Method for detecting XFEL wavefront by using aerosol

Abstract

The invention provides a method for detecting XFEL wavefront by using aerosol, and relates to the field of XFEL wavefront detection. The method for detecting the wavefront of the XFEL by using the aerosol provided by the invention comprises the following steps: step 1) atomizing a polystyrene sphere solution and injecting the atomized polystyrene sphere solution into the focus of the XFEL; 2) obtaining a plurality of diffraction images about the polystyrene spheres; 3) obtaining a wavefront inclination angle of each diffraction image, and obtaining wavefront inclination distribution of the XFEL pulse according to the wavefront inclination angle; 4) obtaining the diffraction intensity of each diffraction image, and obtaining the intensity distribution of XFEL pulses according to the diffraction intensity; and step 5) combining the wavefront tilt distribution of the XFEL pulse with the intensity distribution of the XFEL pulse to obtain the combined distribution of the wavefront tilt and the intensity of the XFEL pulse. According to the invention, the wavefront tilt and intensity distribution of the XFEL pulse can be sensitively detected under high peak intensity.

Description

Technical Field

[0001] The invention relates to the field of XFEL wavefront detection, in particular to a method for detecting XFEL wavefront using aerosol. Background Art

[0002] In recent years, the emergence of ultrabright, ultrafast, ultrashort pulse, and supercoherent free electron laser technology has greatly promoted the development of ultrafast X-ray spectroscopy experimental technology and has been widely used in different research fields such as physics, chemistry, and biological sciences. Through the excitation of samples by femtosecond laser pulses, X-rays can track the microstructural dynamics of samples in various conditions such as solid, liquid, and gas at different time scales. X-ray absorption and emission spectroscopy, diffraction, and scattering imaging are typical tools for detecting laser-induced structural changes.

[0003] Characterization of high-intensity, strongly focused X-ray free-electron laser (XFEL) pulses is crucial for their application in diffraction imaging. The goal of diffraction imaging experiments using X-ray free-electron lasers (XFELs) is to allow a single weakly scattering sample to scatter photons in a brief and intense focused X-ray pulse while avoiding radiation damage as much as possible, thereby achieving "pre-damage detection" and realizing high-resolution imaging in a near-native state, revealing the fine structure of the sample.

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

[0005] When studying high-intensity hard XFEL pulses, one can consider using ablation marks, scintillating crystals, grating interferometers or X-ray-sensitive Hartmann wavefront sensors. However, since XFEL pulses have extremely high peak intensities near a small focus, these instruments may be damaged or their measurements may be difficult to interpret, which poses a great challenge to measuring information from high-intensity hard X-ray pulses. Although the absolute photon intensity can be inferred by measuring pulses whose intensity is strongly attenuated, the introduction of attenuators may distort the more subtle structures in the unattenuated pulse wavefront. Summary of the invention

[0006] In order to solve the above problems, the present invention provides a method for detecting XFEL wavefront using aerosol, which can sensitively detect the wavefront tilt and intensity distribution of XFEL pulses at high peak intensity. These measurements are consistent with the XFEL single particle imaging experiment setup, without the need for additional components and additional complex operations. Combined with the current XFEL repetition frequency, the measurement can be completed in just a few minutes or even seconds of data acquisition time.

[0007] A method for detecting XFEL wavefront using aerosol, characterized by comprising at least the following steps:

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

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

[0010] Step 3) obtaining a wavefront tilt angle of each diffraction image, and obtaining a 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, obtain a joint distribution of the wavefront tilt and intensity of the XFEL pulse.

[0013] In one feasible embodiment, step 1) further comprises: atomizing the spheres in the polystyrene sphere solution through a pneumatic lens and injecting the spheres into the focus of the XFEL;

[0014] Among them, the XFEL frequency is ≥10Hz, the average energy pulse is ≥0.1mJ, the pulse duration is ≤120fs, and the wavelength is Each pulse provides ≥10 11 photons, and the focused spot size is 0.1 to 1.5 μm.

[0015] In a feasible implementation manner, step 2) further includes: acquiring a diffraction image using a detector with a panel size ≥ 20 cm.

[0016] In a feasible implementation, step 2) further includes: performing a preliminary screening on the diffraction image, and then performing a secondary screening by establishing an intensity filter through histogram statistics.

[0017] In one feasible implementation, step 3) further includes the following steps:

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

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

[0020] x′ n =2x Sn -x n

[0021] y′ n =2y Sn -y n

[0022] 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 symmetric to the candidate point [x′ n ,y′ n ];

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

[0024]

[0025] Among them, I(x i ,y i ) represents [x n ,y n ]; I(x i ′,y i ′) represents [x′ n ,y′ n ];

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

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

[0028] S={ΔI n |n=1,2……}

[0029] min{S}

[0030] Among them, S is the set formed by the average intensity difference ΔI of all candidate points;

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

[0032] [Δx / D,Δy / D]

[0033] Where [Δx, Δy] is the distance between the Friedel center coordinate and the detector center pixel coordinate found by minimizing the average intensity difference; D is the distance between the sample and the detector;

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

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

[0036] Step 4-1) Establish the function to be fitted

[0037]

[0038] 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 sphere, R and I 0 is the parameter to be fitted in the function to be fitted f(x);

[0039] Step 4-2) Get all the 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 XFL, p is the pixel size of the detector, and r is the number of pixels from the pixel point to the center pixel point;

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

[0043] δ i =f(x i )-y i

[0044]

[0045] Among them, y i To minimize the experimentally measured data points, f(x i ) is the function to be fitted, x i is the value of the ith x;

[0046] Step 4-4) Establish the optimization function MinS(R,I 0 ), optimize the residual model S and obtain R and I 0 The optimal value of

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

[0048]

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

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

[0051] In a feasible implementation, step 4-2) includes: performing averaging processing on the functions to be fitted f(x) corresponding to points with the same spatial frequency x.

[0052]

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

[0054] In one feasible implementation, the optimization function MinS(R,I 0 ) is the least squares method, which obtains the optimal parameters by solving the partial differential equation. The partial differential equation is as follows:

[0055]

[0056] in, is MinS(R,I 0 )About I 0 The partial differential of is MinS(R,I 0 ) with respect to the partial derivative of R.

[0057] In one possible implementation, in step 4-5):

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

[0059] In one possible implementation, in step 3-3): taking the logarithm of the average intensity difference ΔI

[0060] ΔI log =log(ΔI+1)

[0061] Among them, ΔI log is the logarithmic difference in the mean intensity.

[0062] The method for detecting XFEL wavefront using aerosol provided by the present invention has the following beneficial effects: the present invention can sensitively detect the wavefront tilt and intensity distribution of XFEL pulses at high peak intensity, and these measurements are consistent with the XFEL single particle imaging experiment setting, without the need for additional components and additional complex operations, and combined with the current XFEL repetition frequency, it only takes a few minutes or even seconds of data acquisition time to complete the measurement. In addition, there is no need to break the experimental cavity before each experiment, and only the sample in the aerosol syringe needs to be replaced. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 This is a wavefront tilt distribution diagram of the XFEL pulse of the present invention.

[0064] Figure 2 This is the intensity distribution diagram of the XFEL pulse of the present invention.

[0065] Figure 3 It is the particle size probability distribution diagram of the present invention.

[0066] Figure 4 FIG. 4 is a joint distribution diagram of the wavefront tilt and intensity of the XFEL pulse of the present invention.

[0067] Figure 5 FIG. 2 is a diagram of an experimental device of the present invention. DETAILED DESCRIPTION

[0068] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention. In the description of the present invention, it should be noted that the orientation or position relationship indicated by the terms "left side", "right side", "upper side", "lower side", "above", "below" and the like is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0069] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0070] Furthermore, in the description of the present invention, unless otherwise specified, “plurality” means two or more.

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

[0072] Step 1) atomizing the polystyrene sphere solution and injecting it into the focus of the XFEL;

[0073] Step 2) obtaining a plurality of diffraction images of the polystyrene sphere;

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

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

[0076] Step 5) Combining the wavefront tilt distribution of the XFEL pulse and the intensity distribution of the XFEL pulse, obtain a joint distribution of the wavefront tilt and intensity of the XFEL pulse.

[0077] Next, we will break down the above five steps into details, starting with step 1).

[0078] Before explaining step 1) in detail, a brief explanation of step 1) is given first: the main purpose of step 1) is to allow the polystyrene spheres in the atomized polystyrene solution to act as disposable lenses at random positions, and each injected sphere can detect the local area of ​​the intercepted XFEL pulse and form a diffraction image in the detector.

[0079] Step 1) further includes atomizing the polystyrene ball solution through a pneumatic lens and injecting the spheres into the focus of the XFEL. The XFEL frequency is ≥10 Hz, the average energy pulse is ≥0.1 mJ, the pulse duration is ≤120 fs, and the wavelength is Each pulse provides ≥10 11 photons, and the focused spot size is 0.1 to 1.5 μm.

[0080] In a specific embodiment, the frequency of the XFEL is 10 Hz, the average energy pulse of the XFEL is 1.2 mJ, the pulse duration of the XFEL is 100 fs, the wavelength of the XFEL is 1.2 nm, and each pulse in the XFEL provides an average of 7.5×10 12 photons, and the photon focusing size in XFEL is 1.0μm.

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

[0082] Step 2) also includes acquiring a diffraction image using a detector with a panel size of ≥20 cm. In a specific embodiment, the pixel size of the detector is 2048×2048, and the size of each pixel of the detector is 75×75 μm. 2 .

[0083] Step 2) also includes preliminary screening of the diffraction images, and then secondary screening by establishing an intensity filter through histogram statistics. In a specific embodiment, more than 2,000 diffraction patterns were collected and preliminarily screened, of which 506 contained diffraction data of scattered signals, and then an intensity filter was established through histogram statistics to further screen the diffraction data from individual particles, ultimately leaving 470 diffraction images of individual spheres for further study.

[0084] Before explaining step 3) in detail, a brief explanation of step 3) is given first: the main purpose of step 3) is to find the Friedel center of each diffraction image (i.e., the center of symmetry of the diffraction pattern), and then calculate the wavefront tilt angle of each diffraction image based on the Friedel center of each diffraction image, and then statistically analyze the wavefront tilt angles of all diffraction images to obtain the wavefront tilt distribution of the XFEL pulse.

[0085] The following is a detailed explanation of step 3), which also includes the following steps:

[0086] Step 3-1) Select a suitable pixel area on the diffraction image, and each pixel point in the pixel area becomes a candidate point. In this example, a square area with a side length of 20 (pixels) is selected as the candidate central pixel area with the center position 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 area. As an illustration, in this step, only one diffraction image is processed each time, and a batch of candidate points that may become the Fried center of the diffraction image are first selected, and then the data mapped by each candidate point are compared to obtain the candidate point with the best data performance among the batch of candidate points to become the Fried center of the diffraction image. Therefore, a Fried center can be selected for each image in the end. In a specific embodiment, there are a total of 470 diffraction images, each of which corresponds to a Fried center, and there are a total of 470 sets of center point coordinates.

[0087] Then, the detailed process of selecting the candidate point with the best data performance from all the candidate points of a diffraction image to become the Friedel center of the diffraction image is as described in step 3-2). Step 3-2) obtains the symmetric point about the candidate point for each pixel point on the diffraction image (usually not all pixels are used, but some data close to the center of the candidate area are selected), and 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 symmetric to the candidate point [x′ n ,y′ n ], where the calculation formula for the coordinate points on the diffraction image that are symmetric 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 pixels on this diffraction image are symmetrical about the candidate point according to the above formula, so that each pixel can obtain a symmetrical point symmetrical about the candidate point. For example: the coordinates of the selected candidate point are [x S1 ,y S1 ], then all the pixels on the diffraction image can obtain the symmetric points about the candidate point according to the above formula. Then, continue with step 3-3).

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

[0092]

[0093] Among them, I(x i ,y i ) represents [x n ,y n ], I(x i ′,y i ′) represents [x′ n ,y′ n ] is the diffraction intensity at ]. Among them, I(x i ,y i ) and I(x i ′,y i In a preferred embodiment, in order to improve the sensitivity of the average intensity difference ΔI, the logarithm of the average intensity difference ΔI can be taken 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 ], after processing according to step 3-2) and step 3-3), the next candidate point is selected, and its coordinates are [x S2 ,y S2 ] 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. This candidate point becomes the Friedel center of the diffraction image. The formula is as follows:

[0096] S={ΔI n |n=1,2……}

[0097] min{S}

[0098] Among them, S is the 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 among all the candidate points, and let this candidate point become the Friedel center of the diffraction image. Then, continue with steps 3-6).

[0100] Step 3-6) Obtain the wavefront tilt angle of the diffraction image, the formula is as follows:

[0101] [Δx / D,Δy / D]

[0102] Where [Δx, Δy] is the distance between the Friedel center coordinates found by minimizing the average intensity difference and the detector center pixel coordinates; D is the distance from the sample to the detector. In this step, the wavefront tilt angle of the diffraction image can be obtained based on the Friedel center of the diffraction image. Then, continue with steps 3-7).

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

[0104] Before explaining step 4) in detail, a brief explanation of step 4) is given first: the main purpose of step 4) is to find the diffraction intensity of each diffraction image, and then to statistically calculate the diffraction intensities of all diffraction images to obtain the intensity distribution information of the XFEL pulse.

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

[0106] Step 4-1) Establish the function to be fitted, which is as follows:

[0107]

[0108] Where x is the spatial frequency or scattering vector, f(x) is the function to be fitted, the value of f(x) is the scattering intensity of the sphere, R and I 0 are the parameters to be fitted in the function to be fitted f(x). As an illustration, R and I 0is the final data that we want to obtain through the function to be fitted, and the values ​​of x and f(x) are described in detail in step 4-2).

[0109] Step 4-2) Get all the values ​​of x in step 4-1) and the formula 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 between the pixel and the center pixel of the detector (in units of the number of pixels spaced apart). As an illustration, D, w, and p are all constants, and the value range of r is all pixels in the diffraction image, that is, it is necessary to traverse each pixel in the diffraction image. In other words, the value of x is all 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 pixels at the same distance from the center of the detector, their spatial frequency x should be the same, and the scattering intensity f(x) corresponding to the same spatial frequency x needs to be averaged. In simple terms, it can be compared to: diffuse outward from the center of the detector as the origin, and average the scattering intensity f(x) of the pixels located on the same radius. Therefore, in a preferred embodiment, the scattering intensities f(x) corresponding to points with the same spatial frequency x are averaged, and the formula is as follows:

[0112]

[0113] Then, after determining the range of values ​​of x, we need to actually process f(x), which is described in detail in step 4-3).

[0114] Step 4-3) Establish a residual model. The residual model is as follows

[0115] δ i =f(x i )-y i

[0116]

[0117] Among them, y i To minimize the experimentally measured data points, f(x i ) is the function to be fitted, x i is the value of x at the ith time. As an illustration, y i In fact, it is the scattering intensity collected by the detector. At this time, S is a combination of R and I 0function.

[0118] Step 4-4) Establish the optimization function MinS(R,I 0 ), optimize the residual model S and obtain R and I 0 In a specific embodiment, solving the optimization function MinS(R,I 0 ) is the least squares method, which obtains the optimal parameters by solving the partial differential equation. The partial differential equation is as follows:

[0119]

[0120] in, is MinS(R,I 0 )About I 0 The partial differential of is MinS(R,I 0 ) is the partial differential with respect to R. Generally speaking, the point where the partial differential is equal to zero is the extreme point, so in this embodiment, R and I are respectively 0 The partial differential of is equal to zero, so we can get R and I 0 The extreme point of , that is, the optimal point.

[0121] Step 4-5) Obtain the diffraction intensity of the diffraction image. The formula for the diffraction intensity is as follows:

[0122]

[0123] Among them, I inc The unit is photon flux; ρ PSL is the density of polystyrene; N A is Avogadro's constant; M PSL is the molar mass of polystyrene monomer; f is the average scattering factor of polystyrene monomer under 1KeV radiation; r e is the classical electron radius; ΔΩ is the solid angle enclosed by each detector pixel; G det is the detector gain; Q eff is the quantum efficiency of the detector gain for 1 KeV photons. In a preferred embodiment, PSL =1.05g / cm 3 ;M PSL =1.05 g / mol; f = 58.3; r e =2.8×10 -15 m; ΔΩ=1.1×10 8 rad; G det 7 counts for each photon; Q eff =0.9. Most of the parameters in the formula of this step are constants or can be directly obtained according to the actual situation, so I in step 4-4) 0Substitute the optimal value of into the formula to directly obtain I inc Then, continue with steps 4-6).

[0124] Step 4-6) traverse all diffraction images to obtain the diffraction intensities of all diffraction images. In a specific embodiment, there are 470 diffraction images, so 470 diffraction intensities I can be obtained. inc The data of these 470 diffraction intensities I inc By plotting the data, we can obtain the intensity distribution information of the XFEL pulse. For details, please refer to Figure 2 In another specific embodiment, there are 470 diffraction images in total, so 470 particle size R data can be obtained at the same time. By plotting the 470 particle size R data, the particle size distribution data of the 470 diffraction images can be obtained. For details, please refer to Figure 3 .

[0125] Before explaining step 5) in detail, a brief explanation of step 5) is given first: the main purpose of step 5) is to find a way to merge the two images obtained in step 3) and step 4) together to obtain the distribution of photon flux and wavefront tilt.

[0126] 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. For details, please refer to Figure 4 . Figure 4 The white numbers in the Figure 1 Each circle in Figure 4 Indirect measurements of pulses in the free electron laser can improve the optical systems and imaging experiments of free electron lasers. For example, this can be achieved by maximizing the absolute photon flux and / or reducing the Figure 4 The distribution of wavefront tilt in the sample is used to guide small adjustments of the flexible mirror used to focus the pulse. Unlike profilometry, which detects the wavefront far from the sample injection location, Figure 4 The distribution of photon flux and wavefront tilt is directly displayed, which is very useful for injecting samples under similar conditions.

[0127] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention. These improvements and substitutions should also be regarded as the scope of protection of the present invention.

Claims

1. A method for detecting XFEL wavefront using aerosol, characterized in that: At least the following steps are included: Step 1) atomizing the polystyrene sphere solution and injecting it into the focus of the XFEL; Step 2) obtaining a plurality of diffraction images of the polystyrene sphere; Step 3) obtaining a wavefront tilt angle of each diffraction image, and obtaining a 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; Step 5) Combining the wavefront tilt distribution of the XFEL pulse and the intensity distribution of the XFEL pulse, obtain a joint distribution of the wavefront tilt and intensity of the XFEL pulse.

2. The method for detecting XFEL wavefront using aerosol according to claim 1, characterized in that: Step 1) further includes: atomizing the spheres in the polystyrene sphere solution through a pneumatic lens and injecting the spheres into the focus of the XFEL; Among them, the XFEL frequency is ≥10Hz, the average energy pulse is ≥0.1mJ, the pulse duration is ≤120fs, and the wavelength is Each pulse provides ≥10 11 photons, and the focused spot size is 0.1 to 1.5 μm.

3. The method for detecting XFEL wavefront using aerosol according to claim 1, characterized in that: Step 2) also includes: using a detector with a panel size of ≥20 cm to acquire a diffraction image.

4. The method for detecting XFEL wavefront using aerosol according to claim 1, characterized in that: Step 2) also includes: performing a preliminary screening on the diffraction image, and then performing a secondary screening by establishing an intensity filter through histogram statistics.

5. The method for detecting XFEL wavefront using aerosol according to claim 1, characterized in that: Step 3) also includes the following steps: Step 3-1) Select a suitable pixel area on the diffraction image, and each pixel point in the pixel area becomes a candidate point, where the coordinates of the candidate point are [x Sn ,y Sn ], Sn is the number of pixels in the pixel area; Step 3-2) Get the symmetric point of each pixel on the diffraction image about the candidate point x ′ n =2x Sn -x n and n ′ =2y Sn -and n 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 symmetric to the candidate point [x ′ n ,y n ′ ]; Step 3-3) Obtain the average intensity difference ΔI of the candidate points in step 3-2) Among them, I(x i ,y i ) represents [x n ,y n ]; I(x i ′,y i ′) represents [x ′ n ,y n ′ ]; Step 3-4) traverse each candidate point and obtain the average intensity difference ΔI of each candidate point; Step 3-5) Find the candidate point with the smallest average intensity difference ΔI among all candidate points, which is the Friedel center coordinate of the diffraction pattern S={ΔI n |n=1,2……} min{S} Among them, S is the set formed by the average intensity difference ΔI of all candidate points; Step 3-6) Obtain the wavefront tilt angle of the diffraction image [Δx / D,Δy / D] Where [Δx, Δy] is the distance between the Friedel center coordinate and the detector center pixel coordinate found by minimizing the average intensity difference; D is the distance between the sample and the detector; Step 3-7) traverses all diffraction images, and obtains the wavefront tilt angles of all 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 diffraction images.

6. The method for detecting XFEL wavefront using aerosol according to claim 1, characterized in that: Step 4) also includes the following steps: Step 4-1) Establish the parameters to be fitted Wherein, x is the spatial frequency, f(x) is the function to be fitted, the value of f(x) is the scattering intensity of the sphere, and R and I0 are the parameters to be fitted in the function to be fitted f(x); Step 4-2) Get all the 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 number of pixels from the pixel point to the center pixel point; Step 4-3) Establish a residual model d i =f(x i )-y i Among them, y i To minimize the experimentally measured data points, f(x i ) is the function to be fitted, x i is the value of the ith x; Step 4-4) Establish an optimization function MinS(R,I0), optimize the residual model S, and obtain the optimal values ​​of R and I0; Step 4-5) Obtain the diffraction intensity of each diffraction image Among them, ρ PSL is the density of polystyrene; N A is Avogadro's constant; M PSL is the molar mass of polystyrene monomer; f is the average scattering factor of polystyrene monomer under 1KeV radiation; r e is the classical electron radius; ΔΩ is the solid angle enclosed by each detector pixel; G det is the detector gain; Q eff is the quantum efficiency of the detector gain for 1KeV photons; Step 4-6) traverse all diffraction images to obtain the diffraction intensity of all diffraction images.

7. The method for detecting XFEL wavefront using aerosol according to claim 6, characterized in that: Step 4-2) includes: performing averaging processing on the functions to be fitted f(x) corresponding to points with the same spatial frequency x; Where N is the number of points with the same spatial frequency x.

8. The method for detecting XFEL wavefront using aerosol according to claim 6, characterized in that: The method for solving the optimization function MinS(R,I0) in step 4-4) is the least square method, which obtains the optimal parameters by solving the partial differential equation. The partial differential equation is as follows: in, is the partial differential of MinS(R,I0) with respect to I0, is the partial differential of MinS(R,I0) with respect to R.

9. The method for detecting XFEL wavefront using aerosol according to claim 6, characterized in that: In step 4-5): ρ PSL =1.05g / cm 3 ;M PSL =1.05 g / mol; f = 58.3; r e =2.8×10 -15 m; ΔΩ=1.1×10 8 rad; G det 7 counts for each photon; Q eff =0.

9.

10. The method for detecting XFEL wavefront using aerosol according to claim 5, characterized in that: In step 3-3), take the logarithm of the average intensity difference ΔI ΔI log =log(ΔI+1) Among them, ΔI log is the logarithmic difference in the mean intensity.

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