Scattering melting detection system and use method thereof

Abstract

A high bandwidth time and space discriminating scattering phase change microscopy system configured to detect the onset of melting in a wafer processed by a laser annealing system having ultra-short dwell time and spot size.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of priority to U.S. Provisional Patent Application Serial No. 63 / 337,714, filed on May 3, 2022, and entitled “Scatter Melt Detection Systems and Methods of Using the Same,” the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present disclosure relates generally to temperature measurement, and in particular to phase change microscopy. Background Art

[0004] Pulsed laser melting annealing systems are used in advanced integrated circuit (IC) chip manufacturing for rapid thermal processing of chips. The thermal processing provided by such laser systems can be used for various effects, such as dopant activation, defining junctions, and otherwise changing the material and electrical properties of the chip. However, during annealing using a pulsed laser system, it is important and can be challenging to accurately measure and control the wafer temperature due to the duration of time the laser takes to raise the wafer temperature to the melting temperature and the reduced surface area of ​​the wafer on which the laser acts. Accurate measurement and control of the wafer temperature is also important for annealing system calibration. Summary of the invention

[0005] In one implementation, the present disclosure relates to a method for determining the occurrence of a solid-to-liquid material phase transition of a semiconductor material during a laser annealing process. The method includes: forming an annealing image on a surface of the semiconductor material using an annealing laser beam from an annealing laser; forming a scattering image of the semiconductor surface including an area of ​​the annealing image; and identifying the solid-to-liquid material phase transition of the semiconductor material based on the intensity of light collected in the scattering image.

[0006] In another implementation, the present disclosure relates to a method for analyzing scattered image data, the method comprising: receiving a scattered image of an area of ​​a semiconductor surface captured during a laser annealing process of the semiconductor; and identifying a solid-to-liquid material phase transition of the semiconductor material from the image; wherein the identification comprises identifying statistical changes, time series changes, or geometric nonlinear changes in image intensity according to one or more annealing process control parameters.

[0007] In yet another implementation, the present disclosure relates to a method for performing melt calibration for laser annealing of a semiconductor material. The method includes: annealing a region of semiconductor material using an annealing laser beam from an annealing laser, wherein the annealing includes incrementally varying a power level of the annealing laser below and above a melt threshold power level at which a solid-to-liquid phase transition of the semiconductor material occurs; capturing a scatter image of the region of semiconductor material during annealing; and determining at least one melt threshold set point power level of the annealing laser based on the captured scatter image.

[0008] In yet another implementation, the present disclosure relates to a scatter melting detection system, comprising: a stage configured to support a semiconductor wafer; an annealing laser configured to anneal the semiconductor wafer; and a scatter melting detector, comprising: an image capture device including a focal plane array (FPA); and a scatter optical arrangement configured to block or avoid specular reflection of a light beam formed by the annealing laser and form a scatter image of a surface of the semiconductor wafer on the FPA.

[0009] In yet another implementation, the present disclosure is directed to a laser annealing system comprising: an annealing laser; a storage device comprising at least one annealing laser melting threshold calibration set point specifying operating parameters of the annealing laser to raise the temperature of a localized region of a semiconductor material to a melting threshold under a set of predetermined annealing process conditions, wherein the calibration set point is derived from a scattering image of the semiconductor material acquired during laser annealing of the semiconductor material; and a controller configured to control the annealing laser according to the annealing laser melting threshold calibration set point.

[0010] In yet another implementation, the present disclosure relates to a non-transitory machine-readable storage medium comprising at least one annealing laser melting threshold calibration set point specifying operating parameters of an annealing laser to raise a temperature of a localized region of a semiconductor material to a melting threshold under a set of predetermined annealing process conditions, wherein the calibration is derived from a scattering image of a semiconductor material acquired during a laser annealing process of the semiconductor material.

[0011] In yet another implementation, the present disclosure relates to a method of forming a below-melt reference image and parameters for use with a melt detection algorithm. The method includes: annealing a wafer below melting; capturing image frames using a scatter melt detector; recording annealing laser power levels; creating a below-melt reference image from the captured image frames; processing the below-melt reference image to generate a plurality of below-melt one-dimensional stage scan direction intensity profiles; identifying a region of interest (ROIref) of the below-melt reference image; and creating an average one-dimensional stage scan direction intensity profile.

[0012] In yet another implementation, the present disclosure is directed to a method of detecting whether wafer material is melted during an annealing process. The method includes: annealing a wafer below a melting threshold, equal to a melting threshold, or above a melting threshold, capturing image frames during the annealing using a scatter melt detector, and recording laser power levels; creating an average image from the captured image frames; and creating a melt detection image referencing the average image to a corresponding below-melt reference image for the same wafer type.

[0013] In yet another implementation, the present disclosure relates to a method for detecting whether a wafer material is melted during an annealing process. The method includes: annealing a wafer below a melting threshold, equal to a melting threshold, or above a melting threshold, and capturing an image frame using a scattering melt detector during the annealing; calculating a statistical variation of pixel values ​​within a region of interest ROIref of the image frame, wherein ROIref is a region of the image where an annealing laser image is formed on the wafer; and comparing the calculated statistical variation to identify the onset of melting. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] For the purpose of illustrating the present disclosure, the accompanying drawings show various aspects of one or more embodiments of the present disclosure. However, it should be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the accompanying drawings, in which:

[0015] Figure 1 is a schematic diagram of an example laser annealing system with a scattering melt detector according to the present disclosure;

[0016] Figure 2 is a top view of a semiconductor wafer illustrating an example method of scanning a wafer surface having a preheat line image and an annealing image;

[0017] Figure 3A is a top view close-up of a preheat line image and an anneal image formed on a wafer surface showing the relative size and scan direction of the two images and the scan overlap region defining the dwell time for the melt annealing process;

[0018] Figure 3B is a top view close-up of an alternative example that does not include a preheat laser, showing an annealing image formed on the wafer surface and the sweep direction of the image and the stage scanning direction;

[0019] Figure 3C is a top-down close-up view of a sweep of the annealing image and the volume of liquid semiconductor material (referred to as the melt pool) that increases along the sweep of the annealing image;

[0020] Figure 4Ais a schematic diagram of an example scattering melt detection system, wherein a laser processing beam is used as a light source probe;

[0021] Figure 4B is a schematic diagram of an example scatter melting detection system including a light source probe separated from a laser processing beam;

[0022] Figure 5A is a schematic diagram of an optical arrangement of a scatter imaging system of the present disclosure;

[0023] Figure 5B is a schematic diagram of another example of an optical arrangement of a scatter imaging system of the present disclosure;

[0024] Fig. 6A conceptually and graphically illustrates data captured in an image frame by an image capture device of a scatter melt detector during a sweep of an anneal image with the wafer surface below melt;

[0025] Figure 6B conceptually and graphically illustrates data captured in image frames by an image capture device of a scatter melt detector during a sweep of an anneal image in the event that a pool of liquid material forms on the wafer surface above melting and along the sweep of the anneal image;

[0026] Figure 6C showing data of image frames from a sweep of an annealing image performed by an annealing laser that was not properly calibrated causing portions of the sweep to be below melting and above melting;

[0027] FIG. 7A to FIG. 7C shows test data from a melt threshold calibration, wherein the laser power is gradually increased and an increase in the degree of melting is detected in the test data;

[0028] Figure 8 shows FPA cumulative intensity data for a series of annealing treatments at increasing power levels below and above the melting threshold power level;

[0029] Fig. 9A and Fig. 9B shows scattered image data of a plurality of sequential annealing images scanned along a semiconductor surface using an annealing laser operated at a melting threshold power level;

[0030] Fig.10 is a functional block diagram of an example computing device;

[0031] Fig.11 conceptually illustrates a portion of an example image frame captured by an ICD of a scatter melting detector during an annealing process;

[0032] Fig.12 An example method of generating a below-melt reference image and associated parameters for use by one or more melt detection algorithms is shown;

[0033] Fig.13 An example method of a melt detection algorithm is shown, wherein melt is detected based on nonlinearity of amplitude in an image frame; and

[0034] Fig.14 An example approach to a melt detection algorithm is shown, where melt is detected based on statistical changes in a melt image. DETAILED DESCRIPTION

[0035] Aspects of the present disclosure include a high bandwidth temporally and spatially resolved phase change microscopy system configured to detect the onset of melting in a semiconductor wafer being processed by scanning a CW or QCW (pulse time << dwell time) laser annealing system with an ultra-short dwell time and a small spot size, and for calibrating such a system for an annealing process. In some examples, the melt detection system of the present disclosure is configured to accurately and reliably detect the onset of melting for a laser with an ultra-short dwell time in the range of 10ns to 500ns or 25ns to 250ns and a spot size in the range of 10um to 150um x 10um to 150um.

[0036] Melt annealing involves locally raising the temperature of a wafer surface or subsurface using an incident laser beam until it melts. In an example where the wafer surface is composed of a thin layer of silicon covering a layer of material with a lower melting temperature (e.g., germanium or germanium silicon), the wafer surface can remain solid while the subsurface material melts. The melt detection system described herein can be configured to detect melting in a surface melting process in which melting occurs on the wafer surface, and / or can be configured to detect melting in a subsurface melting process in which the wafer surface remains solid and a volume of material below the wafer surface melts.

[0037] Figure 1Schematic diagram of an example quasi-continuous wave (QCW) laser annealing system ("system") 100 that can be combined with the melt detection system of the present disclosure. As will be understood, system 100 is described and shown by way of example, and the melt detection system of the present disclosure can be used on any laser annealing system in a variety of other laser annealing systems. Certain aspects of an example implementation of system 100 are described in U.S. Patent No. 10,083,843, entitled "Laser Annealing Systems And Methods With Ultra-Short Dwell Times", issued on September 25, 2018, the contents of which are incorporated herein by reference in their entirety. References incorporated into U.S. Patent No. 10,083,843 are also incorporated herein by reference in their entirety, including: U.S. Patent No. 8,309,474; No. 8,546,805; No. 8,865,603; and U.S. Patent Application Serial No. 14 / 497,006, now issued as U.S. Patent No. 9,343,307.

[0038] The system 100 includes a wafer stage 120 that operably supports a chuck 130 having an upper surface 132. The wafer stage 120 is operably connected to a stage controller 124 and is configured to move in an XY plane and optionally in a Z direction via operation of the stage controller. The chuck upper surface 132 is configured to operably support a wafer 10 having a surface 12. In some examples, the wafer 10 may be processed and include a pattern defined by a semiconductor structure that is typically associated with various stages of manufacturing integrated circuit chips, in many cases optically deep, highly patterned multi-layer structures. In other examples, the wafer 10 may be unprocessed, without fabricated structures, and the surface 12 may be an extremely smooth mirror-like surface. As described more below, the unprocessed wafer 10 may be used with the metrology system disclosed herein to calibrate and track the performance of a laser annealing tool. The metrology system disclosed herein may also be used with a well-calibrated annealing system to perform wafer-specific annealing laser power calibration to determine, for example, a melting threshold set point power level for a unique material and surface. In an example, the chuck 130 includes a heater that heats the wafer 10 to a uniform temperature above ambient temperature. The wafer stage 120 is operably connected to a stage controller 124 .

[0039] The system 100 includes an annealing laser system 250 configured to generate a scanning laser beam 268 that forms an annealing pattern 270 ( Figure 2). The annealing laser system 250 includes an annealing laser 260 that emits an initial laser beam 262, a modulator 264 operably connected to a modulator driver, and a scanning optical system 266 that receives the initial laser beam and generates a scanning laser beam 268. In an example, the annealing laser 260 can be a QCW fiber laser that emits a scanning laser beam 268 having a wavelength of, for example, 532 nm. The foregoing is provided by way of example, and other annealing laser systems now known or later developed can be used with the metrology system disclosed herein. In an example, the modulator 264 is an acousto-optic modulator (AOM) that is used in conjunction with the scanning optical system 266 to selectively and alternately block and pass the initial laser beam 262 to control the scanning of the annealing image 270 that causes a sweeping motion of the annealing image across the wafer surface.

[0040] In some examples, the system 100 may also optionally include a preheating laser system 150 that operates in conjunction with the annealing laser system 250 and is configured to generate a preheating laser beam 168. The preheating laser beam 168 is used to reduce the wafer surface (or wafer subsurface) temperature T S Increase to below the melting temperature T M The pre-annealing temperature T PA To preheat the wafer surface 12.

[0041] The preheating laser system 150 may include a preheating laser 160 and a line forming optical system 166. The preheating laser 160 may include a diode laser, a fiber laser, or a CO 2 Laser, such as a continuous wave (CW) p-polarized 10.6 μm CO 2 Laser. In an example, the line forming optical system 166 is configured so that the preheating laser beam 168 is incident on the wafer surface 12 at a near normal angle of incidence or a larger oblique angle of incidence. In an example embodiment, the incident angle of the preheating laser beam 168 is substantially equal to the Brewster angle of the wafer surface 12, so that the adverse pattern density effects from non-uniform optical absorption are reduced or minimized.

[0042] The line forming optical system 166 is configured to receive the initial laser beam 162 from the preheating laser 160 and thereby form a preheating line image 170 ( Figure 23). The line forming optical system 166 and the scanning optical system 266 can each include lenses, mirrors, apertures, filters, active optical elements (e.g., variable attenuators, etc.), and combinations thereof. In examples, one or both of the line forming optical system 166 and the scanning optical system 266 can be configured to perform beam conditioning, for example, to homogenize and / or provide a laser beam having a selected cross-sectional shape to their respective laser beams 162 and 262. Non-limiting example optical systems suitable for performing such beam conditioning are disclosed in U.S. Pat. Nos. 7,514,305, 7,494,942, 7,399,945, and 6,366,308, the contents of which are incorporated herein by reference in their entireties. In examples, the initial laser beam 262 from the annealing laser 260 is of high quality (e.g., a substantially Gaussian beam) and is used without substantial (in some cases, without any) beam conditioning.

[0043] The system 100 also includes a scatter melting detector 280, which is configured with a scatter optical arrangement for detecting scattered light from a region of interest of the wafer surface 12, as described in more detail below, for temporally and spatially resolving the scattered light to detect the onset of melting. The scatter optical arrangement of the present disclosure includes a system based on a spatially resolved sensor or sensor array that does not detect specular reflections from a flat wafer surface, without the far-field specular reflection diffraction limit of the probe beam. An example form of a scatter optical arrangement is dark field imaging. Probe control (e.g., polarization and wavelength) and optical post-measurement selection (e.g., polarization filters, birefringent crystals, etc.) can also be used to capture the same or similar scatter information.

[0044] The example laser annealing system 100 also includes a controller 300. In an example, the controller 300 is or includes a computer, such as a personal computer or a workstation. The controller 300 preferably includes any of many commercially available microprocessors, a suitable bus architecture for connecting the processor to a memory device such as a hard drive, and suitable input and output devices (e.g., a keyboard and a display, respectively). The controller 300 can be programmed via instructions (software) contained in a non-transitory computer readable medium (e.g., a memory, a processor, or both), which cause the controller to perform various functions of the system 100 to achieve annealing of the wafer 10.

[0045] The controller 300 is operably connected to the preheating laser system 150 and the scanning laser system 250 and controls the operation of these systems. The controller 300 is electrically connected to the modulator 264 and uses the control signal SMod to control the operation of the modulator. In an example, the controller 300 includes a digital signal processor (DSP) (not shown) to control the scanning functions in the preheating laser system 150 and the scanning laser system 250. In some examples, the controller 300 can also be operably connected to the scattered melting detector 280 and the scanning optical system 266, and is configured to receive and process the melting signal SM generated by the scattered melting detector during the laser annealing process for controlling the annealing laser system 250 or the preheating laser system 150, just like adjusting the power level of the scanning laser beam 268 to achieve the desired processing conditions. In other examples, the controller 300 can be based on the computer readable storage device 1016 ( Fig.10 ) to control the power level of the annealing laser system 250. The controller 300 or a separate computing device may also be configured to control components of the scatter melt detector 280, such as controlling an image capture device (ICD) of the melt detector.

[0046] In an example of the operation of the system 100, the system controller 300 sends a first control signal S1 to the preheating laser 160, in response to which the preheating laser 160 generates an initial laser beam 162. The initial laser beam 162 is received by the optical system 166, which thereby forms a preheating laser beam 168, which forms a preheating line image 170 at the wafer surface 12. The system controller 300 also sends a second control signal S2 to the annealing laser 260, in response to which the annealing laser 260 generates an initial laser beam 262. The initial laser beam 262 is received by the scanning optical system 266, which is controlled by the control signal SS to form a scanning laser beam 268, which in turn forms an annealing image 270 at the wafer surface 12. The system controller 300 also sends a third control signal S3 to the stage controller 124 to cause the controlled movement of the stage 120 to move (scan) the wafer 10 relative to the preheat line image 170 and the annealing image 270. In the example where the chuck 130 provides wafer preheating, the system controller 300 may also send another control signal (not shown) to the chuck controller to start or control wafer preheating. Typical chuck preheating ranges from room temperature (25°C) to 400°C.

[0047] Figure 22 is a top view of the wafer 10, which illustrates an example method of scanning the wafer surface with the annealing image 270 and, in an example using the preheating laser system 150, with the preheating line image 170. The movement of the preheating line image 170 relative to the wafer surface 12 can be achieved by translating the stage 120 in a first direction, such as the y-direction, as indicated by arrow AR1, also referred to herein as the preheating scanning direction or the stage scanning direction. The portion of the wafer surface 12 associated with the preheating line image 170 represents a locally preheated portion of the wafer surface, wherein the wafer surface temperature T S Increase to the pre-annealing temperature T PA The annealing image 270 formed by the scanning laser beam 268 moves relative to the wafer surface 12 in a second direction orthogonal to the first direction, such as the x direction, as indicated by arrow AR2 and also referred to herein as the annealing scanning direction or the sweeping direction.

[0048] The scanning optical system 266 is configured to scan or sweep the annealing image 270 in the x-direction across the length of the preheating line image 170. In one example, the scanning speed of the annealing image 270 is sufficiently fast compared to the movement of the preheating line image 170 that the preheating line image is substantially stationary during the scanning of the annealing image.

[0049] Once the annealing image 270 reaches the end of the preheat line image 170, by activating the modulator 264 ( Figure 1 ) so that it blocks the transmission of the initial laser beam 262 to turn off the scanning laser beam 268 and the corresponding annealing image 270. When the scanning laser beam 268 is "off", the preheating line image 170 moves in the y direction so that the next portion of the wafer surface 12 can be scanned. In an example, the movement of the preheating line image 170 can be continuous, such as by continuously moving the stage 120 in the y direction. Once the preheating line image 170 is in place, the scanning laser beam 268 is turned back on by placing the modulator 264 in the transmission mode when the scanning optical system 266 can direct the scanning laser beam 268 and the corresponding annealing image 270 to the starting position at the first end of the newly positioned preheating line image 170. Then, the scanning of the annealing image 270 is performed on the newly positioned preheating line image 170. Figure 2 An example method of scanning substantially the entire wafer surface 12 (e.g., at least the patterned portion) by repeating the scanning method described above is shown. In other examples where the annealing system does not include a preheating laser, such as the preheating laser system 150, the preheating line image 170 is omitted, and the annealing image 270 can be similarly quickly scanned in the x-direction while the wafer 10 is moved in the y-direction by the stage 120.

[0050] Figure 3Ais a top view close-up of one of the preheat line image 170 and the annealing image 270 formed on the wafer surface 12. The preheat line image 170 has a proximal end 172, a distal end 174, and an opposing side 173. The preheat line image 170 has a long direction (dimension) extending from the proximal end 172 to the distal end 174 and having a length L1. The preheat line image 170 also has a narrow direction (dimension) measured between the opposing sides 173 having a width W1. In the example, the length L1 is in the range of 5 mm to 20 mm, with an exemplary length L1 in the range of 7 mm to 12 mm. Also in the example, the width W1 is in the range of 50 μm to 200 μm, with an exemplary width W1 being 150 μm. In the example embodiment, the preheat laser beam 168 ( Figure 1 ) has a Gaussian intensity distribution in the scan direction (e.g., y direction) and a relatively flat top distribution in the long (cross-scan) direction (e.g., x direction). The beam width W1 can be defined as 1 / e of the Gaussian distribution 2 The intensity value or the full width at half maximum (FWHM) of a Gaussian distribution.

[0051] The annealing image 270 overlaps a portion of the preheating line image 170, and the overlapping area is referred to herein as the scan overlap region (SOR). The annealing image 270 has a long dimension of length L2 and a narrow dimension of width W2. In the example shown, the annealing image 270 has a substantially Gaussian intensity distribution in the x-direction and the y-direction. The long dimension L2 of the annealing image 270 is in the direction of the short dimension W1 of the preheating line image 170. In the example, the length L2 is in the range of 100 μm to 500 μm, while the width is in the range of 10 μm to 50 μm, and in some examples, the width is in the range of 15 μm to 20 μm or in the range of 16 μm to 18 μm. The scanning direction AR2 of the annealing image 270 is perpendicular to (orthogonal to) its long direction. The scanning direction AR2 is also referred to as the annealing scan or sweep direction, and is substantially orthogonal to the preheating scan direction AR1. The width W2 of the annealing image 270 defines the width of the scanning overlap region SOR in the annealing scanning direction AR2. The rapid scanning of the annealing image 270 in the scanning direction AR2 causes the SOR to form an annealing illumination line 272 having substantially the same size as the preheating line image 170, which is sequentially moved in the y direction (preheating scanning direction AR1) along the wafer surface 12 by the movement of the stage 120 in the y direction.

[0052] In the example, Figure 3AAs shown in FIG. 1 , the length L2 is substantially greater than the width W1 (e.g., between 2 and 4 times greater), so that the end of the annealing image 270 extends beyond the side 173 of the preheating line image 170. This makes it relatively easy to align the preheating line image 170 and the annealing image 270 to define the scan overlap region SOR. This configuration utilizes the central high-intensity portion of the annealing image 270 to increase the local preheating of the wafer surface provided by the preheating line image 170 to increase the wafer surface temperature T S Up to melting temperature T M .

[0053] In one example, the dwell time t of the scan overlap region SOR is d At 10ns≤t d ≤500ns, and in another example within 25ns≤t d For a width W2 = 15 μm and a dwell time of 25 ns, the scanning speed of the annealing image 20 and thus the scanning speed of the overlap region SOR is v s =(W2) / t d =600m / s. For a dwell time of 250ns t d , the scanning speed is v s =60m / s. For a dwell time of 500ns t d , the scanning speed is v s =30m / s. For a dwell time of 10ns t d , and the scanning speed is 1500 m / s. In one example, the scanning optical system 266 is configured to provide these speeds or any speed therebetween.

[0054] Figure 3B is a top view of another example implementation of system 100 with preheat laser system 150 omitted. Annealing laser system 250 is designed and configured to reduce the wafer surface temperature T S The annealing image 270 is raised to the desired annealing temperature. The rapid scanning of the annealing image 270 in the scanning direction AR2 generates the annealing illumination line 272, which is sequentially moved in the y direction (arrow AR1) along the wafer surface 12 by the movement of the stage 120 in the y direction. In the example, the length L1 of the annealing illumination line 272 is in the range of 3 mm to 12 mm, the width W2 of the annealing image 270 is in the range of 10 μm to 50 μm, and the length L2 of the annealing image 270 is in the range of 100 μm to 500 μm.

[0055] Figure 3C 2 is a top view of a portion of the wafer surface 12 showing three instances in time (labeled a, b, and c) of an annealing image 270 traveling along an annealing illumination line 272 in a scan direction AR2. Figure 3C A molten pool 310 is conceptually shown that has been formed by the scanning laser beam 268, wherein a localized region of the wafer surface 12 has melted and partially or completely transformed from a solid phase to a liquid phase, thereby creating an interface 312 between the solid and liquid phases. In the example shown, the size of the molten pool 310 increases along the scanning direction AR2, which may be due to the increase in optical power density of the laser beam 268 across the annealing illumination line 272 through the annealing image 270. The phase change of the wafer material within the molten pool 310 is a first-order phase change that causes discontinuities in both the density of the wafer material and the form of atomic or molecular interactions. The phase change results in a significant change in the refractive index of the material due to the different electromagnetic interactions in the two different phases (solid and liquid) of the material. In the example, the refractive index of the liquid phase within the molten pool 310 is substantially higher than the refractive index of the solid phase wafer material outside the molten pool 310, for example, for typical IC semiconductor materials, the refractive index is on the order of about 100% to 300% higher.

[0056] The interface 312 between the molten pool 310 and the solid phase material surrounding the molten pool acts as the main scatterer of the incident light, wherein the magnitude of the wide field structure factor increases with the radius r of the molten pool 310. l The scatter imaging systems disclosed herein are designed and configured to detect scattered light that occurs at the beginning of melting and when the molten pool 310 initially begins to form. The intensity of the scattered light increases rapidly and nonlinearly as the size of the molten pool 310 increases, and the scatter imaging systems of the present disclosure can be configured to detect the increase in scattered light intensity caused by the increase in the extent of the melted wafer material.

[0057] In the solid phase below melting, the relationship between the intensity of the reflected light signal and the material temperature can be approximated as a roughly linear γT, where γ is a scaling factor and T is the material temperature. For a melt pool 310 that is smaller than the wavelength of the incident light (e.g., the wavelength of the laser beam 268), the scattering intensity of the melt pool 310 and the interface 312 is approximately αV 4 / 3 , where α is a scaling factor and V is the volume of the melt pool or the fourth power of the melt pool radius, where α>>γ. For a melt pool 310 that is significantly larger than the wavelength of the incident light, the radius r l The discontinuity in the melt pool is the main scatterer into the wide field, with a size of approximately αV 2 / 3 Therefore, the overall scaling relationship between increasing optical power and melt pool size is highly nonlinear and may eventually saturate the scatter imaging system. Figure 3CIn the example shown in , the initial formation of the melt pool 310 will cause a sharp discontinuity in the light detected by the scattered melt detector 280 due to the sudden increase in scattered light emitted from the area surrounding the melt pool. As the size of the melt pool 310 increases (e.g., the size of the melt pools 310b and 310c compared to the melt pool 310a), the intensity of the light detected by the scattered melt detector 280 will increase nonlinearly by the order of the fourth power of the increased radius of the melt pool, which may quickly saturate the melt signal SM generated by the melt detector. The scattered melt detector 280 and the scattered imaging channel disclosed herein are designed and configured to be highly sensitive to the onset of melting, wherein the discontinuous increase in the intensity of the light captured by the melt detector occurs essentially instantaneously at the onset of melting, thereby causing the intensity of the light signal to increase by several orders of magnitude.

[0058] During the annealing process, the scattered melt detector 280 can be used to capture light from the area surrounding the annealing image 270, including light diffracted, reflected, or refracted by optical structures in the annealing image area. In an example, the scattered melt detector 280 generates a melt signal SM representative of the detected light and sends the melt signal to the controller 300. In an example, the controller 300 receives the melt signal SM and can use the signal to create a feedback loop that controls one or more characteristics of the annealing laser system 250 and, in some examples, one or more characteristics of the preheat laser system 150, such as power level, so that the wafer surface temperature T can be controlled. S In some examples, the scatter melt detector 280 can be used to calibrate and track the optical performance of the annealing laser system 250. And in some examples, the scatter melt detector 280 can be used to develop a wafer-specific laser power calibration that provides a melting threshold laser power set point for a set of predetermined annealing process conditions.

[0059] Figure 4A A side view of an example implementation of a scattering melt detector 280 is shown. In the example shown, the melt detector 280 receives light from the wafer surface 12 along a scattering detector path 402 that has an angle α1 relative to the surface normal N that is different from the angle α2 of the scanning laser beam 268. In the example shown, the scanning laser beam 268 is used as a probe for scattering thermometry measurements and as an annealing laser beam. In other examples, a light source other than the scanning laser beam 268 can be used as a probe. Utilizing the scanning laser beam 268 as a light source for scattering measurements provides the benefit of a simpler arrangement because it does not require an additional light source and because it only illuminates a field of view around a small annealing image 270 that can travel across the wafer surface 12 quickly (e.g., up to about 1 km / s).

[0060] The scanning laser beam 268 has an incident angle α2 different from the angle α1 relative to the surface normal N, and forms an annealing image 270 on the wafer surface 12. The angle α1 of the scatter detector path 402 is designed so that the specular reflection 268R of the scanning laser beam 268 from the surface 12 of the wafer 10 does not enter the scatter detector path 402, thereby enabling scatter observation by the melt detector 280.

[0061] The melt detector 280 includes an optical device 404 and an image capture device (ICD) 406. The ICD 406 includes or is electrically connected to at least one pixelated two-dimensional CCD or CMOS focal plane array (FPA) and associated electronic devices including a processor and a memory unit for storing captured images as known in the field of image capture devices. The optical device 404 is configured to image the wafer surface 12 onto the FPA. In an example, the ICD 406 is configured to capture the scattering image at an image frame capture rate of, for example, about 50us, over a relatively long exposure time frame compared to the dwell time of the laser beam 268, such that at least one complete sweep of the annealing image 270 across the annealing illumination line 272 is captured in a single image frame.

[0062] Optics 404 may include one or more lenses, mirrors, filters, gratings, apertures, or other components. Light collected along scatter detector path 402 (e.g., scattered light) is collected by optics 404 and, in some cases, reflected and / or filtered, and imaged onto the FPA of image capture device 406. The field of view (FOV) of optics 404 may include the entirety of wafer surface 12 or a portion thereof. For example, the FOV of optics 404 may be in scanning direction AR2 (see FIG. Figure 3B ) can be approximately equal to the length L1 of the annealing illumination line 272, or the width in the direction AR2 can be approximately 5% to 50% greater than the length L1 of the annealing illumination line. The FOV of the optical device 404 is in the stage scanning direction AR1 (see Figure 3B ) may be the same as the width of the FOV in the annealing image scanning direction AR2, or may be greater or less than the width of the FOV in the scanning direction AR2. In an example, the width of the FOV of the optical device 404 in the stage scanning direction AR1 is at least twice the diameter or outer extent of the annealing image 270 in the stage scanning direction, so that portions of the wafer surface 12 below melting and outside the annealing image are captured in the same image as portions within the annealing image. The FOV of the optical device 404 in the scanning direction AR2 may be at least 10% greater than the length L1 of the illumination line 272, and in some examples, may be at least 20% greater. The spatial resolution of the ICD 406 may be 10um / pixel to 50um / pixel, and in some examples is approximately 30um / pixel.

[0063] As shown, a light source (here, an annealing laser system 250) generates a scanning laser beam 268 that forms an annealing image 270 on the wafer surface 12. A first portion of the light of the scanning laser beam 268 is specularly reflected by the wafer surface 12 and does not reach the melt detector 280. When the temperature of the wafer surface 12 along the annealing illumination line 272 is below the melting temperature and the wafer material is in a solid phase, the scattered melt detector 280 can detect a certain amount of background light, such as light from photoluminescence and scattered light due to, for example, defects in the wafer surface 12 (e.g., small variations in thickness or large-scale defects such as scratches or dust), or in the case of processed wafers, light diffracted, reflected and / or refracted by optical discontinuities in the wafer (e.g., manufacturing patterns in the wafer surface or sub-surface). Therefore, in the case of an unprocessed and highly polished wafer 10, the melt detector 280 can detect little or no light along the scattered detector path 402, and the field of view of the melt detector 280 is substantially dark. In the case of processed wafers, a certain degree of scattered light associated with the sub-molten solid phase conditions may be captured.

[0064] When the power density of the scanning laser beam 268 is increased to the melting threshold energy density E m When the wafer material at the wafer surface 12 or subsurface undergoes a phase change, a volume of molten liquid phase material is generated, which is approximately located in the annealing image 270. The reflectivity of the molten liquid phase material is substantially different from the reflectivity of the solid phase material. The interface between the liquid phase and the solid phase of the newly formed volume of liquid (e.g., interface 312 ( Figure 3C )) creates a new optical discontinuity in the wafer surface that strongly scatters light into a 2π angular hemisphere above the melted region of the wafer. The reflection observed in the melted region (e.g., melt pool 310) is diffuse and in some examples approaches Lambertian reflectivity. The intensity of the resulting imaging thermoreflectance signal of the melted region will have a significant increase compared to the solid phase, such as an increase on the order of 50%. In contrast, the change in intensity of the scattered imaging thermoreflectance signal along the scatter detector path 402 due to the material phase change from solid to liquid is extreme, such as on the order of 100,000% higher in intensity, which provides extremely high sensitivity for detecting the onset of melting.

[0065] In an example, the ICD 406 is for a time length greater than the dwell time of the annealed image 270 and at a corresponding frequency. The scattering image is captured in the scanning direction AR2. The scattering melting detector 280 analyzes time along the annealing laser scanning direction AR2, where the annealing image 270 moves at a speed v, where x=v*t. In this way, the captured scattering image can be used to decompose the scattering signal data along the x direction (scanning direction AR2) into bandwidths of In the case where the scatter image frame includes an entire sweep or multiple sweeps of the annealing image 270, the scatter melting detector 280 can be used to measure the process uniformity across the entire annealing image sweep strip in a single image frame. In an example, the scatter melting detector 280 is configured to capture the process uniformity for all points x=v·(t±t d ) is a spatially resolved scattering pattern used to measure the frequency The melting behavior and uniformity under annealing conditions are highly practical and useful for the optimization of the annealing laser system 250.

[0066] Figure 4B Another example implementation of the scatter melting detector 280 is shown, in which a detection light source 410 separate from the annealing laser system 250 is used as a probe for scattering measurements. The example shown has Figure 4A , including a detector including an optical device 412 and an ICD 406. The optical device 412 may include the same or similar components as the optical device 404. The detection light source 410 may be a pulsed light source that emits a detection light 420 that is incident on the wafer surface 12 in an area that overlaps with the annealing image 270. Figure 4A As in the example shown in Figure 4B The scattered melt detector 280 in FIG. 4 has a scattered detector path 416 such that the optical device 412 does not capture the specular reflection 420R of the probe light 420 or the specular reflection 268R of the scanning laser beam 268. In the example shown, the melt detector 280 receives light from the wafer surface 12 along the scattered detector path 416, which has an angle α1 different from the angle α2 of the scanning laser beam 268 or the angle α3 of the probe light 420 relative to the surface normal N. The probe light source 410 can be a diode or an optical fiber connected to a laser source, and can emit light of a narrower wavelength, such as green light, blue light, NIR, or light in the telecommunication band, such as between 1260 nm and 1675 nm. The optical device 412 can be configured to filter out wavelengths of light other than the probe light 420. The probe light source 410 may be configured to emit pulses of probe light 420 at a greater frequency or shorter duration than the frame rate of the ICD 406 so that discrete portions of the anneal illumination line 272 may be imaged.

[0067] Figure 5A and Figure 5BTwo alternative optical arrangements 500, 501 for scatter imaging are conceptually shown. Arrangement 500 includes an objective lens 502 and an image forming lens 504 for forming a scatter image of a region of wafer surface 12 including melt pool 310 on an ICD, such as an FPA of ICD 406. Arrangement 500 corresponds to Figure 4A and Figure 4B , where a scanning laser beam 268 ( Figure 4A ) or a separate probe light source (e.g. Figure 4B 4 (probe light 420 in the example of FIG. 4 ) is incident on an object, such as melt pool 310. In terms of Fourier optics, due to the spatial position and numerical aperture of lenses 502 and 504, zero-order light 530 (non-scattered light) does not reach objective lens 502, so that the image formed on the FPA comes from high-order diffraction intensity 532 scattered by melt pool 310 and / or other optical scatterers or discontinuities on the surface or sub-surface of the wafer.

[0068] Figure 5B An alternative optical arrangement 501 is shown in which at least one opaque aperture 520 is used to block zero-order light 530 (non-scattered light) from reaching the FPA of an ICD, such as ICD 406, so that the image formed on the FPA by the objective lens 510 and the image forming lens 512 is derived from higher-order diffraction intensity 532 scattered by the melt pool 310 and / or other optical scatterers or discontinuities on the surface or sub-surface of the wafer. Figure 4A Scattering melting detector 280 or Figure 4B The scatter melting detector may be modified to have an optical arrangement 501 that utilizes at least one opaque aperture 520 to form a scatter image.

[0069] Fig. 6A The data captured in an image frame by the ICD 406 of the scatter melt detector 280 during a sweep of the anneal image 270 when the wafer surface 12 is below melting is conceptually and graphically illustrated. Figure 6B Conceptually illustrated is the change in data captured in the image as the optical power of the annealing laser system 250 is increased and the temperature of the wafer surface 12 exceeds the melting threshold and the wafer material begins to melt.

[0070] When below melt, the image captured by melt detector 280 is a result of probe intensity scattered by the roughness of the wafer and, in some cases, by resonant scatterers embedded in wafer surface 12. In the thin film approximation, due to the height difference The induced roughness imposes itself as a random holographic phase grating Take itself as imposed on the electric field. For a uniform wafer manufacturing process, the fluctuating power spectrum is The square of the Fourier transform of Usually in excess of is non-zero, and will therefore be uniformly Scattered into a hemisphere above the wafer plane. Fig. 6A This weak and relatively flat response that may occur below melting is conceptually shown.

[0071] For processed and highly patterned wafers 10, some material manufacturing processes include sparse optical scatterers in the film, which may produce random images that may provide false melting signals. However, when the image data from the melt detector 280 is averaged across the compiled image frames, the false melting signals below melting can be distinguished from the true melting signals because the high intensity signals appear uniformly in the compiled image frames across the entire scan of the annealing illumination line 272 as the optical power density of the annealing laser 250 increases. Various aspects of the present disclosure include compiling a set of high resolution images of the wafer 10 below melting to sample the shape of the illumination probe beam, such as the scanning laser beam 268 or the probe light 420 from the probe light source 410. The image data below melting can then be distinguished from the image data above melting, which will include the area of ​​radius r melt <r beam 310 and the associated interface 312. The shortened absorption length of the probe beam in the liquid phase portion of the wafer material in the melt pool reduces scattering caused by subsurface optical discontinuities in the processed wafer, thereby simplifying the scattered optical response when the melting threshold is exceeded, which further helps detect the onset of melting.

[0072] Figure 6C An image frame of test data from an example implementation of the system 100 for identifying melting using the amplitude of captured light is shown. Figure 6C An example of a system that is not properly optimized is shown, where the start (top of the image) and end (bottom) of the anneal image scan are both above melt, and the dark area in the middle is just below melt. The optical power density of the anneal laser system 250 is not properly calibrated, causing undesirable fluctuations in optical power that result in the start and end of the sweep being above melt and the middle of the scan being below melt.

[0073] FIG. 7A to FIG. 7C Test data from a melt threshold calibration for a specific processed wafer type having a unique material stack and at a specific chuck temperature is shown. FIG. 7A to FIG. 7C One or more sweeps of three different strips from a swept laser beam 268 are shown, where a strip is a series of consecutive sweeps. Fig. 7A In the embodiment, the power of the annealing laser system 250 is set to 132W. Figure 7B In the next band, the power level is increased to 135W and Figure 7C In the third band in FIG. 1 , the power is increased to 138 W. The arrows point to the locations in the image where the signal is saturated, indicating that the high light intensity in these areas of the image is caused by a sharp increase in scattered light due to melting of the wafer material. FIG. 7A to FIG. 7C The images in FIG. 1 also show low-intensity artifacts caused by the inherent roughness and non-uniformity of the processed wafer (some of the low-intensity artifacts are outlined with dashed circles in each figure). However, the high-intensity locations corresponding to the melted regions of the wafer have a greater spatial density and a size that is many orders of magnitude larger than the background light below the melt in the scattering image, and stand out strongly from the background scattering. FIG. 7A to FIG. 7C An example is shown where the melting threshold can be calibrated for a specific processed wafer type with a unique material stack by increasing the laser power and studying the melt metrology.

[0074] Figure 8 Shown from FIG. 7A to FIG. 7C 4 shows additional data from the same calibration process. The Y-axis is the cumulative intensity of light captured by the FPA of the ICD 406. More specifically, the Y-axis is the sum of all grayscale values ​​of all pixels in the image, where, as is known in the art, each pixel of the FPA records the intensity level of the incident light on a grayscale between 0 (black) and 1 (white). The X-axis is the annealed image sweep number. Figure 8 A first plurality of scans of the annealing image at 132 W is shown, and the sum of the grayscale values ​​is a first value that is low and represents sub-melting conditions and background light scatter captured by the FPA of the ICD 406 . Figure 8 An increase in grayscale values ​​is shown as the power is increased to 135 W (which is determined to be the melting threshold), and then the intensity of light captured by the ICD 406 increases dramatically as the laser power is increased to 138 W (which is determined to be above the melting threshold), with a liquid volume of wafer material forming consistently over a larger proportion of the annealing image scan.

[0075] Fig. 9A and Fig. 9B Test data for a well optimized system is shown with the power of the annealing laser system 250 set at what is determined to be the melting threshold of the semiconductor wafer. Fig. 9A and Fig. 9B The same data in two different formats is shown. Each data is a collection of distribution analysis from many image frames in the direction of high-speed spot sweep. Fig. 9A In , the Y-axis is intensity and the X-axis is the position along the annealing image sweep, where the light intensity profiles of multiple consecutive sweeps overlap. Fig. 9B, the same sweep intensity distribution is shown on a three-dimensional color map, where the Y-axis is the position in the annealing image sweep direction, the X-axis is the position in the image frame and stage scan directions, and the color indicates the intensity of the light signal. Fig. 9B is a mosaic of multiple image frames captured using the scatter melting detector 280 .

[0076] Using knowledge of the velocity of the anneal image and the spatial resolution of the ICD, positions in the image frame can be converted to instances in time and specific positions along the anneal image sweep. By way of example, if the velocity of the anneal image sweep is 500 m / s and the spatial resolution of the ICD is 30 um / pixel, then each pixel represents 60 ns in time, and an image of an anneal image sweep with a 50 ns exposure can be decomposed into 60 ns time increments. More generally, the scatter melting detector 280 (e.g. Figure 4A The example shown) can be used to spatially resolve all points x=v·(t±t d ) to measure the frequency The melting behavior and uniformity under the condition of annealing laser 250 is practical and useful for optimization. In the example of using a pulse probe separated from the processing laser beam, such as in Figure 4B In this case, higher frequency data can be obtained.

[0077] In some examples, there may be less variability in the optical power density of the scanning laser beam 268 across the sweep of the annealing image 270. Therefore, a method of calibrating the annealing laser system 250 may include analyzing the melt signal from the scattered melt detector 280 at a specific point in the sweep across multiple sweeps to eliminate any effects from variations in optical power along the sweep in the calibration process. By way of example, Fig. 9B Position 902 in FIG. 1 shows a particular sweep position at which a melt signal from multiple sweeps at position 902 may be analyzed. For example, the power level of the annealing laser system 250 may be adjusted incrementally, such as by a fraction of a percentage of the total power, to identify a percentage of the sweep of the annealing image where melt is detected. For example, for a given chuck temperature T ch and residence time t dwell , there is a melting threshold energy density E m (T ch ,t d ), and the actual energy density transferred is E m ±δ E Since the power occasionally reaches the melting threshold, the power E m -δ E Melting is rarely detected at E above the range of this process. m +δ EBy changing the power of the scanning laser beam 268 from below E m -δ E Change to above E m +δ E And analyzing the percentage of time that melting is detected at a particular sweep position (e.g., position 902), E can be independently identified from energies below which melting is never detected and energies above which melting is present in all or substantially all sweeps. m and δ E In an example, during the annealing process, the power level of the scanning laser beam 268 is incrementally varied across the annealing image sweep. Thus, the foregoing calibration process may be repeated at multiple sweep positions to determine the melting threshold power level set point across the entire sweep of the annealing image.

[0078] Controller

[0079] Fig.10 1 is a block diagram illustrating the physical components of one example implementation of one or more computing devices 1000 that may be used with the annealing system of the present disclosure, including for providing the functionality of the controller 300, the stage controller 124, and the melt detector 280. Shown is at least one processor 1002 coupled to a chipset 1004. A memory 1006, a network adapter 1008, and a communication module 1010 are also coupled to the chipset 1004. Peripheral devices 1012 and a display 1014 are coupled to the computing device 1000. In another embodiment, the memory 1006 is directly coupled to the processor 1002. A storage device 1016 is also coupled to the chipset 1004.

[0080] The storage device 1016 may be any non-transitory computer readable storage medium, such as a hard drive, a compact disk read only memory (CD-ROM), a DVD, or a solid state storage device. The storage device 1016 may include any software or data that may be stored in a computer storage device that communicates with an annealing system known in the art of laser annealing systems. Fig.10 Also shown are a non-limiting example list of applications 1020 that may be stored on the storage device 1016 , as well as a melting threshold 1022 and an annealing laser melting calibration set point 1024 .

[0081] In the example shown, the application 1020 includes an ICD control application 1030 and an image processing application 1032, which include instructions for controlling an ICD of a scatter melt detector (e.g., ICD 406 of scatter melt detector 280). The ICD control application 1030 may include instructions for controlling functions such as frame rate and shutter speed and for processing signals generated by the FPA of the ICD. The image processing application 1032 may be configured to execute one or more image processing algorithms to analyze light collected from a scatter detector path having a FOV including an annealed image.

[0082] As described herein, when an annealing image, such as annealing image 270, causes the material on or below the wafer surface 12 to begin to melt, the optical properties of the material change substantially, which causes the intensity of the light collected by the scattered melt detector to increase significantly. The image processing application 1032 can be configured to use any of a variety of image processing algorithms to identify the increase in the intensity of the light collected by the ICD. For example, one or more of the following: a fitting algorithm, an edge detection algorithm, an eigenbase decomposition, a feedforward classifier, or detecting any intensity in the captured image frame that exceeds a melting threshold, or an intensity value corresponding to a light scattering effect caused by an interface between a liquid phase and a solid phase of the wafer material. In an example, the image processing application 1032 can be configured to identify an increase in the intensity of light collected by the ICD in an area smaller than the annealing image 270 formed by the processing beam (e.g., laser beam 268). In an example, the image processing application 1032 can compare the light intensity to the melting threshold 1022, which can include a threshold corresponding to the light intensity captured by the scattered melt detector 280 for different sizes of melt pools, or a threshold that associates the light intensity with an intensity and laser power level below melting. Figure 3C As an example, the image processing application 1032 can be configured to detect the onset of melting and the formation of the molten pool 310 and the corresponding interface 312 by detecting the intensity of light captured along the scatter detector path 402 or 416 that exceeds the relative scatter intensity of the surrounding detection beam. In an example, the threshold can be normalized to the sub-melting scattered beam light intensity distribution. The image processing application 1032 can also be configured to analyze the spatial density or spatial range of the image frame including light intensities exceeding the melting threshold in order to distinguish between true melting signals and discrete false signals caused by non-melting scatterers. The image processing application 1032 can also be configured to compare the spatial location of the high intensity signal in the image frame with the known location of the moving annealing image 270 and / or the location of the annealing illumination line 272 to verify whether the high intensity signal overlaps or is in close proximity to the annealing image or the annealing illumination line.

[0083] Fig.11A portion of an example image frame 1100 captured by the ICD 406 during an annealing process is conceptually illustrated. Fig.11 A grid of pixels 1102 and a portion of illuminated lines 272 are shown. Image frame 1100 includes Fig.11 The plurality of columns 1104 (two columns marked as 1104a and 1104b) aligned with the stage scanning direction marked as y in FIG. Fig.11 A plurality of rows 1106 (a row labeled 1106a) are aligned with the annealed image sweep direction labeled x in FIG. 1104. Cross-hatching is included in a column of pixels to illustrate an example of varying gray levels of pixels along a given column 1104.

[0084] Figure 12 to Figure 14 An image processing application such as image processing application 1032 ( Fig.10 ) may be configured to perform an example of a melt detection algorithm. Fig.12 An example method 1200 for generating a reference image below melting and associated parameters is shown. At block 1203, the method 1200 may include annealing a wafer below melting, capturing an image frame with a scatter melt detector, and recording the annealing laser power level. In an example, the laser power may be measured using an on-board detector (OBD) that generates a voltage V corresponding to the optical power density of an annealing laser beam, such as the annealing laser beam 268. ref In other examples, any other sensor technology or technique for monitoring laser power may be used. Block 1203 may also include receiving wafer type information, such as a unique identification number corresponding to a particular wafer design. In block 1203, capturing an image frame such as image frame 1100 ( Fig.11 Thus, block 1203 includes performing an annealing process at an annealing laser power level below the power level that would melt the wafer material so as to collect below-melting image data using a scatter melt detector such as scatter melt detector 280, which can be used as a reference for data during the melting process to detect melting.

[0085] At block 1205, method 1200 may include creating a sub-melted reference image I from the captured image frame. ref , which may include averaging pixel values ​​for a plurality of image frames, excluding any image that includes a wafer edge in the image. At block 1207, the below-melt reference image is processed to generate a plurality of below-melt one-dimensional stage scan direction intensity profiles. Block 1207 may include running a one-dimensional peak detection algorithm or fitting algorithm on one or more columns 1104 of pixels in the stage scan direction, and generating parameters, such as amplitude A, for each one-dimensional intensity profile. ref (x), width w ref(x) and the center of gravity or maximum position y 0,ref (x), where, in this example, the width w ref (x) is the distance from y 0,ref (x) ±y distance, and the full width is 2·w ref (x). Here, y refers to the stage scanning direction, and x refers to the sweep direction (see Fig.11 ). Thus, block 1207 returns the intensity distribution for each column 1104 or a group of columns along the y direction. Block 1207 may also include saving the multiple distributions as a swept distribution.

[0086] At block 1209, a region of interest (ROI) of the reference image below the melt may be identified, referred to herein as ROI ref , which corresponds to the spatial position of the illumination line 272 in the image. The ROI can be determined by identifying pixels with an intensity above the minimum value within the swept distribution ref In this example, ROI ref is determined based on the sweep profile parameters determined in block 1207, for example, a pixel in the reference image having an amplitude greater than black plus a number of gray levels corresponding to the background outside the annealed image (e.g., two gray levels on the scale of 255 gray levels of the FPA) and having a position at y=y 0,ref (x)±2·w ref (x) within the y position of the pixel. At block 1211, method 1200 may include, for example, by ref The grayscale values ​​of the pixels within are added and divided by column 1104 (see Fig.11 ) to create the average one-dimensional stage scan direction intensity distribution.

[0087] Fig.13 An example method 1300 of a melt detection algorithm is shown, wherein melting is detected based on nonlinearity of amplitude in an image frame. At block 1303, method 1300 may include annealing a wafer below a melt threshold, equal to a melt threshold, or above a melt threshold, capturing an image frame using a scatter melt detector, and recording a value referred to herein as V melt, which indicates the power level of the annealing laser beam when the image was captured. Block 1303 may also include receiving wafer information such as a unique ID so that appropriate below-melt reference data obtained in method 1200 can be referenced. At block 1305, method 1300 may include creating an average image from the captured image frames by averaging all image frames of a sweep performed at the same laser power level (excluding any frames that include an edge of the wafer), and saving the average image. At block 1307, a melt detection image I is generated that references the average image created in block 1305 to a corresponding below-melt reference image of the same wafer type. data In an example, the pixel values ​​and corresponding laser power values ​​from the average image of block 1305 may be referenced to the image as follows: Fig.12 The pixel values ​​and corresponding laser powers in the reference image below the melt generated at block 1205 are: Among them, I data is the pixel value of the average image generated at block 1207, I ref is the pixel value of the reference image below the melting point, and V ref and V melt is the corresponding OBD signal value. In block 1309, the melt image value may be compared to a threshold value (e.g., 1.1) to determine whether any melting has occurred in the image. For example, the melt image ROI may be ref The pixel values ​​within are averaged and compared with the threshold.

[0088] In addition or in lieu of performing block 1309, at block 1311, the method may include applying a one-dimensional distribution analysis of the melt detection image generated at block 1307 to identify a narrow peak having a width in the stage scan direction that is smaller than the width of the laser beam. At block 1313, the width w(x) of the identified peak is determined and compared to the width w(x) of the reference image below the melt. If the identified peak has a smaller width, e.g., smaller than the reference image w(x) below the melt, then the peak may be compared to the width w(x) of the reference image below the melt. ref (x) is less than 50% of the width of the annealing image, then it is determined that melting has occurred. The foregoing is based on the energy distribution of the laser beam and assumes a Gaussian distribution in the stage scanning direction y, which causes melting to occur only in a narrow area of ​​the larger annealing image 270. Therefore, a detected intensity peak whose width in the stage scanning direction (orthogonal to the scanning direction) is less than the width of the annealing image in the stage scanning direction indicates a localized melt region or melt pool within the annealing image. By way of example, refer to Fig.11, pixels 1102a to 1102e along column 1104 include cross-hatching indicating different amplitudes of the melt detection image created at block 1307. For example, if pixel 1102c or 1102b to 1102d has an amplitude that is larger than the amplitude of surrounding pixels and, for example, is above a threshold, and the width of pixel 1102b to 1102c in stage scan direction y is the same as annealing illumination line 272 or the corresponding ROI ref If the width of is narrow enough compared to the width of, then method 1300 can determine that melting has occurred. Steps 1311 and 1313 may be most useful for processed wafers with high scatter and can be implemented using a scatter melting detector with high resolution optics.

[0089] Fig.14 Another example algorithm for detecting melting based on melting statistics is shown, method 1400. In block 1403, method 1400 may include annealing the wafer below a melting threshold, at a melting threshold, or above a melting threshold, capturing an image frame using a scatter melting detector, and recording an OBD voltage signal V melt At block 1405, the ROI of the image frame (determined at step 1209) is calculated ref In an example, block 1405 may include calculating a fractional standard deviation, which is a measure of the standard deviation of the pixel values ​​within the ROI. ref The pixel value within the ROI ref The standard deviation of the ratio of the pixel values ​​within the ROI to the mean. A large standard deviation indicates a ref The wide variability of the intensity values ​​within , indicates that the laser power is set at the melting threshold, where there is a large variability in pixels above or below melting, e.g. Fig. 9B In the example shown in . At block 1407 , the calculated standard deviation is compared to a threshold value to determine the presence of melting. Method 1400 may be most useful for wafers with minimal scatter, such as bare silicon wafers.

[0090] Methods 1200, 1300, and 1400 may be selectively used as a melt detection subroutine for a laser annealing process depending on the specific wafer type and application, including calibrating the laser system and determining a laser power calibration table or curve for a specific combination of process conditions, including wafer type, chuck temperature, and dwell time. Parameters and reference data such as V ref ROI ref and V melt , one-dimensional stage scan direction intensity distribution below melting, etc. can be stored in a memory, such as the storage device 1016, and can be accessed by the image processing application 1032 to execute any of the image processing algorithms disclosed in this document.

[0091] The computing device 1000 with the annealing laser control application 1034 can be configured to control one or more parameters of the preheat laser system 150 and / or the annealing laser system 250 to achieve a desired processing condition at or above the melting threshold. The annealing laser control application 1034 can also be configured to control the power level of the annealing laser system 250 according to the annealing laser melt calibration set point 1024. The annealing laser melt calibration set point 1024 can specify a laser power level set point for achieving a sub-melting, melting threshold, or over-melting threshold annealing condition for a specific set of processing conditions (e.g., for a specific chuck heater temperature, dwell time of the annealing image, and type of wafer 10). As described herein, the scatter melt detector 280 can be used to perform a melt calibration of the annealing laser system 250 to determine the annealing laser melt calibration set point 1024.

[0092] In an example, the ICD 406 may have a sweep frequency f that is less than the annealed image. sweep The FOV of the scatter melt detector 280 may include at least one anneal illumination line 272 (i.e., at least one sweep of the anneal image), and in some cases may include multiple anneal illumination lines (multiple consecutive sweeps of the anneal image). Thus, a single image captured by one exposure of the ICD 406 may include at least one sweep of the anneal image 270, and in some examples, multiple sweeps of the anneal image 270. The image processing application 1032 may utilize predetermined information about the known intensity distribution of the material phase change, and extract one or more statistical correlation functions from the captured intensity of multiple sweeps from one or more image frames to characterize the consistency of the melt process, or act as a multi-sampler on the device wafer, or act as a spatially locked frequency to simplify melt detection using fast Fourier transforms.

[0093] In the present disclosure, the scatter melting detector includes a probe such as a probe light source 410 ( Figure 4B ), the application 1020 may also include a probe control application 1036 for controlling the intensity, phase, and / or frequency of the pulsed radiation emitted by the probe light source 410 and / or the pulse timing of the radiation having a varying length or period emitted by the probe and / or the sensor exposure timing, such as the exposure timing of the ICD 406. The probe control application 1036 may include a program for aligning the probe and the ICD with the scanning frequency f through a common clock. sweep The pulse frequency f of the probe 410 is determined based on the sweep frequency, sweep phase, and aspects of the wafer material phase change process to be measured. Probe and pulse phase φ probe and ICD exposureexposure In one example, f Probe and f exposure < <f sweep , so that each ICD exposure n probes is 1. In one example, the frequency ratio R=f sweep / f Probe can be any integer such that statistics can be extracted about the stability of the phase change process. In one example, there may be no f Probe , instead, a random distribution of pulses at known times can be collected for extracting broadband statistics. In some examples, f Probe It can be a sweep The reasonable beat frequency is used to determine and optimize the sweep uniformity. In one example, the detection pulse frequency f is selected Probe , so that f Probe Synchronizing with the sweep of the annealing image 270 in the x-direction so that a subset of synchronized moments in a set of annealing image sweeps are probed with a single pulse, wherein multiple pulses are collected into a single image frame by the ICD 406, so that high bandwidth coherence of the phase change can be extracted from the contrast of the melted region. In some examples, the probe 410 is configured to emit light pulses having a duration of 3 ns to 20 ns, and in some examples, a duration of 5 ns to 15 ns, and in some examples, a duration of 5 ns to 10 ns, and in some examples, a duration of 5 ns to 7 ns.

[0094] The memory 1006 may store instructions and data used by the processor 1002. The network adapter 1008 couples the computing device 1000 to a local area network or a wide area network, and the communication module 1010 provides additional channels for wired or wireless communications. As is known in the art, the computing device 1000 may have a plurality of Fig.10 1000. In some examples, storage device 1016 may be local and / or remote from computing device 1000, such as a separate storage device, cold storage device, storage area network (SAN), or cloud-based storage architecture.

[0095] As is known in the art, computing device 1000 is suitable for executing computer program modules for providing the functions described herein. As used herein, the term module refers to computer program logic for providing a specified function. Therefore, a module can be implemented in hardware, firmware, and / or software. In one embodiment, the program module is stored on storage device 1016, loaded into memory 1006, and executed by processor 1002.

[0096] Some parts of this disclosure describe examples of algorithmic processing or operational aspects. These algorithmic descriptions and representations are typically used by those skilled in the art of data processing to effectively convey the essence of their work to other skilled in the art. Although described functionally, computationally, or logically, these operations are understood to be implemented by computer programs including instructions executed by a processor or equivalent circuit, microcode, etc. In addition, without loss of generality, it sometimes proves convenient to refer to the arrangement of these functional operations as modules.

[0097] Although Fig.10 A single computing device 1000 and storage device 1016 are shown, but it should be understood that the functionality and storage provided by computing device 1000 and storage device 1016 may be implemented in any number of computing devices and storage devices. By way of example, a first computing device 1000 may be used to implement controller 300, and one or more other computing devices 1000 may be used to perform other functionality disclosed herein, such as stage controller 124, chuck heater, melt detector 280, etc.

[0098] The computing device 1000 can be configured to communicate with other computing devices of the system 100 through one or more networks using both a wired communication system and / or a wireless communication system, and the one or more networks may include any combination of a local area network and / or a wide area network. In one embodiment, the network uses standard communication technologies and / or protocols. For example, the network includes a communication link using technologies such as Ethernet, 802.11, Worldwide Interoperability for Microwave Access (WiMAX), 3G, 4G, Code Division Multiple Access (CDMA), Digital Subscriber Line (DSL), etc. Examples of network protocols for communicating via a network include Multi-Protocol Label Switching (MPLS), Transmission Control Protocol / Internet Protocol (TCP / IP), Hypertext Transfer Protocol (HTTP), Simple Mail Transfer Protocol (SMTP), and File Transfer Protocol (FTP). Data exchanged over the network can be represented using any suitable format such as Hypertext Markup Language (HTML) or Extensible Markup Language (XML). Those skilled in the art will recognize that encryption using other suitable technologies will be applicable to various applications based on the nature of the network.

[0099] Examples of the present disclosure include a method for analyzing scattered image data. The method includes: receiving a scattered image of an area of ​​a semiconductor surface captured during a laser annealing process of the semiconductor; and identifying a phase transition of a solid state to a liquid state of the semiconductor material from the image; wherein the identifying includes identifying a statistical, time series, or geometric nonlinear change in image intensity according to one or more annealing process control parameters. In some examples, the one or more annealing process control parameters include laser power or optical power density.

[0100] Examples of the present disclosure also include a method of performing melt calibration for laser annealing of a semiconductor material. The method includes: annealing a region of semiconductor material using an annealing laser beam from an annealing laser, wherein the annealing includes incrementally changing the power level of the annealing laser below and above a melt threshold power level at which the semiconductor material undergoes a solid-to-liquid phase transition; capturing a scatter image of the region of semiconductor material during annealing; and determining at least one melt threshold set point power level of the annealing laser based on the captured scatter image.

[0101] Examples of the present disclosure include a method for controlling an annealing laser operating parameter during a laser annealing process. The method includes controlling an annealing laser operating parameter during an annealing process of a semiconductor material according to a laser annealing temperature calibration created by performing the method described in the preceding paragraphs.

[0102] Examples of the present disclosure also include machine readable instructions configured to cause a processor of a controller of a laser annealing system to control an annealing laser according to annealing process parameters and at least one annealing laser melting threshold calibration set point determined according to the methods disclosed herein.

[0103] Examples of the present disclosure include methods of forming a below-melt reference image and parameters for use with a melt detection algorithm. The method includes: annealing a wafer below melt; capturing image frames using a scatter melt detector; recording annealing laser power levels; creating a below-melt reference image from the captured image frames; processing the below-melt reference image to generate a plurality of below-melt one-dimensional stage scan direction intensity profiles; identifying a region of interest (ROIref) of the below-melt reference image; and creating an average one-dimensional stage scan direction intensity profile.

[0104] Examples of the present disclosure include methods of detecting whether wafer material is melted during an annealing process. The method includes annealing a wafer below a melting threshold, at a melting threshold, or above a melting threshold, capturing image frames during the annealing using a scatter melt detector, and recording laser power levels; creating an average image from the captured image frames; and creating a melt detection image referencing the average image to a corresponding below-melt reference image of the same wafer type.

[0105] The method of paragraph

[0082] further includes comparing the value of the melt detection image with a threshold value to determine whether melting has occurred in one or more regions of the image.

[0106] The method of paragraph

[0082] further includes applying a one-dimensional distribution analysis of the melt detection image to identify a narrow peak having a width in the stage scanning direction that is smaller than a width of the processing laser beam.

[0107] The method of paragraph

[0082] , wherein the below-melt reference image is obtained by performing any of the methods using any of the systems disclosed herein.

[0108] Examples of the present disclosure also include a method of detecting whether a wafer material melts during an annealing process. The method includes: annealing a wafer below a melting threshold, at a melting threshold, or above a melting threshold, and capturing an image frame using a scattering melt detector during the annealing; calculating a statistical variation of pixel values ​​within a region of interest ROIref of the image frame, wherein ROIref is a region of the image where an annealing laser image is formed on the wafer; and comparing the calculated statistical variation to identify the onset of melting.

[0109] The foregoing is a detailed description of illustrative embodiments of the present disclosure. Note that in this specification and the appended claims, unless specifically stated or indicated otherwise, connective language used, for example, in the phrases "at least one of X, Y, and Z" and "one or more of X, Y, and Z" should be taken to mean that each item in the connective list may exist in any number in addition to each other item in the list, or in any number combined with any or all other items in the connective list, and each of the connective lists may also exist in any number. Applying this general rule, the connective phrases in the foregoing examples where the connective list includes X, Y, and Z should each include: one or more of X; one or more of Y; one or more of Z; one or more of X and one or more of Y; one or more of Y and one or more of Z; one or more of X and one or more of Z; and one or more of X, one or more of Y, and one or more of Z.

[0110] Without departing from the spirit and scope of the present disclosure, various modifications and additions may be made. The features of each embodiment in the various embodiments described above may be appropriately combined with the features of other described embodiments to provide a variety of feature combinations in associated new embodiments. In addition, although a plurality of separate embodiments have been described above, what is described herein is only an illustration of the application of the principles of the present disclosure. In addition, although the specific methods herein may be shown and / or described as being performed in a particular order, within the ordinary technical scope of implementing the various aspects of the present disclosure, the order is highly variable. Therefore, this description is intended to be carried out only in an exemplary manner, and does not otherwise limit the scope of the present disclosure.

Claims

1. A method of determining the occurrence of a solid to liquid material phase transition of a semiconductor material during a laser annealing process, the method comprising: forming an annealing image on the surface of the semiconductor material using an annealing laser beam from an annealing laser; forming a scattering image of the semiconductor surface including a region of the annealed image; as well as A solid-to-liquid material phase transition of the semiconductor material is identified based on the intensity of the light collected in the scattered image.

2. The method according to claim 1, wherein: The identifying includes detecting an intensity in the scatter image that reaches or exceeds a threshold, the threshold corresponding to the onset of a solid-to-liquid phase transition of the semiconductor material.

3. The method according to claim 2, wherein: The identifying includes detecting intensity in the scatter image in a region of the scatter image that is within the annealed image and smaller than an area of ​​the annealed image.

4. The method according to claim 1, wherein: The identifying includes identifying a discontinuity in intensity of light collected in the scatter image compared to a below-melt reference image.

5. The method according to claim 1, wherein: The identifying includes identifying a non-linear proportional relationship between the intensity of the light and a processing parameter.

6. The method according to claim 5, wherein: The processing parameter is the power level of the annealing laser or the local power density of the annealing laser.

7. The method according to claim 1, wherein: The laser annealing process includes performing sequential sweeps of the annealing image across the semiconductor surface, wherein each sweep forms an annealing illumination line, wherein forming a scatter image includes forming an image of at least one annealing illumination line.

8. The method according to claim 7, wherein: The step of identifying includes analyzing the intensity of light along the annealing illumination line to determine the extent of a material phase change of the semiconductor material along the annealing illumination line.

9. The method according to claim 7, wherein: The step of identifying includes analyzing the intensity of light along the annealing illumination lines to determine the proportion of the annealing illumination lines where the onset of a solid to liquid phase transition has occurred.

10. The method according to claim 7, wherein: The step of identifying includes analyzing the intensity of light at a first location along the anneal illumination line in a plurality of sequential sweeps of the anneal image to determine at least one of a melting threshold power level or statistical power fluctuations of the anneal laser.

11. The method according to claim 1, wherein: The laser annealing process includes sweeping the frequency f sweep Performing a sequential sweep across the semiconductor surface, the method further comprises utilizing a pulse having a frequency of f Probe The radiation pulse of the probe light source is used to illuminate the semiconductor surface, where f Probe <f sweep .

12. The method according to claim 1, wherein: The identification includes applying one or more of a fitting algorithm, an edge detection algorithm, an eigenbase decomposition, a feed-forward classifier, or detection of any intensity exceeding a threshold in the captured image frame.

13. The method according to claim 1, wherein: The identifying includes identifying statistical changes, time series changes, or geometric nonlinear changes in image intensity according to one or more annealing process control parameters.

14. The method according to claim 13, wherein: The one or more annealing process control parameters include laser power or optical power density.

15. The method according to claim 1, wherein: The identification includes: A melt detection image is created referencing the scatter image to a corresponding below-melt reference image. 16 . The method of claim 15 , further comprising comparing a value of the melt detection image with a threshold value to determine whether melting has occurred in one or more regions of the melt detection image.

17. The method of claim 15, further comprising applying a one-dimensional distribution analysis of the melt detection image to identify a narrow peak having a width in a stage scanning direction that is smaller than a width of the processing laser beam.

18. The method according to claim 15, wherein: A reference image below melting is obtained by performing the following steps, the steps comprising: annealing the wafer below melting; capturing image frames using a scatter melting detector; Record the annealing laser power level; creating a below-melt reference image based on the captured image frames; processing the below-melt reference image to generate a plurality of below-melt one-dimensional stage scan direction intensity distributions; identifying a region of interest (ROIref) of the below-melted reference image; and Create an averaged one-dimensional stage scan direction intensity distribution.

19. The method according to claim 1, wherein: The identification includes: calculating statistical variations of pixel values ​​within a region of interest ROIref of the image frame, wherein ROIref is a region of the image where an annealing laser image is formed on the wafer; and The calculated statistical changes are compared to identify the onset of the melt.

20. A scatter melting detection system, comprising: a stage configured to support a semiconductor wafer; an annealing laser configured to anneal the semiconductor wafer; as well as A scattering melting detector comprising: an image capture device comprising a focal plane array (FPA); as well as A scattering optical arrangement is configured to block or avoid specular reflection of the light beam formed by the annealing laser and form a scattered image of the surface of the semiconductor wafer on the FPA.

21. The system of claim 20, further comprising a processor and a machine-readable storage medium comprising program instructions for execution by the processor to perform the operations of any one of claims 1 to 19.

22. A laser annealing system, comprising: Annealing laser; a storage device comprising at least one annealing laser melting threshold calibration set point, the calibration set point specifying operating parameters of the annealing laser to raise the temperature of a localized region of semiconductor material to a melting threshold under a set of predetermined annealing process conditions, wherein the calibration set point is derived from a scattering image of the semiconductor material acquired during a laser annealing process of the semiconductor material; as well as A controller is configured to control the annealing laser according to the annealing laser melting threshold calibration set point.

23. The system of claim 22, wherein: The calibration set point is determined by a process comprising the steps of any one of claims 1 to 19.

24. A non-transitory machine-readable storage medium, comprising: at least one annealing laser melting threshold calibration set point, the calibration set point specifying operating parameters of the annealing laser to raise the temperature of a localized region of the semiconductor material to a melting threshold under a set of predetermined annealing process conditions, wherein the calibration set point is derived from a scattering image of the semiconductor material acquired during laser annealing of the semiconductor material.

25. The non-transitory machine-readable storage medium of claim 24, wherein: The calibration set point is determined by a process comprising the steps of any one of claims 1 to 19.

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