JP2005056876A - Multi-hierarchical data base for parameter expressing impurity concentration distribution produced by ion implantation and its data extracting program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a multi-hierarchical data base which is made to be configured and maintained easily and to extract data easily from the data base by simplifying the data base. <P>SOLUTION: The multi-hierarchical data base, in which a plurality of data is stored correspondingly to the values of a plurality of categories and from which the data can be extracted by a computer, has a plurality of elements respectively having the names and values of the categories and configured in a multi-hierarchy by correlating the categories to layers. The multi-hierarchy is configured by correlating at least a plurality of lower-layer elements with an elements of upper layers, and in addition, by correlating data with the elements of the lowermost layer. Then a plurality of elements of a second layer which is lower than a first layer is correlated with the first element of a first layer and a plurality of elements of a third layer which is lower than the second layer is directly correlated with the second element of the first layer. Since the multi-hierarchy is configured by omitting the elements of the second layer when the data do not rely upon the values of the elements of the second layer with respect to the values of the second elements of the first layer, it becomes unnecessary to uselessly have identical data groups in a duplicated state. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a multi-hierarchical database and a data extraction program thereof, and more particularly to a multi-hierarchical database of parameters for impurity concentration distribution of ion implantation and a data extraction program thereof.
[0002]
[Prior art]
Multi-layered databases are used in various simulations. An ion implantation process is one of the manufacturing processes of semiconductor devices, and an impurity concentration distribution formed on the surface of a semiconductor substrate by such an ion implantation process is generated by simulation and used for device analysis. . Also in such a simulation of ion implantation distribution, parameters for specifying distribution functions corresponding to various ion implantation conditions are used as a database having a multi-layer structure. The use of a multi-hierarchical database is described in Patent Document 1, for example.
[0003]
FIG. 1 is a configuration diagram of an ion implantation distribution simulator. In the ion implantation distribution simulator, a parameter database 10 and an ion implantation distribution simulation program 12 are installed in a general-purpose computer, and a CPU, a RAM, an input / output device I / O, and the like are connected via a bus 14. When the ion implantation condition 16 is input via the input / output device I / O, the data 18 of the ion implantation distribution corresponding to the condition is output.
[0004]
FIG. 2 is a diagram showing an impurity concentration distribution when ions are implanted and an impurity concentration distribution function generated by simulation. FIG. 2A shows measurement data of the impurity concentration distribution in the depth direction of the substrate by a measuring method such as SIMS (Secondary Ion Mass Spectroscopy) on the surface of the semiconductor substrate ion-implanted by the ion implantation apparatus. The horizontal axis indicates the depth direction, and the vertical axis indicates the impurity concentration. Thus, the impurity concentration distribution by ion implantation has a peak at a predetermined depth from the substrate surface (position of depth 0), and the concentration decreases as the depth increases.
[0005]
It is known that such impurity concentration distribution can be expressed by a dual Pearson function. FIG. 2B is an impurity concentration distribution function by the Pearson function. This concentration distribution function is obtained by synthesizing two functions N1 (x) and N2 (x) based on two sets of parameters (Rp, ΔRp, γ, β, Rp2, ΔRp2, γ2, β2) by a dose ratio r. Is a concentration distribution function.
[0006]
N (x) = φ {rN1 (x) + (1-r) N2) x)}
Here, φ is a dose amount, r is a dose ratio, N1 (x) is a distribution function specified by parameters Rp, ΔRp, γ, and β, and N2 (x) is a distribution specified by parameters Rp2, ΔRp2, γ2, and β2. It is a function.
[0007]
Therefore, the above density distribution function is specified by nine parameters. Conversely, if the above-mentioned one set of parameters corresponding to various ion implantation conditions is created in advance as the parameter database 10 in FIG. 1, when performing ion implantation simulation, the ion implantation conditions are given. The parameters corresponding to the extracted parameters can be extracted, and the impurity concentration distribution of the ion implantation specified by the parameters can be generated. The ion implantation conditions are, for example, the angle of the substrate to be implanted, the rotation angle of the substrate, the cover oxide film thickness of the substrate surface, the implantation energy, the implantation amount (dose amount), and corresponding to these ion implantation conditions, Impurity concentration distribution is reproduced.
[0008]
FIG. 3 is a diagram illustrating an example of a parameter database structure included in a conventional general-purpose simulator. The database shown here has a multi-hierarchical structure and stores data DATA # 1 to # 5 corresponding to combinations of classification items A, B, and C. The classification items A, B, and C are ion implantation conditions such as the substrate angle, the substrate rotation angle, and the cover oxide film thickness, and are classification items of the data DATA # 1 to # 5. . That is, data as parameters is stored corresponding to a predetermined combination of ion implantation conditions.
[0009]
In the conventional database structure, when a hierarchical structure is defined, it is necessary to always have values (Values) for the defined classification items in all layers along the lower layer direction from the root element. That is, for category item A, value = 0 and value = 10 exist, for category item B below it, value = 0 and value = 15 exist, and for category item C there is also some value. And corresponding data is stored in the lowest layer of the hierarchical structure. These elements are connected by, for example, pointers to construct an entire database.
[0010]
In a conventional database structure, a hierarchical structure is defined, and a tree structure is constructed in accordance with the definition. Therefore, information on which classification item is not given to each element, and only the value of the classification item is given.
[0011]
In addition, when data for a desired combination of classification items is extracted from the database, a calculation process that repeats interpolation calculation is performed on the classification items of each layer. For example, with respect to the extraction condition C = 3 in the classification item C, data corresponding to C = 3 is acquired by performing interpolation calculation from the data DATA # 1 of C = 1 and the data DATA # 2 of C = 5. . Similar interpolation calculations are performed for the classification items B and A, respectively. That is, according to the value of the classification item of the extracted data, a pair of classification items of each hierarchy is selected sequentially from the data root, and the interpolation calculation is performed on the data of the lowermost element, and the same interpolation calculation is performed on the upper hierarchy. Repeat for elements. In this way, even if the value of the classification item of the data to be extracted does not match the value of the classification item stored in the database, the data of the element having a pair of values close to the extraction target value is obtained. Data to be extracted can be output by performing interpolation calculation.
[0012]
[Patent Document 1] Japanese Patent Laid-Open No. 2001-344558
[0013]
[Problems to be solved by the invention]
However, depending on the type of database, classification based on classification items of all layers may not be necessary. For example, in the case of the parameter of the distribution function for the ion implantation distribution, if the inclination of the wafer substrate with respect to the ion implantation direction is 0 °, classification of the rotation direction of the wafer substrate is not necessary. When the inclination of the wafer substrate with respect to the ion implantation direction is 0 °, the impurity concentration distribution is the same regardless of the rotation direction of the wafer substrate, and therefore the same parameter is used for any rotation direction. Accordingly, the “rotation direction” classification item is not necessary in the database for the value of the “substrate tilt” classification item of 0 °. However, in the conventional database, it is necessary to provide the classification item of “rotation direction” as described above. When the substrate tilt is 0 °, the data group for the rotation direction value is 0 ° and the rotation direction value is 20 °. Even if the data group for ° is the same, it is necessary to store these data groups in the database in duplicate.
[0014]
Referring to FIG. 3 as an example, if the hierarchical structure A is the classification item of “wafer substrate tilt”, when the value is 0 °, the value of “rotation direction” of the lower layer B is 0 °. Each data group is the same even if the angle is 15 °. That is, data DATA # 4 and DATA # 5 of layer B value = 0 or lower and the data group of layer B value = 15 or lower are the same, so the data group of layer B value = 15 or lower is unnecessary. A dummy data group 20 is formed.
[0015]
However, in order to construct a database and extract data from the database, it is necessary to store even a duplicate data group such as the dummy data group 20 in the database, and it takes time to construct the database. Also, in maintaining the database, when certain data is changed, it is necessary to change the same data in the dummy data group, which requires man-hours for maintenance. Further, when data is extracted, it is necessary to perform interpolation calculation for the classification items of each layer. However, the above-described dummy data group 20 must also be subjected to interpolation calculation, which increases the number of data extraction steps. Have.
[0016]
Therefore, an object of the present invention is to provide a simplified database and a data extraction program therefor without the need to provide a dummy data group.
[0017]
[Means for Solving the Problems]
In order to achieve the above object, according to a first aspect of the present invention, there is provided a multi-hierarchical database that stores a plurality of data corresponding to a plurality of classification item values and is capable of extracting data by a computer.
The plurality of classification items are associated with each layer and constructed in multiple layers, each having a plurality of elements having the name of the classification item and its value,
At least a plurality of lower-layer elements are associated with the upper-layer elements, and the multi-layer structure is constructed by associating data with the lower-layer elements, and the first-layer first elements are A plurality of elements in a second layer below the first layer are associated, and a plurality of elements in a third layer below the second layer are directly related to the second element in the first layer It is characterized by being associated.
[0018]
According to the first aspect described above, when the data of the element value of the second layer does not depend on the value of the second element of the first layer, the element of the second layer is omitted. Thus, since the hierarchical structure is constructed, it is unnecessary to have the same data group redundantly unnecessarily.
[0019]
In order to achieve the above object, the second aspect of the present invention searches the database of the first aspect in response to an input condition comprising a combination of values of a plurality of classification items, and In a data extraction program for causing a computer to execute a data extraction procedure for extracting data corresponding to a combination of classification item values,
A first step of detecting a pair of elements having values close to the input condition in each layer from the top layer to the bottom layer according to the input condition;
Corresponding to the hierarchy by executing interpolation calculation based on the value of the pair of elements for a pair of data that is repeated in order from the bottom layer to the top layer and associated with a pair of elements in each layer A second step of extracting data corresponding to the value of the input condition to be performed and associating the extracted data with an upper layer element;
In the second step, when there is no element having a corresponding classification item in the hierarchy being executed, the interpolation calculation based on the value of the classification item is not performed.
[0020]
According to the second aspect, interpolation calculation is reduced in the data extraction process.
[0021]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the present invention will be described below with reference to the drawings. However, the protection scope of the present invention is not limited to the following embodiments, but extends to the invention described in the claims and equivalents thereof.
[0022]
FIG. 4 is a diagram showing an example of a database structure in the present embodiment. The database shown in FIG. 4 is constructed by building the database shown in FIG. 3 according to the present embodiment. Similar to the example shown in FIG. 3, the first hierarchy A and the second hierarchy B below the data root of the root element RELM. And a third hierarchy C and data groups DATA # 1 to DATA # 5 associated with the third hierarchy. The element ELM of the database in FIG. 4 includes the names of classification items A to C corresponding to the respective hierarchies and their values. For example, the elements ELM11 and ELM12 in the first hierarchy have a classification item name A and values value = 0 and 10, respectively. Similarly, the elements ELM21 and ELM22 in the second hierarchy have the classification item name B and the values value = 0 and 15, respectively, and the elements ELM31 to ELM38 in the third hierarchy have the classification item name C and the value value = 1. , 5, 10, 1, 5 respectively. Then, at least a plurality of lower-layer elements are associated with the upper-layer elements, and data is associated with each of the lower-layer elements to construct the multi-layer structure.
[0023]
4 is characterized in that a plurality of elements ELM21... In a second layer B below the first layer A with respect to the first element ELM12 in the first layer A. The ELM 22 is associated, and the plurality of elements ELM 37 and ELM 38 in the third layer C lower than the second layer B are directly associated with the second element ELM 11 in the first layer A. That is, in the second layer B, the element of the third layer C is directly associated with the second element ELM11 of the first layer A without the element 22 of the second layer B below. As a result, the dummy data group 20 provided redundantly in FIG. 3 disappears from the database of FIG. That is, the elements ELM37 and ELM38 of the third layer C and the data DATA # 4 and DATA # 5 associated therewith are provided in the database without overlapping.
[0024]
By adopting such a configuration, it is not necessary to redundantly provide data groups in the database, the database can be easily constructed and maintained, and the data extraction can be simplified.
[0025]
FIG. 5 is a diagram showing an example of an ion implantation distribution database in the present embodiment. In the database of FIG. 5, each element is described in a node type. Two elements ELM11 and ELM12 having the classification item name “substrate tilt (tilt)” and values 0 and 10 are associated with the first layer below the root element RELM, and the element ELM12 having a substrate inclination of 10 ° is associated with the first element. Two elements ELM21 and ELM22 having the classification item name “substrate rotation angle (rotate)” of the two layers and the values 0 and 20 are associated with each other. Further, under the elements ELM21 and ELM22, three elements ELM31, ELM32, and ELM33 having a classification item name “cover oxide film thickness (tox)” of the third layer and values 0, 5, and 10 are associated. Yes. On the other hand, under the substrate tilt of 0 ° of the first element, the classification item name “cover oxide film” of the third layer does not pass through the element of the classification item name “substrate rotation angle” of the second layer. Three elements ELM31, ELM32, and ELM33 are directly associated with each other. Under all the elements of the third layer, the elements ELM41, ELM42, ELM43 of the classification item name “injection energy (energy)”, values 1, 3, 5 of the fourth layer are associated. Parameters of rp, drp, γ, and β that specify the ion implantation distribution function are associated with the elements of the four layers as data.
[0026]
When the value of the substrate tilt, which is the classification item of the first layer, is 0 °, it does not depend on the substrate rotation angle of the classification item of the second layer, so A third layer element is associated with no intervening second layer element. Therefore, when the substrate tilt is 0 °, data groups classified into the cover oxide film thickness and the implantation energy are associated with each other regardless of whether the substrate rotation angle is 0 ° or 20 °.
[0027]
FIG. 6 is a diagram showing another example of the ion implantation distribution database in the present embodiment. This example is an example in which the same database as that in FIG. 5 is described in XML. Similar to the example in FIG. 5, the classification item “substrate tilt (tilt)” as the first layer below the root element, the second layer The classification item “substrate rotation angle (rotate)” as the third layer, the classification item “cover oxide film (tox)” as the third layer, and the classification item “injection energy (energy)” as the fourth layer. Parameters are associated with the elements of the four layers. When the substrate tilt tilt is 0, the element of the third layer cover oxide film (tox) is associated without the element of the second layer, thereby simplifying the hierarchical structure.
[0028]
7 and 8 are flowcharts of ion implantation distribution simulation in the present embodiment. In this example, the database corresponds to the parameter database, the classification item corresponds to the ion implantation condition, and the data corresponds to the parameter. Moreover, FIG. 9 is a figure explaining the recursive process of a data extraction process. FIG. 10 is a diagram for explaining the processing procedure in the data extraction process of the above flowchart, and a database DB 10 will be described as an example.
[0029]
In the ion implantation distribution simulation, a desired ion implantation condition is input as a value of a database classification item (S10), a parameter corresponding to the ion implantation condition input from the parameter database is extracted (S12), and an impurity concentration based on the extracted parameter is obtained. The impurity concentration distribution is output by the distribution function (S14). However, since the parameter database, which is a database, has only discrete values for each classification item, an interpolation calculation is performed on each layer based on the value of the input classification item (ion implantation condition) and input. It is necessary to extract a parameter corresponding to the value of the classified item (ion implantation condition).
[0030]
In the database DB10 of FIG. 10, the classification item A of the first layer, the classification item B of the second layer, and the classification item C of the third layer are associated under the data route. Therefore, as shown in FIG. 7, the parameter extraction procedure in step S12 includes a procedure (S121) for detecting a pair of elements having values close to the ion implantation conditions in all layers, and each detected pair. The data corresponding to the ion implantation condition which is the value of the classification item of the input condition is extracted by performing interpolation calculation based on the value of the pair of elements for the associated data, and the extracted data is This is a procedure (S122) in which the association with the element is repeated from the lowest layer to the highest layer.
[0031]
Taking the database DB10 of FIG. 10 as an example, when A = 3, B = 10, and C = 2 are input as extraction conditions, a pair of values that are close to the value of the extraction condition input in the first step S121. Elements are detected in each hierarchy. Since the extraction condition of the first layer is A = 3, there are two pairs of elements A = 0 and A = 10 adjacent to the extraction condition, and the second layer is close to the extraction condition B = 10. B = 0 and B = 20, and in the third layer, C = 1 and C = 3, which are close to the extraction condition C = 2. In this way, a pair of elements close to the extraction condition input from the database is detected and developed as in S121 of FIG.
[0032]
Then, in step S122, interpolation calculation is repeatedly performed on the developed database from the lowest layer to the highest layer. In the second procedure S122 of the data extraction process shown in FIG. 8, it is determined whether or not there is data associated with the element in order from the root element to the lower element in the expanded database. Checked (S20), if it does not exist, it moves to the next lower layer, and the data extraction procedure S122 of FIG. 8 is recursively executed. When reaching the lowermost layer, interpolation calculation is performed from a pair of data related to the pair of elements according to the extraction condition, data corresponding to the extraction condition is extracted, and the extracted data is associated with the upper layer element. When the processing of the lowermost layer is finished, the return moves to the upper layer, and the same interpolation calculation is repeated recursively.
[0033]
As shown in FIG. 9, in the recursive data extraction procedure, the interpolation calculation in each of the hierarchies A, B, and C is repeated in the order of steps S100 to S109 starting from the data route for the developed database. . That is, for the hierarchical database, the interpolation calculation is repeated in order from the bottom layer to the top layer by the recursive procedure of FIG.
[0034]
Specifically, taking the expanded database S121 of FIG. 10 as an example, as shown in step S122, there is associated data in the elements A = 0 and A = 10 of the first layer from the data route. Therefore, it moves to a pair of elements C = 1, C = 3 in the lower layer of the element A = 0, and interpolates the pair of data associated with them based on the extraction condition C = 2. The associated data is associated with the upper element A = 0. Similarly, since it moves to a pair of elements B = 0, B = 20 in the lower layer of the element A = 10 and no data is associated with these elements, the lower element C = 1, in the element B = 0. Moving to C = 3, an interpolation operation is performed, data corresponding to the extraction condition C = 2 is extracted, and associated with the element B = 0. Further, the element C = 1, C = 3 under the element B = 20 is moved to perform an interpolation operation, data corresponding to the extraction condition C = 2 is extracted, and associated with the element B = 20. As a result, data is associated with a pair of elements B = 0 and B = 20. Therefore, the second layer is moved, interpolation calculation is performed with B = 10 for a pair of data associated with the elements B = 0 and B = 20, and the obtained data is changed to the upper layer element A = 10. Associate. Finally, the process moves to the first layer, and interpolation calculation is performed with A = 3 for a pair of data associated with elements A = 0 and A = 10, and the obtained data is associated with the data route. Data associated with the data route is data corresponding to the input condition.
[0035]
As is clear from the data extraction process described above, the database in the present embodiment does not needlessly duplicate the same data, so there is no need to duplicately perform interpolation calculations at each layer. Accordingly, there is an advantage that the processing speed is increased also in the data extraction procedure.
[0036]
FIG. 11 is a class diagram of the data extraction program in the present embodiment. It is a class diagram of a program described by object-oriented JAVA (registered trademark) or the like. 50 to 65 are classes, and 50E to 52E and 60E are descriptions of corresponding classes. The data extraction class 50 is a main class of data extraction processing, and has a database and extraction target data as variables and an extraction calculation as a method. The database class 51 has a database file as a node type variable. Specifically, it is the database shown in FIG. The data class 52 is a class that defines data to be extracted, and has variable extraction condition data and parameter data associated therewith.
[0037]
The classification item class 60 is a superclass of a class that defines the processing of the classification item of each layer, and has two classification items of the selected lower layer and values (double values) of the classification items as variables. It has data interpolation calculation as a method. Corresponding to this super class, it has a TILT class 61, a rotation angle class 62, an oxide film thickness class 63, and an energy class 65 that define processing in each layer. FIG. 11 also shows a dose class 64 corresponding to an ion implantation amount not included in FIG. However, this Dose class is excluded from the following description. Only the lowest class Energy class 65 includes a pair of data, but the upper classes 61 to 63 do not include data.
[0038]
FIG. 12 is a diagram showing a database in which a pair of elements is expanded from each layer in accordance with the extraction conditions illustrated for the database of FIG. This expansion process is as described above.
[0039]
FIG. 13 is a diagram for explaining the operation of the data extraction program shown in the class diagram of FIG. Along with the execution of the data extraction class 50, necessary classification item classes are expanded using child nodes (S121). The classification item class developed here corresponds to each element in FIG. 11, and a pair of data data 1 and 2 and the value value of the classification item are given to the energy class at the lowest layer. Under the TILT class 61, the oxide film thickness class 63 (1) is developed for the classification item sel1 without going through the rotation angle class, and for the classification item sel2, the oxide film thickness is passed through the rotation angle class 62. Thickness classes 63 (2) and 63 (3) are developed. Energy classes 65 (1) to 65 (6) are developed under each oxide film thickness class.
[0040]
Then, in the Energy class having the data data1 and data2 as variables, the interpolation calculation defined in the method is performed, and the obtained data is associated with the upper class as the Data class. Furthermore, interpolation calculation is performed on the upper layer class associated with the Data class, and the data class is similarly associated with the upper layer class. Finally, when the interpolation calculation is completed in the TILT class, the data extracted in the data extraction class 50 is associated as the DATA class.
[0041]
As described above, the database in this embodiment has a classification item name and value for each element, and if the data to be extracted does not depend on the value of the classification item, the classification item is omitted and a multi-layer structure is constructed. Therefore, there is no dummy data area, the construction and maintenance of the database is facilitated, and the interpolation calculation in data extraction can be reduced.
[0042]
In the above embodiments, the database of ion implantation distribution has been described as an example, but the present invention can be similarly applied to other databases for simulation and the like.
[0043]
The exemplary embodiments are summarized as follows.
[0044]
(Supplementary note 1) In a multi-tier database that stores a plurality of data corresponding to a plurality of classification item values and can be extracted by a computer,
The elements each having a name of the classification item and a value thereof, and having a plurality of elements constructed in multiple layers in association with each of the plurality of classification items,
At least a plurality of lower-layer elements are associated with the upper-layer elements, and the multi-layer structure is constructed by associating data with the lower-layer elements, and the first-layer first elements are A plurality of elements in a second layer below the first layer are associated, and a plurality of elements in a third layer below the second layer are directly related to the second element in the first layer A multi-level database characterized by being associated.
[0045]
(Appendix 2) In Appendix 1,
The plurality of classification items are a plurality of setting conditions in ion implantation, the data is a parameter of an impurity concentration distribution function, the classification item name of the first layer is a substrate tilt, and the first layer of the first layer The element 2 has a substrate tilt value of 0 °, the first element is a substrate tilt value other than that, and the classification item name of the second layer is a substrate rotation angle. A multi-tiered database.
[0046]
(Appendix 3) In Appendix 1,
A database having a multi-hierarchy structure, wherein the plurality of elements in each hierarchy have the same classification item name and different values.
[0047]
(Additional remark 4) Data extraction which searches the database of Additional remark 1 in response to the input condition which consists of the combination of the value of a some classification item, and extracts the data corresponding to the value combination of the said some classification item In a data extraction program that causes a computer to execute a procedure,
A first step of detecting a pair of elements having values close to the input condition in each layer from the top layer to the bottom layer according to the input condition;
Corresponding to the hierarchy by executing interpolation calculation based on the value of the pair of elements for a pair of data that is repeated in order from the bottom layer to the top layer and associated with a pair of elements in each layer A second step of extracting data corresponding to the value of the input condition to be performed and associating the extracted data with an upper layer element;
In the second step, when there is no element having a corresponding classification item in the hierarchy being executed, an interpolation calculation based on the value of the classification item is not performed.
[0048]
(Appendix 5) In Appendix 4,
The database is
The plurality of classification items are a plurality of setting conditions in ion implantation, the data is a parameter of an impurity concentration distribution function, the classification item name of the first layer is a substrate tilt, and the first layer of the first layer The element 2 has a substrate tilt value of 0 °, the first element is a substrate tilt value other than that, and the classification item name of the second layer is a substrate rotation angle. A data extraction program.
[0049]
(Supplementary note 6) A plurality of ion implantation conditions including at least the tilt of the substrate with respect to the ion implantation direction and the rotation angle of the substrate are classified items, and data of a plurality of impurity concentration distribution function parameters corresponding to the values of the plurality of classified items In a multi-layered database that can be stored and extracted by a computer,
The elements each having a name of the classification item and a value thereof, and having a plurality of elements constructed in multiple layers in association with each of the plurality of classification items,
At least a plurality of lower-layer elements are associated with the upper-layer elements, and the data is associated with the lower-layer elements to construct the multi-hierarchy structure,
A plurality of elements of a second layer corresponding to a rotation angle of the substrate below the first layer are associated with the first element of the first layer corresponding to the tilt of the substrate, and the first element A plurality of elements of a third layer below the second layer are directly associated with a second element of the first layer, the second element of the first layer having a substrate tilt value of 0 ° And the first element is a value of the other substrate tilt.
[0050]
【The invention's effect】
As described above, according to the present invention, a multi-hierarchical database can be simplified, and the construction and maintenance of the database and the data extraction are facilitated.
[Brief description of the drawings]
FIG. 1 is a configuration diagram of an ion implantation distribution simulator.
FIG. 2 is a diagram showing an impurity concentration distribution when ions are implanted and an impurity concentration distribution function generated by simulation.
FIG. 3 is a diagram illustrating an example of a parameter database structure included in a conventional general-purpose simulator;
FIG. 4 is a diagram showing an example of a database structure in the present embodiment.
FIG. 5 is a diagram showing an example of an ion implantation distribution database in the present embodiment.
FIG. 6 is a diagram showing another example of an ion implantation distribution database in the present embodiment.
FIG. 7 is a flowchart of ion implantation distribution simulation in the present embodiment.
FIG. 8 is a flowchart of ion implantation distribution simulation in the present embodiment.
FIG. 9 is a diagram illustrating a recursive process of a data extraction process.
10 is a diagram for explaining a processing procedure by a data extraction process in the flowchart of FIG. 9; FIG.
FIG. 11 is a class diagram of a data extraction program in the present embodiment.
12 is a diagram showing a database in which a pair of elements is expanded from each layer in accordance with the extraction conditions illustrated for the database in FIG. 5. FIG.
13 is a diagram for explaining the operation of the data extraction program of FIG. 11;
[Explanation of symbols]
ELM: element, A, B, C: name of classification item, value: value
10: Database of parameters, 12: Simulation program

Claims (5)

In a multi-tiered database that stores multiple data corresponding to the values of multiple classification items and can be extracted by a computer,
The elements each having a name of the classification item and a value thereof, and having a plurality of elements constructed in multiple layers in association with each of the plurality of classification items,
At least a plurality of lower-layer elements are associated with the upper-layer elements, and the multi-layer structure is constructed by associating data with the lower-layer elements, and the first-layer first elements are A plurality of elements in a second layer below the first layer are associated, and a plurality of elements in a third layer below the second layer are directly related to the second element in the first layer A multi-level database characterized by being associated. In claim 1,
The plurality of classification items are a plurality of setting conditions in ion implantation, the data is a parameter of an impurity concentration distribution function, the classification item name of the first layer is a substrate tilt, and the first layer of the first layer The element 2 has a substrate tilt value of 0 °, the first element is a substrate tilt value other than that, and the classification item name of the second layer is a substrate rotation angle. A multi-tiered database. In response to an input condition composed of a combination of values of a plurality of classification items, a data extraction procedure for searching the database described in Appendix 1 and extracting data corresponding to the combination of values of the plurality of classification items is performed on a computer In the data extraction program to be executed,
A first step of detecting a pair of elements having values close to the input condition in each layer from the top layer to the bottom layer according to the input condition;
Corresponding to the hierarchy by executing interpolation calculation based on the value of the pair of elements for a pair of data that is repeated in order from the bottom layer to the top layer and associated with a pair of elements in each layer A second step of extracting data corresponding to the value of the input condition to be performed and associating the extracted data with an upper layer element;
In the second step, when there is no element having a corresponding classification item in the hierarchy being executed, an interpolation calculation based on the value of the classification item is not performed. In claim 3,
The database is
The plurality of classification items are a plurality of setting conditions in ion implantation, the data is a parameter of an impurity concentration distribution function, the classification item name of the first layer is a substrate tilt, and the first layer of the first layer The element 2 has a substrate tilt value of 0 °, the first element is a substrate tilt value other than that, and the classification item name of the second layer is a substrate rotation angle. A data extraction program. A plurality of ion implantation conditions including at least the tilt of the substrate with respect to the ion implantation direction and the rotation angle of the substrate are classified items, and data of a plurality of impurity concentration distribution function parameters are stored corresponding to the values of the plurality of classified items, In a multi-level database that can be extracted by a computer,
The elements each having a name of the classification item and a value thereof, and having a plurality of elements constructed in multiple layers in association with each of the plurality of classification items,
At least a plurality of lower-layer elements are associated with the upper-layer elements, and the data is associated with the lower-layer elements to construct the multi-hierarchy structure,
A plurality of elements of a second layer corresponding to a rotation angle of the substrate below the first layer are associated with the first element of the first layer corresponding to the tilt of the substrate, and the first element A plurality of elements of a third layer below the second layer are directly associated with a second element of the first layer, the second element of the first layer having a substrate tilt value of 0 ° And the first element is a value of the other substrate tilt.

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