CN114556166B - CMOS color image sensor with metamaterial color separation - Google Patents
CMOS color image sensor with metamaterial color separation Download PDFInfo
- Publication number
- CN114556166B CN114556166B CN201980101356.5A CN201980101356A CN114556166B CN 114556166 B CN114556166 B CN 114556166B CN 201980101356 A CN201980101356 A CN 201980101356A CN 114556166 B CN114556166 B CN 114556166B
- Authority
- CN
- China
- Prior art keywords
- dielectric
- void
- scattering
- scattering structure
- refractive index
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000926 separation method Methods 0.000 title claims description 9
- 238000000034 method Methods 0.000 claims abstract description 55
- 238000004519 manufacturing process Methods 0.000 claims abstract description 32
- 238000005457 optimization Methods 0.000 claims abstract description 32
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 13
- 238000005530 etching Methods 0.000 claims abstract description 7
- 239000011800 void material Substances 0.000 claims description 20
- 230000008569 process Effects 0.000 claims description 18
- 230000003595 spectral effect Effects 0.000 claims description 17
- 229910052751 metal Inorganic materials 0.000 claims description 9
- 239000002184 metal Substances 0.000 claims description 9
- GWEVSGVZZGPLCZ-UHFFFAOYSA-N Titan oxide Chemical compound O=[Ti]=O GWEVSGVZZGPLCZ-UHFFFAOYSA-N 0.000 claims description 8
- 238000000149 argon plasma sintering Methods 0.000 claims description 3
- 239000003989 dielectric material Substances 0.000 claims 1
- 230000010287 polarization Effects 0.000 description 15
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N Silicium dioxide Chemical compound O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 14
- 230000003287 optical effect Effects 0.000 description 13
- 230000035945 sensitivity Effects 0.000 description 13
- 238000009826 distribution Methods 0.000 description 8
- 239000000463 material Substances 0.000 description 8
- 239000000377 silicon dioxide Substances 0.000 description 7
- 235000012239 silicon dioxide Nutrition 0.000 description 6
- 238000004088 simulation Methods 0.000 description 6
- 229910052681 coesite Inorganic materials 0.000 description 4
- 229910052906 cristobalite Inorganic materials 0.000 description 4
- 230000005684 electric field Effects 0.000 description 4
- 229910052682 stishovite Inorganic materials 0.000 description 4
- 229910052905 tridymite Inorganic materials 0.000 description 4
- 238000000701 chemical imaging Methods 0.000 description 3
- 239000003086 colorant Substances 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000006872 improvement Effects 0.000 description 3
- 238000000206 photolithography Methods 0.000 description 3
- 238000001228 spectrum Methods 0.000 description 3
- 238000000411 transmission spectrum Methods 0.000 description 3
- 238000001429 visible spectrum Methods 0.000 description 3
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 2
- 229910004298 SiO 2 Inorganic materials 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 229910052802 copper Inorganic materials 0.000 description 2
- 239000010949 copper Substances 0.000 description 2
- 238000012938 design process Methods 0.000 description 2
- 239000007788 liquid Substances 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 239000002245 particle Substances 0.000 description 2
- 229920000642 polymer Polymers 0.000 description 2
- 239000000758 substrate Substances 0.000 description 2
- 241000408659 Darpa Species 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000000231 atomic layer deposition Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000000151 deposition Methods 0.000 description 1
- 230000008021 deposition Effects 0.000 description 1
- 238000003708 edge detection Methods 0.000 description 1
- 230000005672 electromagnetic field Effects 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000011478 gradient descent method Methods 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 239000002086 nanomaterial Substances 0.000 description 1
- 238000000059 patterning Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000001931 thermography Methods 0.000 description 1
- 238000002834 transmittance Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B5/00—Optical elements other than lenses
- G02B5/02—Diffusing elements; Afocal elements
- G02B5/0205—Diffusing elements; Afocal elements characterised by the diffusing properties
- G02B5/0236—Diffusing elements; Afocal elements characterised by the diffusing properties the diffusion taking place within the volume of the element
- G02B5/0247—Diffusing elements; Afocal elements characterised by the diffusing properties the diffusion taking place within the volume of the element by means of voids or pores
-
- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B5/00—Optical elements other than lenses
- G02B5/02—Diffusing elements; Afocal elements
- G02B5/0268—Diffusing elements; Afocal elements characterized by the fabrication or manufacturing method
-
- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B5/00—Optical elements other than lenses
- G02B5/02—Diffusing elements; Afocal elements
- G02B5/0273—Diffusing elements; Afocal elements characterized by the use
- G02B5/0278—Diffusing elements; Afocal elements characterized by the use used in transmission
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Optics & Photonics (AREA)
- Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Polarising Elements (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
- Optical Elements Other Than Lenses (AREA)
- Optical Filters (AREA)
Abstract
Methods of constructing a multifunctional scattering structure while adhering to the stringent requirements imposed by the manufacturing process are described. The described method and apparatus are based on etching away a network of wires embedded in a 3D structure to form voids, thereby performing an objective function. An optimization algorithm for designing a binarized device that meets manufacturing requirements is also disclosed.
Description
Cross Reference to Related Applications
The present application relates to U.S. patent 16/656,156, entitled "Color And Multi-SPECTRAL IMAGE Sensor Based On 3D Engineered Material" (att. Docket No. P2404-US), filed On 10/17 in 2019, the contents of which are incorporated herein by reference in their entirety.
Government subsidy statement
This invention was completed under government grant from DARPA, grant No. HR0011-17-2-0035. The government has certain rights in this invention.
Technical Field
The present disclosure relates to image sensors, and more particularly, to a metamaterial beam splitter (METAMATERIAL SPECTRUM SPLITTERS) fabricated using CMOS fabrication techniques.
Background
Optical systems are typically designed by modular combinations of elements to achieve complex functions. For example, the lens and the diffractive optics may be combined to perform hyperspectral imaging (HYPERSPECTRAL IMAGING). The method is intuitive and flexible, and can access a wide range of functions from a finite element set. However, the overall size and weight of the optical system may limit its range of applications. Recent advances in nanofabrication may alleviate this limitation by replacing cumbersome elements with planar arrays of resonant nanostructures of sub-wavelength thickness. By designing the scattering of individual elements in the array, these devices can reproduce the versatility of complex optical systems in individual elements. However, efforts to combine multiple metasurfaces (metasurface) to achieve more complex functions have been hampered by reduced scattering efficiency, which is inversely proportional to the number of tasks performed simultaneously.
The inherent tradeoff between versatility and efficiency in these systems is due to the limited degrees of freedom that is proportional to the volume of the device and the maximum refractive index contrast. In particular, this limits the range of independent functions that any ultra-thin system can perform, such as sorting light according to frequency, polarization and angle of incidence (sort). In contrast, three-dimensional scattering elements with a thickness greater than one wavelength typically encode many simultaneous functions, but so far are inefficient due to weak scattering and low refractive index contrast.
Historically, optical designs have been modular, and this mode provides an intuitive way to build and reconfigure optical settings. With advances in nano-fabrication technology, it has become possible to fabricate structures with sub-wavelength feature sizes, which enables multi-functional optical elements to incorporate more complex set-up functions. Examples include hypersurface lenses that can separate different polarizations and spectral bands. However, the degree of performance and functionality that can be achieved by supersurfaces and other planar structures is inherently limited by the number of controllable optical modes.
Constructing refractive indices with high contrast on the sub-wavelength scale provides a broad optical design space that can be used to demonstrate multifunctional optical elements. So far, this has been mainly used for two-dimensional structures, or metacurves. However, their performance is limited by the available optical degrees of freedom.
To highlight the benefits of the teachings of the present disclosure in the following sections, examples of image sensors are considered herein. Currently, most sensors record color using absorbing filters. Fig. 1A shows a prior art image sensor with an absorptive color filter on top of every four adjacent pixels, two for green, one for blue and one for red. The problem with such image sensors is that the efficiency is limited to around 30% because most of the light is absorbed. Color image sensors are ubiquitous in cell phones, cameras, and various instruments. The color is detected by a simple absorbing filter placed directly on top of each pixel. The absorption properties of the filter mean that more than 2/3 of the light is actually absorbed and lost, i.e. for example red and blue light incident on the green pixel is absorbed and only green light passes.
Disclosure of Invention
In the present application complex three-dimensional (3D) scattering structures are disclosed that allow for separation of colors on bayer patterns, for example, with greater efficiency. Designs that provide polarization information are also described.
The cost effectiveness and mass production of such structures present significant challenges to the design process. The goal is to achieve optimal performance given the inherent limitations associated with large-scale CMOS fabrication processes.
The disclosed methods and devices solve the described challenges and provide a practical solution to the problems described above.
In particular, the disclosed methods and apparatus teach various steps for designing 3D scattering structures using scalable manufacturing processes. Currently, the largest scale fabrication that can handle dimensions less than 100 nanometers is a CMOS foundry fabrication process. In CMOS processes, very complex networks of copper wires can be fabricated, stacked on top of each other and embedded in silicon dioxide. An example of such a network is shown in fig. 1B, where light gray and dark gray represent metal and silica, respectively. However, according to embodiments of the present disclosure, the lines may be etched away using a liquid etchant such that the final 3D scattering structure consists of voids in SiO 2. According to another embodiment of the present disclosure, the 3D scattering structures may be left as voids in SiO2, or the voids may be filled with a higher refractive index material, such as TiO2, using an atomic layer deposition process.
According to a first aspect of the present disclosure, a method for constructing a three-dimensional (3D) scattering structure is disclosed, comprising forming a dielectric structure comprising a first dielectric and a network of metal wires, wherein the position, shape and size of the metal wires are selected according to one or more target functions; and etching the metal wire away from the dielectric structure, thereby forming a structure comprising a space filled with the first dielectric and the void, wherein the location, shape and size of the void are in accordance with one or more objective functions, wherein the 3D light scattering structure so formed is configured to receive electromagnetic waves and scatter the electromagnetic waves in accordance with the one or more objective functions.
Other aspects of the disclosure are provided in the description, drawings, and claims of the application.
Drawings
Fig. 1A shows a prior art image sensor.
Fig. 1B shows a prior art structure of a wire that can be implemented using CMOS foundry fabrication technology, with feature sizes below 100 nanometers.
Fig. 2A-2A' illustrate exemplary three-dimensional (3D) scattering structures according to embodiments of the disclosure.
Fig. 2B-2C illustrate the wavelength separation function of the embodiment of fig. 2A and 2A'.
Fig. 3A-3C illustrate an exemplary three-dimensional (3D) scattering structure according to another embodiment of the present disclosure, where fig. 3B' illustrates a lithographic process according to the teachings of the present disclosure.
FIG. 3D illustrates various steps of an exemplary optimization algorithm in accordance with embodiments of the present disclosure.
Fig. 4A illustrates an exemplary 3D structure made of dielectric and including a wire network in accordance with an embodiment of the present disclosure.
Fig. 4B illustrates an exemplary process of etching away wire mesh within a 3D structure according to another embodiment of the present disclosure.
Fig. 5 shows an exemplary flowchart illustrating the various steps of designing a 3D scattering structure according to the teachings of the present disclosure.
Fig. 6 shows an exemplary graph illustrating refractive index distribution along a horizontal position.
Fig. 7A-7C illustrate graphs representing the performance of 3D scattering structures implemented in accordance with the teachings of the present disclosure.
Detailed Description
Fig. 2A illustrates an image sensor (200) according to an embodiment of the disclosure. The image sensor (200) comprises a three-dimensional (3D) scattering structure (201) acting as a spectral separator. The 3D scattering structure (201) includes a plurality of dielectric pillars (DIELECTRIC PILLAR) (205) formed to scatter light in a predetermined pattern. Incident light (202) passing through the 3D scattering structure (201) is scattered off by the dielectric pillars. By arranging the dielectric pillars (205) according to one or more target functions, the scattering pattern is tailored to perform a desired function. As an example, the 3D scattering structure (201) may be designed as a beam splitter to simultaneously classify and focus the incident light (202) into any number of wavelengths (λ 1,…,λn), each of which is directed to a single pixel on a focal plane (203) located below the 3D scattering structure (201), as shown in fig. 2A. According to embodiments of the present disclosure, the 3D scattering structure (201) may be a porous polymer cube or a cluster of dielectric or semiconductor (e.g. Si) particles embedded in a SiO2 matrix. According to further embodiments of the present disclosure, the 3D scattering structure (201) may be a porous polymer cube or clusters of high refractive index particles embedded in a low refractive index matrix.
Those skilled in the art will appreciate that the image sensor (200) of fig. 2A does not operate based on absorption compared to the prior art image sensor (100) of fig. 1A, and therefore, it provides a significant improvement in efficiency compared to the prior art solutions. This will be quantified later using an exemplary embodiment of the present teachings. As described in more detail throughout the disclosure, the disclosed apparatus and methods provide the following additional benefits over existing solutions:
the 3D scattering structure (201) of fig. 2A may be fabricated by a known and scalable lithographic process.
The 3D scattering structure (201) of fig. 2A may be designed to function as a spectral separator for any spectral band (e.g., infrared, mid-infrared, etc.). In other words, thermal imaging is another potential application of the disclosed teachings in addition to hyperspectral imaging.
The spectral separation function (spectrum splitting function) may be combined with other desired functions such as polarization separation (polarization splitting).
Embodiments according to the present disclosure may also be designed to perform optical image processing, such as Gabor filtering for edge detection.
Fig. 2A 'illustrates an image sensor (200') according to an embodiment of the present disclosure, including an exemplary three-dimensional (3D) scattering structure (21) that acts as a spectral filter. Incident light (22) entering from above is scattered while passing through the 3D scattering structure (21) and classified in a focal plane (23) composed of four sub-pixels, displayed as red, blue, green (x-polarization) and green (y-polarization). As also shown in fig. 2A', the red (600 nm-700 nm) and blue (400 nm-500 nm) spectral bands are classified into opposite quadrants. In addition, the green (500 nm-600 nm) spectral bands are further separated according to linear polarization. The red and blue quadrants may be polarization independent.
According to embodiments of the present disclosure, 3D scattering structures (21) may be designed using a concomitant variable method (adjoint variable method) that generates a structure that optimizes a specified objective function. As an example, and referring to fig. 2A', the objective function may be selected based on the focusing efficiency of the incident light to one of four target areas, depending on frequency and polarization. From the empty volume (empty volume), a full-wave time-domain finite difference (full-WAVE FINITE-DIFFERENCE TIME-domain: FDTD) simulation was performed to calculate the sensitivity of the figure of merit to refractive index disturbances. The prescribed scattering structure is iteratively formed and updated. In other words, the optimal design is created by iterative updating of the initial geometry, each step improving performance. The sensitivity can be calculated by only two simulations, allowing an efficient optimization of the 3D device with modest resources. The sensitivity of multiple incident wavelengths in the visible spectrum can be calculated, assigning each spectral band to a different quadrant, red (600 nm-700 nm), green (500 nm-600 nm) and blue (400 nm-500 nm). The spectral average sensitivity can be used to update the refractive index of the device.
Fig. 2B-2C show simulated intensities of incident light within the 3D scattering structure (21) of fig. 2A'. The intensities were analyzed along diagonal cross-sections intersecting the red and blue quadrants of fig. 2A. Each wavelength undergoes multiple scattering before being focused onto its respective target region. Fig. 2C shows the intensity distribution of incident light within a diagonal cross section through a green pixel for two orthogonal input polarizations. In both cases, plane waves (λ=550 nm) incident from above are preferentially routed to the pixels corresponding to their polarization. At the same time, for the red and blue spectral bands, both polarizations are assigned to the same region, maintaining the mirror symmetry of the objective function.
According to an embodiment of the present disclosure, the 3D scattering structure (21) of fig. 2A' classifies red, green and blue light with an efficiency of 84%, 60% and 87%, respectively. Throughout this disclosure, efficiency is defined as the average over the entire spectrum of the portion of the total power incident on the device that reaches the target quadrant for which the device is designed for the visible spectrum of the embodiment of fig. 2A'.
Referring to fig. 2A and 2A', those skilled in the art will appreciate that the disclosed concepts provide considerable flexibility in defining an objective scattering function, with independent control over any incident polarization, angle, or frequency. However, complex three-dimensional structures present significant challenges to fabrication. Large scale implementation of these devices in image sensors at visible wavelengths would require high manufacturing yields with resolutions below 100 nanometers. This may be achieved by multilayer photolithography, where three-dimensional devices are constructed by repeated material deposition and patterning. Here, each layer consists of a series of patterned mesas (measa) composed of a high index dielectric. The gap space is filled with a low index dielectric forming a planar surface of the substrate that serves as a subsequent layer.
To further clarify the layered manufacturing method discussed above, reference is made to fig. 3A and 3C, which show a layered design of the 3D scattering structure (31) of fig. 3C. In other words, the 3D scattering structure (31) of fig. 3C may be constructed by stacking the multiple layers (301, …, 305) of fig. 3A on top of each other. The fabrication process may be CMOS compatible, where fabrication constraints may be directly combined with the design algorithm. Each layer (301, …, 305) may be produced using photolithography. The 3D scattering structure (31) may be composed of TiO2 and SiO2, which materials are transparent at visible frequencies. These layers (301, …, 305) may be 2 μm by 2 μm layers, each 400nm high. Those skilled in the art will appreciate that these are exemplary dimensions for descriptive purposes and that embodiments according to the present disclosure are also contemplated and have dimensions and layers other than those described above. As shown in fig. 3B, each layer may include a set of irregular TiO2 mesas surrounded by SiO 2. Referring to fig. 3B', a photolithographic process is shown that may begin by growing a thin layer of dielectric (e.g., tiO 2) on top of a substrate (e.g., siO 2) in accordance with the teachings of the present disclosure. A pattern is transferred onto the layer by photolithography and unprotected material is etched away to create a two-dimensional dielectric structure. Finally, the surface is coated (deposited) with a low refractive index dielectric and mechanically polished (planarized). By repeating the same process for each layer and stacking the layers, the desired 3D structure is created. As described above, such a lithographic process provides flexibility in material design and is compatible with industry standard CMOS fabrication processes.
Optimization algorithm
Gradient descent
Referring back to fig. 2A' -3C, as previously described, a three-dimensional dielectric structure optimized to perform the target optical scattering function is designed in accordance with the teachings of the present disclosure. In the case of the exemplary embodiment shown in fig. 2A' -3C, such an objective scattering function includes focusing the incident plane wave to different locations depending on frequency and polarization. Exemplary three-dimensional (3D) scattering structures (21, 31) are composed of spatially dependent refractive index profiles within a cube design areaIs defined. This represents a broad design space, which can express various complex optical versatility. However, determining the optimal refractive index profile for a given objective function remains a challenging inverse design problem, especially for strong scattering devices.
To overcome this challenge, an iterative approach guided by gradient descent (GRADIENT DESCENT) may be implemented in accordance with the teachings of the present disclosure, where, starting from an initial refractive index profile, full wave simulation (FDTD) is used to calculate the sensitivity of the focusing efficiency to refractive index disturbances. The sensitivity can be calculated by only two simulations, allowing an efficient optimization of the three-dimensional device with modest resources. Based on the sensitivity, the initial design is modified to maximize performance while meeting manufacturing constraints. The update process is repeated until the optimized device is able to effectively perform the target function
To further clarify what has been described above, reference is made to fig. 3D, which illustrates various steps of a gradient-based optimization algorithm in accordance with an embodiment of the present disclosure. In step (81), a uniform refractive index distribution is usedTo initialize the algorithm, where n max and n min represent the maximum and minimum values of refractive index, respectively. The distribution is updated continuously so that the focal plane/>The electromagnetic intensity at the target location is maximized. The objective function serves as a proxy for the focusing efficiency while simplifying the sensitivity calculation. In step 74, the sensitivity/>, is calculated from the electromagnetic fields in the two FDTD simulation (forward and companion) steps (72, 73) according to the following expression
Wherein,Is the electric field within the cube when illuminated with a plane wave from above (step 72),/>Is the electric field within the cube when illuminated from below with a point light source at the target location (step 73). The phase and amplitude of the point source is given by the electric field at the target location in forward modeling (forward simulation). Sensitivity can be calculated for multiple incident wavelengths and polarizations in the visible spectrum, each spectral band being assigned to a different quadrant, red (600 nm-700 nm), green (500 nm-600 nm) and blue (400 nm-500 nm). Then, in step (74), the spectral average sensitivity is used to update the refractive index of the device using the following formula:
The step size α may be fixed at a small fraction (e.g., α=0.001) to ensure that the change in refractive index may be considered as a perturbation in the linear range. The sensitivity is recalculated after each update. After several iterations, the algorithm converges to an optimal design, step (75), wherein the resulting structure focuses the incident light with the desired efficiency.
Fig. 4A shows a 3D scattering structure (410) made of a dielectric, the 3D structure (410) comprising a network of wires (415) embedded inside the scattering structure (410). The dielectric may be made of an oxide such as silicon dioxide and the wire network (415) may be made of a metal such as copper. As previously described, to create a complex 3D scattering element that performs the target function, voids may be formed within the 3D structure (410) by etching away the wire network (415) that was originally fabricated within the 3D scattering structure (410). To do this, referring now to fig. 4A-4B, and in accordance with a further embodiment of the present disclosure, a via (420) is etched in the dielectric to access the end of the wire in the wire network (405), and then the wire is etched away using a liquid etchant in order to obtain a void (415').
Throughout this disclosure, the term "wire spacing" refers to the minimum spacing of two adjacent wires of a wire network within a 3D structure from each other. Furthermore, there is a minimum wire feature size imposed by the limitations of the manufacturing process. Thus, when voids are formed within the 3D structure by etching away the wires, the minimum wire spacing sets the minimum dielectric feature size and the minimum wire size sets the minimum void/air feature size. Hereinafter, exemplary steps of a method of designing a 3D scattering structure (410) while taking into account manufacturing process constraints in accordance with the teachings of the present disclosure are described.
Free, continuous optimization
Hereinafter, a 3D structure made of dielectric in which voids are formed according to an objective function will be described. The process may begin with a free optimization, as described above in relation to the sections of fig. 2A-3D, where the refractive index is allowed to continuously vary between air (n=1.0) and the low refractive index material SiO2 (n=1.5). For example, a gradient descent algorithm may be used, wherein the sensitivity of the objective function to exponential changes is calculated at all points in the design area. Referring to the example of fig. 2A' and 3C, the objective function to be optimized may be selected as the electric field strength at different focus points for different bands. Such an objective function may be used when designing the wavelength separator. The design obtained by free and continuous optimization may not meet the requirements imposed by manufacturing constraints. In this context, the term "free optimization" refers to an optimization method that does not impose manufacturing constraints, and the term "continuous optimization" refers to an optimization method that cancels certain manufacturing constraints. For example, in this optimization method, the refractive index may take any value within a set range, not just an extremum. As described in detail in the following paragraphs, the disclosed method addresses this problem by implementing binarization of the refractive index (binarization), and then further optimizing the design using, for example, a gradient descent method, while taking into account manufacturing requirements.
Two-dimensional (2D) shape representation and binarization
In this document, the term "binarization" refers to manufacturing constraints in which only a small amount of material can be selected, thus not allowing a continuous refractive index profile. For example, CMOS technology imposes such fabrication constraints. Considering an example of a 2D shape, the explicit representation (explicit representation) of such a shape may be a series of points in the 2D plane that define the boundaries of such a shape. In the case of a rectangle, the shape may be defined by only four points in the plane. Another way to represent a particular shape, such as a rectangle, or any shape is to use an implicit representation (implicit representation). Herein, the term "level set function (level set function)" refers to a function that is an implicit representation of a geometry. For example, in the case of a 2D shape, the level set function may be defined as a function f (x, y), or in other words, a three-dimensional surface. The outline defined by f (x, y) =constant (e.g., constant equal to 0) defines the boundary of the two-dimensional shape.
As will be described in detail later, it is contemplated that, according to embodiments of the present disclosure, a level set function of a feature may be represented with a geometric shape, such as a rectangle, rather than a free shape as allowed by a free-continuous optimization algorithm. As described below, this approach will allow for an optimal design while meeting the stringent requirements imposed by the manufacturing process. Gradient information from the continuous optimization method can then be mapped to the perturbation of the level set function such that the boundaries of the shape move in a manner that improves the design. When reduced to features having, for example, a rectangular shape (or some other parametrizable shape), the boundary perturbation may be converted to a perturbation of the feature parameters, such as in the case of a rectangle, a center point, and two widths. Hereinafter, examples of features having rectangular shapes will be used to describe the teachings of the present disclosure, bearing in mind that features having shapes other than rectangular are also contemplated.
Level set representation
According to an embodiment of the present disclosure, the design of the aforementioned 3D structure is implemented in 2D while layering is implemented in the propagation direction of the input source. In other words, for example, referring to rectangular features, the position and width of the feature are parameters that are controlled. FIG. 5 shows a flow chart (500) describing various steps of a design process, according to an embodiment of the disclosure. As can be seen from the flow chart (500), an initial optimization design based on free/continuous optimization is first provided (step 510). Such a design will provide a refractive index profile in the horizontal direction in substantially each layer and there are no manufacturing limitations in creating such an initial design. Then, for each layer, the following steps are taken:
1. A program is run to identify peaks in the void index distribution (step 520). The minimum found in this way represents a void region which is not necessarily completely void according to the free/continuous optimization described previously. In other words, some regions may represent local minima.
2. The identified regions are then ranked based on their proximity to the void (step 530). This is performed using design results based on a free/continuous optimization algorithm as described previously. In other words, void features are preferentially placed where free design is most desirable.
3. The void features proceed from highest level to lowest level, each void being replaced by a rectangle approximating the original exponential distribution (step 540). The dimensions of the rectangle are selected to maintain the same volume average refractive index as the original distribution, thereby providing a binary refractive index substitution. This is illustrated in fig. 6, where an exemplary graph representing an exponential distribution versus horizontal position is shown.
4. Each feature needs to meet manufacturing (e.g., CMOS process) constraints (steps 550-570). In other words, the width of each feature is required to meet the minimum width requirement, which, as previously described, is set by the minimum line size that can be manufactured. The distance between the centers of adjacent features needs to meet the manufacturing pitch requirement. Any feature that does not meet these requirements may be omitted.
5. Using the center/width of each feature found in the previous step, a level set function is created (level set function) and assigned to each feature (step 580). As described below, the created level function will be updated (step 580) to improve the performance of the binarized design.
Performance improvements for binary designs
As previously described, according to embodiments of the present disclosure, and in order to meet manufacturing constraints, the 3D structure may be designed based on a specific shape, such as a rectangular bar. As with the design using free/continuous optimization, this design already provides improved overall performance compared to existing solutions. However, free-shape based designs may still yield better overall performance than more specific feature based designs. From the binarization device, gradient information can be used to iteratively update the design to further improve overall performance in accordance with the teachings of the present disclosure. As shown in the flowchart (500) of fig. 5, gradient information from the free/continuous optimization method may be mapped to the width/center perturbations of all rectangular features used in the binarized design (step 580 of fig. 5), step 580). In other words, the gradient of the objective function with respect to the refractive index profile can be mapped to a perturbation of the boundary by the Hamilton-Jacobi equation. This means that we can update the boundary (here the width) with the same information used to optimize the continuous graded index structure. The inventors have noted that when this approach is employed, and after several iterations, a significant improvement in already good performance of the binary design will be obtained, while taking into account the constraints imposed by the fabrication process (e.g. CMOS process). Hereinafter, the performance of the described design method will be described using exemplary embodiments of the present disclosure.
Fig. 7A-7C illustrate performance results associated with exemplary 3D scattering structures optimized for single polarization and tri-color focusing (e.g., red, green, and blue). The 3D structure is made of SiCOH (n=1.3), with air gaps (n=1) formed using the aforementioned method. 8 layers (450 nm/layer) were used, using the 2D method as described previously. Fig. 7A shows the transmission spectrum associated with a design based on free/continuous optimization. Graphs (701A, 702A, 703A) represent transmission plots as a function of wavelength for colors (blue, green, red), respectively. Fig. 7B shows the transmission spectrum associated with the binarized design. Graphs (701B, 702B, 703B) represent curves of transmittance as a function of wavelength for different focal regions. A decrease in performance was noted compared to the results obtained in the case of free optimization. Fig. 7C shows the transmission spectrum obtained after further optimization of the binarized design after gradient information from the free/continuous optimization method is mapped to perturbations in the width/center of all rectangular features used in the binarized design. Graphs (701C, 702C, 703C) represent transmission plots as a function of wavelength for colors (blue, green, red), respectively. It can be noted that the performance of the binarized design is significantly improved.
Claims (13)
1. A method for constructing a three-dimensional (3D) scattering structure, comprising:
forming a dielectric structure comprising a first dielectric and a network of metal wires, wherein the position, shape and size of the metal wires are selected according to a spectral separation function; and
Etching the metal wire away from the dielectric structure to form a structure comprising a space filled with the first dielectric and the void, wherein the location, shape and size of the void are selected according to the spectral separation function,
Wherein the 3D light scattering structure so formed is configured to receive electromagnetic waves and scatter the electromagnetic waves according to a spectral separation function.
2. The method of claim 1, further comprising filling the void with a second dielectric different from the first dielectric, thereby obtaining a 3D light scattering structure made of two different dielectrics.
3. The method of claim 1 or 2, wherein etching is performed by creating vias in the 3D scattering structures.
4. The method of claim 1 or 2, wherein the forming of the dielectric structure is performed by a CMOS process.
5. The method of claim 2, wherein the first dielectric and the second dielectric comprise SiCOH and TiO2, respectively.
6. The method of claim 1 or 2, wherein the forming of the dielectric structure is performed using stacked layers of metal wires.
7. The method of claim 6, wherein the location and size of the void is provided using a gradient descent-based optimization method.
8. The method of claim 7, wherein the voids within each layer have a geometry represented by one or more parameters.
9. The method of claim 8, wherein each geometry is rectangular and the one or more parameters include two widths and a center in a horizontal direction.
10. The method of claim 9, wherein the optimization method comprises providing an initial 3D pattern using a continuous optimization algorithm to produce a refractive index profile in a horizontal direction within each layer.
11. The method of claim 10, wherein the optimization method further comprises:
For each layer:
identifying a minimum of the refractive index profile to provide a location of the void;
ranking the voids based on a continuous optimization algorithm to indicate how each void is binarized;
Setting two widths and centers for each void from highest level to lowest level;
checking each void against a set size and a set spacing requirement to provide a set of acceptable voids; and
The two void widths of the set of acceptable voids are perturbed based on a continuous optimization algorithm to further optimize and improve the overall performance of the 3D scattering structure.
12. The method of claim 11, wherein the set dimensions and the set pitch requirements relate to CMOS fabrication constraints.
13. An image sensor comprising a three-dimensional (3D) scattering structure for use as a spectral separator, the three-dimensional (3D) scattering structure constructed based on any of the foregoing methods.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/US2019/057026 WO2021076154A1 (en) | 2019-10-18 | 2019-10-18 | Cmos color image sensors with metamaterial color splitting |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114556166A CN114556166A (en) | 2022-05-27 |
| CN114556166B true CN114556166B (en) | 2024-05-28 |
Family
ID=75537417
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201980101356.5A Active CN114556166B (en) | 2019-10-18 | 2019-10-18 | CMOS color image sensor with metamaterial color separation |
Country Status (4)
| Country | Link |
|---|---|
| JP (1) | JP7503623B2 (en) |
| KR (1) | KR20220083736A (en) |
| CN (1) | CN114556166B (en) |
| WO (1) | WO2021076154A1 (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113167938A (en) | 2018-10-22 | 2021-07-23 | 加州理工学院 | Color multispectral image sensor based on three-dimensional engineering material |
| US11239276B2 (en) | 2019-10-18 | 2022-02-01 | California Institute Of Technology | CMOS color image sensors with metamaterial color splitting |
| WO2024077086A1 (en) * | 2022-10-05 | 2024-04-11 | Metalenz, Inc. | Shared-aperture camera system and calibration method |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3971065A (en) * | 1975-03-05 | 1976-07-20 | Eastman Kodak Company | Color imaging array |
| US5385114A (en) * | 1992-12-04 | 1995-01-31 | Milstein; Joseph B. | Photonic band gap materials and method of preparation thereof |
| CN101044631A (en) * | 2004-11-30 | 2007-09-26 | 国际商业机器公司 | A damascene copper wiring image sensor |
| KR20080061029A (en) * | 2006-12-27 | 2008-07-02 | 동부일렉트로닉스 주식회사 | Image sensor and fabricating method thereof |
| CN103154777A (en) * | 2010-10-20 | 2013-06-12 | 3M创新有限公司 | Low refractive index diffuser element having interconnected voids |
| CN204481029U (en) * | 2015-04-15 | 2015-07-15 | 张修赫 | A kind of COMS imageing sensor |
| CN107664780A (en) * | 2017-10-11 | 2018-02-06 | 武汉大学 | Dielectric nano brick array structure and its application as high-reflecting film and high transmittance film |
| CN109545812A (en) * | 2018-11-30 | 2019-03-29 | 德淮半导体有限公司 | Imaging sensor and forming method thereof |
| CN111684581A (en) * | 2017-12-01 | 2020-09-18 | 硅源公司 | Three-dimensional integrated circuit |
| CN116344564A (en) * | 2021-12-23 | 2023-06-27 | 豪威科技股份有限公司 | Multi-layered metal stack for active pixel area and black pixel area of image sensor and method thereof |
Family Cites Families (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4653391B2 (en) * | 2003-09-08 | 2011-03-16 | 株式会社リコー | Manufacturing method of light control element |
| WO2007008440A2 (en) * | 2005-07-08 | 2007-01-18 | The Board Of Trustees Of The University Of Illinois | Photonic crystal biosensor fabrication method |
| JP4785194B2 (en) * | 2006-08-25 | 2011-10-05 | 日本碍子株式会社 | Method for manufacturing slab type two-dimensional photonic crystal structure |
| US7833818B2 (en) * | 2008-12-14 | 2010-11-16 | United Microelectronics Corp. | Integrated structure of MEMS device and CMOS image sensor device and fabricating method thereof |
| US20100302481A1 (en) * | 2009-06-01 | 2010-12-02 | Baum Alexandra | Absorbing wire grid polarizer |
| WO2011005530A2 (en) * | 2009-06-22 | 2011-01-13 | The Trustees Of Princeton University | Non-crystalline materials having complete photonic, electronic, or phononic band gaps |
| US20120092770A1 (en) * | 2010-01-29 | 2012-04-19 | Jingjing Li | Non-periodic gratings for shaping reflected and transmitted light irradiance profiles |
| EP2564247A2 (en) * | 2010-04-27 | 2013-03-06 | The Regents Of The University Of Michigan | Display device having plasmonic color filters and photovoltaic capabilities |
| KR101432115B1 (en) * | 2010-07-15 | 2014-08-21 | 한국전자통신연구원 | meta material and manufacturing method at the same |
| US20140339606A1 (en) * | 2013-05-16 | 2014-11-20 | Visera Technologies Company Limited | Bsi cmos image sensor |
| JP2015087431A (en) * | 2013-10-28 | 2015-05-07 | 株式会社東芝 | Optical device and solid state image sensor |
| US20150198812A1 (en) * | 2014-01-15 | 2015-07-16 | Georgia Tech Research Corporation | Photo-Mask and Accessory Optical Components for Fabrication of Three-Dimensional Structures |
| US11089286B2 (en) * | 2015-07-29 | 2021-08-10 | Samsung Electronics Co., Ltd. | Image sensor |
| US9761622B2 (en) * | 2015-09-09 | 2017-09-12 | Taiwan Semiconductor Manufacturing Co., Ltd. | CMOS image sensor structure with crosstalk improvement |
| CA3084438A1 (en) * | 2017-12-04 | 2019-06-13 | California Institute Of Technology | Metasurface-assisted 3d beam shaping |
-
2019
- 2019-10-18 CN CN201980101356.5A patent/CN114556166B/en active Active
- 2019-10-18 JP JP2022515969A patent/JP7503623B2/en active Active
- 2019-10-18 WO PCT/US2019/057026 patent/WO2021076154A1/en active Application Filing
- 2019-10-18 KR KR1020227015534A patent/KR20220083736A/en not_active Application Discontinuation
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3971065A (en) * | 1975-03-05 | 1976-07-20 | Eastman Kodak Company | Color imaging array |
| US5385114A (en) * | 1992-12-04 | 1995-01-31 | Milstein; Joseph B. | Photonic band gap materials and method of preparation thereof |
| CN101044631A (en) * | 2004-11-30 | 2007-09-26 | 国际商业机器公司 | A damascene copper wiring image sensor |
| KR20080061029A (en) * | 2006-12-27 | 2008-07-02 | 동부일렉트로닉스 주식회사 | Image sensor and fabricating method thereof |
| CN103154777A (en) * | 2010-10-20 | 2013-06-12 | 3M创新有限公司 | Low refractive index diffuser element having interconnected voids |
| CN204481029U (en) * | 2015-04-15 | 2015-07-15 | 张修赫 | A kind of COMS imageing sensor |
| CN107664780A (en) * | 2017-10-11 | 2018-02-06 | 武汉大学 | Dielectric nano brick array structure and its application as high-reflecting film and high transmittance film |
| CN111684581A (en) * | 2017-12-01 | 2020-09-18 | 硅源公司 | Three-dimensional integrated circuit |
| CN109545812A (en) * | 2018-11-30 | 2019-03-29 | 德淮半导体有限公司 | Imaging sensor and forming method thereof |
| CN116344564A (en) * | 2021-12-23 | 2023-06-27 | 豪威科技股份有限公司 | Multi-layered metal stack for active pixel area and black pixel area of image sensor and method thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2021076154A1 (en) | 2021-04-22 |
| JP2022553495A (en) | 2022-12-23 |
| CN114556166A (en) | 2022-05-27 |
| JP7503623B2 (en) | 2024-06-20 |
| KR20220083736A (en) | 2022-06-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR102670423B1 (en) | Color and multi-spectral image sensors based on 3D engineered materials | |
| CN114556166B (en) | CMOS color image sensor with metamaterial color separation | |
| US11239276B2 (en) | CMOS color image sensors with metamaterial color splitting | |
| US8958141B1 (en) | Ultra-broadband, plasmonic, high-refractive index materials, UBHRI-GRIN-lenses-and other optical components | |
| JP7462760B2 (en) | Image sensor, method for producing same, and electronic device | |
| US11705632B2 (en) | Symphotic structures | |
| WO2020223399A1 (en) | High-efficiency, large-area, topology-optimized metasurfaces | |
| WO2022018527A1 (en) | Multi-spectral device | |
| WO2020227675A2 (en) | Diffractive axilenses and uses thereof | |
| Peng et al. | Metalens in improving imaging quality: advancements, challenges, and prospects for future display | |
| JP2023548057A (en) | Color router for image sensing | |
| US20140211072A1 (en) | Optical device, solid-state imaging device and method for manufacturing the optical device | |
| US10818711B2 (en) | Narrowband light filters | |
| US20220004016A1 (en) | Broadband polarization splitting based on volumetric meta-optics | |
| US20240322427A1 (en) | Apparatuses and methodology involving electromagnetic metamaterials | |
| Camayd-Muñoz et al. | Scaling laws for inverse-designed metadevices | |
| US20240302567A1 (en) | Volumetric, Nonlocal Metasurface Device That Maps Certain Incident Electromagnetic Waves to at Least One Spot on a Surface of the Device, and Methods of Manufacture | |
| JP7574859B2 (en) | Image pickup element and image pickup device | |
| Roberts et al. | Experimental demonstration of 3D inverse designed metaoptics in mid-infrared | |
| Kim et al. | Design parameters of free-form color routers for subwavelength pixelated CMOS image sensors | |
| Foo et al. | Inverse Design of Oblique Angle Metaoptics for Mid-Infrared Wavelength and Polarization Splitting | |
| Park et al. | Towards subwavelength pixels: nanophotonic color routers for ultra-compact high-efficiency CMOS image sensors | |
| KR20240097939A (en) | Metasurface waveguide coupler for display units | |
| Giloan et al. | Sub-wavelength imaging by space dilation | |
| KR20240160169A (en) | Genome segmenter for imaging |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |