A method of using aerosols to detect XFEL wavefronts

Abstract

The application provides a method for detecting XFEL wavefront by using aerosol, and relates to the field of XFEL wavefront detection.The method for detecting XFEL wavefront by using aerosol comprises the following steps: step 1) atomizing polystyrene ball solution and injecting the polystyrene ball solution into the focus of XFEL; step 2) obtaining a plurality of diffraction images of the polystyrene balls; step 3) obtaining the wavefront tilt angle of each diffraction image, and obtaining the wavefront tilt distribution of the XFEL pulse according to the wavefront tilt angle; step 4) obtaining the diffraction intensity of each diffraction image, and obtaining the intensity distribution of the XFEL pulse according to the diffraction intensity; and step 5) combining the wavefront tilt distribution of the XFEL pulse and the intensity distribution of the XFEL pulse to obtain the joint distribution of the wavefront tilt and the intensity of the XFEL pulse.The application can sensitively detect the wavefront tilt and the intensity distribution of the XFEL pulse under high peak intensity.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of XFEL wavefront detection, and in particular to a method for detecting XFEL wavefronts using aerosols. BACKGROUND

[0002] In recent years, the emergence of ultra-bright, ultra-fast, ultra-short pulse, and ultra-coherent free electron laser technology has greatly promoted the development of ultra-fast X-ray spectroscopy experimental technology, and has been widely used in different research fields such as physics, chemistry, and biology. Through the excitation of the sample by femtosecond laser pulses, X-rays can track the microscopic structure dynamics of the sample under different time scales in solid, liquid, and gaseous states, etc. X-ray absorption and emission spectroscopy, diffraction, and scattering imaging are typical tools for detecting laser-induced structural changes.

[0003] Characterizing high-intensity, strongly focused X-ray free electron laser (XFEL) pulses is essential for their application in diffraction imaging. The goal of diffraction imaging experiments with X-ray free electron lasers (XFEL) is to have a single weakly scattering sample scatter photons in a short but intense focused X-ray pulse while avoiding radiation damage as much as possible, thereby achieving "pre-damage detection" and high-resolution imaging in a near-natural state to reveal the fine structure of the sample.

[0004] To achieve this goal, hard X-ray pulses with peak powers of several tens of GW generated by free electron lasers are focused to micrometer-sized spots. Sample particles are randomly injected into these ultra-high intensity X-ray pulses, and each pulse interaction with the particle material produces a diffraction pattern. Accurate analysis of these focused pulses is essential for determining the optimal injection position of the particle material, maximizing and correctly interpreting its diffraction signal.

[0005] In the study of high-intensity hard XFEL pulses, it is possible to consider using ablation imprint, scintillating crystals, grating interferometers, or X-ray sensitive Hartmann wavefront sensors. However, due to the extremely high peak intensity of XFEL pulses near small focal spots, these instruments can be damaged, or it can be difficult to interpret their measurement results, which poses a great challenge to the measurement of high-intensity hard X-ray pulse information. Although the absolute photon intensity can be inferred by measuring the way the pulse is strongly attenuated, the introduction of an attenuator can distort the smaller structures in the unattenuated pulse wavefront. SUMMARY

[0006] To solve the above problems, the application provides a method for detecting XFEL wavefront using aerosol, which can sensitively detect the wavefront tilt and intensity distribution of XFEL pulse under high peak intensity, and the measurement is consistent with the XFEL single-particle imaging experiment setup without introducing additional elements and additional complex operations, and the measurement can be completed in a few minutes or even a few seconds of data acquisition time combined with the current XFEL repetition frequency.

[0007] A method for detecting XFEL wavefront using aerosol, characterized in that it comprises at least the following steps:

[0008] Step 1) atomizing and injecting a polystyrene ball solution into the focus of XFEL;

[0009] Step 2) obtaining a plurality of diffraction images of the polystyrene balls;

[0010] Step 3) obtaining the wavefront tilt angle of each diffraction image, and obtaining the wavefront tilt distribution of the XFEL pulse according to the wavefront tilt angle;

[0011] Step 4) obtaining the diffraction intensity of each diffraction image, and obtaining the intensity distribution of the FEL pulse according to the diffraction intensity;

[0012] Step 5) combining the wavefront tilt distribution of the XFEL pulse and the intensity distribution of the XFEL pulse to obtain the joint distribution of the wavefront tilt and intensity of the XFEL pulse.

[0013] In an available implementation, step 1) further comprises: atomizing and injecting the balls in the polystyrene ball solution into the focus of XFEL through a pneumatic lens;

[0014] Wherein, the XFEL frequency is ≥10Hz, the average energy pulse is ≥0.1mJ, the pulse duration is ≤120fs, and the wavelength is ≥10 11 photons are provided per pulse on average, and the focused spot size is 0.1-1.5μm.

[0015] In an available implementation, step 2) further comprises: using a detector with a panel size ≥20cm to obtain the diffraction image.

[0016] In an available implementation, step 2) further comprises: preliminarily screening the diffraction image, and then performing secondary screening through an intensity filter established by histogram statistics.

[0017] In an available implementation, step 3) further comprises the following steps:

[0018] Step 3-1) selecting a suitable pixel region on the diffraction image, and each pixel point in the pixel region becomes a candidate point, wherein the coordinates of the candidate point are [xSn , y Sn ], Sn is the number of pixels in the pixel region;

[0019] Step 3-2) obtaining the symmetric point of each pixel point on the diffraction image about the candidate point

[0020] x' n = 2x Sn - x n

[0021] y' n = 2y Sn - y n

[0022] wherein the coordinate point on the diffraction image is [x n , y n ], the coordinate of the candidate point is [x Sn , y Sn ], and the coordinate point on the diffraction image symmetric about the candidate point is [x' n , y' n ];

[0023] Step 3-3) obtaining the average intensity difference ΔI of the candidate point in step 3-2)

[0024]

[0025] wherein I(x i , y i ) represents the diffraction intensity at [x n , y n ]; and I(x i ', y i ') represents the diffraction intensity at [x' n , y' n ];

[0026] Step 3-4) traversing each candidate point and obtaining the average intensity difference ΔI of each candidate point;

[0027] Step 3-5) finding the candidate point with the minimum average intensity difference ΔI among all candidate points

[0028] S = {ΔI n | n = 1, 2, …}

[0029] min {S}

[0030] wherein S is a set formed by the average intensity difference ΔI of all candidate points;

[0031] Step 3-6) obtaining the wavefront tilt angle of the diffraction image

[0032] [Δx / D, Δy / D]

[0033] where [Δx, Δy] is the distance between the Fried center coordinates found by minimizing the average intensity difference from the detector center pixel coordinates; D is the distance between the sample and the detector;

[0034] Step 3-7) traverse all diffraction images, and obtain the wavefront tilt angle of all diffraction images according to steps 3-1) to 3-6), and obtain the wavefront tilt distribution of the FEL pulse according to the wavefront tilt angle of all diffraction images.

[0035] In a feasible implementation, step 4) further includes the following steps:

[0036] Step 4-1) establishing a to-be-fitted function

[0037]

[0038] where x is the spatial frequency, f(x) is the to-be-fitted function, the value of f(x) is the scattering intensity of the sphere, and R and I0 are to-be-fitted parameters in the to-be-fitted function f(x);

[0039] Step 4-2) obtaining all values of x in step 4-1)

[0040]

[0041] where D is the distance between the sample and the detector, w is the wavelength of the XFL, p is the pixel size of the detector, and r is the pixel number of the pixel point from the center pixel point;

[0042] Step 4-3) establishing a residual model

[0043] δ i = f(x i )- y i

[0044]

[0045] where y i is the experimental data point to be minimized, f(x i ) is the to-be-fitted function, and x i is the i-th value of x;

[0046] Step 4-4) establishing an optimization function MinS(R, I0), optimizing the residual model S, and obtaining the optimal values of R and I0;

[0047] Step 4-5) obtaining the diffraction intensity of each diffraction image

[0048]

[0049] wherein p PSL is the density of polystyrene; N A is the Avogadro constant; M PSL is the molar mass of polystyrene monomer; f is the average scattering factor of polystyrene monomer under 1 KeV radiation; r e is the classical electron radius; A is the solid angle of each detector pixel; G det is the gain of the detector; Q eff is the quantum efficiency of the gain of the detector for 1 KeV photons;

[0050] Step 4-6) traversing all diffraction images to obtain the diffraction intensity of all diffraction images.

[0051] In an implementable embodiment, step 4-2) includes: performing mean value processing between the to-be-fitted functions f(x) corresponding to the points with the same spatial frequency x.

[0052]

[0053] wherein N is the number of points with the same spatial frequency x.

[0054] In an implementable embodiment, the method for solving the optimization function MinS(R, I0) in step 4-4) is the least square method, and the optimal parameter is obtained by solving the partial differential equation. The partial differential equation is as follows:

[0055]

[0056] wherein is the partial differential of MinS(R, I0) with respect to I0, is the partial differential of MinS(R, I0) with respect to R.

[0057] In an implementable embodiment, in step 4-5):

[0058] p PSL = 1.05 g / cm 3 ; M PSL = 1.05 g / mol; f = 58.3; r e = 2.8 x 10 -15 m; A = 1.1 x 10 8 rad; G det is 7 counts for each photon; Q eff = 0.9.

[0059] In an implementable embodiment, in step 3-3): taking the logarithm of the average intensity difference AI

[0060] AI log= log (ΔI + 1)

[0061] where ΔI log is the average intensity difference after taking the logarithm.

[0062] The method for detecting the wavefront of XFEL provided by the application has the following beneficial effects: the application can sensitively detect the wavefront tilt and intensity distribution of the XFEL pulse at a high peak intensity, the measurement is consistent with the XFEL single-particle imaging experiment setup, no additional elements are introduced and no additional complex operations are required, and only a few minutes or even a few seconds of data acquisition time is required to complete the measurement in combination with the current XFEL repetition frequency. In addition, the experimental cavity does not need to be broken before each experiment, and only the sample in the aerosol injector needs to be replaced. BRIEF DESCRIPTION OF DRAWINGS

[0063] Figure 1 is the wavefront tilt distribution diagram of the XFEL pulse of the application.

[0064] Figure 2 is the intensity distribution diagram of the XFEL pulse of the application.

[0065] Figure 3 is the particle size probability distribution diagram of the application.

[0066] Figure 4 is the combined distribution diagram of the wavefront tilt and intensity of the XFEL pulse of the application.

[0067] Figure 5 is the experimental device diagram of the application. DETAILED DESCRIPTION

[0068] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only some of the embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application. In the description of the application, it should be noted that the terms "left side", "right side", "upper side", "lower side", "upper side", "lower side" and the like indicate the orientation or positional relationship shown in the drawings, and are only used for the purpose of describing the application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the application. In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance.

[0069] In the description of the present application, it should be noted that unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connecting" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, or it can be connected inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0070] In addition, in the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0071] The embodiment of the present application provides a method for detecting XFEL wavefront using aerosol, which comprises at least the following steps:

[0072] Step 1) atomize and inject the polystyrene ball solution into the focus of XFEL;

[0073] Step 2) obtain a plurality of diffraction images of the polystyrene ball;

[0074] Step 3) obtain the wavefront tilt angle of each diffraction image, and obtain the wavefront tilt distribution of the XFEL pulse according to the wavefront tilt angle;

[0075] Step 4) obtain the diffraction intensity of each diffraction image, and obtain the intensity distribution of the XFEL pulse according to the diffraction intensity;

[0076] Step 5) combine the wavefront tilt distribution of the XFEL pulse and the intensity distribution of the XFEL pulse to obtain the joint distribution of the wavefront tilt and intensity of the XFEL pulse.

[0077] Next, the above five steps are disassembled and explained, starting with step 1).

[0078] Before explaining step 1) in detail, first explain step 1) briefly: the main purpose of step 1) is to make the polystyrene balls in the atomized polystyrene solution act as random position disposable lenses, and each injected ball can detect the local area of the intercepted XFEL pulse and form a diffraction image in the detector.

[0079] In step 1), the balls in the polystyrene ball solution are atomized by a pneumatic lens and injected into the focus of the XFEL. Among them, the XFEL frequency is ≥ 10 Hz, the average energy pulse is ≥ 0.1 mJ, the pulse duration is ≤ 120 fs, and the wavelength is ≥ 10 11 photons are provided per pulse on average, and the focused spot size is 0.1-1.5 μm.

[0080] In one embodiment, the XFEL has a frequency of 10 Hz, the XFEL has an average energy pulse of 1.2 mJ, the XFEL has a pulse duration of 100 fs, the XFEL has a wavelength of 1.2 nm, the XFEL provides 7.5 x 1011photons per pulse on average, and the XFEL has a photon focus size of 1.0 μm. 12 In one embodiment, the XFEL has a frequency of 10 Hz, the XFEL has an average energy pulse of 1.2 mJ, the XFEL has a pulse duration of 100 fs, the XFEL has a wavelength of 1.2 nm, the XFEL provides 7.5 x 1011photons per pulse on average, and the XFEL has a photon focus size of 1.0 μm.

[0081] Before explaining step 2) in detail, a brief explanation of step 2) is provided: the main purpose of step 2) is to obtain the diffraction image of the polystyrene sphere in step 1).

[0082] In step 2), a detector with a panel size of > 20 cm is used to obtain the diffraction image. In one embodiment, the detector has a pixel size of 2048 x 2048, and each pixel of the detector has a size of 75 x 75 μm 2 .

[0083] In step 2), the diffraction image is preliminarily screened, and then a secondary screening is performed by establishing an intensity filter through histogram statistics. In one embodiment, more than 2000 diffraction patterns are collected, and after preliminary screening, 506 diffraction data containing scattering signals are obtained. Then, a secondary screening is performed by establishing an intensity filter through histogram statistics, and diffraction data from a single particle is further screened, and finally 470 diffraction images of single spheres are left for further study.

[0084] Before explaining step 3) in detail, a brief explanation of step 3) is provided: the main purpose of step 3) is to find the Friedel center (i.e., the center of symmetry of the diffraction pattern) of each diffraction image, and then to calculate the wavefront tilt angle of each diffraction image according to the Friedel center of each diffraction image. The wavefront tilt distribution of the XFEL pulse can be obtained by statistically analyzing the wavefront tilt angles of all diffraction images.

[0085] The following is a detailed explanation of step 3):

[0086] Step 3-1) selects an appropriate pixel region on the diffraction image, and each pixel point in the pixel region becomes a candidate point. In this example, a square region with a side length of 20 (pixels) is selected as the candidate center pixel region, with the center of the diffraction image as the center. The coordinates of the candidate point are [x Sn ,y Sn], Sn is the number of pixels in the pixel region. As an illustration, in this step, each time is only for a diffraction image processing, first select a batch of possible Fried center of the diffraction image candidate points, and then each candidate point mapped out the data comparison, the data of the candidate points in the performance of the best candidate point as the Fried center of the diffraction image, therefore, each image can finally select a Fried center. In a specific embodiment, a total of 470 diffraction images, each diffraction image corresponds to a Fried center, a total of 470 center point coordinates set.

[0087] Then, in all the candidate points of a diffraction image, the data performance of the best candidate point is selected as the Fried center of the diffraction image, as described in step 3-2). Step 3-2) obtains the symmetry point of each pixel point on the diffraction image about the candidate point (usually all pixel points will not be used, but the data in the part near the center of the candidate region will be selected). The coordinate point on the diffraction image is [x n ,y n ], the coordinates of the candidate point are [x Sn ,y Sn ], the coordinate point on the diffraction image about the candidate point is [x' n ,y' n ], wherein the calculation formula of the coordinate point on the diffraction image about the candidate point is as follows:

[0088] x' n = 2x Sn -x n

[0089] y' n = 2y Sn -y n

[0090] As an illustration, in this step, a candidate point is first selected from the candidate points, and then all the pixel points on the diffraction image are symmetrical about the candidate point according to the above formula, so that each pixel point can obtain a symmetric point about the candidate point. For example: the coordinates of the selected candidate point are [x S1 ,y S1 ], then all the pixel points on the diffraction image can be symmetrical about the candidate point according to the above formula. Then, continue to step 3-3).

[0091] Step 3-3) obtains the average intensity difference ΔI of the candidate point in step 3-2);

[0092]

[0093] wherein I(xi , y i ) represents the diffraction intensity at [x n , y n ], and I(x i ', y i ') represents the diffraction intensity at [x' n , y' n ]. Wherein, I(x i , y i ) and I(x i ', y i ') can be directly measured by the detector. In a preferred embodiment, in order to improve the sensitivity of the average intensity difference ΔI, the average intensity difference ΔI can be taken logarithm to enhance its intensity dynamic range: ΔI log = log(ΔI + 1).

[0094] Step 3-4) traverse each candidate point and obtain the average intensity difference of each candidate point. For example, first select a candidate point with coordinates [x S1 , y S1 ], and then select the next candidate point with coordinates [x S2 , y S2 ] after processing according to step 3-2) and step 3-3), until all candidate points are traversed and the average intensity difference of all candidate points is obtained.

[0095] Step 3-5) find the candidate point with the smallest average intensity difference ΔI among all candidate points, and this candidate point becomes the Fried center of the diffraction image, as shown in the following formula:

[0096] S = {ΔI n | n = 1, 2, …}

[0097] min {S}

[0098] Wherein, S is a set formed by the average intensity difference ΔI of all candidate points.

[0099] This step is actually to select the candidate point with the smallest average intensity value ΔI from all candidate points, and let this candidate point become the Fried center of the diffraction image. Then, continue to step 3-6).

[0100] Step 3-6) obtain the wavefront tilt angle of the diffraction image, as shown in the following formula:

[0101] [Δx / D, Δy / D]

[0102] where [Ax, Ay] is the distance between the center of the Friedel center and the center pixel of the detector found by minimizing the average intensity difference; D is the distance between the sample and the detector. In this step, the wavefront tilt angle of the diffraction image can be obtained according to the Friedel center of the diffraction image. Then, continue step 3-7).

[0103] Step 3-7) traverses all the diffraction images and obtains the wavefront tilt angle of all the diffraction images according to steps 3-1) to 3-6), and obtains the wavefront tilt distribution of the XFEL pulse according to the wavefront tilt angles of all the diffraction images. In a specific embodiment, the wavefront tilt angles of 470 pictures are plotted and the distribution is observed, and the wavefront tilt distribution of the XFEL pulse can be as shown in Figure 1 Figure 1 The darker the color, the more diffraction images at the tilt angle. Then, continue step 4).

[0104] Before detailing step 4), a brief description of step 4) is given: the main purpose of step 4) is to find the diffraction intensity of each diffraction image, and then to statistically analyze the diffraction intensity of all diffraction images, so as to obtain the intensity distribution information of the XFEL pulse.

[0105] The following is a detailed explanation of step 4), which further includes the following steps:

[0106] Step 4-1) establishes a fitting function, which is as follows

[0107]

[0108] where x is the spatial frequency or scattering vector, f(x) is the fitting function, the value of f(x) is the scattering intensity of the sphere, R and I0 are fitting parameters in the fitting function f(x). As an illustration, R and I0 are the final data to be obtained by the fitting function, while the values of x and f(x) are detailed in step 4-2).

[0109] Step 4-2) obtains all the values of x in step 4-1), which is as follows

[0110]

[0111] ​where D is the distance between the sample and the detector, w is the wavelength of the XFEL, p is the pixel size of the detector, and r is the distance (in units of the number of pixels) between the pixel and the center pixel of the detector. As an illustration, D, w, and p are constants, and the value range of r is all the pixels in the diffraction image, that is, each pixel in the diffraction image needs to be traversed, in other words, the value of x is also all the pixels in the diffraction image. In a specific embodiment, each diffraction image contains 2048*2048 pixels, so the value range of r is 1415 discrete points, and the value range of x is also 1415 discrete points. Then, according to the definition of r, it can be known that the unit of r is the number of pixels, so for the pixels with the same distance from the center of the detector, their spatial frequencies x should be the same, and for the scattering intensity f(x) corresponding to the same spatial frequency x, it needs to be averaged. In simple terms, it can be compared to: taking the center of the detector as the origin and diffusing outward, and averaging the scattering intensity f(x) of the pixels located on the same radius. Therefore, in a preferred embodiment, the scattering intensity f(x) corresponding to the points with the same spatial frequency x is averaged, and the formula is as follows:

[0112]

[0113] Then, after determining the value range of x, f(x) needs to be actually processed, and the processing process is described in detail in step 4-3).

[0114] Step 4-3) establishes a residual model, and the residual model is as follows

[0115] δ i = f(x i )- y i

[0116]

[0117] where y i is the data point measured in the minimization experiment, f(x i ) is the function to be fitted, and x i is the value of the i-th x. As an illustration, y i is actually the scattering intensity collected by the detector, at this time, S is a function containing R and I0.

[0118] Step 4-4) establishes an optimization function MinS(R, I0) to optimize the residual model S and obtain the optimal values of R and I0. In a specific embodiment, the method for solving the optimization function MinS(R, I0) is the least square method, and the optimal parameters are obtained by solving the partial differential equation. The partial differential equation is as follows:

[0119]

[0120] wherein, is the partial derivative of MinS(R, I0) with respect to I0, is the partial derivative of MinS(R, I0) with respect to R. Generally, the point where the partial derivative equals zero is the extreme point, so in this embodiment, the extreme points of R and I0, i.e. the optimal points, can be obtained by setting the partial derivatives of R and I0 equal to zero, respectively.

[0121] Step 4-5) obtains the diffraction intensity of the diffraction image, and the formula of the diffraction intensity is as follows:

[0122]

[0123] wherein, I inc is the diffraction intensity; ρ PSL is the density of polystyrene; N A is the Avogadro constant; M PSL is the molar mass of polystyrene monomer; f is the average scattering factor of polystyrene monomer under 1 KeV radiation; r e is the classical electron radius; ΔΩ is the solid angle surrounded by each detector pixel; G det is the gain of the detector; Q eff is the quantum efficiency of the gain of the detector to 1 KeV photons. In a preferred embodiment, ρ PSL = 1.05 g / cm 3 ; M PSL = 1.05 g / mol; f = 58.3; r e = 2.8 x 10 -15 m; ΔΩ = 1.1 x 10 8 rad; G det = 7 counts per photon; Q eff = 0.9. Most of the parameters in the formula of this step are constant or can be directly obtained according to the actual situation, so the optimal value of I0 in step 4-4) is brought into the formula, and the value of I inc can be directly obtained. Then, step 4-6) is continued.

[0124] Step 4-6) traverses all the diffraction images to obtain the diffraction intensities of all the diffraction images. In a specific embodiment, there are a total of 470 diffraction images, so 470 diffraction intensities I inc can be obtained. The data of the 470 diffraction intensities I inc can be plotted, and the intensity distribution information of the XFEL pulse can be obtained, which can be referred to in detail in Figure 2In another embodiment, a total of 470 diffraction images are obtained, and then 470 data of particle size R are obtained simultaneously. The particle size distribution data of the 470 diffraction images can be obtained by plotting the 470 data of particle size R. For details, please refer to Figure 3 .

[0125] Before the step 5) is described in detail, the step 5) is described briefly. The main purpose of the step 5) is to find the two graphs obtained in the step 3) and the step 4) to be fused together, so as to obtain the distribution of the photon flux and the wavefront tilt.

[0126] The step 5) combines the wavefront tilt distribution of the XFEL pulse and the intensity distribution of the XFEL pulse to obtain the joint distribution of the wavefront tilt and the intensity of the XFEL pulse. For details, please refer to Figure 4 . Figure 4 The white numbers in Figure 1 correspond to each circle in Figure 4 . Through the indirect measurement of the pulse in Figure 4 , the optical system of the free electron laser and the imaging experiment can be improved. For example, the slight adjustment of the bendable mirror for focusing the pulse can be guided by maximizing the measured value of the absolute photon flux and / or reducing the distribution of the wavefront tilt in Figure 4 . Unlike the profile measurement of the wavefront far away from the sample injection position, directly shows the distribution of the photon flux and the wavefront tilt, which is very useful for injecting the sample under similar conditions.

[0127] The above description is only the preferred embodiment of the present application. It should be pointed out that for ordinary skilled in the art, without departing from the technical principles of the present application, a number of improvements and replacements can be made, and these improvements and replacements should be considered as the protection scope of the present application.

Claims

1. A method of using aerosols to detect XFEL wavefronts, characterized by, At least comprising the following steps: Step 1) atomizing and injecting the polystyrene ball solution into the focus of XFEL; Step 2) obtaining a plurality of diffraction images of the polystyrene balls; Step 3) determining the Friedel center by analyzing the symmetry of each image, calculating the wavefront tilt angle of each diffraction image according to the distance between the Friedel center and the detector center, and obtaining the wavefront tilt distribution of the XFEL pulse according to the wavefront tilt angle; Step 4) obtaining the diffraction intensity of the incident light of each diffraction image by fitting the intensity data of the diffraction image with the spherical scattering intensity function of the polystyrene ball, and obtaining the intensity distribution of the XFEL pulse according to the diffraction intensity; Step 5) obtaining the joint distribution of the wavefront tilt and intensity of the XFEL pulse by combining the wavefront tilt distribution of the XFEL pulse and the intensity distribution of the XFEL pulse.

2. The method of using an aerosol to detect an XFEL wavefront of claim 1, wherein, In step 1), the balls in the polystyrene ball solution are atomized by a pneumatic lens and injected into the focus of XFEL; wherein the XFEL frequency is > 10 Hz, the average energy pulse is > 0.1 mJ, the pulse duration is < 120 fs, and the wavelength is > 0.1 nm. 11 > 10 photons per pulse, and the focused spot size is 0.1-1.5 μm.

3. The method of using an aerosol to detect an XFEL wavefront of claim 1, wherein, In step 2), the diffraction images are obtained using a detector with a panel size ≥20cm.

4. The method of using an aerosol to detect an XFEL wavefront of claim 1, wherein, In step 2), the diffraction images are preliminarily screened, and then screened again by establishing an intensity filter through histogram statistics.

5. The method of using an aerosol to detect an XFEL wavefront of claim 1, wherein, In step 3), the following steps are further included: Step 3-1) selecting a suitable pixel region on the diffraction image, each pixel point in the pixel region becoming a candidate point, wherein the coordinates of the candidate point are [x Sn ,y Sn ], and Sn is the number of pixel points in the pixel region; Step 3-2) obtaining the symmetry point of each pixel point on the diffraction image with respect to the candidate point x' n = 2x Sn - x n y' n = 2y Sn - y n Among them, the coordinate point on the diffraction image is [x n ,y n ], the coordinates of the candidate point are [x Sn ,y Sn ], the coordinate point on the diffraction image is symmetrical about the candidate point and is [x′ n ,y n ′]; Step 3-3) obtaining the average intensity difference ΔI of the candidate point in step 3-2) where I(x i ,y i ) represents the diffraction intensity at [x n ,y n ]; I(x i ',y i ') represents the diffraction intensity at [x' n ,y' n ]; Step 3-4) traversing each candidate point and obtaining the average intensity difference ΔI of each candidate point; Step 3-5) finding the candidate point with the smallest average intensity difference ΔI among all candidate points, which is the Friedel center coordinate of the diffraction image S = {ΔI n |n = 1, 2,...} min{S} Where S is a set formed by the average intensity difference ΔI of all candidate points; Step 3-6) obtaining the wavefront tilt angle of the diffraction image [Δx / D,Δy / D] Where [Δx,Δy] is the distance between the Friedel center coordinate found by minimizing the average intensity difference and the detector center pixel coordinate; D is the distance between the sample and the detector; Step 3-7) traversing all diffraction images and obtaining the wavefront tilt angle of all diffraction images according to steps 3-1) to 3-6), and obtaining the wavefront tilt distribution of the XFEL pulse according to the wavefront tilt angle of all diffraction images.

6. The method of using an aerosol to detect an XFEL wavefront of claim 1, wherein, In step 4), the following steps are further included: Step 4-1) establishing the parameters to be fitted Where x is the spatial frequency, f(x) is the function to be fitted, the value of f(x) is the scattering intensity of the ball, R and I0 are the fitting parameters in the fitting function f(x); Step 4-2) obtaining all values of x in step 4-1) Where D is the distance between the sample and the detector, w is the wavelength of XFL, p is the pixel size of the detector, and r is the pixel number of the pixel point from the center pixel point; Step 4-3) establishing a residual model delta i = f(x i )- y i where y i is the measured data point, f(x i ) is the function to be fitted, and x i is the value of x at the ith data point. Step 4-4) establishing an optimization function MinS(R,I0), optimizing the residual model S, and obtaining the optimal values of R and I0; Step 4-5) obtaining the diffraction intensity of each diffraction image where p PSL is the density of polystyrene; N A is Avogadro's number; M PSL is the molar mass of polystyrene monomer; f is the average scattering factor of polystyrene monomer at 1 KeV radiation; r e is the classical electron radius; AΩ is the solid angle subtended by each detector pixel; G det is the detector gain; Q eff is the quantum efficiency of the detector gain for 1 KeV photons; Step 4-6) traversing all diffraction images to obtain the diffraction intensity of all diffraction images.

7. The method of using an aerosol to detect an XFEL wavefront of claim 6, wherein, The step 4-2) includes: making mean value processing between the to-be-fitted functions f(x) corresponding to the points with the same spatial frequency x; Wherein, N is the number of points with the same spatial frequency x.

8. The method of using an aerosol to detect an XFEL wavefront of claim 6, wherein, The method for solving the optimization function MinS(R, I0) in the step 4-4) is a least square method, and the optimal parameter is obtained by solving a partial differential equation as follows: wherein is the partial derivative of MinS(R, I0) with respect to I0, is the partial derivative of MinS(R, I0) with respect to R.

9. The method of using an aerosol to detect an XFEL wavefront of claim 6, wherein, In the step 4-5): p PSL = 1.05 g / cm 3 ; M PSL = 1.05 g / mol; f = 58.3; r e = 2.8 x 10 -1d m; ΔΩ = 1.1 x 10 8 rad; G det = 7 counts per photon; Q eff = 0.

9.

10. The method of using an aerosol to detect an XFEL wavefront of claim 5, wherein, In the step 3-3): taking logarithm of the average intensity difference ΔI ΔI log = log(ΔI+1) where ΔI log is the average intensity difference after taking the logarithm.

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