CN114322836B - Heuristic search-based periodic nanostructure morphology parameter measurement method and device - Google Patents
Heuristic search-based periodic nanostructure morphology parameter measurement method and device Download PDFInfo
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Abstract
The invention provides a method and a device for measuring morphology parameters of a periodic nano structure based on heuristic search, wherein the method comprises the following steps: obtaining a measurement signal of a periodic nanostructure to be measured; constructing a simulation signal database and a Jacobian matrix database based on a three-dimensional morphology parameter design value of a periodic nano structure to be detected and an optical scattering characteristic modeling method; establishing a heuristic search model, and determining a target simulation signal corresponding to the measurement signal based on the heuristic search model, a simulation signal database and a Jacobian matrix database; and determining a target three-dimensional morphology parameter discrete value corresponding to the target simulation signal based on the simulation signal database, and taking the target three-dimensional morphology parameter discrete value as the three-dimensional morphology parameter of the periodic nano structure to be detected. According to the invention, through heuristic search, the efficiency of measuring the morphology parameters of the periodic nano structure can be greatly improved while the accuracy of measuring the morphology parameters of the periodic nano structure is ensured.
Description
Technical Field
The invention relates to the technical field of optical precision measurement, in particular to a heuristic search-based periodic nanostructure morphology parameter measurement method and device.
Background
The optical scatterometer is a periodic nanostructure three-dimensional morphology measurement technology based on a model, and compared with nanometer measurement means such as a scanning electron microscope, a transmission electron microscope, an atomic force microscope and X-ray laminated diffraction imaging, the optical scatterometer has the advantages of high speed, non-destructiveness and the like, so the optical scatterometer is very suitable for being used in the field of on-line measurement of the periodic nanostructure three-dimensional morphology.
In the periodic nanostructure three-dimensional topography measurement based on the optical scatterometer, in order to ensure the online measurement speed, the optical scatterometer relies on an online search method based on a database, namely library matching. The basic principle is that for a certain periodic nano structure to be measured, a plurality of parameter values are discretely taken in the upper and lower ranges of the nominal value (namely the design value) of the three-dimensional morphology, and corresponding simulation signals are calculated, so that a simulation signal database is gradually generated. After the database is built, the measurement signals obtained by the online measurement of the optical scatterometer are compared with each simulation signal in the database in real time until the nanostructure three-dimensional morphology value corresponding to the most similar simulation signal is found, namely the output value.
However, in the conventional optical scatterometer based on library matching, the scale of library matching and the mesh generation precision cause a contradiction between speed and measurement accuracy: the larger the library scale is and the finer the mesh generation is, the more accurate the three-dimensional morphology measurement result is, but the online search time is increased in a geometric progression.
Disclosure of Invention
In view of the above, it is necessary to provide a method and an apparatus for measuring morphology parameters of a periodic nanostructure based on heuristic search, so as to solve the technical problem that the measurement of morphology parameters of a periodic nanostructure in the prior art cannot take into account both the measurement accuracy and the measurement speed.
In order to solve the technical problem, the invention provides a method for measuring the morphology parameters of a periodic nano structure based on heuristic search, which comprises the following steps:
obtaining a measurement signal of a periodic nanostructure to be measured;
respectively constructing a simulation signal database and a Jacobian matrix database based on the three-dimensional morphology parameter design value of the periodic nanostructure to be detected and an optical scattering characteristic modeling method;
establishing a heuristic search model, and determining a target simulation signal corresponding to the measurement signal based on the heuristic search model, the simulation signal database and the Jacobian matrix database;
and determining a target three-dimensional morphology parameter discrete value corresponding to the target simulation signal based on the simulation signal database, and taking the target three-dimensional morphology parameter discrete value as the three-dimensional morphology parameter of the periodic nanostructure to be detected.
In some possible implementation manners, the respectively constructing a simulation signal database and a jacobian matrix database based on the three-dimensional morphology parameter design value of the periodic nanostructure to be detected and the optical scattering property modeling method includes:
determining an upper limit and a lower limit of the three-dimensional morphology parameter design value, and discretizing the three-dimensional morphology parameter design value based on the upper limit and the lower limit to obtain a plurality of three-dimensional morphology parameter discrete values;
determining a plurality of simulation signals and a plurality of Jacobian matrixes which correspond to the discrete values of the three-dimensional morphology parameters one by one on the basis of the optical scattering characteristic modeling method;
constructing the simulation signal database based on the plurality of simulation signals and the plurality of three-dimensional morphology parameter discrete values in one-to-one correspondence with the plurality of simulation signals;
and constructing the Jacobian matrix database based on the plurality of Jacobian elements and the plurality of three-dimensional morphology parameter discrete values which are in one-to-one correspondence with the plurality of Jacobian matrices.
In some possible implementations, the heuristic search model is:
in the formula (I), the compound is shown in the specification,
discrete values of the three-dimensional morphology parameters searched for the (i + 1) th time are obtained;
discrete values of the three-dimensional morphology parameters searched for the ith time are obtained;
is a gradient operator;
a Jacobian matrix of the discrete values of the three-dimensional morphology parameters searched for the ith time;
is a coefficient matrix;
simulation signals corresponding to the three-dimensional morphology parameter discrete values searched for the ith time;
is a measurement signal; []1 is a matrix [ alpha ], [ alpha ] and a]The inverse matrix of (d); []TIs a matrix]The transposed matrix of (2).
In some possible implementations, the determining a target simulated signal corresponding to the measured signal based on the heuristic search model, the simulated signal database, and the jacobian matrix database includes:
step 1, determining a current simulation signal to be compared in a simulation signal database;
step 2, determining an evaluation function, and determining an evaluation function value between the measurement signal and the current simulation signal to be compared based on the evaluation function;
step 3, judging whether the evaluation function value is larger than a preset threshold value or not;
step 4, if the evaluation function value is smaller than or equal to a preset threshold value, taking the current simulation signal to be compared as the target simulation signal;
and 5, if the evaluation function value is larger than a preset threshold value, determining a next simulation signal to be compared based on the heuristic search model, taking the next simulation signal to be compared as the current simulation signal to be compared, and repeating the steps 2 to 5.
In some possible implementation manners, the current comparison simulation signal is a first simulation signal in the simulation signal database.
In some possible implementations, after the determining the discrete values of the target three-dimensional topography parameter corresponding to the target simulation signal based on the simulation signal database, the method further includes:
constructing a robust statistical correction model;
and correcting the target three-dimensional morphology parameter discrete value based on the robust statistical correction model to obtain an accurate three-dimensional morphology parameter discrete value.
In some possible implementations, the robust statistical correction model is:
in the formula (I), the compound is shown in the specification,
discrete values of the accurate three-dimensional shape parameters are obtained;
discrete values of the target three-dimensional morphology parameters are obtained;
correcting values for the three-dimensional shape parameters; argmin { } is a least squares function;
is a robust evaluation function;
for measuring signals
The kth wavelength component value of;
a k-th wavelength component value of the target emulated signal;
a k-th row in a Jacobian matrix corresponding to the discrete value of the target three-dimensional topography parameter;
and designing a three-dimensional shape parameter design value of the periodic nano structure to be tested.
On the other hand, the invention also provides a device for measuring the morphology parameters of the periodic nano structure based on heuristic search, which comprises the following components:
the measurement signal acquisition unit is used for acquiring a measurement signal of the periodic nanostructure to be measured;
the database construction unit is used for respectively constructing a simulation signal database and a Jacobian matrix database based on the three-dimensional morphology parameter design value of the periodic nano structure to be detected and an optical scattering characteristic modeling method;
the heuristic search unit is used for establishing a heuristic search model and determining a target simulation signal corresponding to the measurement signal based on the heuristic search model, the simulation signal database and the Jacobian matrix database;
and the target value determining unit is used for determining a target three-dimensional morphology parameter discrete value corresponding to the target simulation signal based on the simulation signal database, and taking the target three-dimensional morphology parameter discrete value as the three-dimensional morphology parameter of the periodic nanostructure to be detected.
In another aspect, the present invention further provides an electronic device, including: one or more processors;
a memory; and
one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the heuristic search based periodic nanostructure topography parameter measurement method described in any of the possible implementations above.
In another aspect, the present invention further provides a computer storage medium, on which a computer program is stored, where the computer program is loaded by a processor to execute the steps in the periodic nanostructure topography parameter measurement method based on heuristic search described in any one of the above possible implementation manners.
The beneficial effects of adopting the embodiment are as follows: according to the periodic nanostructure morphology parameter measurement method based on heuristic search, provided by the invention, the heuristic search model is established, the target simulation signal is determined based on the heuristic search model, the constructed simulation signal database and the Jacobian matrix database, and compared with the prior art that the target simulation signal can be determined only by traversing the simulation signal database, the periodic nanostructure morphology parameter measurement method based on heuristic search can greatly improve the efficiency of measuring the periodic nanostructure morphology parameter while ensuring the accuracy of the periodic nanostructure morphology parameter measurement.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart of one embodiment of a method for measuring morphology parameters of periodic nanostructures based on heuristic search according to the present invention;
FIG. 2 is a schematic structural diagram of one embodiment of a periodic nanostructure to be measured according to the present invention;
FIG. 3 is a schematic flow chart of one embodiment of S102 of FIG. 1;
FIG. 4 is a schematic diagram of an embodiment of a simulation signal database and Jacobian matrix database construction process provided by the present invention;
FIG. 5 is a schematic flow chart of one embodiment of S103 of FIG. 1;
FIG. 6 is a schematic structural diagram illustrating an embodiment of a target simulation signal searching process in the prior art;
FIG. 7 is a schematic structural diagram illustrating a target simulation signal searching process according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of the robust statistical correction provided by the present invention;
FIG. 9 is a flowchart illustrating one embodiment of robust correction provided by the present invention;
FIG. 10 is a schematic structural diagram of an embodiment of a periodic nanostructure topography parameter measurement apparatus provided in the present invention;
fig. 11 is a schematic structural diagram of an embodiment of an electronic device provided in the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The invention provides a method and a device for measuring morphology parameters of a periodic nano structure based on heuristic search, which are respectively explained below.
Fig. 1 is a schematic flowchart of an embodiment of a method for measuring morphology parameters of a periodic nanostructure based on heuristic search, as shown in fig. 1, the method for measuring morphology parameters of a periodic nanostructure based on heuristic search includes:
s101, obtaining a measurement signal of a periodic nanostructure to be measured;
s102, respectively constructing a simulation signal database and a Jacobian matrix database based on a three-dimensional morphology parameter design value of the periodic nanostructure to be detected and an optical scattering characteristic modeling method;
s103, establishing a heuristic search model, and determining a target simulation signal corresponding to the measurement signal based on the heuristic search model, a simulation signal database and a Jacobian matrix database;
s104, determining a target three-dimensional shape parameter discrete value corresponding to the target simulation signal based on the simulation signal database, and taking the target three-dimensional shape parameter discrete value as a three-dimensional shape parameter of the periodic nano structure to be detected.
Compared with the prior art, the periodic nanostructure morphology parameter measurement method based on heuristic search provided by the embodiment of the invention can greatly improve the efficiency of measuring the periodic nanostructure morphology parameters while ensuring the accuracy of the periodic nanostructure morphology parameter measurement by establishing the heuristic search model and determining the target simulation signal based on the heuristic search model and the constructed simulation signal database and Jacobi matrix database.
In some embodiments of the present invention, as shown in fig. 2, a typical periodic nanostructure to be measured can be a diffraction grating with a trapezoidal cross section, and the cross section of the grating can be fully characterized by four sets of parameters, namely, the period, the top width W, the height H, and the bottom width D of the trapezoid. For the field of industrial measurement, the period is often known, and therefore, the three-dimensional morphology parameters of the periodic nanostructure to be measured mainly include the top width W, the height H and the bottom width D of the trapezoid, and the three parameters can be uniformly represented by one three-dimensional morphology parameter P to be measured: p = [ W, H, D ].
In some embodiments of the present invention, as shown in fig. 3, step S102 includes:
s301, determining the upper limit and the lower limit of the three-dimensional morphology parameter design value, and discretizing the three-dimensional morphology parameter design value based on the upper limit and the lower limit to obtain a plurality of three-dimensional morphology parameter discrete values;
s302, determining a plurality of simulation signals and a plurality of Jacobian matrixes which correspond to a plurality of three-dimensional morphology parameter discrete values one by one based on an optical scattering characteristic modeling method;
s303, constructing a simulation signal database based on the plurality of simulation signals and the plurality of three-dimensional morphology parameter discrete values which are in one-to-one correspondence with the plurality of simulation signals;
s304, constructing a Jacobian matrix database based on the multiple Jacobian elements and the multiple three-dimensional morphology parameter discrete values which are in one-to-one correspondence with the multiple Jacobian matrices.
In some embodiments of the present invention, as shown in fig. 4, steps S301 to S304 specifically include:
for the three-dimensional shape parameter P = [ D, H, W ] to be measured]In other words, random discrete operation is performed in advance within the value range defined by the lower limit and the upper limit of the three-dimensional shape parameter, and then m groups of three-dimensional shape parameter discrete values P are generatedj = [Dj, Hj, Wj](wherein j = 1, 2, … m). For each group of three-dimensional shape parameter discrete values PjThe corresponding simulation signal, such as P, is calculated by using an optical scattering characteristic modeling algorithmjThe corresponding calculated simulation signal can be represented as Rj = [Rj1, Rj2, …, Rjn](where j = 1, 2, … m; where n denotes that there are n wavelength points in the measurement signal and the simulation signal, respectively). Thus, each three-dimensional shape parameter discrete value PjAnd its corresponding simulation signal RjWhich together form a basic unit in the simulation signal database.
Similarly, for each set of three-dimensional shape parameter discrete values PjCorrespondingly calculating the Jacobian matrix JjWherein the Jacobian matrix is the simulation signal RjDiscrete value P of signal pair three-dimensional shape parameter under certain wavelengthjThe partial derivative of a component).
Specifically, the periodic nanostructure optical scattering characteristic simulation modeling algorithm may be any one of a strict coupled wave method, a time domain finite difference method, a finite element method, and a moment method.
It should be noted that: the simulation signal database and the Jacobian matrix database are generated by off-line calculation, the simulation signal database and the Jacobian matrix database can be used in a plurality of on-line measurement scenes only by calculating the simulation signal database and the Jacobian matrix database once, the simulation signal database and the Jacobian matrix database are prevented from being repeatedly calculated, and the measurement efficiency of the three-dimensional morphology parameters is further improved.
In some embodiments of the invention, the heuristic search model is:
in the formula (I), the compound is shown in the specification,
discrete values of the three-dimensional morphology parameters searched for the (i + 1) th time are obtained;
discrete values of the three-dimensional morphology parameters searched for the ith time are obtained;
is a gradient operator;
a Jacobian matrix of the discrete values of the three-dimensional morphology parameters searched for the ith time;
is a coefficient matrix;
for the ith searchedSimulation signals corresponding to the dimension and shape parameter discrete values;
is a measurement signal; []-1Is a matrix]The inverse matrix of (d); []TIs a matrix]The transposed matrix of (2).
As can be seen from the above equation: by introducing the gradient operator to search the target simulation signal in the simulation signal database, the ergodic search strategy in the prior art is avoided, the search efficiency is greatly improved, and the efficiency of measuring the three-dimensional morphology parameters is improved.
In some embodiments of the present invention, as shown in fig. 5, step S103 includes:
s501, determining a current simulation signal to be compared in a simulation signal database;
s502, determining an evaluation function, and determining an evaluation function value between the measurement signal and the current simulation signal to be compared based on the evaluation function;
s503, judging whether the evaluation function value is larger than a preset threshold value or not;
s504, if the evaluation function value is smaller than or equal to a preset threshold value, taking the current simulation signal to be compared as a target simulation signal;
and S505, if the evaluation function value is larger than a preset threshold value, determining a next simulation signal to be compared based on the heuristic search model, taking the next simulation signal to be compared as the current simulation signal to be compared, and repeating S502-S505.
In a specific embodiment of the invention, the merit function is a least squares merit function.
In order to avoid the technical problem that the determination rate of the target simulation signal is low or the target simulation signal cannot be determined due to the fact that the current simulation signal to be compared cannot be determined or the determination process of the current simulation signal to be compared is complex, in a preferred embodiment of the present invention, the current simulation signal to be compared is the first simulation signal in the simulation signal database.
By setting the current simulation signal to be compared as the first simulation signal in the simulation signal database, the current simulation signal to be compared can be quickly determined, and the efficiency of measuring the three-dimensional morphology parameters is further improved.
In order to compare the differences between the embodiments of the present invention and the prior art more intuitively, as shown in fig. 6 and 7, the conventional method for determining the target simulation signal from the simulation signal database is to compare the measured signal with all the data in the simulation signal database to find the optimal value, and the basic principle is as shown in fig. 6: each basic cell in the simulation signal database is represented by a gray circle, and the measurement signal is represented by a gray square. Firstly, comparing a measurement signal with a first simulation signal in a database through an evaluation function, and directly outputting a three-dimensional morphology parameter corresponding to the simulation signal as an optimal value and terminating the rest search process once the evaluation function value between the measurement signal and the first simulation signal is judged to be less than a given threshold value. If the evaluation function value is greater than the given threshold value, the second simulation signal is compared with the measurement signal in a consistent manner, and the steps are repeated until the evaluation function value is less than the given threshold value. It can be seen that the traditional library matching method needs to traverse the data in the whole simulation signal database, and further high-speed online measurement is difficult to realize.
The embodiment of the invention provides a method for determining a target simulation signal based on heuristic search, as shown in fig. 7: firstly, the measured signal is still compared with the first simulation signal in the simulation signal database, and if the difference between the measured signal and the first simulation signal is greater than a given threshold value, the heuristic search work is started. As can be seen from fig. 7, the embodiment of the present invention is a gradient search mode, rather than a traversal search, so that the search efficiency is greatly improved, and the efficiency of measuring the three-dimensional morphology parameters is greatly improved.
In the process of constructing the simulation signal database, the corresponding three-dimensional morphology parameter discrete values between every two basic units are discontinuous, so that the target three-dimensional morphology parameter discrete value is limited by the grid precision of the simulation signal database and is difficult to reflect the real three-dimensional morphology value of the periodic nanostructure to be measured; as shown in the grid curved surface in fig. 8, it represents the space where the discrete values Psearch of the three-dimensional topography parameters of the object are located. The actual three-dimensional morphology value Ptrue of the periodic nanostructure to be measured is outside the grid curved surface, so that a deviation exists between a target three-dimensional morphology parameter discrete value Psearch obtained by searching a simulation signal database in a heuristic mode and the actual three-dimensional morphology value Ptrue of the periodic nanostructure to be measured, and the deviation is caused by the grid subdivision precision of the simulation signal database, and the other part of reasons are caused by inevitable measurement errors in measurement signals.
Therefore, in some embodiments of the present invention, as shown in fig. 9, after determining the discrete value of the target three-dimensional topography parameter corresponding to the target simulation signal based on the simulation signal database in step S104, the method further includes:
s901, constructing a robust statistical correction model;
s902, correcting the discrete value of the target three-dimensional morphology parameter based on the robust statistical correction model to obtain an accurate discrete value of the three-dimensional morphology parameter.
Further, as shown in fig. 8, it can be seen that: compared with a target three-dimensional morphology parameter discrete value Psearch, the accurate three-dimensional morphology parameter discrete value P is closer to a real three-dimensional morphology value Ptrue of the periodic nano structure to be detected. Therefore, the target three-dimensional morphology parameter discrete value is corrected through the robust statistical correction model, the non-normal error in the current measurement signal can be inhibited, the deviation caused by simulation signal meshing is reduced to a certain extent, the obtained accurate three-dimensional morphology parameter discrete value is more accurate, and the accuracy of measuring the three-dimensional morphology parameter of the periodic nano structure to be measured is improved.
In some embodiments of the invention, the robust statistical correction model is:
in the formula (I), the compound is shown in the specification,
the three-dimensional shape parameter is an accurate three-dimensional shape parameter discrete value;
discrete values of the target three-dimensional morphology parameters are obtained;
correcting values for the three-dimensional shape parameters; argmin { } is a least squares function;
is a robust evaluation function;
for measuring signals
The kth wavelength component value of;
is the kth wavelength component value of the target emulated signal;
a k line in a Jacobian matrix corresponding to the discrete value of the target three-dimensional morphology parameter;
the design value of the three-dimensional shape parameter of the periodic nano structure to be measured is obtained.
Specifically, the robust evaluation function is:
in the formula (I), the compound is shown in the specification,
is the first derivative of the robust evaluation function;
is any variable;
an Andruss strong oscillation operator;
is a preset constant.
In a particular embodiment of the present invention,
at 1.339, the measurement error in this correction process statistically satisfies the normal distribution assumption with a 95% probability. Thereby eliminating the measurement deviation caused by the abnormal distribution as much as possible.
In order to better implement the heuristic search-based periodic nanostructure topography parameter measurement method in the embodiment of the present invention, on the basis of the heuristic search-based periodic nanostructure topography parameter measurement method, as shown in fig. 10, correspondingly, an embodiment of the present invention further provides a heuristic search-based periodic nanostructure topography parameter measurement apparatus 1000, which includes:
a measurement signal acquisition unit 1001 configured to acquire a measurement signal of the periodic nanostructure to be measured;
the database construction unit 1002 is used for respectively constructing a simulation signal database and a Jacobian matrix database based on the three-dimensional morphology parameter design value of the periodic nanostructure to be detected and an optical scattering characteristic modeling method;
a heuristic search unit 1003, configured to establish a heuristic search model, and determine a target simulation signal corresponding to the measurement signal based on the heuristic search model, the simulation signal database, and the jacobian matrix database;
and the target value determining unit 1004 is used for determining a target three-dimensional morphology parameter discrete value corresponding to the target simulation signal based on the simulation signal database, and taking the target three-dimensional morphology parameter discrete value as the three-dimensional morphology parameter of the periodic nanostructure to be detected.
The heuristic search-based periodic nanostructure morphology parameter measurement device 1000 provided in the above-mentioned embodiment can implement the technical solutions described in the above-mentioned heuristic search-based periodic nanostructure morphology parameter measurement method embodiments, and the specific implementation principles of the above-mentioned modules or units can be referred to the corresponding contents in the above-mentioned heuristic search-based periodic nanostructure morphology parameter measurement method embodiments, and are not described herein again.
As shown in fig. 10, the present invention also provides an electronic device 1100 accordingly. The electronic device 1100 includes a processor 1101, a memory 1102, and a display 1103. Fig. 10 shows only some of the components of the electronic device 1100, but it is to be understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead.
The storage 1102 may in some embodiments be an internal storage unit of the electronic device 1100, such as a hard disk or a memory of the electronic device 1100. The memory 1102 may also be an external storage device of the electronic device 1000 in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc., provided on the electronic device 1100.
Further, the memory 1102 may also include both internal storage units and external storage devices of the electronic device 1100. The memory 1102 is used to store application software and various types of data for installing the electronic device 1100.
The processor 1101 may be a Central Processing Unit (CPU), microprocessor or other data Processing chip in some embodiments, for running program code stored in the memory 1102 or Processing data, such as the periodic nanostructure topography parameter measurement method of the present invention.
The display 1103 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch panel, or the like in some embodiments. The display 1103 is used to display information at the electronic device 1000 as well as to display a visual user interface. The components 1101 and 1103 of the electronic device 1100 communicate with each other via a system bus.
In one embodiment, when the processor 1101 executes a heuristic search based periodic nanostructure topography parameter measurement procedure in the memory 1102, the following steps may be implemented:
obtaining a measurement signal of a periodic nanostructure to be measured;
respectively constructing a simulation signal database and a Jacobian matrix database based on a three-dimensional morphology parameter design value of a periodic nano structure to be detected and an optical scattering characteristic modeling method;
establishing a heuristic search model, and determining a target simulation signal corresponding to the measurement signal based on the heuristic search model, a simulation signal database and a Jacobian matrix database;
and determining a target three-dimensional morphology parameter discrete value corresponding to the target simulation signal based on the simulation signal database, and taking the target three-dimensional morphology parameter discrete value as the three-dimensional morphology parameter of the periodic nano structure to be detected.
It should be understood that: the processor 1101, when executing the program for measuring the topographic parameters of the periodic nanostructures based on heuristic search in the memory 1102, may also perform other functions in addition to the above functions, which may be referred to in the description of the corresponding method embodiments above.
Further, the type of the mentioned electronic device 1100 is not specifically limited in the embodiment of the present invention, and the electronic device 1100 may be a portable electronic device such as a mobile phone, a tablet computer, a Personal Digital Assistant (PDA), a wearable device, and a laptop computer (laptop). Exemplary embodiments of portable electronic devices include, but are not limited to, portable electronic devices that carry an IOS, android, microsoft, or other operating system. The portable electronic device may also be other portable electronic devices such as laptop computers (laptop) with touch sensitive surfaces (e.g., touch panels), etc. It should also be understood that in other embodiments of the present invention, the electronic device 1100 may not be a portable electronic device, but rather a desktop computer having a touch-sensitive surface (e.g., a touch panel).
Accordingly, the present application also provides a computer-readable storage medium, which is used for storing a computer-readable program or instruction, and when the program or instruction is executed by a processor, the method steps or functions provided by the above method embodiments can be implemented.
Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program, which is stored in a computer-readable storage medium, to instruct related hardware. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.
The method and the device for measuring the morphology parameters of the periodic nanostructure based on heuristic search are described in detail, specific examples are applied in the method to explain the principle and the implementation mode of the method, and the description of the examples is only used for helping to understand the method and the core idea of the method; meanwhile, for those skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (8)
1. A method for measuring morphology parameters of a periodic nano structure based on heuristic search is characterized by comprising the following steps:
obtaining a measurement signal of a periodic nanostructure to be measured;
respectively constructing a simulation signal database and a Jacobian matrix database based on the three-dimensional morphology parameter design value of the periodic nanostructure to be detected and an optical scattering characteristic modeling method;
establishing a heuristic search model, and determining a target simulation signal corresponding to the measurement signal based on the heuristic search model, the simulation signal database and the Jacobian matrix database;
determining a target three-dimensional morphology parameter discrete value corresponding to the target simulation signal based on the simulation signal database, and taking the target three-dimensional morphology parameter discrete value as a three-dimensional morphology parameter of the periodic nanostructure to be detected;
the heuristic search model is as follows:
in the formula (I), the compound is shown in the specification,
obtaining the discrete value of the three-dimensional morphology parameter searched for the (i + 1) th time;
discrete values of the three-dimensional morphology parameters searched for the ith time are obtained;
is a gradient operator;
a Jacobian matrix of the discrete values of the three-dimensional morphology parameters searched for the ith time;
is a coefficient matrix;
simulation signals corresponding to the three-dimensional morphology parameter discrete values searched for the ith time;
is a measurement signal; []-1Is a matrix]The inverse matrix of (d); []TIs a matrix]The transposed matrix of (2);
the determining a target simulated signal corresponding to the measured signal based on the heuristic search model, the simulated signal database, and the Jacobian matrix database comprises:
step 1, determining a current simulation signal to be compared in a simulation signal database;
step 2, determining an evaluation function, and determining an evaluation function value between the measurement signal and the current simulation signal to be compared based on the evaluation function;
step 3, judging whether the evaluation function value is larger than a preset threshold value or not;
step 4, if the evaluation function value is smaller than or equal to a preset threshold value, taking the current simulation signal to be compared as the target simulation signal;
and 5, if the evaluation function value is larger than a preset threshold value, determining a next simulation signal to be compared based on the heuristic search model, taking the next simulation signal to be compared as the current simulation signal to be compared, and repeating the steps 2 to 5.
2. The method for measuring morphology parameters of periodic nanostructures based on heuristic search according to claim 1, wherein the method for modeling the three-dimensional morphology parameter design value and the optical scattering property based on the periodic nanostructures to be tested to respectively construct the simulation signal database and the Jacobi matrix database comprises:
determining an upper limit and a lower limit of the three-dimensional morphology parameter design value, and discretizing the three-dimensional morphology parameter design value based on the upper limit and the lower limit to obtain a plurality of three-dimensional morphology parameter discrete values;
determining a plurality of simulation signals and a plurality of Jacobian matrixes which correspond to the discrete values of the three-dimensional morphology parameters one by one on the basis of the optical scattering characteristic modeling method;
constructing the simulation signal database based on the plurality of simulation signals and the plurality of three-dimensional morphology parameter discrete values in one-to-one correspondence with the plurality of simulation signals;
and constructing the Jacobian matrix database based on the plurality of Jacobian elements and the plurality of three-dimensional morphology parameter discrete values which are in one-to-one correspondence with the plurality of Jacobian matrices.
3. The method as claimed in claim 1, wherein the current simulation signal to be compared is the first simulation signal in the simulation signal database.
4. A heuristic search based periodic nanostructure topography parameter measurement method of claim 1, further comprising, after said determining target three-dimensional topography parameter discrete values corresponding to the target simulation signals based on the simulation signal database:
constructing a robust statistical correction model;
and correcting the target three-dimensional morphology parameter discrete value based on the robust statistical correction model to obtain an accurate three-dimensional morphology parameter discrete value.
5. The periodic nanostructure topography parameter measurement method based on heuristic search of claim 4, characterized in that the robust statistical correction model is:
in the formula (I), the compound is shown in the specification,
discrete values of the accurate three-dimensional shape parameters are obtained;
discrete values of the target three-dimensional morphology parameters are obtained;
correcting values for the three-dimensional shape parameters; argmin { } is a least squares function;
is a robust evaluation function;
for measuring signals
The kth wavelength component value of;
is the kth wavelength component value of the target emulated signal;
a k line in a Jacobian matrix corresponding to the discrete value of the target three-dimensional morphology parameter;
and designing a three-dimensional shape parameter design value of the periodic nano structure to be tested.
6. A periodic nanostructure morphology parameter measurement device based on heuristic search is characterized by comprising:
the measurement signal acquisition unit is used for acquiring a measurement signal of the periodic nano structure to be measured;
the database construction unit is used for respectively constructing a simulation signal database and a Jacobian matrix database based on the three-dimensional morphology parameter design value of the periodic nano structure to be detected and an optical scattering characteristic modeling method;
the heuristic search unit is used for establishing a heuristic search model and determining a target simulation signal corresponding to the measurement signal based on the heuristic search model, the simulation signal database and the Jacobian matrix database;
a target value determining unit, configured to determine a target three-dimensional morphology parameter discrete value corresponding to the target simulation signal based on the simulation signal database, and use the target three-dimensional morphology parameter discrete value as a three-dimensional morphology parameter of the periodic nanostructure to be detected;
the heuristic search model is as follows:
in the formula (I), the compound is shown in the specification,
discrete values of the three-dimensional morphology parameters searched for the (i + 1) th time are obtained;
discrete values of the three-dimensional morphology parameters searched for the ith time are obtained;
is a gradient operator;
a Jacobian matrix of the discrete values of the three-dimensional morphology parameters searched for the ith time;
is a coefficient matrix;
simulation signals corresponding to the three-dimensional morphology parameter discrete values searched for the ith time;
is a measurement signal; []-1Is a matrix]The inverse matrix of (d); []TIs a matrix]The transposed matrix of (2);
the determining a target simulated signal corresponding to the measured signal based on the heuristic search model, the simulated signal database, and the Jacobian matrix database comprises:
step 1, determining a current simulation signal to be compared in a simulation signal database;
step 2, determining an evaluation function, and determining an evaluation function value between the measurement signal and the current simulation signal to be compared based on the evaluation function;
step 3, judging whether the evaluation function value is larger than a preset threshold value or not;
step 4, if the evaluation function value is smaller than or equal to a preset threshold value, taking the current simulation signal to be compared as the target simulation signal;
and 5, if the evaluation function value is larger than a preset threshold value, determining a next simulation signal to be compared based on the heuristic search model, taking the next simulation signal to be compared as the current simulation signal to be compared, and repeating the steps 2 to 5.
7. An electronic device, comprising:
one or more processors;
a memory; and
one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the heuristic search based periodic nanostructure topography parameter measurement method of any of claims 1-5.
8. A computer-readable storage medium, having a computer program stored thereon, wherein the computer program is loaded by a processor to perform the steps of the method for periodic nanostructure topography parameter measurement based on heuristic search according to any of the claims 1-5.
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