Method for determining surface roughness of specimen surface of specimen

Abstract

To provide a method for determining surface roughness of a specimen surface, a computer program product, a data processing system, and a specimen processing system.SOLUTION: The method includes a step of acquiring multiple measurement data. Each one of the measurement data indicates a surface topology of the specimen surface on the basis of an optical three-dimensional measurement of the specimen surface by an image sensor. Each one of the measurement data is associated with a different brightness level of a light source illuminating the specimen surface or with a different exposure of the image sensor. The method further includes the steps of: acquiring first calculated data indicating surface roughness of the specimen surface for each one of the measurement data; and determining second calculated data indicating the surface roughness of the specimen surface for all measurement data on the basis of the first calculated data.SELECTED DRAWING: None

Description

[Technical Field]

[0001] The present invention relates generally to the field of determining the surface roughness of a specimen, particularly a semiconductor wafer having an etched wafer surface, and more particularly to a method for determining the surface roughness of a specimen surface, a computer program product, a data processing system, and a specimen processing system. [Background technology]

[0002] For quality control purposes or other purposes, as described further below, it may be useful to measure the surface roughness of a sample surface of a sample, i.e., a substrate surface of a substrate. Such a sample may be a semiconductor wafer. Specifically, the sample or wafer may be etched by a chemical solution, i.e., a wet chemical reaction involving one or more chemical etchants. This may be done, for example, by immersing the sample in a bath containing the chemical solution or by dispensing the chemical solution onto the surface of the wafer. When a semiconductor wafer is used as the sample, a wet etching process is often used to reduce the thickness of the wafer, or in the process of reducing the thickness of the wafer, particularly on the backside of the wafer rather than the front side. As a result of wet chemical etching, the surface roughness of the sample surface may be altered in a controlled manner, particularly to achieve a target value or range of surface roughness.

[0003] Wet etching may be performed in the back-end-of-the-line (BEOL) stages of semiconductor manufacturing processes. In an exemplary BEOL process for wafer-based power semiconductor devices, wet etching may be used for wet chemical surface finishing of the wafer. Typically, wet etching is preceded by tape bonding or the use of a glass carrier wafer and backgrinding of the wafer. In a typical BEOL process for semiconductor manufacturing, wet etching is followed by contact formation, annealing, and backside metallization. Therefore, surface roughness can play an important role in the quality of the sample and, ultimately, the quality of the device using the sample, e.g., a (power) semiconductor device.

[0004] It is known to process images, particularly real-time images, of a sample surface to measure its surface roughness. To obtain accurate results, it may be desirable to adjust the parameters of the camera capturing the image to eliminate external interference. For example, the adjustment or calibration of the camera parameters may need to take into account the reflective properties of a particular sample surface and / or material, such as a silicon wafer. However, accurately measuring surface roughness remains challenging, and it may be desirable to measure surface roughness as accurately, quickly, and reliably as possible for different types of samples, particularly or at least differing in size, material, and / or reflective properties. Summary of the Invention [Problem to be solved by the invention]

[0005] The above problems are at least partially solved or alleviated by the subject matter of the independent claims of the present disclosure, further examples of which are incorporated in the dependent claims.

[0006] According to a first aspect of the present disclosure, A method (300) for determining the surface roughness of a sample surface of a sample (1), comprising: The method (300) comprises: acquiring a plurality of measurement data, each of the measurement data indicating a surface topology of the sample surface based on an optical three-dimensional measurement of the sample surface by an image sensor, and each of the measurement data being associated with a different brightness level of a light source illuminating the sample surface or a different exposure of the image sensor; obtaining first calculated data indicating the surface roughness of the sample surface for each of the measurement data; determining second calculation data indicating the surface roughness of the sample surface for all measurement data based on the first calculation data; A method (300) is provided, comprising:

[0007] The disclosed method enables accurate, rapid, and reliable determination of the surface roughness of a sample surface using multiple measurement data in which the measurement parameters of the optical three-dimensional measurement, i.e., the brightness level of the light source used or the exposure of the image sensor, are different. Then, multiple measurement data are calculated from the multiple measurements in such a way that the exact surface roughness of the sample surface is determined for all measurement data or for all measurements, and a single accurate value of surface roughness can be reflected as a result of the method. In other words, first, multiple measurements of the sample surface are performed using optical three-dimensional measurement of the sample surface, and as a result, measurement data indicative of the surface topology of the sample surface is provided. For example, each measurement data may indicate or include surface topology data in the form of, for example, a three-dimensional (surface topology) image or cloud point data. For each of the multiple measurements, and thus for each of the multiple measurement data, a different brightness level of the light source that illuminates the sample surface during measurement, i.e., acquires an image of the sample surface by the image sensor, may be used. Alternatively, for each of the multiple measurements, and thus for each of the multiple measurement data, a different exposure of the image sensor may be used. Second, for each of the multiple measurements or each of the multiple measurement data, first calculated data indicating the surface roughness, particularly a surface roughness value, of the sample surface may be acquired, particularly determined, or calculated by the data processing system. In particular, the respective surface roughnesses or surface roughness values ​​may be different, based on the observation that different brightness levels or different exposures produce different surface roughness values. Third, based on the first calculated data, second calculated data may be determined, particularly calculated by the data processing system, and more specifically, the second calculated data reflecting the surface roughness, particularly a surface roughness value, may be determined based on the first calculated data. More specifically, the second calculated data may represent all the measurements or measurement data, which may be an exact single surface roughness value or a surface roughness value for the entire sample surface. This method is highly reliable when performed on multiple samples, because using measurement data obtained by varying the brightness level of the light source or the exposure level of the image sensor produces reproducible results independent of the size, material, and reflection characteristics of different samples (e.g., shiny or rough sample surfaces).

[0008] The method of the first aspect may be, in particular, at least partially or completely computer-implemented. This means that at least one, several, or all of the steps of the method may be performed by a data processing system including one or more data processing devices or computers or computing units, which may be part of a system for performing a wet etching process, i.e., a wet etching processing system. Different steps may be performed by the same computer or by different computers. In this specification, a computer is understood as a data processing device capable of performing some, several, or all of the steps defined by the method. The one or more computers may be configured as or provided within one or more sensor units, control units, and / or other units of the sample processing system, or may be provided separately as part of the sample processing system. The one or more sensor units may have an image sensor. For example, the sensor unit may be configured as a camera unit having an image sensor and / or a light source.

[0009] The acquisition of the plurality of measurement data may be performed, for example, by a data processing system. Alternatively, or additionally, the acquisition of the plurality of measurement data may be performed by a sensor unit or a camera unit, which may transmit the plurality of measurement data to the data processing system. Alternatively, or additionally, the method of the present disclosure may include, in addition to acquiring the plurality of measurement data, measuring the measurement data, for example, by a sensor unit or a camera unit of the sample processing system. The measurement data may be or include, for example, image data indicative of a three-dimensional surface topology in a coordinate system and / or a point cloud representing points of the three-dimensional surface topology.

[0010] The obtaining of the first calculated data and / or the determination of the second calculated data may be performed, for example, by a data processing system. In particular, the first calculated data and / or the second calculated data may be based on calculations by the data processing system, where the calculation of the first calculated data uses a plurality of measurement data as input and / or the calculation of the second calculated data is based on the first calculated data.

[0011] To obtain, in particular to determine, the first calculated data, for example, a calculation method, simulation, or formula for determining the surface roughness or surface roughness value of the sample surface using the respective measurement data as input may be used. The method, simulation, or formula may be configured so that the surface roughness is determined based on physical properties or on physical principles that take the sample surface into account. Depending on the value representing the computerized or calculated surface roughness, the mathematical method or formula may vary. For example, the average or arithmetic mean of the profile height deviations from the mean line (usually referred to as Ra, Raa, or Ryni) may be used as the surface roughness value. Such an average or arithmetic mean Ra may be used, for example, for the surface roughness indicated by either the first calculated data or the second calculated data. Additionally or alternatively, other values ​​or metrics may be used to represent surface roughness, such as, but not limited to, the quadratic mean or root mean square of the profile height deviation from the mean line (commonly referred to as Rq or RM), the maximum valley depth below the mean line (commonly referred to as Rv), the maximum peak height above the mean line (commonly referred to as Rp), the maximum peak-to-valley height of the profile, skewness, kurtosis, the average distance between the highest peak and the lowest valley, a number based on the number of highest peak values ​​and / or lowest valley values ​​(e.g., 5), an ISO grade number, and / or any other value. The calculation methods, simulations, or formulas may vary for each example of the aforementioned values ​​or metrics.

[0012] To determine the second calculated data, the surface roughness values ​​of each of the plurality of measured data can be combined with one another in any of a variety of ways, as described below.

[0013] The specimen may be, for example, a wafer, in particular a semiconductor wafer. The semiconductor wafer may be used in the manufacture of integrated circuits. In particular, the wafer may be etched on its front side and on its opposite back side. The wafer may have any reflective or reflecting properties. The wafer may comprise silicon, in particular crystalline silicon, or other semiconductor materials such as, but not limited to, germanium, gallium arsenide, indium phosphide, silicon carbide, gallium nitride, sapphire, etc. The specimen may be of any size and shape. The specimen may be, for example, disk-shaped. The specimen may be referred to as a substrate, in particular a disk-shaped substrate. The specimen may be any substrate other than a wafer, for example a metal substrate or a glass substrate.

[0014] The optical three-dimensional measurement may be based on, for example, white light interferometry. In other words, white light interferometry may be used for optical three-dimensional measurement. A camera with an image sensor may be part of the apparatus for white light interferometry. The image sensor may be, for example, a charge-coupled device (CCD) image sensor. The light source may be, for example, a white light source. White light interferometry is particularly accurate when the surface varies in nanometers, for example, in the range of 50 nm to 500 nm, as is the case with wafer surfaces.

[0015] Each of the measurement data may be associated with a different brightness level or exposure, with an increase or decrease in gain between successive measurements by the image sensor. Thus, for example, multiple measurement values ​​or multiple measurement data may be acquired successively by varying the brightness level or exposure with successively increasing or decreasing gain. The gain may be predetermined or predefined. For example, the gain may be predetermined or predefined as an absolute value and / or a relative value (e.g., a % of a nominal brightness level or nominal exposure). For example, the gain may be a fixed value, particularly a fixed value throughout all measurements. Alternatively, the gain may vary throughout the measurements. For example, the gain may be smaller or larger, or otherwise, in an initial measurement compared to a later measurement.

[0016] For example, the gain may be in the range of 0.1% to 8% of the nominal brightness level or nominal exposure, particularly in the range of 0.5% to 6%, more particularly in the range of 1% to 4%. The nominal brightness level or nominal exposure may be defined, for example, by the technical limitations of the light source and / or the image sensor. The nominal brightness level or nominal exposure may be the maximum brightness level or maximum exposure. The exposure is also called the exposure ratio or exposure value. The exposure is, for example, the amount of light per unit area (e.g., mm 2 ) may be defined as the amount of light per unit area. The nominal or maximum exposure may be, for example, the maximum amount of light per unit area that the image sensor can record or utilize. Gains within this range have been found to provide accurate results for the surface roughness indicated by the second calculated data, at least with acceptable or fast decision times.

[0017] Alternatively or additionally, for example, the gain may be increased or decreased (particularly by magnitude) in a range from 5% or more, particularly 10% or more, of the nominal brightness level or nominal exposure to 80% or more, particularly 90% or more, more particularly approximately or exactly 100% of the nominal brightness level or nominal exposure, which has been found to provide accurate results of the surface roughness indicated by the second calculated data, at least within acceptable or fast decision times, using a substantially fully usable or suitable range of different brightness levels or exposures.

[0018] By defining the magnitude of the gain and the relative range with respect to the nominal brightness level or exposure within which the gain is increased or decreased, the number of measurements or measurement data, particularly images, acquired from the sample surface by the image sensor can be defined. For example, the number of measurements, measurement data, and / or images may be in the range of 10-900, particularly 20-900, more particularly 20-180, and even more particularly 40-120, such as 90, at a gain of 1% of the nominal brightness level or exposure between 10% and 100% of the nominal brightness level or exposure. These numbers have been found to be advantageous because the data obtained thereby is sufficient to obtain accurate second calculation data, and the method can be performed relatively quickly.

[0019] One of the brightness level and the exposure can be maintained substantially constant or approximately constant, for example, during successive measurements by the image sensor. In other words, one of the brightness level and the exposure can be increased or decreased during successive measurements, while the other is maintained constant. It has been found that varying only one of the aforementioned measurement parameters is sufficient to generate multiple measurement sets for determining a single, accurate surface roughness value. This simplifies the method and allows for very rapid determination of the roughness value for all multiple measurement data, compared to varying both measurement parameters (which could, for example, be sequential, simultaneous, or random).

[0020] The method (300) may include filtering each of the measurement data by one or more of the following steps: removing data points outside the sample surface; removing noise; cropping an image representative of the surface topology indicated by the measurement data; and leveling the image, and the first calculated data is based on each of the filtered measurement data. In other words, before acquiring the first calculated data, filtered measured data is generated for each of the measured data, and then the first calculated data is obtained based on the filtered measured data. Filtering improves the accuracy of the first calculated data, thereby improving the accuracy of the second calculated data, by filtering values, data points, etc., from the multiple measured data. Without filtering, the results of the second calculated data would be inaccurate, for example, because they are based on noise, outliers, or data that do not accurately reflect the sample surface. As an example, when removing data points outside the sample surface, for example, in an image or point cloud, spikes may be removed from the image or point cloud, for example, line by line. Additionally or alternatively, for example, when removing noise, the surface represented by the image or point cloud may be smoothed, for example, by average filtering. Additionally or alternatively, for example, by cropping the image to represent the surface topology, image padding at the image borders may be avoided. Additionally or alternatively, for example, by flattening the image, rough surfaces in the image may be separated from other surfaces and image waviness may be removed. For example, the ISO 25178 standard may be used at least in part or in full for each of the measurement data filtering means described herein, or alternatively, in particular for all of the filtering means described herein.

[0021] For example, determining the second calculated data may include calculating a density function for each surface roughness of the sample surface for each measurement data, and determining the surface roughness of the sample surface for all measurement data based on the density function. In particular, the density function may indicate the probability of different surface roughness values ​​from the first calculated data based on the plurality of measurement data. In particular, the density function may be a probability density function indicating the probability of a surface roughness value within a range of surface roughness values ​​based on the surface roughness values ​​of the first calculated data. As an example, the density function may plot, for example, a probability expressed in % or point values ​​against, for example, a surface roughness expressed in nm. Interestingly, it has been found that by calculating a density function for each surface roughness of the plurality of measurement data, significant maxima, or peaks when the density function is graphed, may be observed across different brightness levels or exposure ranges.

[0022] Thus, for example, for all measurement data, the surface roughness of the sample surface may be determined based on or as the maximum value of the density function. The surface roughness of all measurement data, particularly a single surface roughness value, may be the maximum or peak of the density function, or a value that is approximately or near the maximum or peak of the density function, such as an average near the peak.

[0023] Determining the second calculated data may include, for example, repeating the acquisition of multiple measurement data, the first calculated data, and determining the second calculated data if the calculated density function shows two peaks of the surface roughness of the sample surface for all measurement data. More specifically, the steps of the aforementioned method may be repeated, for example, if both peaks meet the peak threshold and / or if both peaks differ in size from each other within the peak threshold. Two or more peaks, especially if they meet the peak threshold and are therefore of similar or sufficient size, may be interpreted as a signal to repeat the method for determining the surface roughness of the sample surface. For example, but not limited to, dust particles or the like may be the root cause of two peaks or maxima in the density function. If two peaks still exist after repeating the aforementioned steps, the measurement or sample may be rejected and, for example, treated as a scrapped part.

[0024] It should be noted that the determination of the second calculated data may alternatively or additionally be performed in a manner different from using a density function or selecting a maximum or peak of the density function, for example, determining an average, arithmetic, or other value from the surface roughness of the sample surface for the measured data or density function, respectively, is an example of such a different manner.

[0025] For example, the sample surface may be an etched sample surface. Further, the method may include obtaining control data for controlling one or more settings of a wet etching process performed on one or more further samples based on the second calculated data. This allows the method to control the wet etching process by controlling one or more settings of the wet etching process based on second calculated data that accurately reflects the measurement data. In particular, the control data may be obtained to control one or more settings of a wet etching process for etching a previously measured additional sample following an already etched sample using the same wet etching process, particularly using the same container containing the same chemical solution used to etch the previous sample. This allows the method to perform the wet etching process of the sample as quickly as possible while minimizing the required resources, such as wet chemicals, and eliminating their premature replacement, and with consistent quality, such as a substantially consistent target surface roughness range, without relying on potentially inaccurate statistical techniques. Instead, the method uses actual measurement data of one or more parameters, particularly target parameters of the wet etching process related to the target size of the etched sample or before and after etching of the sample, and / or quality parameters of the wet etching process related to the quality of the etched sample (particularly related to the size or dimensional tolerance or accuracy of all etched samples for one or more parameters). However, in addition to using the surface roughness indicated by the second calculated data, alternative or additional measurement data of one or more other parameters, such as, for example, a measured thickness or material removal of the specimen, may be used to determine the control data. In other words, measurement data indicative of the thickness and / or material removal of the specimen due to wet etching may alternatively or additionally be used as a basis for obtaining the control data.

[0026] The acquisition of the control data may be performed, for example, by a data processing system. Alternatively, or additionally, the acquisition of the control data may be performed by one or more control units and / or one or more operational units of the wet etching processing system configured to execute one or more control settings. In a further variation of the foregoing, the data processing system may provide the control data to one or more control units and / or one or more operational units, which may acquire and subsequently execute the control data. For example, one or more control units and / or operational units may be configured to at least partially replace the chemical solution, e.g., change the composition of the chemical solution by adding one or more chemical etchants to the chemical solution, and / or control the etching duration of the specimen. For example, the operational unit may be or include, but is not limited to, a dispenser or dispensing unit for dispensing the chemical solution onto the surface of the specimen, a pump fluidly connected to the dispenser and the container, a supply line to the container of the wet etching processing system, a container containing the chemical solution, etc.

[0027] Alternatively or additionally, the disclosed method may include, in addition to acquiring the control data, executing the control data, i.e., one or more settings to be controlled, for example, by one or more control units and / or one or more operation units of the wet etching processing system. Acquiring the control data may in particular be determining the control data by a data processing system. As explained further below, acquiring the control data may also be updating the control data, in particular already acquired or existing control data.

[0028] Here, controlling one or more settings may refer, for example, to determining or setting one or more settings, such as the lifespan of wet chemicals, or in other words, the lifespan of a chemical solution. Alternatively, or in addition, controlling one or more settings may refer, for example, to adjusting a current or currently set setting, such as a setting related to the lifespan of a chemical solution change, for example, by shortening or extending the lifespan, so that the change of the chemical solution in the container begins earlier or later depending on the second calculated data. Further examples of controlling settings are provided below, and the controls in the described examples of determining or setting and adjusting may be applied to these settings interchangeably.

[0029] The wet etching process may be a single-sample etching process in which a single sample can be continuously etched by dispensing a chemical solution onto the sample surface. For example, the chemical solution may be dispensed by dripping, spraying, or the like onto the sample surface, particularly one side of a wafer, more specifically the backside, using a nozzle, spray system, or similar dispensing unit of the wet etching processing system. The sample may be rotated as needed during chemical solution dispensing or wet etching to improve distribution of the chemical solution on the surface. The opposite side may not need or should not be exposed to the chemical solution. In such cases, a gas flow or the like may be supplied to that side to prevent the chemical solution from reaching that side, particularly the wafer surface. The single-sample etching process may be performed by a type of wet etching processing system called a single-sample wet etching processing system. Only one sample may be etched at a time in at least one processing chamber or etching apparatus. This differs from, for example, batch etching, in which multiple samples are placed on a carrier and immersed in a chemical bath for etching. However, methods other than batch etching or single-sample etching may also be performed.

[0030] The second calculated data may be continuously determined for the samples etched by the wet etching process, and the control data may be continuously acquired or updated based on the second calculated data. For example, to acquire the second calculated data, consecutive samples may be measured one by one or every few consecutive samples. In particular, a sampling or sampling mode may be used in which a predetermined number of samples and / or sample order is used to acquire the second calculated data for the samples according to the number and / or sample order. The number of samples may indicate, for example, per measured chemical solution, per number of samples (e.g., 100 samples), and / or the like. The sample order may indicate the number of samples measured within the consecutive samples. For example, the number of consecutive samples may indicate every two, five, or ten samples, or a varying (e.g., fixedly varying) or dynamically adopted number of consecutive samples. Sampling, particularly the number of samples and / or sample order, may depend, for example, on the type of wafer (e.g., material and / or size), the type and / or composition of the chemical solution used, second calculation data from previously measured etched samples, and / or previously acquired control data. By acquiring or updating control data based on each of these second calculation data, the wet etching process can be constantly monitored during wet etching of the samples. In particular, the wet etching process can be monitored so that if the second calculation data indicates a quality change for one or more consecutive samples, e.g., an etched sample deviating from a target range for one or more target parameters or approaching a threshold value of the target range, the control data can be updated and one or more settings can be controlled to counter the quality change, particularly quality degradation, for example, by adjusting the settings and / or determining or setting new settings. For example, the chemical solution in the container can be at least partially or substantially completely replaced (meaning that remnants or residues of the previous chemical solution may still be contained in the container, but most of the chemical solution may be replaced).

[0031] For example, at least one of the one or more settings may relate to at least partial replacement of a chemical solution. The at least partial replacement of a chemical solution may be a complete or substantially complete replacement of the chemical solution contained in a vessel of a wet etching processing system (i.e., some residue or remnants of the previous chemical solution may remain in the vessel, but most of the chemical solution may have been replaced). For example, the setting for chemical solution replacement may indicate a time, particularly a lifetime, after which the chemical solution should be at least partially replaced, particularly with a chemical solution of the same type and / or composition. Additionally or alternatively, for example, the setting for chemical solution replacement may indicate an amount or substance of chemical solution, e.g., one or more chemical etchants, to be replaced. For example, by providing new, fresh chemical solution or wet chemistry as a bath in the vessel, active chemicals or substances, e.g., one or more chemical etchants, are again present and / or may etch the sample within target parameters to meet established sample quality requirements.

[0032] In addition to or alternatively to at least partially replacing the chemical solution, for example, at least one of the one or more settings may involve changing the etching time. Etching time refers to the (total) time of etching a sample in a wet etching process, and may be determined by, correspond to, or substantially correspond to, for example, the supply time and / or amount of chemical solution supplied per sample. Thus, for example, by adjusting, determining, and / or setting the supply time and / or amount of chemical solution supplied per sample, etching quality can be maintained constant within target parameters. For example, by increasing the supply time over the life of a wet chemistry, even a wet chemistry that is chemically weaker or less reactive in terms of etch rate can be used to obtain samples whose target parameters are within the target range, at the expense of increased etching time and, therefore, increased processing time per sample. However, this may be an acceptable trade-off before, for example, replacing the chemical solution, and may help maintain quality control of the etched samples.

[0033] Additionally or alternatively, at least one of the one or more settings may involve changing the composition of the chemical solution, e.g., at least partially replacing the chemical solution and / or changing the etching time. For example, one or more chemical etchants, other chemicals, and / or additional etchants (other than the one or more chemical etchants in the chemical solution) may be added to the chemical solution to change the composition of the chemical solution. This is also referred to as spiking or buffering with the respective chemicals, e.g., etchants. This may involve adding a less effective or ineffective chemical etchant (e.g., but not limited to, hydrofluoric acid (HF)) that may have already reacted with and oxidized the sample into the container containing the chemical solution before triggering a nearly complete replacement of the chemical solution or increasing the etching time to an undesirable level. Additionally or alternatively, the percentage or amount of water in the chemical solution may be determined.

[0034] In addition to or instead of at least partially replacing the chemical solution, changing the etching time and / or changing the composition of the chemical solution, e.g., at least one of the one or more settings, may be associated with changing the distribution of the chemical solution on the sample. For example, adjusting the ejection profile of the chemical solution onto the sample surface may change the distribution of the chemical solution on the sample. For example, the ejection profile may include a pattern of chemical solution ejected per time. Alternatively or additionally, adjusting the ejection direction, rotation speed, and / or orientation of the sample may change the distribution of the chemical solution on the sample. Based on the second calculation data, the change in distribution may be utilized, for example, to provide a more uniform thickness and / or surface roughness distribution on the sample surface.

[0035] The method may further include, for example, the following steps: acquiring second measurement data indicative of the composition of the chemical solution, wherein the control data is further based on the second measurement data. In particular, the amount of one or more chemical etchants in the chemical solution may be indicated by the second measurement data. The second measurement data may be acquired or determined based on a measurement unit of the wet etching processing system, for example, an optical spectrometer. Therefore, measurement data indicative of the surface topology of the sample surface based on optical three-dimensional measurement of the sample surface by an image sensor may also be referred to as first measurement data herein. By acquiring the second measurement data and creating control data based thereon, control data may be acquired that takes into account the composition of the chemical solution, for example, the amounts of various chemicals such as chemical etchants, and other surfaces containing, for example, chemically reacted or less effective or ineffective amounts of chemical etchants (e.g., oxidizing etchants) contained in the chemical solution. This can be useful because the first measurement data can be related to the composition of the chemical solution, and for example, if the amount of chemically active or effective, e.g., oxidizing chemical etchant in the chemical solution is low, the deviation of one or more of the target parameters from the target range can be attributed to the composition, and control data can be obtained or updated by, for example, changing the composition of the chemical solution by adding one or more chemical etchants.

[0036] The control data may further be based on threshold data, which indicates a threshold value for the surface roughness of the specimen. The threshold value indicates, provides, or is associated with a target value or target range for each target parameter of the surface roughness. This may ensure that the target parameter is maintained within a desired target range. For example, if the target parameter is outside the threshold, e.g., above or below the threshold (depending on the definition of the threshold), the control data may be obtained or updated to control one or more settings. The control data may depend on the amount by which the target parameter is above or below the threshold, i.e., the target value or target range. For example, one or more settings, such as the etching time, may be controlled in correlation with, e.g., proportionally to, the amount by which the threshold is exceeded or exceeded.

[0037] Alternatively, or additionally, the control data may be obtained, at least partially or completely, as the output of a machine learning algorithm. The machine learning algorithm is trained using at least the second calculation data and / or control data from a previous wet etching process. The previous wet etching process may have used a different chemical solution or wet chemistry. For example, the previous wet etching process may have used a chemical solution that does not necessarily have the same composition, but rather has the same composition, but has been chemically exhausted in terms of reactivity to the etching process and replaced with a new chemical solution. Thus, the machine learning algorithm, which may be executed by the data processing system, may learn or train based on at least the second calculation data and / or control data, and obtain or update the control data as the output of the machine learning algorithm in an optimized manner based on previous historical data from the previous wet etching process. For example, the previous wet etching process may have used different and / or the same type and / or size of specimens, and the machine learning algorithm may have learned optimal or near-optimal control of one or more settings of the control data based on the different specimens. Also, or alternatively, in a previous wet etching process, different settings and / or different amounts within settings, such as etching time or the amount of etching solution added to fill a chemical reservoir, were controlled, and the machine learning algorithm may have learned the optimal or near-optimal settings to be controlled in terms of determining or setting those and / or those amounts for the particular measurement data (e.g., a particular total thickness variation range). The machine learning algorithm may thereby recognize and provide as output one or more settings to be controlled to optimally process the particular measurement data (e.g., a particular total thickness variation range).

[0038] It should be noted that determining the control data based on threshold data may be based on a deterministic approach rather than a machine learning approach, but does not necessarily exclude a machine learning algorithm approach. Rather, the control data may be obtained, selected from, or a combination of both, or otherwise used in combination. Furthermore, other or additional methods for obtaining the control data may be employed, such as neural networks or other artificial intelligence techniques.

[0039] The method is configured to control two or more wet etching processes, particularly processes each using a different chemical solution, and includes acquiring control data for each of the two or more wet etching processes. Second calculation data may also be determined for each of the two or more wet etching processes. The two or more wet etching processes may improve etching of the sample. The two or more wet etching processes may be performed sequentially, particularly for each sample. For example, one of the wet etching processes may be used to prepare the sample surface for etching. For example, this wet etching process may use HF as the chemical solution. Next, or instead, one of the wet etching processes may be used for polish etching of the sample surface. In this case, a different chemical solution (in terms of composition) may be used, for example, including HNO3, HF, H2SO4, and H3PO4. Next, for example, a wet etching process may be used for rough etching of the sample surface. Again, a different chemical solution may be used, for example, including HNO3, HF, and H2SO4. Therefore, each wet etching process can treat the sample surface differently based on the chemical or wet chemistry composition used to achieve the aforementioned objectives, i.e., preparation, polishing, and rough etching. Using a method for controlling two or more, particularly consecutive, wet etching processes, each with a different chemistry, sample quality can be optimized by controlling one or more settings in each of the two or more wet etching processes based on second calculation data for each wet etching process or thereafter. Therefore, this method can be applied to all consecutive wet etching processes using different or the same chemical compositions on the same sample surface.

[0040] According to a second aspect of the present disclosure, there is provided a computer program product comprising instructions which, when executed by a computer or data processing apparatus, cause the computer or data processing apparatus to perform a method according to the first aspect of the present disclosure.

[0041] A computer program product may be a computer program, in particular a computer program itself, i.e. a computer program consisting of or including program code for being executed by a computer or data processing apparatus, or it may be a product such as a data storage, in particular a computer-readable data storage medium, capable of storing a computer program at least temporarily or permanently.

[0042] According to a third aspect of the present disclosure, there is provided a data processing system configured to perform the method according to the first aspect of the present disclosure.

[0043] The data processing system may include one or more computers or data processing devices as described above, and optionally a computer program product according to the second aspect of the present disclosure.

[0044] According to a fourth aspect of the present disclosure, there is provided a sample processing system comprising the data processing system of the third aspect of the present disclosure, a light source for illuminating the sample surface, and an image sensor for acquiring a plurality of measurement data.

[0045] The sample processing system may in particular be configured as a wafer processing system for processing wafers, in particular as a wet etching system, in other words as a system for performing a wet etching process.

[0046] For example, the sample processing system may include a container containing a chemical liquid for wet etching the sample, and a dispenser fluidly connected to the container for dispensing the chemical liquid from the container onto the sample surface.

[0047] The image sensor and the light source may be part of a measurement system of the sample processing system. Furthermore, the measurement system may comprise a measurement unit, e.g., in the form of an optical spectrometer, for acquiring second measurement data. Furthermore, the wet etching processing system may comprise a chamber or device for accommodating the sample during dispensing of the chemical solution onto the sample surface. Furthermore, a rotation unit for rotating the sample during dispensing of the chemical solution may be provided in the wet etching processing system. Furthermore, the wet etching processing system may comprise a supply line, a pump, and / or the like for fluidly connecting the dispenser and the container. Similarly, the wet etching processing system may comprise an exhaust line, a pump, and / or the like for fluidly connecting the exhaust of the chamber or device and the container, thereby allowing the chemical solution used to etch the sample in the chamber or device to be exhausted and recirculated back to the container.

[0048] When two or more different wet etching processes are used, particularly when each process uses a different chemical solution, the wet etching processing system may include two or more containers for each of the different chemical solutions. Furthermore, the wet etching processing system may include separate chambers or drains within a single chamber or device for discharging each of the different chemical solutions individually and recycling them to their respective containers. The wet etching processing system may also include an actuator for moving the specimen between at least two chambers or drain sections, which may be rotatable or rotatably connected to a rotation unit, e.g., in the form of a linearly movable shaft for moving the specimen between the two chambers or drain sections.

[0049] It should be noted that the above aspects, examples, and features may be combined with each other regardless of the aspects involved.

[0050] These and other aspects of the present disclosure will become apparent from and be elucidated with reference to the drawings described hereinafter. [Brief explanation of the drawings]

[0051] The exemplary embodiments are further described with reference to the drawings.

[0052] [Figure 1] FIG. 1 is a perspective view showing an example of a sample processing system. [Figure 2] FIG. 2 is a schematic diagram illustrating an example of the sample processing system of FIG. 1 and its components. [Figure 3] FIG. 3 is a perspective view of an example of the chamber of the sample processing system of FIGS. 1 and 2 while etching a wafer. [Figure 4] FIG. 1 is a schematic diagram showing an example of a BEOL process in a semiconductor manufacturing process. [Figure 5] 5 is a schematic diagram illustrating an example of the relationship between the results of different settings controlled during the different etching processes shown in FIG. 4 and wafer quality as defined herein. [Figure 6] 5 is a schematic diagram illustrating an example of the relationship between the results of different settings controlled during the different etching processes shown in FIG. 4 and wafer quality as defined herein. [Figure 7] FIG. 5 is a schematic diagram illustrating an example of the relationship between a method for controlling the wet etching process of FIG. 4 and wafer quality as defined herein. [Figure 8] FIG. 3 is a schematic diagram illustrating an example of a method for determining the surface roughness of a sample surface within the sample processing system of FIGS. 1 and 2. [Figure 9] 1A and 1B are schematic diagrams showing examples of optical three-dimensional measurement results of a sample surface at different brightness levels. [Figure 10] 1A and 1B are schematic diagrams showing examples of optical three-dimensional measurement results of a sample surface at different brightness levels. [Figure 11] FIG. 1 is a schematic diagram showing an example of calculated roughness of a sample surface in multiple optical 3D measurements at different brightness levels. [Figure 12] FIG. 10 is a schematic diagram showing an example of calculated roughness of a sample surface in multiple optical 3D measurements at different exposure ratios. [Figure 13]FIG. 1 is a schematic diagram illustrating an example of the use of kernel density estimation to calculate surface roughness. [Figure 14] 12A and 12B are schematic diagrams illustrating an example of density functions of optical 3D measurements at different brightness levels in FIG. 11. [Figure 15] 13A and 13B are schematic diagrams illustrating an example of density functions of optical 3D measurements at different exposure ratios in FIG. 12.

[0053] The figures are schematic and not to scale. As a rule, identical or similar parts, elements and / or steps are provided with identical or similar reference numbers in the figures. DETAILED DESCRIPTION OF THE INVENTION

[0054] 1 shows a perspective view of a sample processing system 10, illustrated here as a wet etching processing system, i.e., a system for performing a wet etching process according to the embodiment. However, alternatively or additionally, other processes of a sample 1 may be provided by the sample processing system 10. The sample processing system 10 of this embodiment comprises a housing 11 and an acquisition unit 12 for acquiring a sample 1 (a semiconductor wafer 1 in this embodiment) (see FIG. 3).

[0055] As shown in Figure 1, wafers 1 may be retrieved from respective containers 40 (shown in Figure 1) that house wafers 1. Two containers 40 are shown here by way of example only, but there may be fewer or more containers 40. For example, one or more containers 40 may house wafers 1 that have not yet been processed, and in particular not yet wet-etched, by the sample processing system 10, while one or more other containers 40 may retrieve or receive wafers 1 after they have been processed or wet-etched by the sample processing system 10.

[0056] Additionally, sample processing system 10 includes a data processing system 20, shown here with a monitor and interface for receiving input from a human operator. Although data processing system 20 is illustrated outside housing 11, it may alternatively be located inside housing 11, for example, without the monitor and interface.

[0057] FIG. 2 schematically illustrates a sample processing system 10. In general, the locations, sizes, and numbers of the systems, sections, etc. illustrated in the sample processing system 10 are merely shown schematically, and in practice, may be different in location, size, or number from those illustrated. Wafers 1 to be etched are received from one or more of the illustrated containers 40, for example, via an acquisition section 12, which is an opening inside the housing 11, by a handling section 13, among others. The handling section 13 may include one or more handling means 14, such as one, two, or more robot arms, for handling the wafers 1. In particular, the handling means 14 may provide the wafers 1 to be etched to a processing section 15, which may include a chamber 16 or device for etching the wafers 1. In particular, there may be a plurality of processing sections 15 and / or chambers 16 or devices. For example, the wafers 1 may be processed in parallel by the respective sections and / or chambers 16. Similarly, one or more handling means 14 may again receive the etched wafers 1 and provide them in one or more other containers 40 for receiving processed wafers 1 .

[0058] The chamber 16 or apparatus may be supplied with a chemical solution 18 containing one or more chemical etchants for etching the wafer 1. The chemical solution 18 may be contained in one or more containers 17, i.e., tanks for containing the chemical solution 18. The containers 17 may range, for example, from one to four. The containers 17 may be located inside the sample processing system 10, particularly the housing 11, or may be located externally thereto, for example, connected to the sample processing system 10 via a hose. The chemical solution 18 is also referred to herein as a bath or a bath of the chemical solution 18. In particular, as illustrated below with reference to FIG. 4, different chemical solution compositions may be provided in two or, as illustrated by way of example, three or more containers 17 for different wet etching processes 131, 132, 133.

[0059] The sample processing system 10, e.g., processing unit 15, may further comprise one or more measurement systems 30, which may comprise one or more sensor units including one or more camera units, in particular one or more image sensors and one or more light sources, for obtaining first measurement data indicative of the material removal, thickness, and / or surface roughness of the one or more wafers 1 etched by the chemical liquid 18 after one, several, or each of the wet etching processes 131, 132, 133. Optionally, the measurement system 30 may comprise a measurement unit, e.g., in the form of an optical spectrometer, for obtaining second measurement data indicative of the composition of the chemical liquid 18 in the container 17.

[0060] 2, data processing system 20 may include data processing device 21, for example, in the form of one or more computers or computing units. Data processing system 20 may further include computer program product 22, for example, in the form of a computer-readable storage medium, on which computer program product 23, for example, in the form of a computer program, may be stored. When data processing device 21 executes the instructions of computer program product 23, method 200, shown in FIG. 7 and described below, may be performed. Alternatively, or additionally, when data processing device 21 executes the instructions of computer program product 23, method 300, shown in FIG. 8 and described below, may be performed. Also, for example, separate computer program products 23 may be provided for methods 200 and 300.

[0061] FIG. 3 shows a perspective view of the chamber 16 of the sample processing system 10. In this example, wet etching is shown as a single-wafer etching process, in which a single wafer 1 is successively etched by dispensing a chemical solution 18 onto the surface of the single wafer 1. However, as described above, other types of wet etching processes using a chemical solution 18 may alternatively be used, such as batch etching. In this example, the chemical solution 18 is supplied (e.g., pumped) to, for example, a nozzle-shaped dispenser 19, which dispenses the chemical solution 18 onto the surface, particularly the front surface, of the wafer 1 disposed within the chamber 16. Therefore, the processing unit 15 may be provided with supply lines, pumps, etc., connecting the container 17 to the chamber 16, particularly the dispenser 19. The container 17 may also be provided with a discharge line for discharging the chemical solution 18. As an example, during the dispensing of the chemical solution 18, the wafer 1 may be rotated, for example, by a rotation unit (not shown) disposed below the wafer 1 and driven by an actuator such as an electric motor. Furthermore, as shown in FIG. 3, for example, for successive wet etchings using different chemical solutions 18, the wafer 1 may be raised to different levels or exhaust sections of the chamber 16 by an actuator such as an electric motor or the same actuator.

[0062] 4 is a schematic diagram of a back-end-of-the-line (BEOL) process 100 in a semiconductor manufacturing process. In the illustrated exemplary BEOL process for a power semiconductor device using a wafer 1, wet etching may be used for wet chemical surface finishing 130 of the wafer 1. Typically, wet chemical surface finishing 130 is preceded by tape bonding or use of a glass carrier wafer 110, and wafer back grinding 120. In a typical BEOL process 100 in semiconductor manufacturing, wet etching may be followed by contact formation and annealing 140 and backside metallization 150.

[0063] Furthermore, as shown in wet chemical surface finishing 130, for example, three different wet etching processes 131, 132, and 133 may be performed consecutively, and the wet etching processes 131, 132, and 133 may be distinguished from one another by using three different chemical solutions 18, as shown in FIG. 2 . For example, the first wet etching process 131 is used to prepare the surface of the wafer 1 to be etched. For example, this wet etching process may use HF as the chemical solution 18. The second wet etching process 132 is used to polishly etch the surface of the wafer 1. In this case, a chemical solution 18 with a different composition may be used, for example, including HNO3, HF, H2SO4, and H3PO4. The third wet etching process is used to roughly etch the surface of the wafer 1. Again, a different chemical solution 18, for example, including HNO3, HF, and H2SO4, is used. Thus, each wet etching process 131, 132, 133 treats the surface of the wafer 1 differently based on the chemical solution 18 or wet chemistry composition used to achieve the aforementioned objectives: surface preparation, polishing, and rough etching.

[0064] FIG. 5 is a schematic diagram of the etching results for a time-based setting called fixed time correction during the third wet etching process 133 shown in FIG. 4. Specifically, the graph on the left side of FIG. 5 shows that as the baths of chemical solution 18 in the respective containers 17 for rough silicon etching etched to roughen the surface age, the amount of silicon (Si) removed (μm) and the roughness Ra (nm) decrease linearly for each wet-etched wafer 1. Here, the roughness Ra is preferably selected as the average or arithmetic mean of the deviations of the profile height from the mean line. This is because, during the third wet etching process 133 for the wafer 1, the chemical solution 18 changes over its lifetime, particularly due to chemical reactions between the material of the wafer 1 (e.g., Si) and the chemical solution 18. As a result, the etching solution in the chemical solution 18 is consumed, its effectiveness decreases, or it becomes ineffective. As the wet chemistry changes over its lifetime, using the same chemical solution 18 in the first wet etching process 131 can result in varying etch results for successively etched wafers 1 over the lifetime of the wet chemistry.

[0065] Therefore, to maintain the desired consistency in Si removal and roughness across wafers 1 etched in the same chemical solution 18 bath, it may be necessary to change the chemical solution 18 bath. However, an alternative approach is to perform a fixed time correction based on time. A control setting for this operation could be to change the etching time and correct the time based on the amount of time the chemical solution 18 bath has been used. For example, as the bath's usage time increases, the time spent dispensing chemical solution 18 on each wafer 1 could be increased, thereby allowing the chemical solution 18 to etch the surface of the wafer 1 for longer. As shown in the right graph of Figure 5, this effectively reduces the degradation of Si removal and roughness over time, allowing for control of the etch quality, i.e., the consistency of the etch results, of wafers 1 etched using the same bath over time.

[0066] FIG. 6 is a schematic diagram of the etching results for the fixed time correction setup described above with reference to FIG. 5 and the setup for buffering or spiking a chemical etchant, such as HF, into the chemical solution 18 during the second wet etching process 132 shown in FIG. 4. The graph on the left side of FIG. 6 illustrates how the Si removal volume (in μm) per wet-etched wafer 1 decreases, particularly linearly, as the bath of chemical solution 18 in each container 17 for rough silicon etching to roughen the surface ages. Therefore, to maintain the desired Si removal quality and roughness, the bath of chemical solution 18 must be replaced. However, as an alternative operation, a fixed time correction based on time may be performed, as shown in the center graph, as described above with reference to FIG. 5. The control setting for this operation is to modify the etching time to correct the time based on the previous usage time of the chemical solution 18 bath. Specifically, as the bath usage time increases, the time for dispensing the chemical solution 18 onto each wafer 1 may be increased, thereby increasing the time available for the chemical solution 18 to etch the surface of the wafer 1. As seen in the center graph of FIG. 6, this effectively reduces the degradation of Si removal and roughness over bath usage time, allowing for control of the quality of wafers 1 etched over time using the same bath. An alternative control action could be buffering or spiking a chemical etchant, such as HF, as shown in the right graph of FIG. 6. A control setting based on this could involve modifying the composition of chemical solution 18, for example, by adding HF as a chemical etchant, thereby buffering or spiking HF into chemical solution 18. As shown in the right graph, this could further improve the consistency of Si removal over the usage time of the chemical solution 18 bath.

[0067] Figure 7 shows a schematic diagram of a method 200 (left side of Figure 7) and the etch results (right side of Figure 7) of controlling any, more than one, or all of the wet etch processes 131, 132, and 133 of Figure 4. For example, in Figure 7, method 200 is shown as being performed for the second wet etch process 132 and the third wet etch process 133, which may be performed sequentially.

[0068] In a first step 210 of the method 200, measurement data is obtained that indicates the amount of material removal (e.g., Si (μm), thickness (e.g., wafer thickness (mm)), and / or surface roughness (e.g., Ra (nm)) of the wafer 1 that was last etched by the respective chemical solutions 18 used in the second wet etching process 132 or the third wet etching process 133. This step may be performed, in particular, by the data processing system 20 and / or the measurement system 30. For example, the measurement system 30 may obtain the measurement data by measurement and transfer it to the data processing system 20. The data processing system 20 may thereby obtain the measurement data and further process it, in particular for a second step 220 that follows the first step 210.

[0069] In a second step 220, control data for controlling one or more settings of each of the second wet etching process 132 and the third wet etching process 133 is generated based on the measurement data. The control data is then acquired, particularly determined, by the data processing system 20 after the measurement data of the etched wafer 1 is obtained. For example, the one or more settings may be a change in the etching duration (e.g., the aforementioned fixed time correction), a change in the composition of the chemical solution 18 (e.g., the aforementioned HF buffering or spiking), and / or at least a partial or complete replacement of the chemical solution 18 (i.e., a partial or complete replacement of the bath of the chemical solution 18 in the container 17 in each of the second wet etching process 132 and the third wet etching process 133).

[0070] In particular, method 200 may be performed twice: once on wafer 1 after second wet etching process 132 and once on wafer 1 after third wet etching process 133. This provides control data for controlling one or more settings of each of second and third wet etching processes 132 and 133. As shown on the right side of FIG. 7 , these settings may then be controlled after each wet etching process 132 and 133 to optimize the results. Here, controlling second and third wet etching processes 132 and 133 demonstrates that Si removal and roughness can be kept constant or nearly constant over very long bath usage periods. This quality control can be particularly enhanced by using a combination of the aforementioned settings. For example, first, the etching time can be changed, then the composition of chemical solution 18 can be changed, and finally, the chemical solution 18, i.e., the bath, can be changed. This is indicated by the stars in the graph.

[0071] Further, as shown in FIG. 7, the first step 210 and the second step 220 may be repeated, for example, for each wafer 1 processed by the second wet etching process 132 and / or the third wet etching process 133, or every few wafers, thereby continuously monitoring the bath or chemistry 18 using measurement data from the wafers 1 and updating the control data as necessary or beneficial.

[0072] When using the measurement data obtained from the measurement system 30 for method 200 or other purposes, such as for quality control assurance, the measurement data received directly from the measurement system 30 may not be accurate enough to provide high etch quality as shown in FIG. 7 , and it may be desirable to at least increase the accuracy of the measurement data. This is because the measurement data, e.g., the surface roughness indicated thereby, may not be an accurate or repeatable measurement for different types of wafers 1, e.g., having shiny or rough surfaces.

[0073] It is known to process images, particularly real-time images, of the sample surface to measure the surface roughness of the sample 1. To obtain accurate results, it may be desirable to adjust the parameters of the camera capturing the images and to eliminate external interference. For example, the adjustment or calibration of the camera parameters may take into account the reflective properties of the sample's particular surface and / or material. However, while accurately measuring surface roughness remains challenging, it is highly desirable to measure surface roughness as accurately, quickly, and reliably as possible for different types of samples 1, particularly or at least different in size, material, and / or reflective properties, so that the method 200 can provide high-quality etching results.

[0074] To this end, a method 300 as schematically shown in Figure 8 may be performed, for example, separately from, as part of, or in addition to the method 200 of Figure 7. The method 300 is configured to determine the surface roughness of a sample surface of a sample 1, in particular a wafer 1, in a sample processing system 10.

[0075] The measurement system 30 and / or the data processing system 20 are configured to acquire multiple measurement data, each of which is indicative of the surface topology of the wafer surface based, inter alia, on optical three-dimensional measurements of the wafer surface by the same image sensor, and each of which is associated with a different brightness level of a light source illuminating the wafer surface or a different exposure of the image sensor. To acquire the multiple measurement data, steps 310, 320, 330, and 340 of the method 300 are repeated multiple times.

[0076] Specifically, in step 310, optical 3D measurement of the sample surface can be performed by the image sensor at a particular brightness level of the light source or a particular exposure level of the image sensor. The optical 3D measurement can be based on white light interferometry. For example, method 300 can start with a 10% or 11% brightness level of the light source (compared to a nominal, e.g., maximum, brightness level) or a 10% or 11% exposure ratio of the image sensor (compared to a nominal, e.g., maximum, exposure ratio). The results of the optical 3D measurement at the 11% brightness level are exemplarily shown in FIG. 9 , which shows the surface in three dimensions: height (μm), x-axis, and y-axis (in pixels). Similar results can be obtained with an 11% exposure ratio (not shown).

[0077] Optionally, in step 320, the measurement data obtained in step 310, i.e., measurement data representing or including optical 3D measurements at a particular brightness level or exposure ratio, may then be filtered, for example, according to the ISO 25178 standard. For example, in sub-step 321, data points outside the sample surface may be removed. Further, for example, in sub-step 322, noise may be removed. Further, for example, in sub-step 323, an image representing the surface topology may be cropped, as shown in FIG. 9 . Also, for example, in sub-step 324, the image may be flattened.

[0078] Next, in step 330, it is determined whether the brightness level or exposure ratio is at a predetermined threshold or level. If "No," method 300 proceeds to step 340, where the brightness level or exposure ratio is increased by a predetermined gain (e.g., 1% or less or 1% or more), and steps 310-330 and / or 340 are repeated. Meanwhile, other parameters, such as the brightness level or exposure ratio, may be maintained constant, e.g., at 100% or any other value. Thus, the resulting multiple measurement data are associated with different brightness levels or exposures that increase stepwise until a predetermined threshold or limit, e.g., 100% brightness level or exposure, is reached, as exemplarily shown in FIG. 10 for a brightness level of 100%. Thus, if the result of step 330 indicates that the threshold or level has been reached, method 300 proceeds with steps 350 and 360.

[0079] Generally, if the result of step 330 is "yes," or after determining it at every step 330, or at any other step, or between any steps of method 300, method 300 may include obtaining, particularly by data processing system 20, first calculated data indicative of the surface roughness of the sample surface for each of the measurement data. In other words, a surface roughness value, e.g., as the average or arithmetic mean of profile height deviations from the mean line (Ra), may be determined, particularly calculated, for each of a plurality of measurement data, i.e., surface topologies from optical three-dimensional measurements at a particular brightness level or exposure. Thus, for each measurement, there may be one calculated surface roughness value associated with the measurement.

[0080] The calculated roughness values ​​are shown in Figure 11 for increasing brightness levels (%). The repetition of steps 310-330 and / or 340, i.e., measuring the surface topology, filtering the measurement data, and increasing the brightness level or exposure by a gain, is also referred to herein as a sweep, specifically a brightness sweep for increasing brightness levels or an exposure ratio sweep for increasing exposure ratios. Figure 12 shows the calculated roughness values ​​when the same sample surface is measured at different exposure ratios rather than different brightness levels. In both cases, measurements are taken within the range of 10-100% of the respective increased parameter. It can be seen that the calculated roughness values ​​vary significantly depending on the brightness level or exposure ratio used. It should also be noted that the results also depend on the reflective properties of the sample being measured, i.e., wafer 1. That is, a highly glossy wafer 1 exhibits different reflective properties than a less glossy or rougher wafer 1. Therefore, it is not possible to simply calibrate an image sensor to a specific brightness level or exposure ratio such that results for different wafer surfaces are comparable to each other.

[0081] Furthermore, as shown in Figures 11 and 12, the brightness and exposure ratio sweeps ultimately yield nearly identical sample roughness results. The key difference between brightness and exposure ratio is the measurement time. For the exposure ratio sweep, the measurement time was found to be approximately 2.5 minutes, whereas for the brightness level sweep, the measurement time was approximately 52 seconds. This is because brightness can be updated instantly during measurement acquisition, whereas the exposure ratio requires the entire image sensor or camera to be reset, which takes approximately three times longer than the brightness approach.

[0082] After obtaining the first calculated data, second calculated data is generally determined, particularly by the data processing system 20, and the second calculated data indicates the surface roughness of the sample surface for all the measurement data based on the first calculated data. In other words, the surface roughness values ​​of all the measurement data are integrated into a single surface roughness value that represents the accurate surface roughness value of the sample surface.

[0083] To determine the second calculated data, the method 300 may include calculating a density function of the surface roughness of each of the sample surfaces for each of the measurement data in step 350, and determining the surface roughness of the sample surfaces for all of the measurement data based on the density function in step 360. To calculate the density function, for example, kernel density estimation (KDE) as exemplarily shown in FIG.

[0084] Specifically, KDE can be applied to the entire resulting list of collected and calculated roughness values ​​to calculate the sample roughness for all measured data. KDE is a statistical method that estimates the probability density function (PDF) of a random variable. Unlike histograms, which divide data into bins, KDE can provide a smoother representation of the data distribution.

[0085] All data points x i (e.g., measured data points), the kernel function K(xx i ), which is usually a smooth, symmetric function such as a Gaussian. A kernel function is then centered at each data point. The width of the kernel function is determined by the choice of bandwidth "h." A larger bandwidth will result in a smoother estimate, while a narrower bandwidth will result in a more accurate but potentially noisy estimate. The final step is to sum these kernel values ​​over all observed data points. This gives the contribution of all data points to the density estimate at point "x," as shown in Figure 13.

[0086] Therefore, the estimated density at x (peak) is:

number

[0087] 14 and 15 are graphs showing the relationship between density functions and sample roughness values ​​for the luminance sweep (FIG. 14) and the exposure ratio sweep (FIG. 15) results of method 300. Both the luminance sweep and the exposure ratio sweep show similar results for the surface roughness of the sample surface, i.e., about 289 nm and about 299 nm. Specifically, the peaks in the graphs can be determined to be the surface roughness of the sample surface in all the measurement data shown or included in the second calculated data.

[0088] Optionally, three regions of interest may be observed: the region to the left of the peak, the region below the peak, and the region to the right of the peak. First, the region to the left of the peak may be considered an underexposed region, where not enough light reaches the sample 1. Next, the amount of light is increased until a second region is reached. The second region, the region directly below the peak, may be considered an overexposed region, where all valid calculations are obtained in this region. The amount of light is then further increased until a third region of overexposure is reached, where the amount of light exceeds the amount required for the sample 1. The more accurate the roughness calculation, the higher the density peak in the overexposed range.

[0089] Finally, there is no need to adjust parameters to be effective in roughness calculations. Method 300 with brightness or exposure ratio sweeps works for any type of wafer surface, whether shiny or rough. Peaks and therefore accurate surface roughness are detected regardless of the sample's reflectivity.

[0090] While the invention has been illustrated and described in detail in the drawings and foregoing description, such illustration and description are illustrative or exemplary and not restrictive. The invention is not limited to the disclosed embodiments. Other variations of the disclosed embodiments can be understood and effected by those skilled in the art and practicing the claimed invention, from a study of the drawings, the disclosure, and the claims.

[0091] As used herein, the word "comprising" does not exclude other elements or steps, and the indefinite articles "a" or "an" do not exclude a plurality. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. Furthermore, as used herein, "at least one" or similar expressions (e.g., "one or more"), with respect to a list of one or more entities, should be understood to mean at least one entity selected from any one or more of the entities in the list of entities, but does not necessarily include at least one of all entities specifically listed in the list of entities, nor does it exclude any combination of entities in the list of entities. This definition also recognizes that entities other than those specifically identified in the list of entities to which "at least one" or similar expressions refer may optionally be present, whether or not related to those specifically identified entities. Thus, as a non-limiting example, "at least one of A and B" (or, synonymously, "at least one of A or B," or "at least one of A and / or B," or "one or more of A and B," "one or more of A or B," or "one or more of A and / or B") can refer, in one example, to at least one A with no B (and optionally including entities other than B); in another example, to at least one B with no A (and optionally including entities other than A); and in yet another example, to at least one (and including one or more) A and at least one (and optionally including other entities) B. In other words, the terms "at least one," "one or more," and "and / or" are open-ended expressions that function as both conjunctions and disjuncts.For example, the phrases "at least one of A, B, and C," "at least one of A, B, or C," "one or more of A, B, and C," "one or more of A, B, or C," and "A, B, and / or C" may each mean A alone, B alone, C alone, A and B in combination, A and C in combination, B and C in combination, A, B, and C in combination, and optionally any of the above in combination with at least one other entity.

[0092] The phrase "indicating" as used herein can mean, for example, "reflecting" and / or "including." Accordingly, an entity, element, and / or step referred to herein as "indicating" may be used synonymously or interchangeably with one, two, or all of the entity, element, and / or step "including" and the entity, element, and / or step "reflecting."

[0093] Furthermore, as used herein, phrases such as "based on," "related to," "related to," and "associated with" should not be construed with respect to only the entities, elements, and / or steps to which they refer unless otherwise expressly stated. Rather, these phrases should be understood inclusively unless otherwise expressly stated; for example, an entity, element, or step referenced by these or similar phrases, such as "based on," or another entity, element, or step, does not exclude that the respective entity, element, or step may also be "based on" entities, elements, or steps other than the one to which it refers.

[0094] Designations such as "first," "second," etc., of methods and steps provided herein are intended only to make the methods and their steps mutually referable and distinguishable. The designations of methods and steps in no way limit the scope of the present disclosure. For example, if the present disclosure describes a third step of a method, the first or second step of the method need not be explicitly described as necessary or performed or present before the third step. Furthermore, presenting methods or steps in a particular order is intended to facilitate understanding of examples of the present disclosure and does not limit the scope of the present disclosure. In general, methods and steps may be performed in any practicable order unless an explicitly required order is mentioned. Specifically, terms such as "first," "second," "third," or "(a)," "(b)," "(c)," etc. in the specification and claims are used to distinguish between similar elements and not necessarily to describe an order or chronology. It should be understood that the terms used in this manner are interchangeable under appropriate circumstances, and that the embodiments of the present invention described herein can operate in orders other than those described or illustrated herein.

[0095] In the context of the present invention, the indicated numerical values ​​are usually associated with a range of accuracy that a person skilled in the art would understand to still ensure the technical effect of the feature in question. As used herein, the deviation from the indicated numerical value is in the range of ±10%, preferably ±5%. The deviation from the indicated numerical interval of ±10%, preferably ±5%, as mentioned above, is also indicated by the terms "about" and "approximately" used in relation to the numerical values ​​herein.

[0096] Any reference signs in the claims should not be construed as limiting the scope of the invention. [Explanation of symbols]

[0097] 1. Sample 10. Sample Processing System 11. Housing 12 Acquisition Department 13 Handling section 14 Handling means 15 Processing section 16 Chamber 17 Container 18 Chemical liquid 19 Dispenser 20 Data Processing System 21 Data processing device 22 Computer Program Products 23 Computer Program Products 30 Measurement System 40 containers 100 BEOL process 130 Wet Chemical Surface Finishing 200 ways 210 First Step 220 Second Step 300 ways

Claims

1. A method (300) for determining the surface roughness of the sample surface in sample (1), The above method (300) is, A step of acquiring multiple measurement data, wherein each of the measurement data represents the surface topology of the sample surface based on optical three-dimensional measurement of the sample surface by an image sensor, and each of the measurement data is associated with different brightness levels of a light source illuminating the sample surface or different exposures of the image sensor. For each of the aforementioned measurement data, a first calculated data indicating the surface roughness of the sample surface is obtained; Based on the first calculation data, a second calculation data indicating the surface roughness of the sample surface is determined for all measurement data, including, Method (300).

2. The sample (1) is a wafer. The method according to claim 1 (300).

3. The aforementioned optical three-dimensional measurement is based on white light interferometry. The method according to claim 1 (300).

4. Each of the aforementioned measurement data is associated with a different brightness level or different exposure that increases or decreases in gain between consecutive measurements by the image sensor. The method according to claim 1 (300).

5. The aforementioned gain is, The magnitude ranges from 0.1% to 8% of the nominal luminance level or nominal exposure. and / or Between 5% and 80% of the nominal brightness level or nominal exposure. The method according to claim 4 (300).

6. Between consecutive measurements by the image sensor, either the brightness level or the exposure is maintained substantially constant. The method according to claim 4 (300).

7. The above method (300) is, The steps include removing data points outside the surface of the sample, The steps to remove noise, A step of extracting an image representing the surface topology shown by the measurement data, The steps include leveling the aforementioned image, One or more of the steps include filtering each of the measurement data, Includes, The first calculation data is based on each of the filtered measurement data. The method according to claim 1 (300).

8. The step of determining the second calculation data is: For each of the aforementioned measurement data, the steps include calculating a density function for each of the surface roughness values ​​of the sample surface, A step of determining the surface roughness of the sample surface for all measurement data based on the density function, including, The method according to claim 1 (300).

9. For all measurement data, the surface roughness of the sample surface is determined based on the density function, or as the maximum value of the density function. The method according to claim 8 (300).

10. The step of determining the second calculation data is: The steps include acquiring multiple measurement data and the first calculation data, If the calculated density function shows two peaks for the surface roughness of the sample surface for all measurement data, the second calculation data is determined. including, The method according to claim 8 (300).

11. The aforementioned sample surface is an etched sample surface. The method described above Based on the second calculation data, the steps include obtaining control data to control one or more settings of a wet etching process (131, 132, 133) performed on one or more further samples (1), including, The method according to claim 1 (300).

12. When executed by a data processing device (21), the data processing device (21) is instructed to perform the method (300) according to claim 1. Computer program products (22, 23).

13. A device configured to carry out the method (300) described in claim 1, Data processing system (20).

14. A sample processing system (10) comprising the data processing system (20) described in claim 13, The aforementioned sample processing system (10) is A light source for illuminating the surface of the sample, An image sensor for acquiring the aforementioned multiple measurement data, Equipped with, Sample processing system (10).

15. The aforementioned sample processing system (10) is A container (17) for containing a chemical solution (18) for wet etching the sample (1), A dispenser (19) is fluidly connected to the container (17) and dispenses the chemical solution (18) from the container (18) onto the sample surface of the sample (1), Equipped with, The sample processing system (10) according to claim 14.

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