetermined without numerical differentiating displacementdata. Defects in objects normally create strain concentrations;it is easier to correlate defects with strain anomalies

0957-0233/04/010035+09$30.00 © 2004 IOP Publishing Ltd Printed in the UK 35

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G Udupa et al

using shearography than displacement anomalies applyingholography. Furthermore, rigid body motions do not producestrain, thus shearography is insensitive to such motions anddoes not need to adopt any particular device for vibrationisolation [2].

The bare, ground, lapped or etched wafer surfaces are usedto inspect the subsurface defects by digital shearography [3].The qualitative inspection of subsurface defects and theprinciples and method of inspection are described in this paper.The quantitative analysis and serial automatic measurement ofsmall areas are being carried out using a macro focus lens atdifferent locations on the wafer to detect distributed subsurfacewafer particles of micron size.

2. Inspection in semiconductor wafer manufacturing

The Semiconductor Industry Association’s (SIA) InternationalTechnology Roadmap for Semiconductors [4] identifies lackof progress in the inspection and characterization of defectsand particles on wafers to be a potential barrier to deviceminiaturization. The roadmap specifies that by 2005, 30 nmparticles must be detectable on bare silicon and nonmetallicfilms, 39 nm particles on metallic films and 100 nm particleson wafer backsides, for which no solutions currently exist.Semiconductor wafer manufacturers already use lasers todetect particles on expensive silicon wafers, which containhundreds of chips. But the manufacturing operation must beshut down while workers try to determine what the particlesare made of and where they came from, especially when largequantities are found. The source of the particles must beeliminated before production can resume. As the features incircuits are getting smaller every 18 months or so, the size of akiller defect is getting smaller and smaller. Because circuits innew computer chips are only slightly wider than the particles,the contaminants are large enough to short-circuit the tiny‘wires’ in the chips. With the need to detect smaller defects,the costs of inspecting wafers are skyrocketing. In order fornew advances to be implemented in production environments,improvements in sensitivity must be achieved.

The processing cost of silicon wafers and the control ofdefects (at sub-micron size and, especially, those present atsubsurface level) on these wafers are most critical to the waferfabrication/reclamation industries. It has been reported thatmillions of dollars were lost each year owing to the failureof detecting these defects in silicon wafers prior to the waferfabrication/reclamation processes. The wafers produced bythe wafer fabrication process are called as ‘prime’ wafers.Wafers which fail to meet certain standards, will be rejectedat different stages of the fabrication process. These rejectedwafers are known as ‘test’ wafers. ‘Test’ wafers are usefulfor monitoring the operation of the device manufacturing stepsduring trial runs before the start of actual device manufacturingusing the ‘prime’ wafers. ‘Test’ wafers can be used 5–6times for trail runs and, prior to each trial, they have to beprocessed or reclaimed (stripping and lapping through to finepolishing). Wafer reclamation is a re-processing technologyused on rejected wafers during the wafer fabrication.

In wafer reclamation industries, a general rule is that awafer with a subsurface defect at a depth of 15 µm and adefect size of more than 10 µm in diameter is considered to

be a defective wafer. This is because, each time the wafer isreclaimed, about 15 µm thickness of wafer will be processedand inspected for particles.

The study of defects in silicon crystals has been an integralpart of silicon research activity from the earliest days of thesilicon transistor. In the mid-1970s, Rozgonyi [5] noted theimportance of suitable diagnostics in detecting and identifyingthe various types of defects in the crystal. Over the lasttwo decades, many new diagnostic tools have been developedand effectively employed. This led the industry to a greatlyimproved understanding of defects in silicon and resulted ina significant reduction in yield losses while the number ofprocessing steps increased more than eightfold [6].

Typically, a semiconductor wafer may have a very largenumber of defects, of varying patterns, such as swirl, clusteror random particles, voids, scratches, cracks or damage,which may have resulted from a great number of causes,such as crystal pulling during crystal growth or impropercontrol of process parameters during the lapping, etchingand polishing processes. Among all of these, the mostinteresting were the ‘swirl’ defects, which were attributed tovacancy clustering such as voids or vacancy-type dislocationloops, until their discovery by electron microscope. Swirldefects are classified into two types: ‘A’ (larger) and ‘B’(smaller). In 1975, ‘A’ defects were identified as interstitial-type dislocation loops by electron microscopy, although ‘B’defects could not be detected [7]. The practitioners inthe production lines prefer abbreviations like ‘COP’ (crystaloriginated particles or pits) or ‘LPD’ (light point defects). TheCOPs have attracted much interest because they may decreasereliability and manufacturing yield of semiconductor devices.Recently, COPs have been recognized as surface defectsor micro-pits generated during the crystal ingot growingprocess and detected by particle counters after surface cleaningprocesses [8].

In order to increase the yield in the manufacturing process,the said defects are to be detected at an early stage of theprocess as well as controlled during the production process.In the mid 1980s, surface (visual) defects (scratches, voids,particles, masking errors, etc) were considered to have thegreatest impact on semiconductor yield. This led to thedevelopment of automatic surface defect detection equipmentand fabrication procedures designed to identify, control andeliminate sources of surface defects. Commercial wafer defectinspection systems, such as KLA’s Tencor instrument, arecurrently available to surface inspect the defects at the endof the manufacturing process in semiconductor industries.Unfortunately the same level of success has not been achievedfor subsurface (non-visual) defects. Optical or e-beamtechniques that have been used successfully to identify andremove sources of surface defects cannot be applied tosubsurface defects. Some of these defects are generallyassociated with open contacts or vias, gate dielectric defects orparametric variation, and residues or voids within the devicestructures. Without tools to identify, measure and analyse thesedefects, attempts to eliminate them are limited to trial anderror efforts. As a result, subsurface defects comprise 65%of all the reasons for yield loss [9]. So it is very important todetect and analyse the subsurface defects in the wafer beforemaking them into devices. An attempt has been made here for

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Defect detection in unpolished Si wafers by digital shearography

READY FOR IC FABRICATION

RECYCLE BIN

Defect?yes no

Our process

Unpolished Silicon Wafers

Defect?no

RECYCLEBIN

yesSilicon wafers

Patterned Wafer

Significant reduction of defective wafers &Cost savings

Unpolished Silicon Wafers

Polishing (whole batch)

Polishing (good wafers only)

Conventional process

Figure 1. The flowchart for in-line metrology of subsurface defectdetection for semiconductor wafer manufacturing/reclamationindustries.

the first time to detect subsurface defects in an unpolished Si-wafer by digital shearography. Figure 1 shows the flowchartfor in-line metrology of subsurface defect detection proposedto benefit the semiconductor wafer manufacturing/reclamationindustries.

3. Principles of digital shearography

Digital shearography falls in the family of digital specklepattern interferometry (DSPI). Digital shearography is anoptical interferometric technique that measures surface strainconcentrations caused by surface and subsurface flaws ordefects due to some sort of load, usually either thermal, vacuumor vibration excitation. In shearography one object point splitsinto two in the image plane by a shearing device, thus twolaterally sheared images are observed using CCD camera. Theshearing device may use a Michelson interferometric principleor a double refractive prism. The two laterally sheared imagesinterfere with each other producing a random interferencepattern commonly known as a speckle pattern. The patternis random, and depends on the characteristics of the surfaceof the object. When the object is deformed, by temperature,pressure or other means, the random interference pattern willchange. The amount of the change depends on the soundnessof the object. A comparison of the random speckle patternsfor the deformed and undeformed states, and their respectivefringe patterns, gives information about the structural integrityof the object. A flaw or defect in the object usually induces astrain concentration which is translated into an anomaly in thefringe pattern. The method is called shearography because oneimage of the object is laterally displaced, or sheared, relativeto the other image.

Digital speckle shearing interferometry or digitalshearography uses a CCD camera and computer imageprocessing to produce the fringe anomaly patterns indicativeof the defects in objects. The applicability of shearinginterferometry to measuring deformations is further enhancedusing phase shifting (also called phase stepping). Understable conditions, phase shifting interferometers have a highersensitivity than systems without phase shifting. Phase shiftinginterferometers calculate the phase distribution from severalinterference patterns, which is then displayed on a videomonitor.

Shearographic image may be mathematically representedas [10]

I = I0(1 + µ cos φ) (1)

where I is the intensity distribution of the speckle patternreceived at the image plane of the camera, I0 is the intensity ofthe laterally sheared images (dc intensity), µ is the amplitudeof modulation of the speckle patterns (visibility) and φ is therandom phase angle.

After the object is deformed, the intensity distributionbecomes

I ′ = I0[1 + µ cos(φ + �φ)] (2)

where �φ denotes phase change due to surface deformation(change in the optical path length of light scattered from twoneighbouring points). The difference of intensities I and I ′ is

Id = I ′ − I = 2I0[µ sin(φ + �φ/2) sin(�φ/2)] (3)

where Id manifests itself as a fringe pattern in which dark fringecorresponds to

�φ = 2nπ with n = 0, 1, 2, 3 . . . .

Bright fringes correspond to �φ = (2n + 1)π .It may be shown that �φ is related to the relative

displacement (δu, δv, δw) of the two neighbouring pointsP(x, y, z) and P(x + δx, y, z), where δx is the amount ofshearing in the x direction, as follows:

�φ = 2π/λ(Aδu + Bδv + Cδw) (4)

where (u, v,w) and (u + δu, v + δv,w + δw) are thedisplacement vectors of P(x, y, z) and P(x + δx, y, z).A, B and C are sensitivity factors that are related to thepositions of the illumination point Ps(xs, ys, zs) and the cameraPc(x0, y0, z0), as represented in figure 2, and

A = (x − x0)/R0 + (x − xs)/Rs

B = (y − y0)/R0 + (y − xs)/Rs

C = (z − y0)/R0 + (z − xs)/Rs

R20 = x2

0 + y20 + z2

0 and R2s = x2

s + y2s + z2

s .

When surface points are considered, �φ is related to thedisplacement derivative through the following:

�φ = 2π/λ[Aδu/δx + Bδv/δx + Cδw/δx]δx or

�φ = 2π/λ[A∂u/∂x + B∂v/∂x + C∂w/∂x]δx(5)

where λ is the wavelength.If the beams are confined in x–z plane and θ is the

angle between the illumination beam and the z-axis (imagingdirection), the sensitivity factor B becomes zero and themeasurement is insensitive to ∂v/∂x . For measuring the slope(first order derivative) of the out-of-plane displacement asin our experimental configuration, the phase changes due tosurface deformation in this case can be expressed as

�φ = 2π/λ[(sin θ)∂u/∂x + (1 + cos θ)∂w/∂x]δx . (6)

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G Udupa et al

Z

Y

X

Deformationafter loading

Ps (xs, ys, zs)

Pc (x0, y0, z0)P (x+u, y+v, z+w)

BeforeLoading

P (x, y, z)

Figure 2. Position of a point on a specimen in relation toillumination and camera point before and after the deformation.

For normal illumination θ = 0, equation (6) becomes

�φ = 4π/λ[∂w/∂x]δx .

If the shear is along y direction, then

�φ = 4π/λ[∂w/∂y]δy.

4. Description of the wafer defect detection system

In the present work, surface and subsurface defects are detectedand evaluated by stressing the silicon wafer while lookingfor defect-induced anomalies in a fringe pattern, generated bythe interference of two speckle patterns, in the CCD cameraand digital image processing. Figure 3 shows a schematicdiagram of the measuring system based on an out-of-planedisplacement gradient sensitive configuration. The major partsare the illumination source, shearographic head and the imageacquisition. The source of light is a 35 mW He–Ne laser at awavelength of 632.8 nm. The shearographic head consists of aCCD camera and the shearing element. The shearing elementis an interferometer in Michelson arrangement. A beamsplitter and two adjustable mirrors (M3 and M4), followedby a zoom lens, image the wafer onto the CCD camera.The direction and amount of shear are altered by tilting themirror M4 through the required angle. The CCD arrayhas 752 (H) × 582 (V) pixels. A macro video zoom lens(18–108 mm, f 2.5), with the working distance variablebetween a maximum of infinity (without close up lens) and aminimum of 140 mm (with close up lens), is fixed to the CCDcamera (2/3′′ format). The zoom lens can be manually adjustedfor focus and aperture control. With the working distance atabout 600 mm, the zoom lens and camera were capable ofrecording a field of view that ranged from 198 mm × 264 mmat the low magnification to 33 mm × 44 mm at the highmagnification. Using the close up lens, the size of the fieldof view is about 6 mm × 8 mm at a working distance of140 mm. To view a 200 mm diameter wafer, the camera-to-object distance was about 600 mm. The camera was connectedto a Pentium 4 computer for image acquisition and analysis.

The wafer under test is illuminated by a laser beam througha collimator and a spatial filter (SF2). A 10×-microscopeobjective combined with 25 µm pinhole spatial filter (SF2)is used to get the required beam expansion. The scatteredlight from the wafer is imaged on a CCD camera through the

PC

Mirror M1

Spatial filter SF1

Collimator

CCDCamera

ZoomLens

BeamSplitter

Mirror M3

Mirror M4

Mirror M2

Spatial filter SF2

Wafer

ThermalLoading Device

Wafer Mount

He-Ne Laser

Figure 3. A schematic diagram of the wafer defect detection systemsensitive to out-of-plane displacement gradient.

shearing element. The shearing element allows a coherentsuperposition of two laterally displaced images of the waferin the image plane. The lateral displacement is called theshear of the images. The superposition of the two imagesis called the shearogram, which is an interferogram of anobject wave with the sheared object wave as a reference wave.Two such interferograms are recorded for different loadingconditions of the wafer sample. The loading should inducesome deformation or alter the deformation state of the surfaceof the sample. Typical loading methods are thermal, acousticalor vacuum and could be applied in a static or dynamic way.In the present work, an infrared lamp is used as the source ofthermal loading. Figure 4 shows the experimental set-up ofthe wafer defect detection system.

The absolute difference of two shearograms recordedfor different loading situations of the wafer results in aninterference fringe pattern, which is directly correlated to thedifference in deformation state. Defects inside the wafer mayalter the local surface deformation induced by the loading andresult in a disturbance of the (more or less regular) loadingfringes. This allows the detection and classification of defectsusing the shearographic fringe images.

5. Results and discussion

5.1. Study of surface defects in Si wafer

Before inspecting unpolished wafers for subsurface defects, astudy was carried out to investigate the nature and existence

38


SF1

SF2

TOP VIEW

Mirror 3

Mirror 4

Mirror 2

Mirror 1

Zoom Lens

CCDCamera

Collimator

He- Ne Laser

Wafer mount

UnpolishedWafer

IR Lamp

FRONT VIEW

Figure 4. The experimental set-up of the wafer defect detectionsystem.

of COPs on the processed wafer surface. First the polishedwafers were inspected using a wafer inspection system, inthis case a KLA Tencor instrument. The processed waferswere subsequently measured using a Wyko optical profilerto study the defects quantitatively. Figure 5 shows a ‘swirl’defect revealed after final polishing as seen by the KLA Tencorinstrument. These are micro-defects, located in a spiral patternin wafers cut perpendicular to the crystal growth direction. Thewafer defect map obtained by this instrument does not showwhether the defects are of class ‘A’ or ‘B’. The instrumentshows these defects in the form of black dots on the wafer map.To classify these defects requires a high magnification scanningelectron microscope, which shows clearly the defects as infigure 6 [11]. The A-swirl defect (the black–white contrasts)are larger size defects much smaller in number whereas theB-swirl defects (white dots) are a lot of small defects. Closeevaluation shows that the B-swirls are designated as shallow

Cluster SwirlDefects

ϕ 200 mm

Figure 5. Typical ‘swirl’ defects in a polished Si wafer revealed bya KLA Tencor instrument.

A-swirl

B-swirl

Figure 6. Types of swirl defects as seen by scanning electronmicroscope.

pits (see inset figure) whereas the A-swirls are designated ashillocks.

To characterize the defects on the wafer during thereclamation processes, an optical profiler is used to measurethe surface defects generated either during the wafer processingor during crystal growth or both. Figure 7 shows the resultsof 2D and 3D surface topography measurements of a singledefect on the lapped Si wafer by an optical profiler. Thethree-dimensional representation of the surface topographyprovides a clear indication of size, depth and shape of thedefect. The defects are almost circular (or rectangular) inshape at the surface and tapered down like a cup up to adepth of about 205 nm as shown in figure 7. The diameterof the defects varies from 5 to 10 µm. The depth and shapeof the defect change as the process changes from lappingto fine polishing. Figure 8 shows the results of 2D and3D surface topography measurement of a single defect onthe fine polished Si wafer. The defects are irregular (orelliptical) in shape at the surface and taper down like conesor pyramids to a depth of about 5 nm. The size (diameter)

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G Udupa et al

Table 1. Surface topography parameters of processed Si wafers (measurement area: 225.7 µm × 296.7 µm).

Sl. Parameters/ Ra Rq Rz Rt Defect Defectno processes (nm) (nm) (nm) (nm) diameter (µm) depth (nm)

1 Lapping 1.92 6.31 221.1 296.5 10–15 2002 Etching 1.44 1.99 44.61 67.09 5–10 503 Stock polishing 1.10 1.32 8.10 11.84 2–8 104 Fine polishing 0.85 1.08 7.94 8.58 0.05–5 5

14.6

12.0

10.0

8.0

6.0

4.0

2.0

0.00.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.2

54.41

30.00

10.00

-10.00

-30.00

-50.00

-70.00

-90.00

-127.86

-0.00-0.02-0.04-0.06-0.08-0.10-0.12-0.14-0.16-0.18-0.20

0 10 20 30 40 50

um

um

um

um

um

nm

Rq 56.93 nmRa 36.63 nmRt 205.32 nmRp 7.43 nmRv -197.89 nm

-0.00-0.02-0.04-0.06-0.08-0.10-0.12-0.14-0.16-0.18-0.20

0 5 10 15 20 25 30 35 40

um

um


Y Profile

X Profile

nm54.4

-127.90.0

0.018.2

14.6

Figure 7. The 2D and 3D surface topography map of a single defect on the lapped Si wafer by a Wyko optical profiler indicating averageroughness (Ra), RMS deviation (Rq), peak to valley height (Rt), maximum peak height (Rp) and maximum valley depth (Rv) of the surfaceprofile.

0.94

0.00

-1.00

-2.00

-3.00

-3.86

0.94

0.00

-1.00

-2.00

-3.00

-3.86

nm

um

0.500.00

-0.50-1.00-1.50-2.00-2.50-3.00-3.50-4.00

0 1 2 3 4 5 6 7 8 9



Y Profile

X Profilenm

nm

nm

um

0

-1

-2

-3

-40 2 4 6 8 10

nm

um

0.9

0.0 9.0

-3.910.1 0

Figure 8. The 2D and 3D surface topography map of a single defect on the polished Si wafer by a Wyko optical profiler indicating averageroughness (Ra), RMS deviation (Rq), peak to valley height (Rt), maximum peak height (Rp) and maximum valley depth (Rv) of the surfaceprofile.

of the defects typically varies from 5 µm to 50 nm at thesurface. Table 1 shows the surface topography parametersof the processed Si wafers along with defect size during thewafer processing stages. The optical profiler gives four surfaceroughness parameters, indicative of the surface roughness and

designated as average roughness (Ra), RMS deviation (Rq),ten-point height (Rz) and peak to valley height (Rt) of thesurface under measurement. As the value of surface roughnessparameters decreases, there is a considerable decrease in sizeand depth of defects in the Si wafer from the lapping to fine

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ϕ15

ϕ20

ϕ20

ϕ15

ϕ5ϕ2

ϕ10

ϕ2

ϕ10

ϕ5

mm

mm

1.8

1.6

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0.00.0 0.5 1.0 1.5 2.0 2.4

(a) (b)

(c) (d)

Figure 9. Demonstration of the measurement range (a) two bonded wafers with simulated subsurface defects, (b) contour map of a 2 mmdefect by a Wyko optical profiler, (c) fringe pattern showing four subsurface defects and (d) fringe pattern showing a 2 mm subsurfacedefect.

polishing process. However, these defects affect the finalperformance and decrease reliability and manufacturing yieldof semiconductor devices. Some of these defects or voidsmay be originally embedded (during crystal growth) in thesilicon wafer and will be revealed at the surface after thepolishing process (as seen in figure 5) and result in rejectionof wafers at the end of the final process. The difficult task isto detect these subsurface defects in unpolished Si wafers andsort them into defective and non-defective wafers. This helpsnot only in reducing scrap but also saving both the processingand manpower costs associated with producing swirl free non-defective wafers for IC packaging.

5.2. Study of subsurface defects in an unpolished Si wafer

Defects/flaws in silicon wafers induce strain concentrations onthe wafers. Shearography reveals these defects by translatingthe defect-induced strain concentrations to anomalies in thefringe patterns. An unpolished wafer of 200 mm diameterand thickness about 700 µm was clamped along the edges ina wafer mount, leaving 190 mm diameter exposure area forlaser illumination on one side of the wafer. Thermal loadingwas applied using an infrared lamp was placed at its centre onother side of the wafer as shown in figure 4. The temperaturegradient induces thermal stresses in the wafer. Either thedouble exposure or the real-time method can be used to performthe subtraction. The Image-Pro Plus software along withimage processing card was installed in a Pentium 4 computer

and a program written using the Auto-Pro scripting facilitiesavailable in the software to perform the above methods ofsubtraction. The real-time subtraction was carried out usingthe fixed reference frame method or the permanently refreshedreference frame method [12]. A lateral shear of 10 mm wasused throughout the experiment.

The suitability of the measurement range for thisapplication can be demonstrated using two bonded wafers asshown in figure 9(a). The two unpolished wafers of 200 mmdiameter were bonded at specific spots with various sizes usinga steel filled epoxy adhesive. The simulated defects substitutedbetween the two wafers vary in size from approximately 2to 20 mm diameter. Figure 9(b) shows the contour mapof a defect with about 2 mm diameter seen using the lowmagnification objective lens (2.5×) available in the opticalprofiler. The diameter of the defects may change a little afterthe bonding. The fringe pattern in figure 9(c) successfullyreveals the location of the four simulated subsurface defects ofsize 5, 10, 15 and 20 mm as seen by the bull’s-eye anomaly inthe fringe pattern. In comparison with figure 9(a), the bull’s-eye corresponds to the positions of the four simulated defects.However the smallest simulated defect, of size 2 mm, was notdetected when viewing the whole wafer surface. An attempthas been made to detect this defect by reducing the field ofview with the zoom lens. Figure 9(d) shows the detection ofthe smallest defect, which shows the position correctly at thecentre of the wafer. Similar experiments were also conductedin detecting debonds between two bonded wafers. The present

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(a)

(b)

Defects

Figure 10. (a) The subsurface defects in an unpolished Si wafer and(b) the good unpolished Si wafer.

application needs to detect defects within the range of thethickness of the wafer. This proves that the technique is ableto detect the subsurface defects present 700 µm below thesurface, which is of interest in this application. The minimumsize of the subsurface defect that can be detected in a wafer isdifficult to say precisely as it depends on several factors such asthe shearing amount, the type of the defect, the type of loadingand its condition, and the size of the field of viewing. However,the study of swirl defects or pits discussed above reveals thatthe size of the subsurface defect in an unpolished Si wafer isnormally about 10 µm. Defects larger than 10 µm may bepresent either individually or in the form of cluster defects asseen in figure 5. The cluster defect is a series of swirl defectsgrouped together to form a bigger defect. The defects in theouter ring in figure 5 may be considered as a group of clusterswirl defects as it forms a thick ring about 20 mm wide. In thiscase it is easy to detect the defects by digital shearography orholography techniques. It is observed that not all the measuredwafers are of this type. The defect distribution inside the wafervaries from circular pattern to a random distribution of swirldefects from few hundred to few thousand particles or pits.

Cluster SwirlDefects

100

50

0.2 0.5 1 2 5 10 20 50 100 500 20000.160 9900Diameter (µm)

1000

100

10

1

mm2

Area

Cou

nt

Figure 11. The surface defects map after polishing the wafer offigure 10(a), revealed by a KLA Tencor instrument with a graphshowing defect particle count and the corresponding defect size.

Figure 10(a) shows a typical fringe anomaly pattern for thesubsurface wafer defects. The pattern may vary depending onthe distribution of COPs inside the wafer. Typical flaw/defectindications depicted in fringe patterns are: (a) bull’s-eyes,(b) abrupt curvature changes, (c) abrupt fringe density changesand (d) fringe discontinuity. However in figure 10(b), for non-defective (good) wafers, the fringe patterns show lines of equalout-of-plane derivative of displacement due to loading andthere is no abrupt change of curvature and/or discontinuityof fringes. The results are repetitive, and it shows that thetechnique is capable of differentiating the ‘good’ wafers from‘defective’ wafers before the wafer reclamation or fabricationprocesses. The defective unpolished wafer of figure 10(a) hasbeen sent for polishing to verify the presence of subsurfacedefects. After the polishing process, the wafer was inspectedusing a KLA Tencor instrument for surface defects. The defectmap obtained on the final polished silicon wafer shows defectsizes varying from sub-micrometre to hundreds and thousandsof micrometres (up to about 10 mm), as shown in figure 11. Theinstrument counts the number of particles on the wafer surfacebased on its size and plots it on a graph showing particle countand the corresponding size, as in figure 11.

The technique detects the bigger defect particles or voids(cluster defects) present inside the wafer in the form of thebull’s-eye as seen in figure 10(a). However the detection ofsmaller (tens of micron) individual defect particles could notbe revealed; this may need a higher macro focus zoom lens toperform serial measurement on a smaller area or the use of alower wavelength light source. Since the location of defectsin the wafer thickness direction is not known, it is difficult tocompare the defects in figure 10(a) with the mapped defects offigure 11. Further work is needed to quantify the results usingthe phase shifting method.

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6. Conclusions

A wafer defect detection system for detecting subsurfacedefects in an unpolished silicon wafer has been investigatedbased on digital shearography. In the present work, swirldefects (cluster defects) and groups of particles can be detectedqualitatively by whole field measurement of the wafer surfacein few seconds. The cluster defects and COPs are detected bythermally stressing the wafer while looking for defect-inducedanomalies in the fringe pattern. Preliminary tests show thatabout 95% of the results (in a batch of 100 unpolished wafers)obtained by the system are in agreement with the resultsobtained by the Tencor instrument in terms of detecting clusterswirl defects or particles. Since the depths of the subsurfacedefects are unknown, its difficult to compare the results withthe surface defect results obtained after processing the wafer.However, the results obtained are repetitive and hence usefulto sort defective and non-defective unpolished wafers. Thestudy of surface defects on processed wafers show that mostof the defects in nature are pits or voids and the minimum sizeof an individual defect in an unpolished wafer is about 10 µm.The system can detect cluster swirl defects of size at least5 mm when viewing the whole wafer surface. By reducingthe size of field of view, the working distance and controllingthe other parameters such as amount of shear, stable loadingconditions etc, the system could be able to detect defect sizesof a hundred to a few hundred micrometres. To evaluate thesize of the subsurface defect needs correct identification of itslocation and depth in the thickness direction. To investigate thedetection of micro-size defects in the wafer needs improvementin the performance of the system. Future improvements tothe system include replacing the available zoom lens with along working distance microscope to inspect a field of viewof 1 mm or less. The disadvantage in this case is that it takesmore time to inspect the whole wafer surface and may require alocal stressing at the point of measurement in order to registerany underlying defects. Also a scanning stage is required toscan the wafer when viewing a small area on the surface. Ifthe subsurface defects are greater in number, the detectionand identification of individual defects becomes more difficultand complex. It is observed that some of the wafers aretransparent to IR radiation causing difficulty in measurement.Other loading methods such as vacuum or pressure are beingdeveloped to avoid such problems and to get a more uniformloading condition. A higher pixel resolution camera may beincorporated for increased image definition. Further work isbeing carried out to determine quantitatively the depth and

size of the defects using a phase shifting technique to makethis system suitable for in situ inspection on the factory floor.This will enhance the system’s capability greatly by providingcritical information and further assisting in determining ‘good’wafers from ‘defective’ wafers before wafer reclamation orfabrication processes.

Acknowledgments

This research work was supported by the Economic De-velopment Board, Singapore (Grant No COY-15-IDS/I122-1S99/50890) in collaboration with International Semiconduc-tors Products (ISP) Pte. Ltd, Singapore. Authors would liketo thank Dr Usha of ISP for her help in the experimental work.

References

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