Zijian Xu

Sparse-scan ptychography accelerates data acquisition but compromises the overlap-induced redundancy essential for stable blind reconstruction. In low-overlap cases, object errors are often transferred to the probe update, causing crosstalk and artifacts. In this work, we propose a sparse-scan ptychography method termed hybrid-scan ptychography, which combines a hybrid-overlap scanning strategy with a reference-guided ePIE reconstruction algorithm. In this method, a localized high-overlap scan is used to establish a reliable probe estimate for reconstructing a wide field of view scanned on a low-overlap grid. As a stabilizing prior, this probe estimate is integrated into the ePIE probe update for the low-overlap region through an additional quadratic regularization term, thereby ensuring accurate probe reconstruction for sparse-scan region. This method effectively suppresses sparse-scan artifacts and ensures robust, high-fidelity reconstruction, as demonstrated by numerical simulations and soft X-ray ptychography experiments. With the new method, the acquisition efficiency of ptychography can be increased by at least 2 times without significant resolution reduction.

X-ray ptychography has an ultrahigh resolution at the nanoscale and an extended field of view, making it widely used in many cutting-edge fields. In this technique, precisely determining the scanning position is crucial for improving imaging quality and resolution. In this study, we propose and validate a novel method for correcting rotational position errors in ptychography. This method combines the Fourier-space bisection search with the ptychography reconstruction algorithm. By progressively rotating the diffraction pattern in Fourier space and continuously narrowing the predicted angular error interval based on the reconstruction errors from inner loops, the method iteratively approaches and determines the deflection angle of the detector plane relative to the sample plane (around the optical axis). This method can correct rotational angle errors efficiently in Fourier space and is highly robust against uncertainties in experimental parameters and diffraction signal quality. Both simulation and experimental reconstructions demonstrate the method's capability to precisely correct rotational errors and recover fine sample structures, thereby improving imaging resolution.

X-ray ptychography has the advantage of nanoscale resolution and extended field-of-view (FOV), which has led to its widespread application in many cutting-edge research fields. Currently, the technique faces the following challenges: greatly increased time cost for large FOV and increased reconstruction difficulty due to large data volume. In this study, we present a synergistic method to improve the efficiency of large FOV ptychography by integrating a large-probe large-step scanning strategy with an iterative partition reconstruction (IPR) algorithm. To increase the probe size beyond the detector Fourier window, we develop an upsampling-multimode fusion algorithm that enables ptychography scan with a step size over 5 µm using only stepper motors, thus improving the acquisition efficiency by more than 12 times compared to conventional ptychography and STXM. Meanwhile, we propose an IPR method with an adaptive sample splicing mechanism for raster scan or partition scan, which effectively suppresses the artifacts due to probe variations, significantly reduces the hardware requirements for reconstruction while improving reconstruction efficiency, and eliminates 10% overlapping redundancy in conventional tile scan, further improving efficiency. Verification experiments using probes of 20 and 25 µm demonstrated the performance of the developed strategy, which provides a new solution for high-resolution, large FOV ptychography.

This study developed a novel Click-SNAs dual-mode probe based on click chemistry, which achieved high specificity fluorescence and synchrotron X-ray microscopy imaging of neuronal cells.

X-ray ptychography is an ultrahigh resolution imaging technique widely used in synchrotron radiation facilities. Its imaging performance relies on the quality of the acquired signals. However, the X-ray detectors used often suffer from signal loss due to sensor gaps, beamstops, defective pixels, overexposure, or other factors, resulting in degraded image quality. To suppress and compensate for the effects of signal loss, we proposed the known probe approach to partially recover the lost signals and introduced the high probe divergence strategy by investigating the effects of probe divergence on reconstruction quality under signal loss conditions. Both simulation and experiment results show that high probe divergence can effectively suppress the impact of signal loss on reconstruction quality while using a known probe as the initial probe for reconstruction can largely recover missing signals in Fourier space, resulting in a much better image than using a guessed initial probe. These strategies allow for high-quality imaging in the presence of signal loss without secondary data acquisition, significantly improving experimental efficiency and reducing radiation damage compared to previous strategies.

X-ray ptychography is a lensless imaging technology with promising applications that can achieve nanometer resolution. However, the noise in the diffraction patterns degrades the performance of the phase recovery algorithms for ptychography. In reconstructed objects, the artifacts can affect details. We categorize the noise in the diffraction patterns into static intensity (SI) and dynamic random noise (DRN), which lead to periodic artifacts (PAs) and random noise in the reconstructed object. A denoising method for X-ray ptychography is therefore proposed to suppress the SI and DRN by a unified mathematical model. An explicit noise constraint based on the physical diffraction model and an implicit prior regarding the object for network extraction are integrated to construct a joint noise constraint. Simulations and soft X-ray experiments demonstrate the advanced capability of the proposed method for noise suppression. Compared with other methods (extended ptychographical iterative engine and periodic-artifact suppressing algorithm), the proposed method has high robustness and generality.

Dynamic behavior is prevalent in biological and condensed matter systems at the nano- and mesoscopic scales. Typically, we capture images as “snapshots” to demonstrate the evolution of a system, and coherent X-ray diffraction imaging (CDI), as a lensless imaging technique, provides a nanoscale resolution, allowing us to clearly observe these microscopic phenomena. This paper presents a new dynamic CDI method based on zone-plate optics aiming to overcome the limitations of existing techniques in imaging fast dynamic processes by integrating the spatio-temporal dual constraint with a probe constraint. In this method, the modulus-enforced probe constraint and the temporal correlation of the dynamic sample low-frequency information are exploited and combined with an empty static region constraint in the dynamic sample. Using this method, we achieved a temporal resolution of 20 Hz and a spatial resolution of 13.2 nm, which were verified by visualized experimental results. Further comparisons showed that the reconstructed images were consistent with the ptychography reconstruction results, confirming the accuracy and feasibility of the method. This work is expected to provide a new tool for materials science and mesoscopic life sciences, promoting a deeper understanding of complex dynamic processes.