Secondary ion mass spectrometry analysis

Abstract

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

Description

9897-PCSECONDARY ION MASS SPECTROMETRY ANALYSIS CROSS REFERENCE

[0001] This application claims priority from US provisional patent 63 / 476,948 filing date 12 / 22 / 2022 which is incorporated herein by its entirety. BACKGROUND

[0002] As the metrology tolerances for accurate and precise material quantification for semi-conductor process control continues to scale with smaller device dimensions, the need to quantitate directly on complex 2D and 3D target geometries is becoming increasingly necessary. For many years, the material properties of solid film test structures have been considered surrogates that adequately correlate to final device performance. However, with the more complex processes, materials and shrinking dimensions, this correlation is increasingly less reliable, and is pushing process metrology onto more complex 2D and 3D test structures with physical properties that are more consistent with the final device performance. SUMMARY

[0003] There may be provided systems, methods, and computer readable medium as illustrated in the specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0004] The embodiments of the disclosure will be understood and appreciated more fully from the following detailed description, taken in conjunction with the drawings in which:

[0005] FIG.1 is an example of a system;

[0006] FIG.2 is an example of a method;

[0007] FIG.3 is an example of a method;

[0008] FIG.4 is an example of a 3D structural element segmented to columns;

[0009] FIG.5 is an example of a model and a tilted model;

[0010] FIG.6 is an example of an iteration of a method;

[0011] FIG.7 is an example of shape changes occurring during a sputtering process;

[0012] FIG.8 is an example of a method that includes a regression process;

[0013] FIG.9 is an example of a spectra;

[0014] FIG.10 is an example of a spectra;

[0015] FIG.11 is an example of planar calibration samples; and

[0016] FIG.12 is an example of calibration samples.9897-PC DESCRIPTION OF EXAMPLE EMBODIMENTS

[0017] Secondary Ion Mass Spectrometry (SIMS) has played an important role in the direct quantification of materials by virtue of its direct composition sensitivity. Furthermore, dynamic SIMS is able to quantify material composition as well as provide a direct depth sensitivity that provides a valuable description of a 1D depth profile of atomic concentration. It is expected that SIMS will play an increasing role in semi- conductor process control in the future, and the ability to accurately quantitate will require the capability to predict SIMS signals on complex 2D and 3D structures. Examples of a SIMS system and techniques are disclosed in US 10,056,242, incorporated herein by reference.

[0018] SIMS is fundamentally an ion beam technology that requires sophisticated ion source, charge and mass resolution hardware to produce primary ion species (for e.g. O+ and Cs-) and to create and separate the secondary ions for final detection and quantitation. Nonetheless, the resulting secondary ion signal intensity for a given species X can be defined as follows:is the sputter yield (# atoms removed / incident , is the ion yield (fraction of ions produced from initial sputtered atoms), is the transmission factor (fraction of secondary ions able to pass through to be detected). Finally, and are the isotopic and composition fraction the species X.

[0019] The sputter rate (the rate of removal of a given material with species X in z) can be expressed as follows:and are the matrix density and raster area respectively. The sputter yieldyield are fundamental properties of the material and composition, and in principle can vary somewhat over time (as for e.g. composition may change with depth or z). As a result, the very complex dynamics of SIMS sputtering can be empirically encoded into these effective material parameters, but preferably should be calibrated from known reference materials for accurate quantitation of unknown composition. With proper calibration for solid films, the signal intensity vs. time can be translated into composition vs. depth in a relatively straightforward manner by using the two9897-PC equations above. Furthermore, there is effectively a 1:1 correspondence to time vs. depth for solid films.

[0020] The situation is considerably more complex for SIMS on structure where the surface material erosion can no longer be considered as a ‘planar’ process, due to local topography relative to the primary beam. In addition, there can be lateral material variation (in addition to vertical). The sputtering process and generated secondary ion signals on structure are no longer strictly correlated to a physical depth that is related to time.

[0021] As a result, the parameters in the above equations preferably should now be considered to have additional spatial dependencies that can be most generally written in differential form as:at the surface of the structure, and where are the different coordinates and primary beam incident angle (relative totime t corresponding to the location of each differential area . The intensity produced by each local surface region results from a sputter process that is consuming material according to the local sputter rate defined as . In an incremental time interval , the sputtered depth will result in a local, differential erosion on the structure that will alter the shape over time, further affecting the local surface conditions for subsequent sputtering and signal production. The values as a function of time are not known a-priori, and are determined dynamically as the sputtering of the structure evolves.

[0022] The total Signal intensity from species X produced vs time is then just the sum over all differential surface intensities calculated at different times :

[0023] Figure 1 illustrates an example of SIMS-based analysis system 9, the SIMS- based analysis system includes: A. Memory circuit 10 that is 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 is indicative of an estimated geometry of the 3D structural element and an estimated9897-PC concentration of materials within the 3D structural element. The 3D structural element is non-planar. B. Calibration information circuit 20 that is configured to obtain calibration information regarding an estimated relationship between SIMS related parameters and concentrations of materials of the model; wherein the SIMS related parameters comprise ion yield and sputter rate. C. SIMS simulating circuit 30 that is configured to provide a (i) an updated model of the 3D structural element, the updated model is indicative of changes undergone by the 3D structural element during the sputtering process, and (ii) a simulated SIMS spectrum of the 3D structural element; wherein the simulated SIMS spectrum is indicative of estimated SIMS related parameters. D. Fitting circuit 40 that is configured to determine at least one of geometry and material concentration parameters based on the simulated SIMS spectrum and the measured SIMS spectrum.

[0024] According to an embodiment, the SIMS related parameters further include primary ion impact energy and impact angle.

[0025] According to an embodiment, the SIMS simulating circuit 30 is configured to simulate, in an iterative manner, the sputtering process to provide the updated model of the D structural element and the simulated SIMS spectrum of the D structural element.

[0026] According to an embodiment, the SIMS-based analysis system 9 further includes a discretization circuit 50 that is configured to virtually segment the estimated model of the reference D structural element to a grid of columns; wherein each column is associated with column structure information and column material information.

[0027] According to an embodiment, the difference circuits communicate with each other using communication system 60.

[0028] According to an embodiment, the SIMS simulation circuit 30 is configured to simulate the sputtering process per column.

[0029] According to an embodiment, the fitting circuit 40 is configured to perform a regression based fitting process.

[0030] According to an embodiment, the regression based fitting process is applied on sputtering rate and ion yield values.

[0031] According to an embodiment, the calibration information is obtained using measurements or simulations of planar test 3D structural elements.9897-PC

[0032] According to an embodiment, the calibration information is obtained by further using measurements or simulations of non-planar test 3D structural element.

[0033] According to an 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 D structural element.

[0034] According to an embodiment, the calibration information is obtained by further using measurements or simulations of a first non-planar test 3D structural element that comprises an open array of spaced apart lines, and of a second non-planar test 3D structural element that comprises a filled array of spaced apart lines.

[0035] According to an embodiment, each one of the open array and the filled array includes (i) variations, within an estimated critical dimension variation window, of critical dimension, and (b) variations, within an estimated pitch variation window, of pitch values.

[0036] According to an embodiment, the SIMS simulating circuit 30 is configured to simulate mixing and roughness effects that impact the simulated SIMS spectrum by applying a mixing length per depth function and a roughness per depth function.

[0037] According to an embodiment, the SIMS simulating circuit 30 is a library.

[0038] According to an embodiment the SIMS simulation circuit performs the simulations mentioned above in real time (during the actual sputtering process).

[0039] According to an embodiment the SIMS simulation circuit performs the simulations mentioned above, in off-line (before the execution of the sputtering process).

[0040] According to an embodiment, the mixing length per depth function equals ^^^^ r^^^^^^^ ^for z> -w, wherein z is depth from which ions are sputtered, w is the mixing length.

[0041] According to an embodiment, the roughness per depth function equals ^^^^^^^ ^ e^^ ^.to an embodiment, the SIMS-based analysis system further includes a model circuit 60 that is configured to generate the estimated model by applying a tilt operation on an initial estimated model, the tilt operation represents a tilt angle of an ion beam used during the sputtering process.

[0043] According to an embodiment, the SIMS-based analysis system is a part of a SIMS system that executes the sputtering process.

[0044] According to an embodiment, the SIMS-based analysis system is a computerized system that is not a SIMS system that executes the sputtering process – it may9897-PC even be a remote computerized system, a cloud environment computerizes system, and the like.

[0045] According to an embodiment, the mentioned above circuits are implemented by one or more processing circuits and are included in or implemented by one or more integrated circuits. More than a single circuit mentioned above may be implemented by a single integrated circuit. Additionally or alternatively, a circuit of the mentioned above circuits is implemented by more than a single integrated circuit.

[0046] According to an embodiment, the memory unit 10 includes a volatile memory and / or a non-volatile memory. The memory unit 10 may be a random access memory (RAM) and / or a read only memory (ROM). According to an embodiment, the non-volatile memory unit is a mass storage device, which can provide non-volatile storage of computer code, computer readable instructions, data structures, program modules, and other data for the processor or any other unit of vehicle. For example and not meant to be limiting, a mass storage device can be a hard disk, a removable magnetic disk, a removable optical disk, magnetic cassettes or other magnetic storage devices, flash memory cards, CD-ROM, digital versatile disks (DVD) or other optical storage, random access memories (RAM), read only memories (ROM), electrically erasable programmable read-only memory (EEPROM), and the like.

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

[0048] Figure 1 illustrate communication system 130 as being in communication with various circuits and the memory unit 10.

[0049] The communication system 130 may include a bus. The 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 can comprise an Industry Standard Architecture (ISA) bus, a Micro Channel 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 Interconnects (PCI), a PCI-Express bus, a Personal Computer Memory Card Industry Association (PCMCIA), Universal Serial Bus (USB) and the like. The bus, and all buses specified in this description can also be implemented over a wired or wireless network connection and each of the subsystems.

[0050] Figure 1 also illustrates network 170 that is located outside system 8 is used for communication with other systems – such as SIMS measurement system (not shown) or other remote computing system. By way of example, a remote computing system can be a9897-PC personal computer, a laptop computer, portable computer, a server, a router, a network computer, a peer device or other common network node, and so on. Logical connections between the processor and either one of remote computing systems can be made via a local area network (LAN) and a general wide area network (WAN). Such network connections can be through a network adapter (may belong to communication system 170) which can be implemented in both wired and wireless environments. Such networking environments are conventional and commonplace in offices, enterprise-wide computer networks, intranets, and a network such as the internet.

[0051] Figure 2 illustrates an example of method 100 that is computer implemented and is for SIMS-based analysis. The method includes: A. Step 110 of storing, by a memory circuit, (i) an estimated model of a three dimensional (3D) structural element, and (ii) a measured SIMS spectrum of the 3D structural element; the model is indicative of an estimated geometry of the 3D structural element and an estimated concentration of materials within the 3D structural element; wherein the 3D structural element is non- planar. B. Step 120 of obtaining, by a calibration information circuit, calibration information regarding an estimated relationship between SIMS related parameters and concentrations of materials of the model; wherein the SIMS related parameters comprise ion yield and sputter rate. C. Step 130 of providing, by a SIMS simulating circuit, (i) an updated model of the 3D structural element, the updated model is indicative of changes undergone by the 3D structural element during the sputtering process, and (ii) a simulated SIMS spectrum of the 3D structural element; wherein the simulated SIMS spectrum is indicative of estimated SIMS related parameters. According to an embodiment the iterations end when a predefined number of iterations are executed and / or when a difference between the outcome of one iteration to a consecutive iteration are smaller than a threshold – and further iterations are prevented. D. Step 140 of determining, by a fitting circuit, at least one of geometry and material concentration parameters based on the simulated SIMS spectrum and the measured SIMS spectrum. According to an embodiment fitting iterations end when a predefined number of fitting iterations are executed and / or when a difference between the outcome of one fitting iteration to a9897-PC consecutive fitting iteration are smaller than a threshold – and further fitting iterations are prevented

[0052] According to an embodiment, the SIMS related parameters further include primary ion impact energy and impact angle.

[0053] According to an embodiment, step 130 includes step 131 of simulating, by the SIMS simulating circuit, in an iterative manner, the sputtering process to provide the updated model of the D structural element and the simulated SIMS spectrum of the 3D structural element.

[0054] According to an embodiment, method 100 further includes step 125 of virtually segmenting, by a discretization circuit, the estimated model of the reference 3D structural element to a grid of columns. Each column is associated with column structure information and column material information. According to an embodiment step 130 includes simulating the sputtering process per column.

[0055] According to an embodiment, step 140 includes performing a regression based fitting process.

[0056] According to an embodiment, the regression based fitting process is applied on sputtering rate and ion yield values.

[0057] According to an embodiment, the calibration information is obtained using measurements or simulations of planar test 3D structural elements.

[0058] According to an embodiment, the calibration information is obtained by further using measurements or simulations of non-planar test 3D structural element.

[0059] According to an 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 D structural element.

[0060] According to an embodiment, the calibration information is obtained by further using measurements or simulations of a first non-planar test 3D structural element that comprises an open array of spaced apart lines, and of a second non-planar test 3D structural element that comprises a filled array of spaced apart lines.

[0061] According to an embodiment, each one of the open array and the filled array includes (i) variations, within an estimated critical dimension variation window, of critical dimension, and (b) variations, within an estimated pitch variation window, of pitch values.

[0062] According to an embodiment, step 130 includes step 132 of simulating mixing and roughness effects that impact the simulated SIMS spectrum by applying a mixing length per depth function and a roughness per depth function.9897-PC

[0063] According to an embodiment, step 131 is executed in real time (during the actual sputtering process).

[0064] According to an embodiment, step 131 is executed off-line (before the execution of the sputtering process).

[0065] According to an embodiment, the mixing length per depth function equals ^^^^ r^^^^^^^ ^for z> -w, wherein z is depth from which ions are sputtered, w is the mixingAccording to an embodiment, the roughness per depth function equals ^^^^e^^^^^^^^√^^. to an embodiment, method 100 includes initialization step 105.step 105 may include generating the estimated model by applying a tilt operation on an initial estimated model, the tilt operation represents a tilt angle of an ion beam used during the sputtering process. See model 240 and tilted ion beam that is converted to t tilted model 242 with a normal incidence ion beam.

[0068] According to an embodiment, there is provided a non-transitory computer readable media that stores instructions for: (a) storing, by a memory circuit, (i) an estimated model of a three dimensional (3D) structural element, and (ii) a measured SIMS spectrum of the 3D structural element; the model is indicative of an estimated geometry of the 3D structural element and an estimated concentration of materials within the 3D structural element; wherein the 3D structural element is non-planar; (b) obtaining, by a calibration information circuit, calibration information regarding an estimated relationship between SIMS related parameters and concentrations of materials of the model; wherein the SIMS related parameters comprise ion yield and sputter rate; (c) providing, by a SIMS simulating circuit, (i) an updated model of the 3D structural element, the updated model is indicative of changes undergone by the 3D structural element during the sputtering process, and (ii) a simulated SIMS spectrum of the 3D structural element; wherein the simulated SIMS spectrum is indicative of estimated SIMS related parameters; and (d) determining, by a fitting circuit, at least one of geometry and material concentration parameters based on the simulated SIMS spectrum and the measured SIMS spectrum.

[0069] In what follows, a physical model and method is defined that can be used for realistic computation of SIMS signals over time.

[0070] It may be assumed that there is a ‘solid film’ (means a 3D structural element that has a flat / planar upper surface) generalization of a sputter and signal generation process9897-PC on a complex structure that requires specification of the materials properties and orientation relative to the primary beam in a way that realistically accounts for the underlying materials and shape variation, along with a method to dynamically evolve the shape over time to produce SIMS profile signals for one or more species from a sputter process.

[0071] The steps for structure definition, parameter calibration, and dynamic evolution of structure and signal production are shown in the flow chart in figure 3 – see method 200 and steps 202, 204, 206, 208, 210, 212, 214, 216 and 220. Steps 202, 204, 205 and 208 follow each other. Step 210 is followed by step 212. Steps 212 and 214 are followed by step 208. Iterations include executing steps 208 and 216. The method 200 ends by step 220.

[0072] Nominal process parameters and geometry description are illustrated below: A. Create initial, starting geometric model which includes geometrical description of 3D structure and material assignment for each material region. Also, it includes the required parametrization of 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. Uniform grid density of columns in XY plane is created (206). ii. Each cell of the grid becomes a base of the “column of materials” iii. Column of materials describes the column and a stack of materials and their heights iv. The columns may be vertical if sputtering is performed perpendicular to the wafer surface v. Or columns can be directed at the angle to the surface according to the direction of the sputter beam Figure 4 illustrates a side view 3D structural element that included eight columns 230(1) – 230(6) - but it should be noted that the grid of columns may be two-dimensional. C. Another requirement for this method is proper calibration of the materials property specific to the SIMS sputter process, and requires proper materials specification of relevant sputter rate, ionization efficiency, angular dependence of sputter rate dependencies of these parameters. These parameters are calibrated or measured using a set of specially designed solid and patterned samples. See steps 210 and 212.9897-PC D. Yet another input to the simulation engine are details of SIMS measurement experiment, like Beam orientation, Beam voltage and Current, Raster area, etc. See, step 214. E. Single simulation step (step 208): i. All above information allows to simulate a sputtering process (sputter rate, detected signal) at each point XY during short interval of time dT (for example, 1 sec). ii. The result of this simulation is a new 3D structure (after dT) and measured signal (during dT). Figure 7 illustrates examples of the shape evolution over time as a result of the sputter process assuming different orientations of the primary ion beam relative to the structure where for example the shape can result in sloping sides and even disconnected geometric regions that require additional physical modeling assumptions (for e.g. kinematics and gravitational effects). F. The above simulation step is repeated iteratively (see step 216) resulting in (step 220): i. Measured signal as a function of sputtering time. ii. Expected 3D structure evolution as a function of sputtering time.

[0073] Figure 6 is an example of iteration 260 – see steps 252, 254, 256, 258, 260, 262, 264, 266, 268, 270 and 270.

[0074] Having defined the model and calculation methods, it can ultimately be directly compared to measured data, and structural and / or compositional parameter optimization via a regression can be performed, as summarized in figure 8- see steps 353, 354, 356, 358, 360, 362, 364 and 366.

[0075] Another example of a SIMS measurement is illustrated below.

[0076] An initial step includes using solid test wafers

[0077] On solid test wafers with known properties: fit simulated spectrum (using solid geometry) to measured spectrum using regression on Sputter Rate and Ion Yield parameters, and other parameters (like MRI model, e.g., mixing model parameters)

[0078] Table 1 provides an example of the outcome of the initial step.

[0079] Results is a table of Ion Yield efficiency as a function Ge (or other material) concentration:9897-PC Ge % is SiGe material Ion Yield (*) 10 1.7 25 5.1 35 8.3 Table 1

[0080] In table 1 the Ion Yield is an effective or “system” Ion Yield which includes transition factor of the measurement system and detectors efficiency.

[0081] Also, it provides values of mixing model parameters.

[0082] Next step - on patterned test wafers with known properties: fit simulated spectrum (using solid geometry) to measured spectrum using regression on Sputter Rate and Ion Yield parameters, angular dependence of Sputter Rate and Ion Yield, MRI mixing model parameters, and other parameters.

[0083]

[0082] Results are shown in table 2 of Ion Yield efficiency, Sputter Rate, and other parameters for different Ge (or other material) concentration: Ge % is SiGe material Ion Yield Sputter Rate 10 1.7 1.7 25 5.1 1.75 35 8.3 1.85 Table 2

[0084] For production wafers: fit simulated spectrum (using relevant geometry) to measured spectrum using regression on Sputter Rate and Ion Yield parameters. Mixing model parameters are used based on test wafers values.

[0085] Result is Ion Yield efficiency for different part of the structure. For example – see table 3. Part of the Structure Ion Yield Ge concentration Top part of EPI Diamond 6.8 To be determined Bottom part of EPI 4.2 To be determined Diamond Table 3

[0086] To get the value of Ge concentration in different part of the structures (last column at Table 2) we can perform interpolation using values from Table 1 for the second columns of Table 2.9897-PC

[0087] Regression

[0088] The regression may be a part of step 140 of figure 2.

[0089] Perform the SIMS spectrum simulation for given geometry, material properties (Sputter rate, Ion Yield), mixing model parameters, and other parameters.

[0090] Perform comparison of between measured and simulated SIMS spectrum (example of SIMS spectra are provided in graphs 410, 420, 430 and 440 of figure 9 and 10, in which the simulated SIMS spectra are denoted 411, 421, 431 and 441, whereas the measured SIMS spectra are denoted 412, 422, 432 and 442) using one of the metrics: ^ TF =^ ^ ^M^^− S^^^Or^ TF = ^ ^ ^log ^M^^^ − log ^S^^^^ Here target function measured and simulatedspectra.

[0091] Perform minimization of TF by changing parameters of model (for example, Sputter Rate and Ion Yield) to minimize the value of target function.

[0092] SIMS Spectrum simulation (can be a part of step 131)

[0093] Inputs for SIMS Spectrum simulation: 3D Geometrical model i. can be complex 3D structure. ii. simple solid stack, e.g., layers of different materials. SIMS Material Table (see below Table 4) Columns correspond to SIMS Species. B. Rows corresponds to “Materials’ form geometrical model. C. Special column is a Sputter Rate column – removal rate in Angstroms per seconds for specific experimental conditions. D. Ion Yield for different species at different materials

[0094] MRI Mixing model parameters (including depth dependence of these parameters).

[0095] Optional: Angular Dependence of Sputter Rate and Ionization Yield – table 49897-PC Species Materials Sputter rate (30)Si+ (70)Ge+ Air 10120 0 SiGe_top 1.537 4381.1 1783.8 Si_mid 1.288 6746 0 SiGe_Bot 1.733 1987.4 2921.4 Si 1.418 5569.4 0 Ion Yield Table 4 Example of SIMS Material Table with Sputter Rate and Ion Yield.

[0096] Simulation Algorithms: there are several simulation modes such as full 3D simulation for “Open” Structures or flat Top simulation for “Filled” Structures.

[0097] Mixing (can be a part of step 132).

[0098] In the context of Secondary Ion Mass Spectrometry (SIMS), the modeling of mixing and roughness effects during the sputtering process plays a pivotal role in understanding of depth profiling.

[0099] To properly model the sputtering process, one needs to take into account the mixing and roughness effects to properly model depth resolution. We introduce here two partial Depth Resolution Functions, characterized by the parameters mixing length (w) and roughness (σ). The total depth resolution function, G(z), is expressed as a combination of these partial DRFs: G^z^ =).^.X^z+^G^z − z+^dz′as follows: g^^z^ =^^ e^^^^^^ / ^for z > −w, 0 for z < −w for mixing, and roughness.X(Z’) represents the distribution of sputtered ions at depth z’.

[0101] Incorporation of these functions allows to predict depth profiles more accurately in SIMS experiments, considering both mixing and roughness effects in a comprehensive manner.

[0102] Solid Film calibration9897-PC

[0103] Secondary Ion Mass Spectrometry (SIMS) is a powerful analytical technique employed in semiconductor metrology. It utilizes primary ion beams (i.e.,16O2+or18O2+), directed at the sample surface for layer-by-layer erosion. The ensuing surface erosion results in the ejection of positive and negative secondary ions, as well as neutral atoms and molecules.

[0104] In SIMS analysis, secondary ions of select polarity are extracted and mass separated in the SIMS analyzer, generating secondary ion intensity (cps) vs. time for a particular layer composition. Layer composition is determined by ratios of different secondary ion species. Quantification involves translating these ratios into composition (atoms / cc) or dose (atoms / cm2) using known reference standards qualified by independent techniques.

[0105] The layer depth is derived by using layers of known thickness and determining the erosion yield (atoms / impacting ion). For given primary ion impact conditions and beam current, the layer depth is derived from the time to reach the interface. The depth resolution (nm / decade) post erosion yield calibration is obtained from the falling (decay) edge of the layer signal, such as reaching the silicon interface or another material.

[0106] The erosion yield is influenced by primary ion energy, primary ion impact angle, and sample composition. Similarly, the secondary ion yield is dependent on primary ion energy, primary ion impact angle, and sample composition.

[0107] In SIMS, the calibration of the instrument's response is crucial for accurate quantification of ion concentrations and fractions. Standards have an important role in the calibration process. Utilizing well-characterized standards with known elemental or isotopic compositions allows to establish a correlation between the measured signal intensities and the actual concentrations or fractions of ions in a sample.

[0108] Different primary ion conditions can be applied to optimize analysis conditions for quantification and depth resolution. For instance, a Si(1-x)GeXreference calibration structure covering a range of Ge concentrations per analysis condition provides valuable insights into erosion yield vs. composition and Ge / Si counts vs. composition (secondary ion yield vs. composition), see examples of calibration samples (solid films) – denoted 451, 452, 453 and 454 of figure 11.

[0109] Relevant for SIMS on Structure

[0110] The depth profiling process in SIMS adds another dimension, considering the geometrical structure of the feature. The primary ion impact angle9897-PC changes as a function of the structure between normal incidence to near-glancing angle 89°, requiring quantification parameters like erosion yield vs. impact angle and secondary ion yield vs. impact angle.

[0111] These parameters can be determined either on-tool or by an outside analysis group (a practical example involves a Si0.7Ge0.3structure with 25nm thickness on Silicon).

[0112] The measurement includes time-to-Silicon interface detection as a function of impact angle (which can be done by sample tilt), erosion crater size measurement, and secondary ion signals for various analysis angles.

[0113] Time to interface measurement (at constant primary beam current) provides erosion yield as a function of incident angle, while secondary ion signals (useful) ion yield as a function of angle.

[0114] Model feedback verification

[0115] The SIMS on Structure model predicts the impact of structure geometry on SIMS response, considering composition and impact angle vs. depth. Erosion yield and Si ion yield for filled structures are well-defined due to similar erosion yields in the fill between structures. However, open structures require consideration of changes due to differential sputtering, necessitating iteration to converge to the actual structure.

[0116] Two structure types would be required to calibrate the SIMS response – see open array of lines 462 and filled array of lines 464 of figure 12.

[0117] Each structure type needs to have variation in critical dimensions (CD) and pitch within the relevant range, to model dependence of SIMS signal on structure geometry and dimensions of the structures. CD refers to the key geometric features of the structures, such as the width of lines. Pitch, on the other hand, represents the spacing between these geometric features.

[0118] This calibration is required because the SIMS response is influenced not only by the composition and impact angle but also by the specific geometric characteristics of the structures being analyzed. By incorporating structures with different CD and pitch values, the model can learn and account for how variations in geometry impact the observed SIMS signal.

[0119] When conducting measurements on unknown samples using SIMS, it is advisable to complement the results with additional techniques such as RBS (Rutherford Backscattering Spectrometry), variants of TEM (Transmission Electron Microscopy), TEM / EELS (TEM / Electron Energy Loss Spectroscopy) or TEM / XRF (TEM / X-ray Fluorescence Spectroscopy), or OCD (Optical Critical Dimension). These9897-PC alternative techniques serve as a means of cross-verification and validation, enhancing the reliability of the SIMS measurements and reinforcing the accuracy of the SIMS on Structure model.

[0120] According to an embodiment, multiple SIMS spectra are obtained in parallel for multiple different materials. A SIMS system includes multiple detectors that are tuned to detect different secondary ions associated with different materials. The number of detectors exceeds two, and may be five, ten or more.

[0121] In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the 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.

[0122] The subject matter regarded as the invention is particularly pointed out and distinctly claimed in the concluding portion of the specification. The invention, however, both as to organization and method of operation, together with objects, features, and advantages thereof, may best be understood by reference to the following detailed description when read with the accompanying drawings.

[0123] It will be appreciated 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 of the 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.

[0124] Because the illustrated embodiments of the present invention may for the most part, be implemented using optical components known to those skilled in the art, details will not be explained in any greater extent than that considered necessary as illustrated above, for the understanding and appreciation of the underlying concepts of the present invention and in order not to obfuscate or distract from the teachings of the present invention.

[0125] Any reference in the specification to a method should be applied mutatis mutandis to a device or system capable of executing the method and / or to a non-transitory computer readable medium that stores instructions for executing the method.

[0126] Any reference in the specification to a system or device should be applied mutatis mutandis to a method that may be executed by the system, and / or may be applied mutatis mutandis to non-transitory computer readable medium that stores instructions executable by the system.9897-PC

[0127] Any reference in the specification to a non-transitory computer readable medium should be applied mutatis mutandis to a device or system capable of executing instructions stored in the non-transitory computer readable medium and / or may be applied mutatis mutandis to a method for executing the instructions.

[0128] Any combination of any module or unit listed in any of the figures, any part of the specification and / or any claims may be provided.

[0129] The specification and / or drawings may refer to a processor. The processor may be a processing circuitry. The processing circuitry may be implemented as a central processing unit (CPU), and / or one or more other integrated circuits such as application- specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), full-custom integrated circuits, etc., or a combination of such integrated circuits.

[0130] Any combination of any steps of any method illustrated in the specification and / or drawings may be provided.

[0131] Any combination of any subject matter of any of claims may be provided.

[0132] Any combinations of systems, units, components, processors, sensors, illustrated in the specification and / or drawings may be provided.

[0133] The term “and / or” means additionally or alternatively. Thus – A and / or B may be only A, only B or a combination of A and B.

[0134] Any reference to consisting should be applied mutatis mutandis to consisting and should be applied mutatis mutandis to consisting essentially of.

[0135] While the foregoing written description of the invention enables one of ordinary skill to make and use what is considered presently to be the best mode thereof, those of ordinary skill will understand and appreciate the existence of variations, combinations, and equivalents of the specific embodiment, method, and examples herein. The invention should therefore not be limited by the above described embodiment, method, and examples, but by all embodiments and methods within the scope and spirit of the invention as claimed.

[0001] In the foregoing specification, the invention has been described with reference to specific examples of embodiments of the invention. It will, however, be evident that various modifications and changes may be made therein without departing from the broader spirit and scope of the invention as set forth in the appended claims.

[0002] Those skilled in the art will recognize that the boundaries between logic blocks are merely illustrative and that alternative embodiments may merge logic blocks or circuit elements or impose an alternate decomposition of functionality upon various logic blocks or circuit elements. Thus, it is to be understood that the architectures depicted herein9897-PC are merely exemplary, and that in fact many other architectures may be implemented which achieve the same functionality.

[0003] Any arrangement of components to achieve the same functionality is effectively "associated" such that the desired functionality is achieved. Hence, any two components herein combined to achieve a particular functionality may be seen as "associated with" each other such that the desired functionality is achieved, irrespective of architectures or intermedial components. Likewise, any two components so associated can also be viewed as being "operably connected," or "operably coupled," to each other to achieve the desired functionality.

[0004] Furthermore, those skilled in the art will recognize that boundaries between the above described operations merely illustrative. The multiple operations may be combined into a single operation, a single operation may be distributed in additional operations and operations may be executed at least partially overlapping in time. Moreover, alternative embodiments may include multiple instances of a particular operation, and the order of operations may be altered in various other embodiments.

[0005] Also for example, in one embodiment, the illustrated examples may be implemented as circuitry located on a single integrated circuit or within a same device. Alternatively, the examples may be implemented as any number of separate integrated circuits or separate devices interconnected with each other in a suitable manner.

[0006] However, other modifications, variations and alternatives are also possible. The specifications and drawings are, accordingly, to be regarded in an illustrative rather than in a restrictive sense.

[0007] In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word ‘comprising’ does not exclude the presence of other elements or steps then those listed in a claim. Furthermore, the terms “a” or “an,” as used herein, are defined as one or more than one. Also, the use of introductory phrases such as “at least one” and “one or more” in the claims should not be construed to imply that the introduction of another claim element by the indefinite articles "a" or "an" limits any particular claim containing such introduced claim element to inventions containing only one such element, even when the same claim includes the introductory phrases "one or more" or "at least one" and indefinite articles such as "a" or "an." The same holds true for the use of definite articles. Unless stated otherwise, terms such as “first" and “second” are used to arbitrarily distinguish between the elements such terms describe. Thus, these terms are not necessarily intended to indicate temporal or other prioritization of such elements. The mere9897-PC fact that certain measures are recited in mutually different claims does not indicate that a combination of these measures cannot be used to advantage.

[0008] While certain features of the invention have been illustrated and described herein, many modifications, substitutions, changes, and equivalents will now occur to those of ordinary skill 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.

[0009] It is appreciated that various features of the embodiments of the disclosure which are, for clarity, described in the contexts of separate embodiments may also be provided in combination in a single embodiment. Conversely, various features of the embodiments of the disclosure which are, for brevity, described in the context of a single embodiment may also be provided separately or in any suitable sub-combination.

[0010] It will be appreciated by persons skilled in the art that the embodiments of the disclosure are not limited by what has been particularly shown and described hereinabove. Rather the scope of the embodiments of the disclosure is defined by the appended claims and equivalents thereof.

Claims

9897-PC What is claimed is: CLAIMS 1. A secondary ion mass spectroscopy (SIMS)-based analysis system, the SIMS- based analysis system comprises: a memory circuit that is configured to store (i) an estimated model of a three dimensional (3D) structural element, and (ii) a measured SIMS spectrum of the 3D structural element; the model is indicative of an estimated geometry of the 3D structural element and an estimated concentration of materials within the 3D structural element; wherein the 3D structural element is non-planar; a calibration information circuit that is configured to obtain calibration information regarding an estimated relationship between SIMS related parameters and concentrations of materials of the model; wherein the SIMS related parameters comprise ion yield and sputter rate; a SIMS simulating circuit that is configured to provide a (i) an updated model of the 3D structural element, the updated model is indicative of changes undergone by the 3D structural element during the sputtering process, and (ii) a simulated SIMS spectrum of the 3D structural element; wherein the simulated SIMS spectrum is indicative of estimated SIMS related parameters; and a fitting circuit that is configured to determine at least one of geometry and material concentration parameters based on the simulated SIMS spectrum and the measured SIMS spectrum.

2. The SIMS-based analysis system according to claim 1, wherein the SIMS related parameters further comprise primary ion impact energy and impact angle.

3. The SIMS-based analysis system according to claim 1, wherein the SIMS simulating circuit that is configured to simulate, in an iterative manner, the sputtering process to provide the updated model of the 3D structural element and the simulated SIMS spectrum of the 3D structural element.

4. The SIMS-based analysis system according to claim 3, further comprising a discretization circuit that is configured to virtually segment the estimated model of the reference 3D structural element to a grid of columns; wherein each column is associated with column structure information and column material information.

5. The SIMS-based analysis system according to claim 3, wherein the SIMS simulation circuit is configured to simulate the sputtering process per column.9897-PC 6. The SIMS-based analysis system according to claim 1, wherein the fitting circuit is configured to perform a regression based fitting process.

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

8. The SIMS-based analysis system according to claim 1, wherein the calibration information is obtained using measurements or simulations of planar test 3D structural elements.

9. The SIMS-based analysis system according to claim 1, wherein the calibration information is obtained by further using measurements or simulations of non-planar test 3D structural element.

10. The SIMS-based analysis system according to claim 1, wherein 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 element.

11. The SIMS-based analysis system according to claim 1, wherein the calibration information is obtained by further using measurements or simulations of a first non-planar test 3D structural element that comprises an open array of spaced apart lines, and of a second non-planar test 3D structural element that comprises a filled array of spaced apart lines.

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

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

14. The SIMS-based analysis system according to claim 13, wherein the mixing length per depth function equals ^^^^ r^^^^^^^ ^for z> -w, wherein z is depth from which ions are sputtered, w is the15. The SIMS-based analysis system according to claim 13, wherein the roughness ^^^per depth function^ ^^^^^^.

16. The SIMS-according to claim 1, comprising a model circuit that is configured to generate the estimated model by applying a tilt operation on an initial9897-PC estimated model, the tilt operation represents a tilt angle of an ion beam used during the sputtering process.

17. A method that is computer implemented and is for secondary ion mass spectroscopy (SIMS)-based analysis, the method comprises: storing, by a memory circuit, (i) an estimated model of a three dimensional (3D) structural element, and (ii) a measured SIMS spectrum of the 3D structural element; the model is indicative of an estimated geometry of the 3D structural element and an estimated concentration of materials within the 3D structural element; wherein the 3D structural element is non-planar; obtaining, by a calibration information circuit, calibration information regarding an estimated relationship between SIMS related parameters and concentrations of materials of the model; wherein the SIMS related parameters comprise ion yield and sputter rate; providing, by a SIMS simulating circuit, (i) an updated model of the 3D structural element, the updated model is indicative of changes undergone by the 3D structural element during the sputtering process, and (ii) a simulated SIMS spectrum of the 3D structural element; wherein the simulated SIMS spectrum is indicative of estimated SIMS related parameters; and determining, by a fitting circuit, at least one of geometry and material concentration parameters based on the simulated SIMS spectrum and the measured SIMS spectrum.

18. A non-transitory computer readable media that stores instructions for: storing, by a memory circuit, (i) an estimated model of a three dimensional (3D) structural element, and (ii) a measured secondary ion mass spectroscopy (SIMS) spectrum of the 3D structural element; the model is indicative of an estimated geometry of the 3D structural element and an estimated concentration of materials within the 3D structural element; wherein the 3D structural element is non-planar; obtaining, by a calibration information circuit, calibration information regarding an estimated relationship between SIMS related parameters and concentrations of materials of the model; wherein the SIMS related parameters comprise ion yield and sputter rate; providing, by a SIMS simulating circuit, (i) an updated model of the 3D structural element, the updated model is indicative of changes undergone by the 3D structural element during the sputtering process, and (ii) a simulated SIMS spectrum of the 3D structural element; wherein the simulated SIMS spectrum is indicative of estimated SIMS related parameters; and determining, by a fitting circuit, at least one of geometry and material concentration parameters based on the simulated SIMS spectrum and the measured SIMS spectrum.

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