Improved camera for electron diffraction pattern analysis

Abstract

The invention provides an improved camera for electron diffraction pattern analysis, and particularly relates to a device for detecting a Kikuchi diffraction pattern. The apparatus comprises: an electron column adapted to provide, in use, an electron beam directed toward the sample, the electron beam having an energy in the range of 2 keV to 50 keV, and; an imaging detector for receiving and counting electrons from the sample due to the interaction of the electron beam with the sample, the detector comprising an array of pixels and having a count rate capability of at least 2000 electrons per second for each pixel wherein: the imaging detector is adapted to provide electron energy filtering of the received electrons, the particle detector has an active region and a diffraction pattern for counting received electrons representing said diffraction pattern, and the particle detector has an inert layer on a surface on which electrons enter towards the active region of the detector, where the inert layer disperses the detection energy of 20 keV incident electrons having an energy dispersion of a full width at half maximum of less than 3.2 keV. The invention also provides a method for detecting the Kikuchi diffraction pattern.

Description

[0001] This patent application is a divisional application of the patent application with application number 202180048196X, application date May 5, 2021, and invention title "Improved Camera for Electron Diffraction Pattern Analysis". Technical Field

[0002] This invention relates to an apparatus and method for performing micro-diffraction analysis, particularly electron backscatter diffraction (EBSD) analysis, on a sample to detect Kikuchi diffraction patterns. Background Technology

[0003] In micro-diffraction analysis, an electron beam is directed at a crystalline sample, and the interaction between the electrons in the beam and the sample results in the generation of different types of particles. Electrons originating from the source electron beam are elastically backscattered from the sample and then diffracted by the lattice planes of the crystal, a process of particular interest in materials research. The energies of these electrons are close to those of the main beam, forming the basis of electron backscattered diffraction (EBSD) analysis. For EBSD analysis, the diffraction contrast is captured as an image (diffraction pattern) by a pixelated detector, which is used to measure properties of the sample, such as crystal orientation and strain. Scanning electron microscopy (SEM) is typically used to generate the primary electron beam and to mount the sample and detector.

[0004] As described in US8890065, particle counting pixel arrays can be used as imaging detectors for micro-diffraction analysis. In such a system, the signal amplitude generated by a single particle received at the detector is compared to a threshold to distinguish the signal from system noise, thereby counting the individual particles. Furthermore, since the signal level is controlled by the energy of the incident particle, this threshold can be used to distinguish particles of different energies, counting only those particles with energies greater than a configurable threshold or located within a band between two thresholds. Such particle counting pixel arrays were originally developed for use in high-energy physics experiments or as X-ray detectors (sometimes referred to as hybrid photon counting detectors or HPC detectors), but are now used in EBSD.

[0005] In EBSD, the "signal" of interest is the diffraction contrast in the EBSD pattern, which is primarily carried by electrons whose energies lie within a narrow band between the main beam energy E0 of the SEM (typically 20 keV) and are usually 1-2 keV lower than E0. Electrons with energies below this band do not contribute to diffraction contrast but merely provide background for the measurement, thus reducing the accuracy of the diffraction contrast measurement. If the electron beam is incident on the sample at a small angle relative to the sample surface, the relative fraction of backscattered electrons carrying the diffraction contrast increases; for this reason, traditional EBSD experiments are performed with the sample tilted at a certain angle to achieve this incident geometry.

[0006] To identify the crystal type and generate characteristic Kikuchi diffraction contrast, EBSD patterns are processed to detect lines in the image and correlate them with planes in the crystal. This is typically achieved using the Hough transform method. Once the relationship between lines and angles is measured, the results can be used to find a high-level match with the crystal type. If not enough lines are detected, or a sufficient high-level match with the crystal type cannot be found, the pattern cannot be indexed. If the pattern can be indexed, the crystal orientation can be determined. If the pattern is obtained on a grid of points covering the field of view, a map showing the crystal orientation at each point in the field of view can be obtained. If a significant portion of the patterns cannot be indexed, the orientation map is useless. In this case, the SEM electron beam current must be increased or the acquisition time of individual patterns must be increased to obtain an acceptable proportion of patterns that can be successfully indexed. There are limitations to how much electron beam current can be generated in an SEM, and excessively high electron beam current can damage the sample. Increasing the acquisition time per pixel will further lengthen the time required to acquire the orientation map. Therefore, patterns that aim to achieve a high success rate with the lowest electron beam current and shortest acquisition time are included in the index.

[0007] The percentage of patterns successfully indexed at a given electron beam current and acquisition time depends in part on the sample and different experimental conditions. However, for a specific sample and fixed experimental conditions, the "sensitivity" measurement describes the ability of a detection device to acquire patterns that can be successfully indexed using short acquisition times and low electron beam currents. One measure of sensitivity is the reciprocal of the product (electron beam current x pattern acquisition time), which is necessary to achieve an acceptable percentage (e.g., 95%) of successfully indexed patterns.

[0008] As shown in US8890065, by using a discriminator to accept only pulses above a threshold level equivalent to a specific energy, it is expected to improve the sensitivity of measuring diffraction signals using an electron-counting EBSD detector. As this threshold increases, the signal / background should improve, and optimal results should be obtained when the threshold is close to the main beam energy. Indeed, Vespucci et al. (S. Vespucci et al., “Digital direct electron imaging of energy-filtered electron backscatter diffraction patterns”, Phys. Rev. B - Condens. Matter Mater. Phys., Vol. 92, No. 20, pp. 8-14, 2015) have shown that diffraction contrast measured from band intensity can be improved by increasing the threshold closer to the beam energy, i.e., ((maximum - minimum) / (maximum + minimum)), and when collecting EBSP from diamond at an incident beam energy of 20 keV, the contrast can be increased by a factor of 4 by increasing the threshold from 5.5 keV to 19.4 keV.

[0009] However, when processing diffraction patterns using a similar embodiment of the device shown in US8890065, it was found that while using a higher threshold level could improve the contrast of the diffraction pattern and enable the observation of higher-order diffraction features, the sensitivity decreased with increasing threshold. Therefore, an improved EBSD pattern detection system is needed to enhance sensitivity for orientation imaging applications. Summary of the Invention

[0010] According to a first aspect of the invention, an apparatus for detecting Kikuchi diffraction patterns is provided, the apparatus comprising: an electron column adapted to provide, in use, an electron beam directed toward a sample having an energy in the range of 2 keV to 50 keV; and an imaging detector for receiving and counting electrons from the sample due to the interaction of the electron beam with the sample, the detector comprising a pixel array and having a counting rate capability of at least 2,000 electrons per second for each pixel, wherein: the imaging detector is adapted to provide electron energy filtering of the received electrons in order to count the received electrons representing the diffraction pattern; and the particle detector has an inert layer on a surface on which electrons enter toward the active region of the detector, wherein the inert layer disperses the detection energy of 20 keV incident electrons having an energy dispersion of less than 3.2 keV at half maximum.

[0011] In this paper, "particle detector" refers to a detector that converts the energy of each received particle into an electronic signal, rather than an "indirect" detector, such as one that converts particle energy into light via a fluorescent screen and uses intermediate optics to focus the light onto a sensor. Indirect detectors suffer from inefficient optics, leading to decreased detection sensitivity. Furthermore, indirect detectors typically generate a signal current representing the energy x velocity product of the incident particle stream, whereas a particle detector measures the signal from a single particle.

[0012] The term "pixel" here typically refers to a spatially separated sensitive area of ​​a detector, such that a particle incident on two different pixels will be considered to have hit two different areas of the detector. Therefore, "pixel" can refer to a conventional pixel array in a direct electron detector or CCD known in the art, as well as a separate area, such as in a silicon strip detector, where each "pixel" is an area associated with each contact strip.

[0013] It has been found that imaging detectors are suitable for providing electron energy filtering of received electrons in order to count, or more specifically, preferentially count those received electrons that represent the diffraction pattern, particularly because such a “threshold” can improve the ratio of relevant diffraction information to diffuse background information that does not represent the diffraction pattern. The inventors have realized that, according to the first aspect, a significant improvement to this method can be achieved using a device. This is achieved by including an inert or “dead” layer in the detector, which disperses the electron energy passing through it to a lesser extent than conventional devices. In other words, the device is able to reduce the dispersion of the recorded signal by the effect of the relatively thick inactive layer conventionally used at the sensor inlet.

[0014] The “dead” layer is described in this disclosure as “inert,” and in a sense, the term refers to an inactive material. As explained in more detail later in this disclosure, a typical detector employs a layer of this material to form an electrical connection with the active sensor layer. This inert, inactive, or “dead” layer can be considered as the detector entrance window.

[0015] By reducing the diffusion of electron energy generated through the inert layer, thresholding becomes more effective in distinguishing or separating diffraction-correlated electrons from uncorrelated electrons. In other words, the range of recorded signals attributable to electrons with diffraction information is reduced compared to existing devices.

[0016] The inert layer is adapted or formed such that, or particularly has thickness and material properties such that it disperses the detection energy of 20 keV incident electrons, which have a full width at half maximum (FWHM) of less than 3.2 keV, to produce this advantageous effect. It can be understood that this means that for 20 keV incident electrons, the layer causes diffusion of transmitted electron energy such that the width of the energy spectrum curve of electrons transmitted through the layer (as measured between those energy values) is half the energy peak or the maximum value of the curve.

[0017] Preferably, the inert layer disperses the detection energy of the 20 keV incident electrons, wherein the 20 keV incident electrons have an energy dispersion of less than 2 keV, more preferably less than 1 keV, and even more preferably less than 0.1 keV full width at half maximum (FWHM).

[0018] Preferably, the electron column is part of a scanning electron microscope (SEM) that provides a beam energy in the range of 2 keV to 50 keV during normal operation. Typically, this arrangement places the detector and electron source on the same side of the sample, such that the received particles have a trajectory component returning relative to the sample along the electron beam axis. However, diffraction patterns can also be detected in transmission electron microscopy (EBSD), where the detector is located on the side of the sample opposite to the electron beam. In this configuration, the received particles do not have a trajectory component returning relative to the sample along the electron beam axis. In transmission EBSD, the received “signal” consists of elastically scattered electrons that pass through the sample rather than being reflected from it. It should be understood that the stated energy range of 2 keV to 50 keV for the electron beam represents the useful energy range for EBSD as a SEM technique.

[0019] The data rate required for EBSD experiments necessitates a minimum detector count rate capability. In some experiments, data rates can easily reach 10,000 events per second, thus requiring a detector count rate capability of 2,000 events per second per pixel, preferably 5,000 events per second, more preferably 10,000 events per second, and even more preferably 100,000 events per second. In this invention, this count rate is particularly important when each particle is received indiscriminately by the detector, then filtered and counted, rather than being filtered before impacting the detector.

[0020] The detector has at least one particle counter for counting the received particles representing the diffraction pattern. The counting rate of the at least one particle counter is at least 2,000 events per second, preferably 5,000 events per second, more preferably 10,000 events per second, and even more preferably 100,000 events per second. Most preferably, the counter is capable of having a counting rate of at least 1 x 10⁻⁶ events per second. 6The count rate of events. This is particularly advantageous for the method addressed in this disclosure. In some embodiments, the pixel array and at least one particle counter are a single component having all the features integrated onto a single chip; these are generally referred to as monolithic active pixel sensors (MAPS). However, in other embodiments, the pixel array is combined with at least one particle counter bump-bonded; these are referred to as “hybrid” detectors or hybrid active pixel sensors (HAPS).

[0021] Preferably, each pixel has a corresponding particle counter, providing a one-to-one mapping between pixels and particle counters. In architectures with varying numbers of pixels and particle counters, a one-to-many or many-to-one relationship is created. While other arrangements are conceivable, ideally, the particle counters are placed in an array corresponding to and equally spaced from the pixel array. In HAPS detectors, the pixel array is combined with array bumps of the particle counters; however, both arrays can be single components, as in MAPS.

[0022] Even more preferably, each particle counter generates a separate output signal based on the energy of each received particle. Having a corresponding particle counter for each pixel advantageously increases the rate at which events can be counted. Data rates in EBSD experiments can reach 10,000 events per second or higher per pixel. Each pixel has a corresponding particle counter with a counting rate capability of at least 2,000 events per second, preferably 10,000 events per second. Higher counting rate capabilities, such as 100,000 events per second, are also envisioned. Each pixel with a corresponding particle counter offers a significant advantage in achieving appropriately fast particle measurements compared to sequential readout detectors (such as CCDs). Importantly, the detector used in this invention must be capable of counting particles at a sufficiently high speed.

[0023] Preferably, the electronic amplifier at each pixel introduces an electronic noise energy equivalent with a full width at half maximum (FWHM) of less than 2 keV and preferably less than 1 keV.

[0024] Further improvements achievable in some embodiments involve charge sharing, as described in detail later in this disclosure. Preferably, the particle detector includes circuitry for detecting and correcting charge sharing between individual incident particles that may occur between pixels. Mitigating the effects of charge sharing at pixel boundaries in this manner can also reduce harmful dispersion in the recorded signal. Typically, in such embodiments, the circuitry is configured to perform or achieve the following objectives: summing the electronic signal collected in a given pixel with the electronic signals collected in adjacent pixels; filtering the summed electronic signal by electron energy to count the received particles representing the diffraction pattern; and assigning the counted particles to individual pixels.

[0025] Preferably, the particle detector is configured to output the arrival time and amplitude of the signal captured in each pixel, and a computer algorithm is used or configured to perform the following: identifying cases where a single incident particle generates a consistent electronic signal in multiple pixels; summing multiple electronic signals collected in multiple pixels generated by a single incident particle; performing energy filtering on the summed electronic signals to count the received particles representing the diffraction pattern; and assigning the counted particles to a single pixel.

[0026] In some preferred embodiments, the ratio (active layer sensor thickness) / (pixel-to-pixel spacing) is less than 5.

[0027] Preferably, the device is configured such that the number of electrons counted for each pixel during pattern acquisition is read out as a data unit of 6 bits or less.

[0028] Preferably, the camera sensor array has a configurable pixel amplifier adapted to allow multiple pulse lengths to accommodate different pixel count rates and energy resolution requirements.

[0029] It is understood that, in practice, the energy distributions of electrons representing the diffraction pattern and those not representing the diffraction pattern are typically not separate. Preferably, the overlap between these distributions is resolved by filtering. Therefore, preferably, electron energy filtering is adapted to distinguish receiving particles with energies that represent, or are more representative of, the diffraction pattern from receiving particles with energies that represent, or are more representative of the background.

[0030] Typically, the incident electron beam is incident at an angle ranging from 45° to 90° relative to the plane of the sample surface. However, it is also conceivable to use incident angles relative to the sample surface that are outside this range, such as shallower angles, for example, those commonly used for EBSD, as explained later in this disclosure.

[0031] According to a second aspect of the invention, an apparatus for detecting Kikuchi diffraction patterns is provided, the apparatus comprising: an electron column adapted to provide, in use, an electron beam directed toward a sample having an energy in the range of 2 keV to 50 keV; and an imaging detector for receiving and counting electrons from the sample due to the interaction of the electron beam with the sample, the detector comprising a pixel array and having a counting rate capability of at least 1,000 electrons per second for each pixel, and wherein: the detector is adapted to provide electron energy filtering of the received electrons to count the received electrons representing the diffraction pattern; and the particle detector has an inert layer on a surface on which electrons enter toward the active region of the detector, wherein the inert layer disperses the detection energy of 20 keV incident electrons having less energy dissipation than that caused by transmission through 1,500 nm of inert silicon.

[0032] Any performance and features relating to the foregoing and subsequent embodiments in this disclosure may relate to an apparatus including one or both of the first and second aspects.

[0033] According to a third aspect of the invention, a method for detecting a Kikuchi diffraction pattern is provided, the method comprising: providing an electron beam directed toward a sample using an electron column, the electron beam having an energy in the range of 2 keV to 50 keV; and receiving and counting electrons from the sample due to the interaction of the electron beam with the sample using an imaging detector, the detector comprising a pixel array and having a counting rate capability of at least 2,000 electrons per second for each pixel, wherein the detector is adapted to provide electron energy filtering of the received electrons in order to count the received electrons representing the diffraction pattern, and wherein the particle detector has an inert layer on a surface on which electrons enter toward the active region of the detector, wherein the inert layer disperses the detection energy of the 20 keV incident electrons having an energy dispersion of less than 3.2 keV full width at half maximum (FWHM).

[0034] According to a fourth aspect of the present invention, a method for detecting Kikuchi diffraction patterns using the apparatus according to the first or second aspect is provided. Attached Figure Description

[0035] Embodiments of the present invention will now be described with reference to the accompanying drawings, in which:

[0036] Figure 1 It is a graph showing the energy spectrum of backscattered electrons;

[0037] Figure 2 It is a graph showing the signal versus Poisson noise ratio as a function of the configuration threshold;

[0038] Figure 3 It is a graph showing the signal and background energy spectra of the incident and detected signals;

[0039] Figure 4 This is a schematic diagram of a single pixel in an exemplary particle counting detector;

[0040] Figure 5 This is the energy spectrum of a monoenergetic 20 keV beam passing through 1 μm silicon;

[0041] Figure 6 It is a graph showing the signal and background energy spectra of the incident and detected signals with a 1 μm silicon incident window;

[0042] Figure 7 It is a graph showing the signal-to-Poisson noise ratio of a pattern detected by a detector with a 1μm dead layer;

[0043] Figure 8It is a graph showing the calculated electron energy dispersion of 20 keV electrons transported through silicon layers of different thicknesses;

[0044] Figure 9 This is a graph showing the relationship between signal Poisson noise and threshold energy when using detectors with different dead layer thicknesses and energy dissipation characteristics.

[0045] Figure 10A and 10B The diagram schematically illustrates multiple stages of the process for producing an exemplary imaging detector with dead layers according to the present invention; and

[0046] Figure 11 It is a graph showing the signal-to-Poisson noise ratio of the pattern detected by the charge-sharing effect. Detailed Implementation

[0047] In this disclosure, specific definitions of "signal" and "background" are used, such as Figure 1 As shown. Electrons affected by diffraction effects that contribute to the Kikuchi band contrast are located at width ΔE. diff Within the energy band, just below the main beam energy, most electrons do not diffract into the Kikuchi band and are affected by multiple scattering events within the sample, resulting in continuous energy loss. The energies of these scattered electrons extend down to zero and form a diffuse background in the camera image. Some of these scattered electrons will have the same energy band ΔE. diff The energy level within this band is defined to include electrons affected by diffraction. Two distinct energy bands are defined to describe the scattered electrons incident on the detector: the "signal band," with an energy range of E > E0 - ΔE. diff It essentially contains all signal electrons and also some background electrons; and the "background band," with an energy range of E < E0 - ΔE. diff It contains a negligible number of signal electrons and can be considered to consist only of background electrons. An electron counting detector with a configurable threshold TH can be used to count only those electrons with energies higher than TH.

[0048] The diffuse background changes only slowly throughout the image, while the intensity changes rapidly in the diffraction band regions. Therefore, the (maximum - minimum) intensity observed in the diffraction bands will be determined solely by the number N of electrons detected affected by the diffraction effect. 信号 The intensity (maximum + minimum) will be determined by the detected background electron N. 背景 The total number of electrons N 总数 Decision, therefore N 总数 =N 信号+ N 背景 The diffraction contrast ((maximum value - minimum value) / (maximum value + minimum value)) will depend only on N.信号 / ( N 信号 +N 背景 ) = 1 / (1+ N 背景 / N 信号 And it will continue to increase with the increase of TH, provided that the signal-to-background ratio is SBR = N. 信号 / N 背景 Continue to increase.

[0049] The method described here aims to improve the "sensitivity" of electron-counting EBSD detectors. The "sensitivity" of an EBSD detector can be understood as inversely proportional to the electron dose required to collect a diffraction pattern that can be analyzed with defined accuracy and precision. As mentioned above, one way to define accuracy and precision is the percentage of successful indexing of patterns from a specific sample and under fixed experimental conditions. The electron dose is defined as the total number of SEM primary electrons exposed to the sample during diffraction pattern acquisition and is directly proportional to the product SEM main beam current multiplied by the exposure time. Longer exposure times result in lower pattern acquisition rates. High electron doses can damage some samples. Therefore, it is desirable to employ detectors with high sensitivity so that EBSD patterns can be successfully indexed as quickly as possible with minimal electron dose.

[0050] The emission of backscattered electrons from a sample is a stochastic process, meaning that the energy and direction of a single emitted electron are influenced by a statistical distribution. Therefore, the number of electrons incident on a single pixel of the detector during EBSD pattern measurements fluctuates around the mean according to a Poisson probability distribution. This partial randomization of the signal amplitude in each pixel has the effect of introducing random “Poisson” noise into EBSD pattern measurements, thereby masking Kikuchi diffraction contrast and making it more difficult to index the patterns.

[0051] Therefore, the ease of detecting a signal depends on the magnitude of the noise introduced by the signal relative to statistical fluctuations, referred to here as the signal-to-Poisson noise ratio (SPNR). For fixed experimental conditions and electron dose, the sensitivity of the EBSD experiment increases with increasing SPNR.

[0052] For EBSD patterns, the amplitude of the signal in a pixel is proportional to the average number of detected electrons carrying diffraction contrast, while statistical noise is controlled by the Poisson count statistics in the total number of detected electrons.

[0053]

[0054] SPNR and sensitivity obviously depend on SBR and N. 信号 To maximize SPNR, the system needs to be configured with SBR and N. 信号 The best combination.

[0055] For electronic counting EBSD detectors, N 信号 Both SPNR and SBR are affected by TH; therefore, SPNR varies as a function of TH. Figure 2 This shows how changing the TH value affects the SPNR. At very low TH values, all background and signal electrons are detected. As TH increases, background electrons are excluded, the SBR increases, but N... 信号 Since TH remains constant, SPNR also increases. For a theoretically "perfect" electron detector (perfect in that it can detect every incident electron and measure its energy without error), SPNR will continue to rise as TH increases, until TH = E0 - ΔE diff Because any higher TH value will exclude some signal electrons carrying diffraction contrast, thus reducing N. 信号 When TH rises above E0 - ΔE diff At this time, more background electrons will be excluded, but the most significant impact is that some signal electrons carrying diffraction contrast will not be detected. Therefore, the decrease in SPNR is mainly due to N 信号 Lower results. Therefore, for a perfect electronic detector, TH is set to a value close to E0 - ΔE. diff This will result in optimal SPNR and sensitivity.

[0056] For samples and experimental conditions where a larger proportion of the emitted background electrons is present, the relative increase in SPNR due to an increase in the energy threshold may be greater. This is because the SBR may be significantly improved if only signal electrons are selectively detected. For example, for many practical reasons, EBSD analysis is preferably performed using a beam incident at a large angle (in the range of 45° to 90°) relative to the sample surface plane (“large angle” condition). However, in this case, a significantly larger portion of the emitted backscattered electrons is background electrons compared to conventional experiments with a beam incident at a small angle (~20°) relative to the sample surface. Therefore, EBSD experiments are rarely performed under large angle conditions due to extremely low SPNR and sensitivity. If the SPNR is increased by raising the energy threshold, EBSD analysis of the sample can be performed under large angle conditions at higher rates or lower electron beam currents.

[0057] Electronic noise and pulse buildup

[0058] Figure 2This illustrates the ideal scenario, but in practical detectors, the relationship between TH and SPNR becomes complex due to a combination of physical effects. One known problem is that the pulse amplitude caused by a single incident electron will be affected by electron noise. Therefore, if the electron noise amplitude drops below TH, any diffracted electrons with incident energies above TH may not be detectable. Similarly, if the amplitude of the electron noise fluctuation is above TH, any scattered background electrons with incident energies below TH can still be detected. For a setting close to E0 - ΔE... diff These effects limit the SBR and N in the acquired EBSD patterns. 信号 . Figure 3 This demonstrates how electronic noise at half-maximum width at half-maximum (FWHM) of 2 keV affects the measurement of both the signal and background bands by effectively distributing the measurements above and below the true energy. This is when TH is set to E0 - ΔE. diff At this point, this is close to optimal in a perfect detector; however, due to noise fluctuations, some signal electrons will fall below TH, which will reduce N. 信号 And SPNR. If TH decreases, this will increase the number of signal electrons, but also allow for the detection of more background electrons. Therefore, the optimal value of SPNR is achieved with a perfect detector, where TH is slightly below E0 - ΔE. diff And it was achieved with a lower SPNR.

[0059] Effective blurring of the energy threshold caused by electronic noise is often reported as the “energy resolution” of particle counting cameras, but its related impact on the “sensitivity” of EBSD used for pattern resolution has not been recognized (as stated above). Vespucci et al. conducted EBSD experiments using a camera with an electronic noise FWHM of 2 keV. Our simulations predict that up to 30% improvement can be achieved at optimal SPNR if the amplitude of the electronic noise is reduced to 1 keV FWHM.

[0060] Therefore, to maximize the SPNR of EBSD, it is desirable to minimize the contribution of electronic noise to the measurement. Electronic noise can be improved through the design and fabrication of the imaging sensor, but it is also affected by the choice of electronic filtering for the readout amplifier of each pixel. Increasing the filtering time constant on each pixel amplifier reduces voltage noise and allows the threshold TH to be set higher to improve the optimal SPNR and sensitivity for EBSD pattern resolution. However, if the time constant is increased, the probability of unresolved pulses due to the arrival of a single electron increases. Since the pulse arrival time has a Poisson distribution over time, the probability of two pulses arriving within the resolution time of the pixel amplifier will increase with the count rate. The electrons of most impact detectors are diffuse background electrons, so any unresolved coincidence is more likely to occur between two background electrons. When this "stacking" occurs, the measured pulse height will be approximately the sum of the pulse heights seen from a single event, and may exceed TH even if none of the individual pulses exceed the threshold if they do not arrive together. Therefore, when the average pixel count rate is of the same order as the reciprocal of the pulse pair resolution time, stacking will allow more background events to be accepted, thereby reducing SPNR.

[0061] When a camera acquires EBSD patterns, the pixel count rate is directly affected by the electron beam current incident on the sample. When spatial resolution is of concern or the sample is damaged, a lower electron beam current is preferred to reduce sample dose and the lateral size of the focused electron beam. In this case, the pixel count rate will be low, and it is advantageous to increase the filter pulse duration of the pixel amplifier to reduce electronic noise and allow for higher SPNR and EBSD sensitivity through thresholding. When the sample can withstand high doses and the SEM can operate at high beam currents without affecting spatial resolution, the acquisition time per EBSD pattern can be reduced due to the high pixel count rate. In this case, the pixel amplifier filter needs to provide a sufficiently short pulse length to avoid significant build-up. Although the associated increase in electronic noise will reduce the SPNR achievable at a fixed count value in the image, increasing the count value will improve the SPNR so that EBSD pattern resolution can still be achieved at a higher rate than with a lower electron beam current. To meet a range of different sample and spatial resolution requirements, it is advantageous for the camera sensor array to have a configurable pixel amplifier, which allows for multiple pulse lengths to accommodate different pixel count rate and energy resolution requirements.

[0062] The performance of any practical sensor exhibits local variations, including the electron transport properties of the sensor layer or the electron counting circuitry. Due to these variations, the response to incident electrons will differ from pixel to pixel. Therefore, in practice, if TH is set to the same nominal level across all pixels, the range of incident electron energies that generate the count is non-uniform across all pixels. When averaging over all pixels, this effect, in addition to the influence of electronic noise, further obscures the energy threshold.

[0063] Some particle counting detectors have incorporated features to compensate for variable pixel threshold effects, thereby improving the uniformity of energy filtering characteristics across all pixels. These features typically apply an "offset" to the local electron threshold in each pixel to equalize the energy filtering characteristics across all pixels. These "threshold adjustment" features improve the energy filtering resolution of the entire sensor.

[0064] Furthermore, we found that the benefits of using a particle counting camera to improve the sensitivity of EBSD cannot be realized unless the camera includes at least two other key features related to the occurrence rate of charge sharing between the incident window and pixels.

[0065] Sensor dead zone and energy dissipation

[0066] The particle counting detector includes an active sensor layer in which the energy of the incident particles is absorbed by the interaction of a series of released electron-hole pairs. Figure 4 A schematic cross-sectional view of a single pixel is shown. A charge cloud forms and is swept toward the collecting electrode 402 by an internal electric field. The amount of released charge is measured at the collecting electrode, and this signal charge is typically proportional to the energy of the incident particle. The sensor depth to which the charge is released depends on the type of incident particle (e.g., X-rays or electrons) and the particle's energy. For incident electrons, the higher the energy, the deeper they penetrate the active sensor layer 401, but the electrons must first pass through an inactive material used to form an electrical connection with the active sensor layer. This inactive layer 403 effectively forms the sensor's "incident window." If the incident electrons lose any energy through inelastic interactions within this layer, this energy has no effect on the signal charge; therefore, this layer is sometimes referred to as a "dead layer." Furthermore, some charge released near the dead layer may recombine before being swept toward the collecting electrode, potentially leading to further loss of signal charge. Thus, energy may be lost as the incident electrons pass through the dead layer, and some released signal charge may be lost before collection, so the measured energy may be less than the incident electron energy.

[0067] As explained by Segal et al. (JD Segal et al., "Thin-Entrance Window Sensors for Soft X-rays at LCLS-II," 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS / MIC), 2018, pp. 1-2, doi: 10.1109 / NSSMIC.2018.8824674), fully depleted high-resistivity silicon sensors require doped contacts at the entrance window to terminate diodes. Conventionally, this region is created by ion implantation of dopant material, followed by high-temperature annealing to activate the dopant. This annealing also allows the dopant to be distributed deeper, increasing the depth of the inactive layer. Furthermore, a surface metal layer is typically deposited on top of the doped surface layer and connected to a bias voltage. Therefore, in existing devices, a 1-micron aluminum surface metal layer on top of a 2-micron-thick implant in silicon is commonly used for X-ray pixel sensors. When pixel sensors are used to detect X-rays above a few keV, a small fraction of X-ray photons absorbed in the inactive layer will not produce any signal, but any photon reaching the active region will produce a charge signal proportional to the photon's total energy. Therefore, known pixel detectors include relatively thick dead layers that have little effect on X-rays (or high-energy (100 keV) electrons), but have a significant impact on the applications addressed in this disclosure.

[0068] In transmission electron microscopy (TEM), where electron energies typically exceed 100 keV, the thickness of the dead layer is not critical when imaging electrons using a direct-detection semiconductor sensor with thresholding capability. The high energy of the incident particles ensures that any energy loss due to the dead layer is relatively low, and setting the threshold to approximately half the incident energy generally ensures that all particles are counted, and the threshold is high enough to prevent false triggering due to electron noise offset. However, in SEMs where the beam energy may be only 20 keV or lower, the effect of the dead layer can be significant.

[0069] Figure 5 This illustrates how the spectrum of an incident 20 keV monoenergetic electron beam (with a spike at 20 keV) is modified as it propagates through a 1-micron silicon dead layer. Due to numerous random scattering interactions within the layer, electrons lose variable amounts of energy, resulting not only in a reduction in the average energy of the propagating electrons but also in energy dispersion over a wide range. This is particularly evident in the small band ΔE near the beam energy. diff Contribution N 信号 The diffracted electrons will suffer similar energy loss and dispersion. Figure 6A schematic diagram is shown illustrating how the measured energy distribution of the signal and background bands will be detected after transmission through this dead layer, compared to the true incident distribution detected by a "perfect" electron detector. The effect of the dead layer on these low-energy electrons is to obscure both the signal and background distributions, causing them to overlap significantly. This overlap reduces the ability to separate contributions through thresholding.

[0070] If TH is set to a sufficiently low level to capture virtually all signal electrons and make N appear in the measured EBSD pattern 信号 Maximize (e.g.) Figure 6 In TH1, a high proportion of background electrons N will still be detected. 背景 This results in a pattern with a much lower SPNR compared to the situation achieved through thresholding in a perfect detector. For detectors with significant dead layers, optimizing SPNR requires N... 信号 A trade-off is made between SPNR and SBR; therefore, the optimal achievable SPNR and sensitivity are significantly inferior to what a theoretically "perfect" detector could achieve. This effect is... Figure 7 This has been proven in the text. Figure 7 This section explains the relationship between SPNR and TH for a theoretically perfect detector and a detector with an incident window equivalent to a 1-micron silicon dead layer.

[0071] A dead layer is an essential feature of any semiconductor sensor because it needs to make electrical contact with the depletion region of the active region forming the device. Specialized fabrication techniques exist to reduce the effective dead layer thickness sufficiently to allow low-energy photons to reach and be detected in the active region. However, for EBSD involving low-energy electrons, to take advantage of the energy threshold, it is important not only for the transmission through the dead layer but also for the effective dispersion (dispersion) of energy that occurs after the monoenergetic electrons pass through it. This energy dispersion occurs due to the combined effects of inelastic scattering and incomplete charge collection in the dead layer, resulting in a change in the signal received from electrons of a fixed energy. A typical incident window of a direct-detection semiconductor detector consists of a metal contact and an injection layer, which causes the energy dispersion of the detected signal from 20 keV incident electrons to exceed the energy dispersion that would occur from transmission through a 2-micron silicon layer. The inventors have determined that, in order to take advantage of the threshold to improve the sensitivity of EBSD pattern resolution, the dead layer (including any metal contacts) must be reduced so that the effective energy dispersion of a 20 keV electron beam is less than the energy dispersion caused by a 1500 nm inactive silicon layer.

[0072] It is well known that when electrons pass through a thin layer of material, energy dissipation increases with the thickness of the material. This relationship between thickness and energy dissipation can be approximated by a mathematical expression (as described below: Mikheev, N. & Stepovich, Mikhail & Yudina, S.. (2009). “Energy loss spectra for a fast charged particle beam transmitted through a material film of specified thickness”, Journal of Surface Investigation-x ray Synchrotron and Neutron Techniques - JSURF INVESTIG-X-RAY SYNCHRO, 3. 218-222. 10.1134 / S1027451009020086), or more commonly by electron transport simulations (as described below: Attarian Shandiz, M., Salvat, F. and Gauvin, R. (2016), “Detailed Monte Carlo Simulation of electron transport and electron energy loss spectra”, Scanning, 38: 475-491). (https: / / doi.org / 10.1002 / sca.21280). For example, the energy dissipation of an initial monoenergetic (single-energy) beam of 20 keV electrons after propagation through silicon layers of various thicknesses is as follows: Figure 8 As shown, energy dispersion is described as the full width at half maximum (FWHM) of the energy distribution after it has passed through the silicon layer. Methods such as these mathematical models and simulation software can be used to calculate the relationship between energy dispersion and the thickness of the incident window. Therefore, these techniques can be used to calculate the energy dispersion of the dead layer, and thus can be used to determine the appropriate physical, material, and geometric properties of the inert layer according to this disclosure.

[0073] In silicon detectors, the material at the entrance is typically modified via ion implantation to form conductive contacts and a semiconductor pn junction. The conductive region contributes no signal, thus creating a dead layer at the entrance to the detector's active region. Therefore, when electrons enter the detector, they must pass through a thin layer of inactive silicon, which disperses or diffuses the distribution of electron energy before reaching the active region. Reducing the energy dispersion effect of the dead layer increases the detector's usable SPNR, achieved through fabrication techniques that reduce the dead layer thickness. While ion implantation alters the electrical properties of silicon, electron scattering properties remain unaffected, and the dead layer's effect on the measured energy of electrons incident on the sensor is equivalent to the effect of electrons passing through a silicon layer of the same thickness as the dead layer. Besides ion implantation, other processing methods can be used, potentially involving additional thin surface layers such as oxides and nitrides.

[0074] If other materials are present on the surface, they will similarly increase the energy dispersion of electrons reaching the active region of the detector. However, for this invention, regardless of layer thickness or structural materials, the relevant aspect of the incident window is the amount of energy it will disperse through the electrons it transmits. For EBSD, it is convenient to describe the energy dispersion effect of the dead layer using the full width at half maximum (FWHM) of the energy distribution of the initial monoenergetic (single-energy) beam of electrons transmitted through the dead layer at 20 keV. Given this value, the effect of the incident window on electrons with different incident energies is predictable (e.g., through electron transport simulations, as described by Shandiz et al.).

[0075] It has been calculated that if the dead layer induces 3.2 keV FWHM or higher energy dispersion on a 20 keV monoenergetic electron beam (equivalent to the effect of a 1500 nm inactive Si layer), the SPNR of the pattern obtained by the actual detector cannot be meaningfully affected by applying the detection energy threshold TH, such as... Figure 9 As shown in the figure, this figure displays simulated SPNR curves for detectors with different dead-layer thicknesses (similar to...). Figure 7(The curves in the diagram). For these embodiments, 2 keV energy dispersion corresponds to a 1,000 nm thick dead layer, 3.2 keV dispersion corresponds to a 1,500 nm thick dead layer, and 4.8 keV dispersion corresponds to a 2,000 nm thick dead layer. For the 3.2 keV dispersion case, it can be seen that the benefit of the energy filtering concept to SPNR is negligible, while the larger and smaller dispersions described result in worse SPNR and significantly improved SPNR, respectively. That is, for 3.2 keV dispersion, SPNR increases with increasing TH, but to a lesser extent than in the 2 keV case. It is for this reason that the device of the present invention advantageously includes a dead layer that induces energy dispersion of less than 3.2 keV on a 20 keV monoenergetic electron beam normally incident on the sensor.

[0076] Understandable. Figure 9 The results shown depend on other aspects of the detector included in the SPNR simulation. The simulation in this embodiment applies to detectors that firstly lack charge-sharing effects (e.g., using some form of charge summation algorithm) and secondly include an electronic amplifier that introduces electronic noise equivalent to ~2 keV at full width at half maximum (FWHM). Conversely, if the performance of a detector with other detrimental factors (e.g., charge-sharing effects and high noise on the electronic amplifier) ​​is simulated, the SPNR curves will indicate a need for significant reduction in dead-layer energy dissipation to achieve the desired SPNR improvement.

[0077] In a typical exemplary device, the particle counter has pulse processing electronics, where each "event" to be counted is a charge pulse generated by the energy deposited by an incident particle in a pixel. The pulse processing electronics include an amplifier, a discriminator, and a counter. An important aspect of this device is the detector's count rate. In EBSD experiments, the rate at which incident particles hit the detector can be 10,000 events per second. Therefore, to distinguish particles of different energies, the detector's particle counters must each be able to count at a rate of 2,000 events per second. Preferably, the particle counters are capable of counting at a rate of 10,000 events per second, more preferably at a rate of 100,000 events per second. Importantly, regardless of whether individual pixels have their own particle counters, the detector's architecture enables it to have a count rate capability of at least 2,000 events per second per pixel.

[0078] The detector type described in a typical implementation is a "direct detector." This type of detector is capable of detecting any type of particle that meets an energy threshold, such as electrons, X-rays, and light photons. However, the invention is not limited to direct detectors, and other types of detectors capable of imaging and particle counting at a suitable rate per pixel can be used. Direct detectors can have surface coatings, such as scintillators that convert energy into light, provided the response time is short enough to allow resolution of signals from individual particles. Another example of a type of direct detector that can be used is a silicon strip detector. Detectors using sequential readout (such as CCDs) typically cannot count at a sufficiently fast rate; however, such detectors can be used in principle.

[0079] Figure 10A and 10B An exemplary manufacturing process for forming a detector according to this disclosure is illustrated. The device is described in stages 1001 to 1020, detailing various stages of its fabrication. The resulting device is an imaging detector having an inactive layer on its surface with a thickness of less than 100 nm, which produces the necessary low-energy dispersion in transmitted electrons. In embodiments of the invention, the sensor is bonded to a Medipix3 readout chip. The method described in US8890065 includes using a Medipix2 readout chip. This readout chip comprises an array of 256x256 pixels, with each region being 55 μm. 2 And it can reach speeds of up to ~1x10 per second. 6 The counting speed is the primary factor. Medipix3 is now preferred, featuring on-chip charge-sharing correction and configurable counter depth B (discussed below).

[0080] Figure 10A and Figure 10B The illustrations in each diagram show exemplary materials that form the components shown.

[0081] In stage 1001, a 100 nm to 300 nm SiO2 layer is deposited on an N-type silicon wafer. In stage 1002, photoresist patterning and boron implantation are performed. Photoresist removal and activation via standard annealing are shown in Figure 1003. In stage 1004, the SiO2 layer on the wafer's entrance window side is thinned, and a protective photoresist layer is formed on the readout side. In stage 1005, arsenic is implanted onto the entrance window side using ion implantation with ion energies in the range of 5 keV to 15 keV. Activation is then performed in stage 1005 by microwave annealing. Conventionally, annealing is performed at temperatures exceeding 700°C, which leads to significant diffusion of the arsenic dopant in the silicon. In this embodiment, microwave annealing in stage 1006 allows dopant activation without raising the temperature of the bulk silicon above 500°C, resulting in negligible diffusion. The photoresist typically cannot withstand the annealing process and is removed at this stage. In stage 1007, electrical contact openings are etched to the implanted region. In step 1008, aluminum is deposited on both sides by sputtering. In step 1009, the aluminum on the pixel side is patterned by etching, and the photoresist is removed in step 1010. Then, in step 1011, a passivation layer is deposited (e.g., by plasma-enhanced chemical vapor deposition (PECVD) using SiO2 or SiN, or by atomic layer decomposition (ALD) using Al2O3 at a low temperature below 400°C). In step 1012, the passivation layer on the readout side is patterned by photolithography and etching. In step 1013, the field metal (Ti-W + Cu or Au) deposited by sputtering is shown. As shown in step 1014, this is required for electroplating to deposit the under-bump metal (Ni). Then, in step 1015, the photoresist used for this deposition is removed. As shown in step 1016, the passivation layer and aluminum are removed from the entrance window. In step 1017, the opening of the aluminum contact in the entrance window is etched, and then the photoresist used in this etching process is removed in step 1018. The wafer (not shown) is then diced to produce the sensor chip and the readout chip. At step 1019, similar to the process described for the readout chip (excluding the sensor chip), the field metal and under-bump metal are produced, and the solder bumps are electroplated. Finally, at step 1020, the sensor chip and the readout chip are bonded together using bump bonding.

[0082] Charge sharing

[0083] Another problem with pixel detectors is that a portion of the scattered charge cloud generated by a single incident particle can reach the readout electrodes of adjacent pixels, effectively sharing the charge released by a single input particle between the pixel and its neighbors. This is more likely to occur when the incident particle enters the sensor near the pixel boundary. When using pixel detectors to detect photons, this “charge sharing” effect is known to cause some reduction in imaging resolution because the response spreads out from the central pixel. However, for pixel detectors with a threshold, if the charge collected in adjacent pixels is low, the pulse of that pixel may not exceed TH. If only the pulse of the central pixel exceeds TH, full imaging resolution is maintained. Therefore, to optimize spatial resolution and avoid multiple pixels counting the same photon when using a single photon counter with a single energy beam, the threshold is typically set to 50% of the incident photon energy.

[0084] We found that for EBSD, this charge sharing severely limits the extent to which SPNR can be improved through thresholding. In EBSD, because electron energies are typically 20 keV or lower, electrons incident on the sensor are absorbed near the inlet surface, so the released charge cloud must drift almost the entire depth of the sensor before reaching the readout electrode. As the cloud drifts, lateral diffusion increases the chance that some charge will cross the boundary between two pixels. The degree of charge sharing varies depending on where the incident electrons land relative to the pixel boundary. This results in a variable reduction in pulse amplitude, so some signal electrons that would normally be counted are now rejected because the generated pulse is below TH. This effect is most pronounced when TH is set close to the main beam energy E0.

[0085] Figure 2 The embodiments described herein illustrate that for a theoretically perfect detector, when TH is set to approximately E0 - ΔE diff At this time, the SPNR and sensitivity of EBSD can be optimized. Typically, E0 can be 20 keV, ΔE diff The energy can be 1 keV, with TH correspondingly set to 19 keV. Therefore, in this embodiment, if >1 keV (5%) of the deposited energy is shared with another pixel, signal electrons with 20 keV energy (i.e., greater than TH) will not be counted. For a pixel detector with a depth of 300 μm and a pixel size of 55 μm x 55 μm, we estimate that more than 60% of the 20 keV signal electrons are incident close enough to the pixel boundary that >1 keV of deposited energy will not be collected by the pixel on which the electrons are incident. In these cases, the measured electron energy will drop below TH, and although the incident energy is higher than TH, more than 60% of the signal electrons will still not be detectable.

[0086] While the reduction in pulse amplitude in photon detectors can be mitigated by reducing TH, in EBSD, reducing TH will decrease SBR, leading to a decrease in SPNR and pattern resolution sensitivity. The variable loss of charge on the pixels to which electrons are incident produces results similar to the energy loss and scattering that occurs when incident electrons are scattered within the inert material of a dead layer. Similar to the energy loss in the dead layer ( Figure 6 and Figure 7 When charge sharing exists, the optimal SPNR is reduced relative to the perfect detector and is obtained when the TH value is lower than that of the perfect detector.

[0087] From the description of the charge-sharing mechanism above, it will be recognized that charge sharing can be reduced to some extent by appropriately selecting sensor design parameters. Sensor pixel pitch is a crucial factor, as a larger pitch reduces the proportion of pixel regions close to the boundary of another pixel. Furthermore, the depth of the active sensor layer reduces the degree of charge sharing; a thinner layer allows the charge cloud to drift a shorter distance before being collected in the pixel electrodes. This shorter drift time results in reduced lateral diffusion of the charge cloud, limiting the probability of the cloud crossing the boundary between adjacent pixels.

[0088] As the charge cloud drifts across the sensor layer, its lateral radius is linearly proportional to its depth, allowing the lateral size of the charge cloud to be estimated as a function of the sensor layer thickness. This can be correlated with the pixel pitch to calculate the impact of charge sharing on SPNR. SPNR simulations in EBSD experiments (Si sample, 20keV beam energy) show that pixelated sensors designed with a ratio (active sensor layer thickness / pixel pitch) greater than 5 exhibit a significant decrease in optimal SPNR at high TH due to the charge sharing effect. Therefore, the ratio (active sensor layer thickness / pixel pitch) for pixelated electron counting sensors operating at high TH should be less than 5 to observe a significant improvement in SPNR from energy thresholding.

[0089] When the sensor thickness cannot be further reduced, and the pixel pitch or pixel size cannot be increased, the impact of charge sharing can be reduced by including additional circuitry to achieve a "summation node" for each pixel that sums the signals in the pixel and its neighboring pixels. All pixels have a detection threshold TH. det The summation node has a separate threshold equivalent to TH to distinguish between background electrons and signal electrons. If the summation node exceeds TH, the count is only assigned to pulses exceeding TH. det One or more pixels. TH det Set to a value low enough to detect pulses reduced due to charge sharing, but high enough to reduce pulses from neighboring pixels exceeding TH. detAn alternative approach is to include a circuit that compares the pulse in a single pixel with the pulses of all its neighboring pixels when any summing node exceeds TH. If the measured pulse amplitude is greater than all its neighbors and at least one neighboring summing node is above TH, a count is assigned to the pixel. These “charge summation” circuits significantly reduce the impact of charge sharing on SPNR, but effective electronic noise increases because electronic noise from individual contributing pixels is combined when the voltages at the summing nodes are summed. However, our simulations of SPNR in EBSD applications show that the SPNR improvement from reducing charge sharing significantly outweighs the reduction from the increase in effective electronic noise.

[0090] If the information output by the sensor is sufficient to identify and reconstruct single-particle events from signals from multiple pixels (e.g., if the sensor simultaneously provides the arrival time and amplitude of the signals captured in each pixel, such as the Timepix3 sensor; or if the desired average count rate is << 1 / pixel / frame), the charge summation algorithm can also be implemented off-chip.

[0091] In one implementation of the off-chip charge summation algorithm, a sensor such as Timepix3 can be configured to output the arrival time and amplitude of each electronic event recorded by the detector. In this case, a computer algorithm can be used to identify electronic events recorded in directly adjacent pixel clusters at near-simultaneous intervals and consider them as potential instances of charge sharing. In another implementation, a sensor such as Timepix or Timepix3 is configured to measure the total energy deposited in each pixel during a single exposure, and the electron beam current or exposure time is reduced such that the average number of incident electrons per pixel in a single exposure is << 1. In this case, the cluster of adjacent pixels whose deposited energy is measured in a single exposure is likely generated by a single incident electron rather than multiple incident electrons affected by charge sharing. In both implementations, the energies measured in these adjacent pixels are summed, and if the summed energy is less than the primary electron beam energy (i.e., the summed energy may come from a single incident electron), the cluster of adjacent events is assumed to be a single charge-sharing event. In this case, the summed energy from the electronic events is allocated to the single pixel in the adjacent pixel cluster that contributed the largest energy to the sum, and the energy measured in all other pixels generated by that electronic event is set to zero.

[0092] The processing steps applied in the external charge-sharing correction method for sensors are essentially the same as those performed by the "charge summation" circuit on the sensor; however, the processing is applied by a computer program or integrated circuit separate from the readout chip, rather than by the integrated circuit on the readout chip itself. These algorithms can be useful when acquiring EBSD patterns from beam-damaged samples using sensors without charge summation circuitry. In this case, it is necessary to successfully index the EBSD patterns acquired with the lowest possible electron beam dose. Therefore, it is useful to acquire data with a low dose and SPNR, and then process the data post-acquisition to eliminate charge-sharing effects and improve the SPNR to a level that allows for successful indexing of the patterns.

[0093] Data transmission rate

[0094] Another objective of the disclosed apparatus and method is to improve the speed at which EBSD patterns can be transferred and processed from outside the sensor. During the acquisition of a single EBSD pattern, the electronic count in each pixel is stored on the sensor as a data unit with a predefined but typically programmable number of digital bits B. Typical values ​​for B used in electronic counting experiments are 8, 12, 16, or 24. During a single acquisition, the maximum count value that the electronic counter can record at each pixel is (2... B – 1). If any pixel exceeds this value during a single acquisition, the count recorded at that pixel will be invalid, and the acquired pattern will no longer be an accurate measurement of the sample diffraction pattern.

[0095] After the image acquisition is completed, the electronic counter at each pixel reads at a fixed rate R of bits per second (bps). 比特 Read bit-depth B from sensor 读取 (usually B) 读取 = B), the rate is defined by the sensor and data transmission electronics. Therefore, the rate at which a complete EBSD pattern can be read from the sensor per second is R. 帧 = R 比特 / (B 读取 .N 像素 ), where N 像素 It represents the total number of pixels on the sensor. R 帧 A limit was set on the maximum pattern acquisition rate for EBSD experiments because a new pattern acquisition could not begin until the electronic counter on the sensor had fully read the previously acquired pattern. For a given detector, R... 比特 and N 像素 It is fixed; therefore, in order to obtain a faster EBSD acquisition rate, it is preferable to make B... 读取 minimize.

[0096] The sensors used in the EBSD experiment require B 读取The value depends on the electron count required per pixel in the EBSD pattern for the pattern to be successfully indexed. For detectors that do not distinguish between signal and background electrons, most electron counts will correspond to background electrons; this significantly increases the average count per pixel required for successful indexing. Detectors that prioritize counting signal electrons will obtain successfully indexed patterns with a much smaller electron count per pixel. This allows for the selection of a significantly smaller B0 value for successful EBSD experiments. 读取 This value results in an improved frame readout rate R. 帧 .

[0097] Without selective electron detection, the number of electrons required per pixel to acquire an indexable pattern is typically at least 50. Allowing for a suitable error margin, this requires B... 读取 A value greater than 6 is required to ensure the acquired pattern is suitable for indexing. However, for detectors that acquire patterns with high SBR due to energy-selective counting, indexed patterns have been successfully acquired with 20 electrons per pixel or typically less. Therefore, in successful EBSD experiments, B 读取 It can be set to 6 or usually smaller. Although the small B... 读取 A value that is desirable for fast readout is used, but for other purposes, the detector's B... 读取 Configured to up to 12 bits (e.g.) or higher B 读取 This will be very useful. However, not all patterns require this number of bits to be successfully analyzed. Therefore, the number of bits B read from the register... 读取 The configurable parameters of the detector are advantageous, enabling the readout of B. 读取 (Potentially less than B) for fast data transmission. Number of bits read B 读取 It should be less than or equal to the number of bits used for storage, if B 读取 It is useful to be configurable to 6 bits or less, 5 bits or less, 4 bits or less, 2 bits or less, or even 1 bit or less.

[0098] Improved atomic number contrast

[0099] The total number of backscattered electrons emitted by a material increases with its average atomic number. Therefore, the total number of backscattered electrons in an EBSD image is an indicator of the average atomic number of the material struck by the incident electron beam. If the beam scans a grid of positions on the sample surface and records the total count of backscattered electrons at each position, a map showing the distribution of materials with different atomic numbers can be created. This map provides additional information to complement the crystallographic information obtained from the diffraction pattern. Furthermore, if only the counts from a set of pixels covering a sub-region of the map are summed at each beam position, rather than summing all counts in the EBSD map, the map can be made more representative of the specific contrast mechanism associated with a finite angular range of emitted electrons, defined by the shape of the sub-region used for summation.

[0100] The energy distribution of backscattered electrons is also affected by the atomic number of the samples. Samples with high atomic numbers contain a larger proportion of high-energy electrons than those with low atomic numbers. Therefore, if low-energy backscattered electrons are excluded through energy filtering, the ratio of signals from high-to-low atomic number samples is greater than the ratio of the total signal obtained without energy filtering. Consequently, if energy thresholding is used to measure EBSD patterns and generate electron backscattering intensity maps, as described above, these maps will exhibit greater intensity contrast between sample regions with different atomic numbers when low-energy electrons are excluded through thresholding.

[0101] Exemplary device

[0102] In an exemplary apparatus corresponding to a preferred embodiment, the detector is a direct electron detector, comprising a sensor layer coupled with a pixelated array of bumps for particle counting electronics. The detector is positioned as close as possible to the sample to maximize the proportion of electrons backscattered from the sample when it strikes the detector in an EBSD experiment. The sensor layer is a monolithic semiconductor such as silicon, whose sample-facing surface layer is doped to allow electrical connection to the sensor layer, thus creating a dead surface layer. Backscattered electrons striking the detector pass through the dead layer, releasing a charge cloud in the active portion of the sensor layer; the energy of the striking electrons dispersed in the dead layer is less than the energy dissipation induced by the 1500 nm inactive silicon layer. Preferably, the dead layer should be 100 nm or less to induce energy dissipation of less than 100 eV on a 20 keV monoenergetic electron beam. The total thickness of the sensor layer can typically be 300 μm.

[0103] A pixelated array of particle counting electronic circuitry typically comprises an array of 256x256 pixels. Each pixel's particle counting circuitry includes an amplifier for measuring the energy of the received electrons. If the measured energy of the received electron is greater than a threshold, the circuitry generates a counting event to distinguish between background electrons and signal electrons. To effectively select signal electrons, the particle counting circuitry measures the energy of the received electrons, whose electron noise distribution has an FWHM equivalent to less than 2 keV, preferably less than 1 keV. The recorded count values ​​for each pixel in each pattern acquisition are stored, wherein the memory can be configured to provide a 12-bit counter per pixel, or can be configured as a 4-bit counter, or read as a 4-bit counter, to facilitate rapid readout of the acquired pattern from the detector.

[0104] Preferred implementations of the detector include additional features to mitigate the impact of charge sharing on SPNR. In one implementation, the pixelated array of the particle counting electronics is spaced sufficiently large such that the fraction (sensor layer thickness) / (pixel spacing) is 5 or less. For example, if the sensor layer thickness is 300 μm, the spacing is greater than 60 μm, although a spacing greater than 100 μm is also conceivable. In another implementation, the particle counting circuit is supplemented by an additional summing node for each pixel, which sums the charge released by a single incident electron collected by the pixel and its neighboring pixels. If the combined signal in the summing node exceeds a threshold, the summing node generates a counting event and assigns the count to the single pixel that measures the largest amount of charge compared to its neighboring pixels.

Claims

1. Apparatus for detecting a Kikuchi diffraction pattern, the apparatus comprising: an electron column adapted to provide, in use, an electron beam directed at a sample, the electron beam having an energy in the range 2 keV to 50 keV, and; an imaging detector for receiving and counting electrons from the sample as a result of interaction of the electron beam with the sample, the detector comprising an array of pixels and having a count rate capability of at least 2,000 electrons per second for each pixel, wherein: the imaging detector is adapted to provide electron energy filtering of received electrons in order to count received electrons representative of the diffraction pattern, and a particle detector having an inert layer on a surface through which the electrons enter an active region of the detector, wherein the inert layer disperses a detection energy of 20 keV incident electrons having a spread of less than 3.2 keV full width at half maximum.

2. Apparatus according to claim 1, wherein an electronic amplifier at each pixel introduces an electronic noise energy equivalent of less than 2 keV and preferably less than 1 keV full width at half maximum.

3. Apparatus according to any one of the preceding claims, wherein the particle detector comprises circuitry for detecting and correcting for charge sharing of a single incident particle which can occur between pixels.

4. Apparatus according to claim 3, wherein the circuitry implements: summing of the electronic signals collected in a given pixel with the electronic signals collected in adjacent pixels; electron energy filtering of the summed electronic signals to count received particles representative of the diffraction pattern; and allocation of the counted particles to a single pixel.

5. Apparatus according to any one of the preceding claims, wherein the particle detector outputs a time of arrival and amplitude of the signals captured in each pixel, and a computer algorithm is used to: identify instances where a single incident particle produces consistent electronic signals in multiple pixels; sum the multiple electronic signals collected in multiple pixels produced by a single incident particle; energy filter the summed electronic signals to count received particles representative of the diffraction pattern; and allocation of the counted particles to a single pixel.

6. Apparatus according to any one of the preceding claims, wherein the ratio (active layer sensor thickness) / (pixel to pixel pitch) is less than 5.

7. Apparatus according to any one of the preceding claims, wherein the number of electrons counted per pixel during a pattern acquisition is read out as a 6 bit or less data unit.

8. Apparatus according to any one of the preceding claims, wherein the camera sensor array has a configurable pixel amplifier adapted to allow multiple pulse lengths to be implemented to accommodate different pixel count rate and energy resolution requirements.

9. Apparatus according to any one of the preceding claims, wherein the electron energy filtering is adapted to distinguish between received particles having energies more representative of the diffraction pattern and received particles having energies more representative of background.

10. Apparatus according to any one of the preceding claims, wherein the incident electron beam is incident at an angle in the range 45° to 90° relative to the plane of the sample surface. ​ 11. The apparatus of any of the preceding claims, wherein the inert layer disperses a detection energy of 20 keV incident electrons less than an energy spread caused by transmission through 1500 nm of inert silicon.

12. A method of detecting a Kikuchi diffraction pattern, the method comprising: providing an electron beam directed at a sample using an electron column, the electron beam having an energy in a range of 2 keV to 50 keV, and; receiving and counting electrons from the sample due to interaction of the electron beam with the sample using an imaging detector, the detector comprising an array of pixels and having a count rate capability of at least 2,000 electrons per second for each pixel, wherein the detector is adapted to provide electron energy filtering of received electrons so as to count received electrons representative of the diffraction pattern, and wherein, the particle detector has an inert layer on a surface through which the electrons enter an active region of the detector, wherein the inert layer disperses a detection energy of 20 keV incident electrons having an energy spread of less than 3.2 keV full width at half maximum.

13. A method of detecting a Kikuchi diffraction pattern using the apparatus of any of claims 1 to 11.

Images