Solid surface treatment device and method

Abstract

To provide a solid surface treatment device and method that can perform sufficient surface treatment with high accuracy with a small number of trimming scans when trimming solids such as thin films using GCIB.SOLUTION: In a solid surface treatment device that flattens the surface of a solid using a gas cluster ion beam, a predetermined filtering process is first performed on the film thickness of the solid, a surface profile simulation of the solid is performed from the result of the predetermined filtering process on the solid and a trimming profile of the gas cluster ion beam calculated from a removal amount function, surface processing (Trimming) of the solid is performed based on the result of the surface profile simulation of the solid, the result of the surface processing (Trimming) is measured, the measured result of the surface processing is compared with a target value (Target), and the processing is repeated until the result of the surface processing matches the target value.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a solid surface processing apparatus and method for processing the surface of a solid, such as an optical thin film or a semiconductor wafer, by irradiating the surface of the solid with a gas cluster ion beam (GCIB). [Background technology]

[0002] In recent years, film thickness and surface roughness have been identified as device parameters that determine the functionality of metal electrodes in RF filters, MEMS, photonic devices, and so on. What is required here is post-processing to smooth the surface of the solid at the nanometer level and achieve the desired film thickness, i.e., surface treatment (trimming) to make the thickness of the solid uniform. Gas cluster ion beams (GCIBs) are attracting attention as a trimming source because, unlike monomer ion beams, atoms in the irradiated area are not only sputtered but also move laterally parallel to the wafer surface, which is known as the lateral sputtering effect, making the surface more likely to be flattened.

[0003] On the other hand, although the beam diameter focused through an Einzel lens or the like is on the order of a few mm, the ion current in the beam cross section is not uniform and forms a profile with a peak at the center of the beam. Therefore, it is known that the etching rate distribution in the beam cross section roughly reflects the current profile. Therefore, in order to achieve a uniform and desired film thickness within the target trimming area of ​​a solid, such as an optical thin film, it was necessary to scan the beam and / or the solid while taking into account the beam's ion current profile and / or trimming distribution.

[0004] [Patent Document 1] Patent No. 52312382 DISCLOSURE OF THE INVENTION [Problem to be solved by the invention]

[0005] However, the conventional method for achieving a uniform and desired film thickness has been to irradiate the beam on different etching locations one after another, measure the film thickness when the etching is complete, and if there are any high locations, etch further to reduce the film thickness distribution. This process of trimming and measurement is repeated until the desired film thickness distribution is achieved.

[0006] Another conventional method involves varying the scan speed and acceleration to equalize the entire trimming area, again by repeating trimming and measurement to improve film thickness distribution. In other words, conventionally, the distribution was adjusted based solely on actual measurement results, which required repeated trimming and measurement, which took a lot of processing time and also posed the risk of over-trimming. Furthermore, as mentioned above, the film thickness distribution is measured before trimming. However, if the film thickness profile has steep irregularities, it is difficult to experimentally determine the beam dwell time and scan speed, and so trimming and measurement are repeated to make the film thickness distribution uniform. This makes the process more complicated, requiring more repetitions, and can result in a film thickness distribution that differs from the expected one. Furthermore, because beam parameters such as pressure, processing pressure, and acceleration voltage are strongly correlated with the beam trimming distribution, the trimming recipe must be experimentally adjusted from scratch every time the parameters are changed, which is a time-consuming and labor-intensive process.

[0007] The present invention has been made in response to the above-mentioned conventional problems, and aims to provide a solid surface treatment apparatus and method that can efficiently and precisely perform surface treatment to make the thickness of a solid uniform by performing noise removal processing and / or smoothing processing on the film thickness distribution measured before trimming.

[0008] Another object of the present invention is to provide a solid surface treatment apparatus and method that can perform highly accurate planarization and film thickness treatment with fewer trimming scans by optimizing the ion beam scanning method on the solid through simulation before trimming. [Means for solving the problem]

[0009] In order to achieve the above object, a solid surface treatment apparatus according to the present invention is a solid surface treatment apparatus that performs surface treatment to make a solid uniform in thickness by using a gas cluster ion beam, a control unit for controlling the surface treatment of the solid, The control unit (a) subjecting the solid film thickness to a predetermined filtering process; (b) performing a surface profile simulation of the solid from the result of the predetermined filtering process on the solid and the trimming profile of the gas cluster ion beam obtained by the removal amount function; (c) performing surface trimming of the solid based on the results of the surface profile simulation of the solid; (d) Measure the results of the surface treatment (Trimming), (e) comparing the measured surface treatment results with the target value (Target); (f) The process of (a) to (e) is repeated until the result of the surface treatment matches the target value.

[0010] Another feature of the present invention is a solid surface treatment apparatus that performs surface treatment to make the thickness of a solid uniform by using a gas cluster ion beam under the control of a control unit, comprising: A solid surface treatment method comprising the steps of: (a) performing a predetermined filtering process on the film thickness of the solid by the control unit; (b) performing a surface profile simulation of the solid by the control unit from the result of the predetermined filtering process on the solid and the trimming profile of the gas cluster ion beam obtained by the removal amount function; (c) performing surface trimming of the solid body by the control unit based on the results of the surface profile simulation of the solid body; (d) measuring the results of the surface treatment (Trimming) by the control unit; (e) comparing the measured surface treatment result with a target value (Target) by the control unit; (f) repeating the processes (a) to (e) by the control unit until the result of the surface treatment matches the target value. [Effects of the Invention]

[0011] According to the present invention, in the surface treatment (trimming) of a solid by GCIB, it is possible to perform sufficient planarization and film thickness processing with high accuracy with a small number of trimming scans. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a schematic diagram showing a configuration of a solid surface treatment apparatus 1 according to an embodiment of the present invention. [Figure 2] FIG. 2 is a block diagram of the internal configuration of the control unit 33 shown in FIG. [Figure 3] FIG. 3 is a flowchart of the solid surface treatment performed by the solid surface treatment apparatus 1 shown in FIG. [Figure 4] FIG. 4 is a functional block diagram of the surface treatment of the solid 27 performed by the control unit 33. [Figure 5] FIG. 5 is a functional block diagram of the pre-treatment 48 of a sample thin film 27 and the surface profile simulation process of the thin film 27, which are achieved by the surface profile simulation program. [Figure 6]FIG. 6 is an explanatory diagram showing an example of pre-processing in the pre-processing unit 55, an example of residence time map creation processing in the residence time map creation unit 61, and an example of GCIB recipe creation processing in the GCIB recipe creation unit 63. [Figure 7] FIG. 7 is a conceptual diagram conceptually expressing the selection process in the surface profile simulation process 51 shown in FIG. [Figure 8] FIG. 8 is an explanatory diagram conceptually showing how a dwell time map is calculated from the dwell time of a charged particle. DETAILED DESCRIPTION OF THE INVENTION

[0013] A solid surface treatment apparatus embodying the present invention and a solid surface treatment method using the same will be described below with reference to the drawings.

[0014] FIG. 1 is a schematic diagram showing the construction of a solid surface treatment apparatus according to the present invention. This solid surface treatment device is designed to perform surface treatment to make the thickness of a solid uniform, and examples of solids that can be used include optical thin films used in optical devices and semiconductor wafers used in semiconductor devices. In this embodiment, we will explain the case where the surface of an optical thin film is treated to flatten it to a desired thickness as a surface treatment for making the thickness of a solid uniform. Here, the surface treatment of a thin film consists of three processing elements: (a) removing surface roughness, (b) uniforming to a target thickness, and (c) patterning. The present invention is not limited to surface treatment of optical thin films, but can also be applied to flattening the surface of semiconductor wafers used in semiconductor devices, and further to fine patterns of any shape formed on a solid. The solid surface processing apparatus shown in FIG. 1 is merely an example, and any configuration may be used as long as it is a solid surface processing apparatus that executes a solid surface processing program including a surface profile simulation process, which will be described later.

[0015] As shown in FIG. 1, in the solid surface treatment apparatus 1 of this embodiment, a source gas 3 is injected into a vacuum cluster generation chamber 7 through a nozzle 5, and gas molecules of the source gas 3 are agglomerated in the cluster generation chamber 7 to generate clusters. Here, the size of the clusters is determined by the particle size distribution based on the size and shape of the nozzle 5 and the gas pressure and temperature at the nozzle outlet 5a.

[0016] The clusters generated in the cluster generation chamber 7 are passed through a skimmer 9 and introduced as a gas cluster beam 11, where they are irradiated with thermal electrons by an ionizer 13, ionizing the neutral clusters and forming an ionized gas cluster beam (GCIB) 15. The GCIB 15 is accelerated by an accelerating electrode 17 , focused by a magnetic field concentrator 19 , and injected into a sputtering chamber 21 . The GCIB 15 that enters the sputtering chamber 21 has a positive charge. The positively charged GCIB 15 is electrically neutralized by the neutralizer 23, and the beam diameter is adjusted by the aperture 25 to a predetermined value, and the beam is irradiated onto the surface of the solid target 27. In this embodiment, an optical thin film is applied as a solid.

[0017] Behind the thin film 27 as a solid target, a Faraday cup 28 made of a metal cup is provided at a position a predetermined distance behind the thin film 27 to capture and detect charged particles in a vacuum. The sputtering chamber 21 is filled with a rare gas such as Ar, and by using a chemically active gas (such as SF6), it is possible to process (trimming) the surface of the thin film 27, which is the target.

[0018] A target 27, which is a thin film to be irradiated with GCIB, is fixedly attached to a target support 29 provided in the sputtering chamber 17 via a rotating disk. In this case, a target support 29 is attached so that the GCIB 15 irradiates the surface of the thin film 27, which is the target, that is, the surface to be processed, at a predetermined irradiation angle.

[0019] This solid surface treatment device 1 is equipped with an irradiation angle / direction setting mechanism (not shown) that can change the irradiation angle and irradiation direction of the GCIB 15, as well as a scanning mechanism (not shown) that changes the relative position of the thin film 27 in the XY directions with respect to the GCIB 15.

[0020] Furthermore, this solid surface processing apparatus 1 is provided with a pattern structure measuring apparatus 31 such as an atomic force microscope for measuring the pattern structure (microstructure) of the thin film 27 and obtaining shape data thereof, and the measured shape data is input to a control unit 33 described later.

[0021] This solid surface processing apparatus 1 is equipped with a control unit 33 consisting of a personal computer or the like, which performs a process (process for making the thickness of the thin film 27 uniform) to flatten the thin film surface as described below to obtain a desired film thickness, and also performs control to obtain a GCIB recipe as described below by simulating the surface profile within the thin film plane using the measured GCIB trimming profile in order to optimize the scan pattern, which is the trajectory traced by the gas cluster beam (GCIB) 15, before the solid surface processing. For this purpose, the control unit 33 stores a solid surface processing program for executing processing to flatten the thin film surface to a desired film thickness, as well as a surface profile simulation program for simulating the surface profile of the solid.

[0022] FIG. 2 is a block diagram of the internal configuration of the control unit 33 shown in FIG. As shown in FIG. 2, the control unit 33 is a personal computer (PC) configured to have a RAM 35, a ROM 37, a display monitor 39, a keyboard 41, and a mouse 43 connected to a CPU 45, and the CPU 45 is configured to perform the control described below in accordance with a solid surface treatment program and a surface profile simulation program stored in the ROM 37, based on instructions input by an operator via the keyboard 41 and the mouse 43. The solid surface treatment program may include a surface profile simulation program.

[0023] Next, a method for treating the surface of a thin film using the solid surface treatment apparatus 1 will be described. Here, the solid surface treatment method is described as a method for planarizing the surface of the thin film 27 to obtain a desired film thickness, but the present invention can also be applied to planarizing the surface of a semiconductor wafer such as a silicon substrate. FIG. 3 is a flowchart of the surface treatment performed by the solid surface treatment apparatus 1 shown in FIG. In this surface treatment, a surface profile simulation process is performed to optimize the scan pattern of the surface of the thin film 27 in order to obtain a thin film that is flattened to a desired thickness.

[0024] First, in step 101 of FIG. 3, the control unit 33 performs pretreatment of the thin film 27. That is, as shown in FIG. 4, predetermined filtering is performed on the film thickness (Wafer thickness) of the thin film 27 as a pre-processing. The film thickness (Wafer thickness) of the thin film 27 is obtained from the surface profile of a sample measured in advance. FIG. 4 is a functional block diagram of the surface treatment of the thin film 27 performed by the control unit 33. As shown in FIG. This filtering is performed using a filter such as a Kalman filter, a median filter, or a Conv filter. The filtering performed as pre-processing 48 here is for noise removal. In other words, due to defects in the thin film (nodules, pits, etc.) and measurement noise from the measuring instrument, the measurement data obtained often deviates from the actual surface profile. Therefore, in the present invention, the filtering method described above is used to remove large and small noises present in the measurement data. Specifically, the SN ratio of each of the above filters is calculated, the SN ratios of the filters are compared, and the filter with the largest SN ratio is selected. This allows for an accurate film thickness distribution to be obtained. Although the Kalman filter, median filter, and Conv filter have been mentioned as examples of filters used in the filtering process in the pre-processing unit 55, any filter other than the above-mentioned filters may be used as long as it can remove noise from the measured value and bring it closer to the actual surface profile.

[0025] Next, in step 103, the control unit 33 performs a surface profile simulation process 51 to simulate the surface profile within the thin film surface based on the film thickness of the thin film 27 filtered as preprocessing 48 and the trimming profile of the GCIB (see Figure 4). The trimming profile of the GCIB is determined by a removal amount function based on a previously measured GCIB profile. Here, the surface profile simulation process 51 involves designing a residence time algorithm from the results of filtering performed as pre-processing 48 on the film thickness of the thin film 27 as a sample and the GCIB trimming profile obtained by the removal amount function, as shown in FIG. 5 . The GCIB is controlled by the scanning speed and acceleration. Here, the scanning speed is set to 0 mm / s, and the time during which the beam stays in one place and digs deep is defined as the dwell time. The trimming profile of the GCIB of the thin film 27 as the sample is determined by a removal amount function, which will be described later. The surface profile simulation of the thin film 27 is performed by the control unit 33 in accordance with a surface profile simulation program. Here, the pretreatment 48 of the thin film 27 as a sample and the surface profile simulation process 51 achieved by the surface profile simulation program shown in FIG. 4 can be regarded as a black box achieved by the surface profile simulation program described above. FIG. 5 is a functional block diagram of the pre-treatment 48 of the sample thin film 27 and the surface profile simulation process of the thin film 27, which are achieved by the surface profile simulation program described above. That is, in FIG. 5, the pre-treatment 48 and surface profile simulation process 51 of the thin film 27 as the sample are expressed as a black box 53 achieved by the surface profile simulation program described above.

[0026] As shown in FIG. 5, the black box 53 achieved by the above-mentioned surface profile simulation program is composed of a preprocessing unit 55 that performs filtering as preprocessing 48 on the film thickness (Wafer thk) of the thin film 27 as a sample, a selection processing unit 57 that performs selection processing of a method for designing the above-mentioned dwell time algorithm (DTA) based on the result of the preprocessing 48 by the preprocessing unit 55, a dwell time algorithm (DTA) design unit 59 that designs a dwell time algorithm (DTA) based on the GCIB trimming profile obtained from the combination of five elements selected by the selection processing unit 57 and the removal amount function, a dwell time map creation unit 61 that creates a dwell time map based on the dwell time algorithm (DTA) designed by the dwell time algorithm (DTA) design unit 59, and a GCIB recipe creation unit 63 that creates a GCIB recipe based on the dwell time map from the dwell time map creation unit 61.

[0027] Next, each part of this black box 53 will be described. First, in the pre-processing unit 55, as described above, the film thickness (Wafer thk) of the thin film 27 as a sample is filtered by passing it through any filter such as a Kalman filter, a median filter, or a Conv filter. Here, the filter used in the above filtering process may be any filter other than those mentioned above, as long as it can remove noise from the measured value and bring it closer to the actual surface profile. FIG. 6 is an explanatory diagram showing an example of pre-processing in the pre-processing unit 55, an example of residence time map creation processing in the residence time map creation unit 61, and an example of GCIB recipe creation processing in the GCIB recipe creation unit 63. FIG. 6(a) is a diagram showing how data on the film thickness (Wafer thickness) of the thin film 27 as a sample is subjected to a median filter as preprocessing.

[0028] Next, the selection processing unit 57 is a process that automatically combines five elements: a layering module, a re-mapping module, a deconvolution solver AD (Deconvolution solver AD), an iterative module, and a calibration module, and is composed of at least one of the five elements. Here, the above five elements are automatically combined to create the best possible combination. In other words, the algorithm used in the simulation (DTA: Dwell Time Algorithm) goes through a series of steps consisting of layer division processing, remapping, deconvolution processing, iteration processing, and calibration processing, and since each step has multiple options, the number of combinations is enormous. Therefore, here, the root mean square (rms) of the residual error for all combinations is automatically calculated, so that the optimal solution can be found automatically. That is, the root mean square (rms) of each combination of layer division processing, remapping, deconvolution processing, iterative processing, and calibration processing is calculated, and the smallest calculation result is automatically selected. Furthermore, since the smallest rms value does not necessarily represent the true distribution in a unique distribution, users can refer to the rms value to select a combination that more closely resembles the true distribution and incorporate it into their recipes. Here, the layering module is a process that freely selects from 1st layer, 2nd layer to Nth layer, the re-mapping module is a process that freely selects the edge processing method for film thickness data, the deconvolution solver AD is a process that freely selects algorithms such as FFT, the iteration module is a process that freely selects the number of iterations from 1st, 2nd to Nth, and the calibration module is a process that corrects the trimming distribution of the beam. FIG. 7 is a conceptual diagram conceptually expressing the selection process in the surface profile simulation process 51 shown in FIG. As shown in FIG. 7, the thickness of the thin film 27 is subjected to an optimization process to obtain a residence time map. A feature of the present invention is that it is possible to design an algorithm that involves many processes and complex combinations.

[0029] Next, a dwell time algorithm (DTA) design unit 59 designs a dwell time algorithm (DTA) based on the combination of the five elements selected by the selection processing unit 57 and the trimming profile of the GCIB obtained by the removal amount function. Here, the dwell time refers to the time during which the GCIB, which is controlled by the scan speed and acceleration as described above, stops and stays in one place to dig deep, with the scan speed set to 0 mm / s, and the dwell time algorithm (DTA) is an algorithm for calculating the dwell time map from this dwell time. The design principle of this Dwell Time Algorithm (DTA) is explained. First, the removal volume Z(x,y) is modeled as the convolution between the ion beam removal volume function (BRF) b(x,y) and the dwell time map t(x,y) using the following equation (1): z(x, y) = b(x, y) * t(x, y) (1) Here, * indicates a convolution operation. From this point, a calculation is performed to obtain the dwell time map t(x, y) from the removal amount Z(x, y) and the ion beam removal amount function (BRF) b(x, y), which is a deconvolution process. Therefore, by obtaining a dwell time map using such a dwell time algorithm (DTA), a GCIB recipe can be created, and by using GCIB according to that recipe to make the film thickness of the thin film 27 uniform, more accurate surface treatment can be achieved.

[0030] Next, the stay time map creating unit 61 calculates a stay time map based on the stay time algorithm (DTA) designed by the stay time algorithm (DTA) design unit 59. That is, the staying time map t(x, y) is calculated using the above-mentioned formula (1). FIG. 8 is an explanatory diagram conceptually showing how a dwell time map is calculated from the dwell time of a charged particle. Figure 8 shows how the dwell time map is calculated by scanning from Figure 8(a) to Figure 8(c), and Figure 8(d) shows the results of the scan. In this way, the scan pattern can be optimized by obtaining a dwell time map using the dwell time algorithm (DTA). Then, a GCIB recipe is created from the residence time map, as described below, and the thickness of the thin film 27 can be made uniform by GCIB according to the recipe, thereby achieving highly accurate surface treatment. Furthermore, as a result of designing the above-mentioned dwell time algorithm (DTA) to obtain a dwell time map and optimizing the scan pattern, the number of times of surface treatment (trimming) of the thin film 27, which will be described later, is significantly reduced. FIG. 6(b) is a diagram showing an example of a dwell time map calculated based on the dwell time algorithm (DTA).

[0031] Next, the GCIB recipe creation unit 63 creates a GCIB recipe based on the residence time map t(x, y) from the residence time map creation unit 61. That is, from the residence time map t(x, y), for example, as shown in FIG. 6(c), the GCIB speed value at each position on the X axis and the GCIB speed value at each position on the Y axis are calculated as a GCIB recipe, and the surface treatment (trimming) 52 of the thin film 27 shown in FIG. 4 is performed using the GCIB recipe.

[0032] Next, returning to FIG. 3, in step 105, the control unit 33 performs surface treatment (trimming) 52 of the thin film 27 by GCIB using a GCIB recipe based on the residence time map obtained by the design process 51 of the residence time algorithm (DTA) (see FIG. 4). That is, here, the target surface of the thin film 27 is etched to trim (adjust) the pattern structure, flatten the target surface, and make the thin film 27 have a desired film thickness.

[0033] Next, the surface treatment (trimming) of the thin film 27 by GCIB will be described. In step 105, the etching amount is calculated from the GCIB recipe based on the residence time map obtained by the design process 51 of the residence time algorithm (DTA) so that the microstructure has the desired design size. Thereafter, the thin film 27 is set by an irradiation angle / direction setting mechanism (not shown) so that the thin film 27 has a predetermined irradiation angle θ and irradiation direction φ relative to the GCIB. In this case, the target support 29 is attached so that the GCIB 15 irradiates the surface of the thin film 27, which is the target, that is, the surface to be processed, at a predetermined irradiation angle. Then, together with the calculated etching amount, various conditions such as the material of the target thin film 27 and its etching rate, the GCIB gas species, and acceleration energy are set, and based on these various conditions, a database (not shown) is referenced to determine the dose amount, and the gas class ion beam irradiation process is performed based on that dose amount. That is, the control unit 33 controls the source gas 3 generation unit (not shown), ionizer 13, acceleration electrode 17, magnetic field concentrator 19, neutralizer 23, irradiation angle direction setting mechanism (not shown), scanning mechanism (not shown), etc. based on the dose amount, and gas class ion beam irradiation processing is performed on the surface of the thin film 27, and surface processing (trimming) processing of the thin film 27 by GCIB is performed.

[0034] Next, in step 107, the control unit 33 obtains the results of the film thickness, pattern, uniformity, etc. of the surface-treated thin film 27 (result evaluation 54 in FIG. 4). That is, the control unit 33 measures the transmission spectrum of the thin film 27 and performs an analysis taking into account the interference of light to determine the film thickness, and the film thickness distribution is obtained by measuring and analyzing the spectrum at different measurement points.

[0035] Next, in step 109, the control unit 33 compares the film thickness, pattern, uniformity, etc., which are the measured results of the surface treatment (trimming) of the thin film, with the target values ​​(Target) of the thin film, and determines whether the measured results of the surface treatment of the thin film are the target values ​​(Target) 56 of the thin film (see Figure 4).

[0036] If the result of the thin film surface treatment (trimming) measured in step 109 is equal to the thin film target value (Target) 56 (Yes), the entire thin film surface treatment is completed. This optimizes the scan pattern on the surface of the thin film 27, making the surface of the thin film 27 incredibly flat and achieving a desired film thickness. If the measured result of the surface treatment (trimming) of the thin film does not match the target value (Target) of the thin film (No), the process returns to the dwell time algorithm (DTA) design process 51 of step 101, and the control unit 33 repeats the processes of steps 101 to 107 until the result of the surface treatment (trimming) of the thin film matches the target value (Target). In this embodiment, as described above, a dwell time algorithm (DTA) is designed using surface profile simulation to obtain a dwell time map, so that the result of the thin film surface treatment (trimming) immediately matches the target value (Target) (for example, once). Therefore, with a very small number of thin film surface treatments (trimmings), the results of the thin film surface treatment (trimming) will match the target value (Target).

[0037] As described above, according to the embodiment of the present invention, the surface treatment (trimming) 52 for making the thickness of the thin film 27 uniform by GCIB is performed using a GCIB recipe based on a dwell time map obtained by a surface profile simulation including a dwell time algorithm (DTA) design process, so that highly accurate surface treatment can be performed with fewer trimming scans.

[0038] Although the present embodiment has been described above, the description and drawings that form part of this disclosure should not be understood as limiting, and various embodiments not described herein are also included. That is, the solid surface processing apparatus of this embodiment is merely an example, and any configuration may be used as long as it is a solid surface processing apparatus that executes a thin film surface flattening program including the surface profile simulation program. Furthermore, although the Kalman filter, median filter, and Conv filter have been cited as examples of filters used in the filtering process in the pre-processing unit 55 described above, any filter other than the above-mentioned filters may be used as long as it can remove noise from the measurement value and bring it closer to the actual surface profile. In this embodiment, the solid surface treatment apparatus is designed to perform surface treatment of thin films, but the solid can also be applied to semiconductor wafers used in semiconductor devices, and further, can be applied to fine patterns of any shape formed on a solid. [Explanation of symbols]

[0039] 1 Solid surface treatment device, 3 Raw material gas, 5 Nozzle 7···Cluster generation chamber, 9···Skimmer, 11···Gas cluster beam 13. Ionizer, 17. Acceleration electrode, 19. Magnetic field concentrator, 21...sputtering chamber, 23...neutralizer, 25...aperture, 27 Thin film (target), 28 Faraday cup, 33 Control unit, 35···RAM, 37···ROM, 39···Display monitor, 41···Keyboard, 43···Mouse, 45···CPU, 48···Preprocessing, 51. Surface profile simulation processing, 52. Surface treatment, 54 Measurement processing, 55 Preprocessing section, 56 Target value, 57 Selection processing section, 59: Stay time algorithm design unit, 61: Stay time map creation unit, 63···GCIB Recipe Creation Department

Claims

1. A solid surface treatment apparatus for performing surface treatment to make the thickness of a solid uniform by using a gas cluster ion beam, a control unit for controlling the surface treatment of the solid, The control unit (a) subjecting the solid film thickness to a predetermined filtering process; (b) performing a surface profile simulation of the solid from the result of the predetermined filtering process on the solid and a trimming profile of the gas cluster ion beam obtained by a removal amount function; (c) performing surface trimming of the solid based on the results of the surface profile simulation of the solid; (d) measuring the results of the surface treatment (Trimming); (e) comparing the measured surface treatment results with a target value (Target); (f) A solid surface treatment device for controlling the process, repeating the treatments (a) to (e) until the result of the surface treatment matches the target value.

2. a surface profile simulation of the solid, performing a method selection process for designing a residence time algorithm from the result of the predetermined filtering of the individual; designing a dwell time algorithm based on the trimming profile of the gas cluster ion beam and the selected method; Based on the design of the dwell time algorithm, we create a dwell time map (DTM), 2. The solid surface processing apparatus according to claim 1, further comprising a process of creating an irradiation recipe for the ion beam from the created dwell time map (DTM).

3. 3. The solid surface processing apparatus according to claim 2, wherein the method selection process is a process that automatically combines five elements: a layering module that freely selects 1 layer, 2 layers to N layers; a re-mapping module that freely selects an edge processing method for film thickness data; a deconvolution solver AD (Deconvolution Solver AD) that freely selects an algorithm such as FFT; an iteration module that freely selects the number of iterations from 1, 2 to N; and a calibration module that corrects the trimming distribution of the beam.

4. A solid surface treatment apparatus for performing surface treatment to make the thickness of a solid uniform by using a gas cluster ion beam under the control of a control unit, A solid surface treatment method comprising the steps of: (a) performing a predetermined filtering process on the film thickness of the solid by the control unit; (b) performing a surface profile simulation of the solid by the control unit from the result of the predetermined filtering process on the solid and a trimming profile of the gas cluster ion beam obtained by a removal amount function; (c) performing surface treatment (trimming) of the solid body based on the results of the surface profile simulation of the solid body by the control unit; (d) measuring the results of the surface treatment (Trimming) by the control unit; (e) comparing the measured surface treatment result with a target value (Target) by the control unit; (f) repeating the processes (a) to (e) by the control unit until the result of the surface treatment coincides with the target value.

5. A solid surface treatment program for causing the control unit to execute the solid surface treatment method according to claim 4.

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