Secondary ion mass spectrometry

Abstract

The SIMS-based analysis system includes: (a) a memory circuit configured to store (i) an estimated model of a SIMS-based non-planar three-dimensional (3D) structural element indicating changes undergone by the three-dimensional structural element during a sputtering process and (ii) a measured SIMS spectrum of the 3D structural element; (b) a calibration information circuit configured to acquire calibration information; (c) a SIMS simulation circuit configured to (i) provide an updated model of the three-dimensional structural element and (ii) provide a simulated SIMS spectrum of the three-dimensional structural element; and (d) a fitting circuit configured to determine at least one of shape and material concentration parameters based on the simulated SIMS spectrum and the measured SIMS spectrum.

Description

[Technical Field]

[0001] (cross reference) This application claims priority from U.S. Provisional Patent Application No. 63 / 476,948, filed December 22, 2022, which is incorporated herein in its entirety.

[0002] This application relates to secondary ion mass spectrometry. [Background technology]

[0003] As the metrology tolerances required to accurately and precisely quantify materials for semiconductor process control continue to expand with shrinking device dimensions, there is an increasing need to directly quantify complex 2D and 3D target geometries. For many years, material properties of solid-state film test structures have been considered surrogates that correlate well to final device performance. However, with more complex processes, materials, and shrinking dimensions, this correlation has become increasingly unreliable, and process metrology is shifting to more complex 2D and 3D test structures whose physical properties more closely match final device performance. Summary of the Invention

[0004] Systems, methods, and computer-readable media as exemplified herein may be provided.

[0005] Embodiments of the disclosure will be more fully understood from the following detailed description taken in conjunction with the following drawings. [Brief explanation of the drawings]

[0006] [Figure 1] This is an example of a system. [Figure 2] This is an example of a method. [Figure 3] This is an example of a method. [Figure 4] This is an example of a three-dimensional structural element divided into columns. [Figure 5] 10 is an example of a model and a gradient model. [Figure 6] 1 is an example of an iterative method. [Figure 7] 1 is an example of shape changes that occur during the sputtering process. [Figure 8] 1 is an example of a method that includes a regression process. [Figure 9] This is an example of a spectrum. [Figure 10] This is an example of a spectrum. [Figure 11] 1 is an example of a planar calibration sample. [Figure 12] 1 is an example of a calibration sample. DETAILED DESCRIPTION OF THE INVENTION

[0007] Secondary ion mass spectrometry (SIMS) has played an important role in the direct quantification of materials due to its direct compositional sensitivity. Furthermore, dynamic SIMS can provide direct depth sensitivity that not only quantifies material composition but also provides valuable description of one-dimensional depth profiles of atomic concentrations. SIMS is expected to play an increasingly important role in semiconductor process control in the future, and accurate quantification will require the ability to predict SIMS signals on complex 2D and 3D structures. Examples of SIMS systems and techniques are disclosed in U.S. Pat. No. 10,056,242, which is incorporated herein by reference.

[0008] SIMS is fundamentally an ion beam technique, requiring sophisticated ion source, charge, and mass resolution hardware to generate primary ion species (such as O+ or Cs-) and to generate and separate the secondary ions required for eventual detection and quantification. The resulting secondary ion signal intensity I for a given species X is X can be defined as follows:

[0009]

number

[0010] Here, I P is the primary ion beam current, Y is the sputter yield (removed atoms / incident primary ions), η X is the ion yield (the proportion of ions produced from the initially sputtered atoms), τ X is the transmission factor (the fraction of secondary ions that can pass and be detected). Finally, a X and C X is the isotope ratio and composition ratio of species X.

[0011] The sputter rate (removal rate of a given material with species X in z) can be expressed as:

[0012]

number

[0013] where the additional parameter D M and A rasterare the matrix density and raster area, respectively. The sputter yield and ion yield are fundamental properties of materials and compositions that, in principle, can vary somewhat over time (e.g., if the composition varies with depth or z). As a result, although the highly complex dynamics of SIMS sputtering can be empirically encoded into these useful material parameters, accurate quantification of unknown compositions should preferably be calibrated from known standards (reference materials). With appropriate calibration for solid films, the signal intensity vs. time can be converted to composition vs. depth in a relatively straightforward manner using the two equations above. Furthermore, for solid films, the correspondence between time and depth is essentially 1:1.

[0014] The situation becomes much more complicated in SIMS on structures where the erosion of surface material can no longer be considered a "planar" process due to the local topography relative to the main beam. Furthermore, the material can vary laterally (not just vertically). The sputtering process on the structure and the secondary ion signal produced can no longer be strictly correlated to physical depth relative to time.

[0015] As a result, the parameters in the above equations should preferably be considered to have an additional spatial dependence which can be written in the most general differential form as follows:

[0016]

number

[0017] Here, ΔI i Xis a local differential area ΔA on the surface of the structure i is the differential signal intensity at a given time from x i ,y i ,z i ,θ i is the difference domain ΔA i are the different coordinates at time t corresponding to the position of and the primary beam incidence angle (relative to the normal). The intensity generated by each local surface area is i M The sputtering process consumes material according to the local sputter rate, defined as the depth ΔZ sputtered in an incremental time interval Δt. i =S i M Δt is the result of local differential erosion on the structure, changing its shape over time and further influencing the local surface conditions for subsequent sputtering and signal generation. Y as a function of time i ,η i ,τ i The value of is not known a priori and is determined dynamically as sputtering of the structure progresses.

[0018] Then, the total signal strength from species X generated over time is given by n : It is just the sum of all differential surface intensities calculated at t0+nΔt.

[0019]

number

[0020] FIG. 1 shows an example of a SIMS-based analysis system 9, which includes: A. A memory circuit 10 configured to store (i) an estimated model 11 of a three-dimensional (3D) structural element and (ii) a measured SIMS spectrum 12 of the 3D structural element. The model indicates the estimated geometry of the 3D structural element and the estimated concentration of materials within the 3D structural element. The 3D structural element is non-planar. B. A calibration information circuit 20 configured to obtain calibration information regarding an estimated relationship between SIMS related parameters and concentrations of materials of the model, the SIMS related parameters including ion yield and sputter rate. C. A SIMS simulation circuit 30 configured to (i) provide an updated model of the 3D structural element indicative of changes undergone by the 3D structural element during the sputtering process, and (ii) provide a simulated SIMS spectrum of the 3D structural element, the simulated SIMS spectrum indicative of estimated SIMS-related parameters. D. A fitting circuit 40 configured to determine at least one of shape and material concentration parameters based on the simulated SIMS spectrum and the measured SIMS spectrum.

[0021] In one embodiment, the SIMS-related parameters further include primary ion impact energy and impact angle.

[0022] In one embodiment, the SIMS simulation circuit 30 is configured to iteratively simulate the sputtering process to provide an updated model of the D structural element and a simulated SIMS spectrum of the D structural element.

[0023] In one embodiment, the SIMS-based analysis system 9 further includes a discretization circuit 50 configured to virtually divide the estimated model of a reference D structural element into a grid of columns, each column being associated with column structural information and column material information.

[0024] In one embodiment, the difference circuits communicate with each other using a communication system 60 .

[0025] In one embodiment, the SIMS simulation circuit 30 is configured to simulate a column-by-column sputtering process.

[0026] In one embodiment, the fitting circuitry 40 is configured to perform a regression based fitting process.

[0027] In one embodiment, a regression-based fitting process is applied to the sputtering rate and ion yield values.

[0028] In one embodiment, the calibration information is obtained using measurements or simulations of planar test 3D structural elements.

[0029] In one embodiment, the calibration information is obtained further using measurements or simulations of non-planar test 3D structural elements.

[0030] In one embodiment, the calibration information is obtained using measurements or simulations of planar test 3D structural elements and using measurements or simulations of non-planar test 3D structural elements.

[0031] In one embodiment, the calibration information is obtained by further using measurements or simulations of a first non-planar test 3D structural element consisting of an open array of spaced apart lines, and a second non-planar test 3D structural element consisting of a filled array of spaced apart lines.

[0032] In one embodiment, the open array and the filled array each include (i) variations of critical dimensions within an estimated critical dimensions variation window, and (b) variations of pitch values ​​within an estimated pitch variation window.

[0033] In one embodiment, the SIMS simulation circuit 30 is configured to simulate mixing and roughness effects that affect the simulated SIMS spectrum by applying a mixing length per depth function and a roughness per depth function.

[0034] In one embodiment, the SIMS simulation circuit 30 is a library.

[0035] In one embodiment, the SIMS simulation circuitry performs the above-described simulation in real time (during the actual sputtering process).

[0036] In one embodiment, the SIMS simulation circuitry performs the above-described simulation offline (before the sputtering process is performed).

[0037] According to one embodiment, the blending length per depth function is equal to:

[0038]

number

[0039] where z is the depth from which ions are sputtered and w is the mixing length.

[0040] In one embodiment, the roughness function per depth is equal to:

[0041]

number

[0042] According to one embodiment, the SIMS-based analysis system further includes a model circuit 60 configured to generate an estimated model by applying a tilt operation to an initial estimated model, the tilt operation representing the tilt angle of the ion beam used during the sputtering process.

[0043] In one embodiment, the SIMS-based analysis system is part of a SIMS system that performs a sputtering process.

[0044] According to one embodiment, the SIMS-based analysis system is a computer system that is not the SIMS system that performs the sputtering process, and may be a remote computerized system or a computerized system in a cloud environment.

[0045] In one embodiment, the circuits described above are implemented by one or more processing circuits or are included in or implemented by one or more integrated circuits. One or more of the circuits described above may be implemented by a single integrated circuit. Additionally or alternatively, multiple circuits described above are implemented by multiple integrated circuits.

[0046] In one embodiment, memory unit 10 includes volatile memory and / or nonvolatile memory. Memory unit 10 may be random access memory (RAM) and / or read-only memory (ROM). In one embodiment, the nonvolatile memory unit is a mass storage device that can provide nonvolatile storage of computer code, computer-readable instructions, data structures, program modules, and other data for a processor or other units of the vehicle. For example, and without limitation, the mass storage device can be a hard disk, a removable magnetic disk, a removable optical disk, a magnetic cassette or other magnetic storage device, a flash memory card, a CD-ROM, a digital versatile disk (DVD) or other optical storage device, a random access memory (RAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), etc.

[0047] Any content can be stored in any part or type of memory unit.

[0048] FIG. 1 shows a communication system 130 that communicates with the various circuits and memory units 10 .

[0049] Communications system 130 may include a bus, which represents one or more of several possible types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures may consist of an Industry Standard Architecture (ISA) bus, a MicroChannel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, an Accelerated Graphics Port (AGP) bus, and a Peripheral Component Interconnect (PCI), PCI-Express bus, Personal Computer Memory Card Industry Association (PCMCIA), Universal Serial Bus (USB), and the like. Additionally, the bus and all buses specified in this specification may also be implemented in their respective subsystems via wired or wireless network connections.

[0050] FIG. 1 also shows a network 170 external to system 8, used for communication with other systems, such as a SIMS measurement system (not shown) or other remote computing systems. By way of example, the remote computing systems may be personal computers, laptop computers, portable computers, servers, routers, network computers, peer devices, or other common network nodes. Logical connections between the processor and any one of the remote computing systems may be made via local area networks (LANs) and common wide area networks (WANs). Such network connections may be made via network adapters (which may belong to communication system 170), which may be implemented in both wired and wireless environments. Such network environments are conventionally common in networks such as offices, enterprise-wide computer networks, intranets, and the Internet.

[0051] Figure 2 shows an example of a computer-implemented method 100 for SIMS-based analysis, which includes: A. Step 110 of storing, by a storage circuit, (i) an estimated model of a three-dimensional (3D) structural element and (ii) a measured SIMS spectrum of the 3D structural element, wherein the model indicates an estimated shape of the 3D structural element and an estimated concentration of material within the 3D structural element, and the 3D structural element is non-planar. B. Obtaining calibration information regarding the estimated relationship between the SIMS-related parameters and the material concentration of the model by the calibration information circuitry, step 120. The SIMS-related parameters include the ion yield and the sputter rate. C. Step 130, by the SIMS simulation circuit: (i) providing an updated model of the 3D structural element showing changes undergone by the 3D structural element during the sputtering process; and (ii) providing a simulated SIMS spectrum of the 3D structural element showing the estimated SIMS-related parameters. In one embodiment, the iteration is terminated when a predefined number of iterations has been performed and / or when the difference between the outcome of one iteration to a consecutive iteration is less than a threshold, preventing further iterations. D. Determining 140 by the fitting circuitry at least one of shape and material concentration parameters based on the simulated SIMS spectrum and the measured SIMS spectrum. In one embodiment, the fitting iterations are terminated when a predefined number of fitting iterations have been performed and / or when the difference between the results of one fitting iteration and the results of the successive fitting iteration is less than a threshold, preventing further fitting iterations.

[0052] In one embodiment, the SIMS-related parameters further include primary ion impact energy and impact angle.

[0053] In one embodiment, step 130 includes step 131 of iteratively simulating the sputtering process by a SIMS simulation circuit to provide an updated model of the 3D structural element and a simulated SIMS spectrum of the 3D structural element.

[0054] In one embodiment, method 100 further includes step 125 of virtually segmenting, by a discretization circuit, the estimated model of the standard (reference) 3D structural element into a grid of columns. Each column is associated with column structural information and column material information. In one embodiment, step 130 includes simulating a sputtering process for each column.

[0055] In one embodiment, step 140 includes performing a regression based fitting process.

[0056] In one embodiment, a regression-based fitting process is applied to the sputtering rate and ion yield values.

[0057] In one embodiment, the calibration information is obtained using measurements or simulations of a planar test three-dimensional structural element.

[0058] In one embodiment, the calibration information is obtained using further measurements or simulations of a non-planar test three-dimensional structural element.

[0059] In one embodiment, the calibration information is obtained using measurements or simulations of planar test 3D structural elements and using measurements or simulations of non-planar test 3D structural elements.

[0060] In one embodiment, the calibration information is obtained by further using measurements or simulations of a first non-planar test three-dimensional structural element comprising an open array of spaced apart lines and a second non-planar test three-dimensional structural element comprising a filled array of spaced apart lines.

[0061] In one embodiment, each of the open array and the filled array includes (i) a variation of the critical dimension within an estimated critical dimension variation window, and (b) a variation of the pitch value within an estimated pitch variation window.

[0062] In one embodiment, step 130 includes step 132 of simulating mixing and roughness effects that affect the simulated SIMS spectrum by applying a mixing length per depth function and a roughness per depth function.

[0063] In one embodiment, step 131 is performed in real time (during the actual sputtering process).

[0064] In one embodiment, step 131 is performed offline (before the sputtering process is performed).

[0065] In one embodiment, the blending length per depth function is equal to:

[0066]

number

[0067] where z is the depth to which the ions are sputtered and w is the mixing length.

[0068] In one embodiment, the roughness function per depth is equal to:

[0069]

number

[0070] In one embodiment, the method 100 includes an initialization step 105. The initialization step 105 can include generating an estimated model by applying a tilt operation to an initial estimated model, where the tilt operation represents the tilt angle of the ion beam used during the sputtering process. See model 240, which is converted to tilt model 242 using a normal incidence ion beam and tilted ion beam.

[0071] In one embodiment, a non-transitory computer-readable medium is provided that stores the following instructions: (a) a storage circuit stores (i) an estimated model of a three-dimensional (3D) structural element and (ii) a measured SIMS spectrum of the 3D structural element, the model indicating an estimated shape of the 3D structural element and an estimated concentration of material within the 3D structural element, where the 3D structural element is non-planar; (b) a calibration information circuit obtains calibration information regarding an estimated relationship between SIMS-related parameters and the concentration of material of the model, where the SIMS-related parameters comprise ion yield and sputter rate; (c) a SIM simulation circuit provides (i) an updated model of the 3D structural element, the updated model indicating changes undergone by the 3D structural element during the sputtering process; and (ii) a simulated SIMS spectrum of the 3D structural element, where the simulated SIMS spectrum indicates the estimated SIMS-related parameters; and (d) a fitting circuit determines at least one of the shape and material concentration parameters based on the simulated SIMS spectrum and the measured SIMS spectrum.

[0072] In the following, we define a physical model and methods that can be used for realistic calculation of SIMS signals over time.

[0073] It can be assumed that there exists a generalization of the sputtering and signal generation process on complex structures to "solid membranes" (meaning 3D structural elements with flat / planar top surfaces) where the material properties and orientation relative to the primary beam must be specified in a way that realistically accounts for changes in the underlying material and shape, along with a way to dynamically evolve the shape over time, in order to generate one or more SIMS profile signals from the sputtering process.

[0074] The steps of structure definition, parameter calibration, dynamic evolution of structure and signal generation are shown in the flowchart of Figure 3. See method 200 and steps 202, 204, 206, 208, 210, 212, 214, 216, and 220. Steps 202, 204, 205, and 208 follow one another. Step 210 is followed by step 212. Steps 212 and 214 are followed by step 208. An iteration includes the execution of steps 208 and 216. Method 200 ends at step 220.

[0075] Nominal process parameters and geometry descriptions are given below. A. Create an initial geometric model, including a geometric description of the 3D structure and material assignments for each material domain. Also includes the necessary parameterization of the 3D structure and its material properties. See steps 202 and 204. B. Discretize the geometrical model into a set of vertical “XY Grid of Columns”. i. Create columns of uniform grid density in the XY plane (206). ii. Each cell of the grid is the base of a "column of material." iii. Column of materials represents the columns, stacks of materials, and their heights. iv. If sputtering occurs perpendicular to the wafer surface, the columns are vertical. v. Alternatively, the column can be angled (tilted) relative to the surface according to the direction of the sputter beam. Figure 4 shows a side view of a 3D structural element that includes eight columns 230(1)-230(6). Note that the grid of columns may also be two-dimensional. C. Another requirement of this method is proper calibration of material properties specific to the SIMS sputtering process, which requires appropriate material specifications for the associated sputter rate, ionization efficiency, and angular dependence of the sputter rate dependence of these parameters. These parameters are calibrated or measured using a specially designed set of solid and patterned samples. See steps 210 and 212. D. Another input to the simulation engine is the details of the SIMS measurement experiment (beam orientation, beam voltage and current, raster area, etc.). See step 214. E. Single Simulation Step (Step 208): i. With all the above information it is possible to simulate the sputtering process (sputter rate, detection signal) at each point XY for a short time interval dT (for example 1 second). ii. The result of the simulation is a new 3D structure (after dT) and a measured signal (during dT). Figure 7 shows an example of a shape change over time as a result of the sputtering process, assuming different directions of the primary ion beam relative to the structure. In such cases, for example, the shape may have sloping sides or disconnected geometric regions that require additional physical modeling assumptions (such as kinematics and gravity effects). F. (Step 220) As a result, the above simulation steps are repeated iteratively (see step 216). i. Measured signal as a function of sputtering time. ii. The expected evolution of the 3D structure as a function of sputtering time.

[0076] Figure 6 is an example of iteration 260. See steps 252, 254, 256, 258, 260, 262, 264, 266, 268, 270, 270.

[0077] After the model and calculation method are defined, a direct comparison with measured data can finally be made, and optimization of structural and / or compositional parameters by regression can be performed, as summarized in Figure 8, see steps 353, 354, 356, 358, 360, 362, 364, and 366.

[0078] Another example of SIMS measurement is shown below.

[0079] The first step involves using a solid test wafer.

[0080] For solid test wafers with known properties: Regression of sputter rate and ion yield parameters, as well as other parameters (MRI model, e.g., mixing model parameters), is used to fit the simulated spectrum to the measured spectrum (using the solid geometry).

[0081] Table 1 shows an example of the results of the first step.

[0082] The result is a table of ion yield efficiency as a function of Ge (or other material) concentration.

[0083] [Table 1]

[0084] In Table 1, the ion yield is the effective ion yield, or "system" ion yield, which includes the transition factor of the measurement system and the detectors' efficiency.

[0085] The values ​​of the mixture model parameters are also shown.

[0086] The next step is to fit the simulated spectrum (using solid geometry) to the measured spectrum using regressions of sputter rate and ion yield parameters, the angular dependence of sputter rate and ion yield, MRI mixture model parameters, and other parameters on a patterned test wafer with known properties.

[0087] Table 2 shows the results of ion collection efficiency, sputter rate, and other parameters when the Ge (or other material) concentration is changed.

[0088] [Table 2]

[0089] For production wafers, regression is used on the sputter rate and ion yield parameters to fit simulated spectra (with associated shapes) to the measured spectra. Mixture model parameters are used based on the values ​​from the test wafers.

[0090] The results are ion yields for different parts of the structure, see Table 3 for an example.

[0091] [Table 3]

[0092] To determine the values ​​of the Ge concentration in various parts of the structure (last column of Table 2), interpolation can be performed using the values ​​from Table 1 in the second column of Table 2.

[0093] regression (Regression)

[0094] This regression can be part of step 140 in FIG.

[0095] For a given geometry, material properties (sputter rate, ion yield), mixing model parameters, and other parameters, SIMS spectrum simulations are performed.

[0096] A comparison of the measured SIMS spectrum with the simulated SIMS spectrum (examples of SIMS spectra are shown in graphs 410, 420, 430 and 440 in Figures 9 and 10, simulated SIMS spectra are shown at 411, 421, 431 and 441, and measured SIMS spectra are shown at 412, 422, 432 and 442) is performed using one of the following metrics:

[0097]

number

[0098] or

[0099]

number

[0100] Here, the target function TF is the matching criterion between the measured spectrum and the simulated spectrum.

[0101] The parameters of the model (eg, sputter rate and ion yield) are varied to minimize the value of the target function, and the minimization of TF is performed.

[0102] SIMS spectrum simulation (can be part of step 131)

[0103] Input for SIMS spectrum simulation The 3D shape (geometry) model is i. Complex 3D structures are also possible. ii. A simple solid stack, e.g. layers of different materials. SIMS Materials Table (see Table 4 below) The columns correspond to the SIMS species. B. The rows correspond to the geometric model of the "material". C. The special column is the sputter rate column, which is the removal rate in angstroms per second at specific experimental conditions. D. Ion yields of different species in different materials.

[0104] MRI mixture model parameters (including the depth dependence of these parameters)

[0105] Optional: Angular dependence of sputter rate and ionization yield

[0106] [Table 4]

[0107] Table 4 is an example of a SIMS materials table (including sputter rate and ion yield).

[0108] Simulation Algorithms: There are multiple simulation modes, including full 3D simulation for "open" structures and flat-top simulation for "filled" structures.

[0109] Mixing (can be part of step 132)

[0110] In the context of secondary ion mass spectrometry (SIMS), modeling the effects of mixing and roughness during the sputtering process plays a crucial role in understanding depth profiling.

[0111] To properly model the sputtering process, it is necessary to properly model the depth resolution by taking into account the effects of mixing and roughness. Here, we introduce two partial depth resolution functions (DRFs) with parameters of mixing length (w) and roughness (σ). The total depth resolution function G(z) is expressed as a combination of these partial DRFs.

[0112]

number

[0113] Here, the partial DRFs are defined as follows:

[0114] About Mixing

number

[0115] About roughness

number

[0116] In the above formula, X(z') represents the distribution of sputtered ions at depth z'.

[0117] By incorporating these functions, the effects of both mixing and roughness can be comprehensively considered in SIMS experiments to predict depth profiles more accurately.

[0118] Solid Film Calibration

[0119] Secondary ion mass spectrometry (SIMS) is a powerful analytical technique used in semiconductor metrology. In SIMS, a primary ion beam (i.e., 16 O2 + or 18O2 + ) is irradiated onto the sample surface to erode it layer by layer. The resulting surface erosion releases positive and negative secondary ions, as well as neutral atoms and molecules.

[0120] In SIMS analysis, secondary ions of select polarity are extracted and mass separated in the SIMS analyzer, producing secondary ion intensity (cps) vs. time for a specific layer composition. The layer composition is determined by the ratio of different secondary ion species. For quantification, these ratios are converted into composition (atoms / cc) or dose (atoms / cm) using known reference standards certified by independent techniques. 2 )

[0121] The layer depth is derived by determining the erosion yield (atoms / impacting ions) using a layer of known thickness. For given primary ion bombardment conditions and beam current, the layer depth is derived from the time to reach the interface. The depth resolution (nm / decade) after erosion yield calibration is obtained from the falling (decaying) edge of the layer signal, such as reaching the silicon interface or another material.

[0122] The erosion yield is affected by the primary ion energy, the primary ion impact angle, and the sample composition. Similarly, the secondary ion yield depends on the primary ion energy, the primary ion impact angle, and the sample composition.

[0123] In SIMS, calibration of the instrument response is crucial for accurate quantification of ion concentrations and fractions. Standard samples play an important role in the calibration process. By using well-characterized standards with known elemental or isotopic composition, a correlation can be established between the measured signal intensity and the actual ion concentration or fraction in the sample.

[0124] To optimize analytical conditions for quantitation and depth resolution, various primary ion conditions can be applied. For example, Si and Ge concentrations can be covered for each analytical condition. (1-x) Ge x Reference calibration structure (a Si (1-x) Ge x The reference calibration structure provides valuable insight into the erosion yield vs. composition and Ge / Si counts vs. composition (secondary ion yield vs. composition). See example calibration samples (solid films) labeled 451, 452, 453, and 454 in Figure 11.

[0125] Relevant for SIMS on Structure

[0126] The SIMS depth profiling process adds another dimension by considering the geometric structure of the features. Because the impact angle of the primary ions varies as a function of the structure between normal incidence and near-infrared incidence of 89°, quantification parameters like erosion yield vs. impact angle and secondary ion yield vs. impact angle are required.

[0127] These parameters can be determined on-tool or by an external analysis group (as a practical example, a 25 nm thick Si on silicon 0.7 Ge 0.3 There is structure).

[0128] The measurements include time-to-silicon interface detection as a function of impact angle (enabled by sample tilt), erosion crater size measurement, and secondary ion signals for various analysis angles.

[0129] The time-to-interface measurements (under constant primary beam current) provide the erosion yield as a function of incidence angle, and the secondary ion signal provides the (useful) ion yield as a function of angle.

[0130] Model feedback verification

[0131] The SIMS on Structure model predicts the effect of structure geometry on SIMS response, taking into account composition and impact angle versus depth. The erosion yield and Si ion yield for filled structures are better-defined because erosion yields in the fill between structures are similar. However, for open structures, iterations are required to converge to the actual structure due to the need to account for changes due to differential sputtering.

[0132] Two types of structures are required to calibrate the SIMS response: see Figure 12, line 462 for the open array and line 464 for the filled array.

[0133] To model the dependence of SIM signals on feature shape and feature dimensions, each feature type must vary in critical dimensions (CD) and pitch within relevant ranges. CD refers to the main geometric feature of a feature, such as linewidth, while pitch represents the spacing between these geometric features.

[0134] This calibration is necessary because the SIMS response is affected not only by composition and impact angle, but also by the inherent geometric properties of the structures being analyzed. By incorporating structures with various CD and pitch values, the model can learn to explain how changes in geometry affect the observed SIMS signal.

[0135] When measuring unknown samples using SIMS, it is advisable to complement the results with additional techniques such as Rutherford Backscattering Spectrometry (RBS), variants of Transmission Electron Microscopy (TEM), TEM / Electron Energy Loss Spectroscopy (TEM / EELS) or TEM / X-ray Fluorescence Spectroscopy (TEM / XRF), and Optical Critical Dimension (OCD). These alternative techniques serve as a means of cross-validation and verification, increasing the reliability of SIMS measurements and enhancing the accuracy of "SIMS on structural models."

[0136] According to one embodiment, multiple SIMS spectra are obtained in parallel for multiple different materials. The SIMS system includes multiple detectors tuned to detect different secondary ions associated with the different materials. The number of detectors may be greater than two, such as five, ten, or more.

[0137] In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, it will be understood by those skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the present invention.

[0138] The subject matter which is regarded as the invention is particularly pointed out and distinctly claimed in the concluding portion of the specification. However, the invention, both as to organization and method of operation, together with its objects, features, and advantages, may best be understood by reference to the following detailed description taken in conjunction with the accompanying drawings.

[0139] It will be understood that for simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some elements may be exaggerated relative to other elements for clarity. Further, where considered appropriate, reference numerals may be repeated among the figures to indicate corresponding or analogous elements.

[0140] Because the illustrated embodiments of this invention can, in most cases, be implemented using optical components known to those skilled in the art, no more detail will be provided than is deemed necessary as illustrated above for an understanding and appreciation of the concepts underlying this invention and so as not to obscure or obscure the teachings of this invention.

[0141] References in this specification to a method should apply mutatis mutandis to an apparatus or system capable of performing the method and / or to a non-transitory computer-readable medium storing instructions for performing the method.

[0142] Any reference in this specification to a system or apparatus shall apply mutatis mutandis to a method that can be performed by the system and / or may apply mutatis mutandis to a non-transitory computer-readable medium storing instructions that can be executed by the system.

[0143] Any reference in this specification to a non-transitory computer-readable medium shall apply mutatis mutandis to an apparatus or system capable of executing instructions stored on the non-transitory computer-readable medium and / or may apply mutatis mutandis to a method for executing instructions.

[0144] Any combination of modules or units described in any of the figures, any part of this specification and / or the claims may be provided.

[0145] This specification and / or drawings may refer to a processor. A processor may be a processing circuit. The processing circuit may be implemented as a central processing unit (CPU) and / or one or more other integrated circuits, such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a full custom integrated circuit, or a combination of such integrated circuits.

[0146] Any combination of any of the steps of the methods illustrated in this specification and / or in the drawings may be provided.

[0147] Any combination of the subject matter of any of the claims may be provided.

[0148] Any combination of the systems, units, components, processors, and sensors illustrated in the specification and / or drawings may be provided.

[0149] The term "and / or" means additionally or alternatively. Thus, A and / or B may refer to only A, only B, or a combination of A and B.

[0150] References to "consisting" should also apply mutatis mutandis to "consisting" and to "consisting essentially of".

[0151] While the foregoing written description of the invention will enable one of ordinary skill in the art to make and use what is presently believed to be the best mode thereof, one of ordinary skill in the art will understand and appreciate that there are variations, combinations, and equivalents to the specific embodiments, methods, and examples herein. Accordingly, the invention should not be limited by the embodiments, methods, and examples described above, but rather by all embodiments and methods within the scope and spirit of the invention as defined by the appended claims.

[0152] In the foregoing specification, the invention has been described with reference to specific embodiments thereof. However, it will be evident that various modifications and changes can be made thereto without departing from the broader spirit and scope of the invention as set forth in the appended claims.

[0153] Those skilled in the art will recognize that the boundaries between logic blocks are merely exemplary, and that alternative embodiments may combine logic blocks or circuit elements or impose alternative decompositions of functionality on various logic blocks or circuit elements. Accordingly, it should be understood that the architectures depicted in this specification are merely exemplary, and that in practice many other architectures may be implemented that achieve the same functionality.

[0154] An arrangement of components to achieve the same functionality is substantially "associated" such that the desired functionality is achieved. Thus, for purposes of this specification, any two components that combine to achieve a particular functionality may be considered to be "associated" with each other such that the desired functionality is achieved, regardless of architecture or intervening components. Likewise, any two components so associated may also be considered to be "operably connected" or "operably coupled" to each other to achieve the desired functionality.

[0155] Furthermore, those skilled in the art will recognize that the boundaries between operations described above are merely illustrative. Multiple operations may be combined into a single operation, a single operation may be distributed among additional operations, and operations may be performed with at least partial overlap in time. Furthermore, alternative embodiments may include multiple instances of a particular operation, and the order of operations may be changed in various other embodiments.

[0156] Also, for example, in one embodiment, the illustrated embodiment may be implemented as circuits located on a single integrated circuit or within the same device, or the illustrated embodiment may be implemented as any number of separate integrated circuits or separate devices interconnected with each other in any suitable manner.

[0157] However, other modifications, variations, and alternatives are possible. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense.

[0158] In the claims, reference signs placed between parentheses shall not be construed as limiting the scope of the claim. The word "comprising" does not exclude the presence of other elements or steps recited in the claim. Furthermore, as used in this specification, the words "a" or "an" are defined as one or more. Also, the use of introductory phrases such as "at least one" and "one or more" in a claim shall not be construed as implying that the introduction of another claim element with the indefinite article "a" or "an" limits a particular claim containing such introduced claim element to an invention containing only one of such element, even if the same claim also contains the introductory phrases "one or more" or "at least one" and an indefinite article such as "a" or "an." The same applies to the use of definite articles. Unless otherwise specified, terms such as "first" and "second" are used to arbitrarily distinguish between elements described by such terms. Accordingly, these terms are not necessarily intended to indicate any chronological or other priority of such elements. The mere fact that certain measures are recited in mutually different claims does not indicate that a combination of these measures cannot be used to advantage.

[0159] While certain features of the invention have been illustrated and described herein, many modifications, substitutions, changes, and equivalents will occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.

[0160] It will be understood that various features of embodiments of this disclosure that are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of embodiments of this disclosure that are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination.

[0161] Those skilled in the art will recognize that the embodiments of the present disclosure are not limited by what has been particularly shown and described herein. Rather, the scope of the embodiments of the present disclosure is defined by the appended claims and equivalents thereof.

Claims

1. 1. A secondary ion mass spectrometry (SIMS) based analytical system comprising: a storage circuit configured to store (i) an estimated model of a non-planar three-dimensional (3D) structural element, the estimated model indicating an estimated shape of the 3D structural element and an estimated concentration of material within the 3D structural element, and (ii) a measured SIMS spectrum of the 3D structural element; a calibration information circuit configured to obtain calibration information regarding an estimated relationship between SIMS-related parameters, including ion yield and sputter rate, and the concentration of material in the model; a SIMS simulation circuit configured to (i) provide an updated model of the 3D structural element, and (ii) provide a simulated SIMS spectrum of the 3D structural element, the updated model being indicative of changes undergone by the 3D structural element during a sputtering process, and the simulated SIMS spectrum being indicative of estimated SIMS-related parameters; and a fitting circuit configured to determine at least one of a shape and a material concentration parameter based on the simulated SIMS spectrum and the measured SIMS spectrum; Secondary ion mass spectrometry (SIMS) based analytical system.

2. 10. The SIMS-based analysis system of claim 1, wherein the SIMS-related parameters further include primary ion impact energy and impact angle.

3. 2. The SIMS-based analysis system of claim 1, wherein the SIMS simulation circuitry is configured to iteratively simulate the sputtering process to provide an updated model of the three-dimensional structural element and a simulated SIMS spectrum of the three-dimensional structural element.

4. 4. The SIMS-based analysis system of claim 3, further comprising a discretization circuit configured to virtually divide the estimated model of the reference three-dimensional structural element into a grid of columns, each column being associated with column structural information and column material information.

5. 4. The SIMS-based analysis system of claim 3, wherein the SIMS simulation circuitry is configured to simulate a column-by-column sputtering process.

6. 10. The SIMS-based analysis system of claim 1, wherein the fitting circuitry is configured to perform a regression-based fitting process.

7. 7. The SIMS-based analysis system of claim 6, wherein a regression-based fitting process is applied to the sputtering rate and ion yield values.

8. 10. The SIMS-based analysis system of claim 1, wherein the calibration information is obtained using measurements or simulations of planar test three-dimensional structural elements.

9. 10. The SIMS-based analysis system of claim 1, wherein the calibration information is obtained further using measurements or simulations of non-planar test three-dimensional structural elements.

10. 10. The SIMS-based analysis system of claim 1, wherein the calibration information is obtained using measurements or simulations of planar test three-dimensional structural elements and using measurements or simulations of non-planar test three-dimensional structural elements.

11. 10. The SIMS-based analysis system of claim 1, wherein the calibration information is obtained by further using measurements or simulations of a first non-planar test three-dimensional structure element comprising an open array of spaced lines and a second non-planar test three-dimensional structure element comprising a filled array of spaced lines.

12. 12. The SIMS-based analysis system of claim 11, wherein each of the open array and the filled array includes (i) a variation in critical dimension within an estimated critical dimension variation window, and (b) a variation in pitch value within an estimated pitch variation window.

13. 10. The SIMS-based analysis system of claim 1, wherein the simulation circuitry is configured to simulate mixing and roughness effects that affect the simulated SIMS spectrum by applying a mixing length per depth function and a roughness per depth function.

14. The mixing length per depth function is [0014] where z is the depth to which the ions are sputtered and w is the mixing length.

14. A SIMS-based analysis system according to claim 13.

15. The roughness function per depth is [Equation 15] 14. The SIMS-based analysis system of claim 13, wherein the SIMS-based analysis system is equal to

16. 10. The SIMS-based analysis system of claim 1, further comprising a model circuit configured to generate the estimated model by applying a tilt operation to an initial estimated model, the tilt operation representing an ion beam tilt angle used during the sputtering process.

17. 1. A computer-implemented method for secondary ion mass spectrometry (SIMS)-based analysis, comprising: a storage circuit for storing (i) an estimated model of a three-dimensional (3D) structural element and a measured SIMS spectrum of the 3D structural element, the model indicating an estimated shape of the 3D structural element and an estimated concentration of material within the 3D structural element, the 3D structural element being non-planar; obtaining calibration information regarding an estimated relationship between SIMS-related parameters and concentrations of materials in the model by a calibration information circuit, the SIMS-related parameters including an ion yield and a sputter rate; providing, by a SIMS simulation circuit, an updated model of the 3D structural element and a simulated SIMS spectrum of the 3D structural element, the updated model representing changes undergone by the 3D structural element during a sputtering process, and the simulated SIMS spectrum representing estimated SIMS-related parameters; determining, by a fitting circuit, at least one of a shape parameter and a material concentration parameter based on the simulated SIMS spectrum and the measured SIMS spectrum; method.

18. a storage circuit for storing (i) an estimated model of a three-dimensional (3D) structural element and a measured secondary ion mass spectrometry (SIMS) spectrum of the 3D structural element, the model indicating an estimated shape of the 3D structural element and an estimated concentration of material within the 3D structural element, the 3D structural element being non-planar; obtaining calibration information regarding an estimated relationship between SIMS-related parameters and concentrations of materials in the model by a calibration information circuit, the SIMS-related parameters including an ion yield and a sputter rate; providing, by a SIMS simulation circuit, (i) an updated model of the 3D structural element and (ii) a simulated SIMS spectrum of the 3D structural element, the updated model being indicative of changes undergone by the 3D structural element during a sputtering process, and the simulated SIMS spectrum being indicative of estimated SIMS-related parameters; determining, by a fitting circuit, at least one of a shape parameter and a material concentration parameter based on the simulated SIMS spectrum and the measured SIMS spectrum; A non-transitory computer-readable medium storing instructions.

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