Phase retrieval based on deep learning with bandpass filtering in holographic data storage.

A phase retrieval method based on deep learning with bandpass filtering in holographic data storage is proposed. The relationship between the known encoded data pages and their near-field diffraction intensity patterns is established by an end-to-end convolutional neural network, which is used to predict the unknown phase data page. We found the training efficiency of phase retrieval by deep learning is mainly determined by the edge details of the adjacent phase codes, which are the high-frequency components of the phase code. Therefore, we can attenuate the low-frequency components to reduce material consumption. Besides, we also filter out the high-order frequency over twice Nyquist size, which is redundant information with poor anti-noise performance. Compared with full-frequency recording, the consumption of storage media is reduced by 2.94 times, thus improving the storage density.

Faithful reconstruction of linear polarization wave without dielectric tensor constraint.

Faithful reconstruction is a key and crucial point of polarization holography research, and has significant research interests in the field of holographic storage and image display. In order to realize faithful reconstruction of the reconstructed wave, the interference angle and dielectric tensor should be controlled. In contrast, we used the polarization holography theory described by tensor, and obtained the faithful reconstruction condition of linear polarization wave under arbitrary interference angle without any dielectric tensor constraint, which is further verified by experimental analysis.

Dynamic sampling iterative phase retrieval for holographic data storage.

A dynamic sampling iterative phase retrieval method, which dynamically samples the Fourier intensity distribution of the reconstruction beam captured by the detector, is proposed to shorten the iterative number and decrease the phase error rate of phase retrieval in the phase-modulated holographic data storage. By the dynamic sampling method, that keeping relatively low frequency component of Fourier intensity spectrum at the beginning of iteration and gradually releasing more high frequency component at the subsequent iterations, we shortened the iterative number by 2 times and decreased the phase error rate to some extent because our method provided a better convergent path to the phase retrieval. We also believe the thought of our method can be used in more image retrieval fields.

Lensless phase retrieval based on deep learning used in holographic data storage.

This paper proposes a lensless phase retrieval method based on deep learning (DL) used in holographic data storage. By training an end-to-end convolutional neural network between the phase-encoded data pages and the corresponding near-field diffraction intensity images, the new unknown phase data page can be predicted directly from the intensity image by the network model without any iterations. The DL-based phase retrieval method has a higher storage density, lower bit-error-rate (BER), and higher data transfer rate compared to traditional iterative methods. The retrieval optical system is simple, stable, and robust to environment fluctuations which is suitable for holographic data storage. Besides, we studied and demonstrated that the DL method has a good suppression effect on the dynamic noise of the holographic data storage system.

Frequency expanded non-interferometric phase retrieval for holographic data storage.

A novel frequency expanded non-interferometric phase retrieval method for holographic data storage is proposed. The limitation of twice Nyquist frequency for phase retrieval with high fidelity is broken through. Only 1 times Nyquist size frequency of the hologram is recorded, reconstructed and detected in our method which is the smallest range for complex multi-level phase retrieval in the current holographic data storage report. Required high-order frequencies for quick phase retrieval are generated artificially by expanding 1 times Nyquist frequency to high-order frequencies with utilizations of frequency periodicity. Therefore, our proposed method can increase storage density due to reducing the recording consumption of media and decreasing the recording area by 4 times compared with twice Nyquist frequency recording.

Collinear non-interferometric phase retrieval for holographic data storage.

A collinear non-interferometric phase retrieval method for holographic data storage is proposed. The code rate of the collinear system can be increased by 2 times due to transferring the 50% embedded data from a signal beam to a reference beam. Because the reference beam should be always known both in the recording process and reading process, there is no extra material cost for saving the embedded data. Therefore, the storage density of collinear system is increased by about 2 times compared with previous off-axis non-interferometric phase retrieval systems. Besides, we can enhance the algorithm constraint to shorten iteration numbers by increasing the amplitude weight of the reference beam. In the experiment, we shortened the iteration number and the BER by about 3 times. We also find that the reference number can be reduced by using the collinear way and increasing the amplitude weight of reference. This law allows us to give more code positions to signal so that the data amount in one data page can be increased.

Highly sensitive fluorescent triarylimidazole derivatives for sensing of 2,4,6-trinitrophenol in aqueous solution and its application for actual environment detection.

Two highly sensitive fluorescent triarylimidazole derivatives were synthesized by modifying imidazole with coumarin and large conjugate rigid plane structure. XM-F and XM-L emitted bright yellow-green fluorescent light. Their intense conjugation system generated strong π-π electrostatic interactions with TNP, accompanied by the formation of hydrogen bonds to achieve rapid detection of TNP within 25 s. The detection limits were as low as 0.049 µM and 0.071 µM, respectively. Probes had been successfully applied to rapid detection of TNP in real water samples and manufactured into portable fluorescent test strips. In view of excellent performance of XM-F, it was used to achieve real-time, portable, on-site quantitative detection of TNP by a colorimeter and a smartphone platform. In addition, XM-F also successfully processed into probe-coated TLC plates for efficient detection of fingerprints contaminated with TNP.

Phase retrieval in holographic data storage by expanded spectrum combined with dynamic sampling method.

Phase retrieval in holographic data storage by expanded spectrum combined with dynamic sampling method is proposed, which serves to both reduce media consumption and to shorten the iterative number of phase code retrieval. Generally, high-fidelity phase retrieval requires twice Nyquist frequency in phase-modulated holographic data storage. To increase storage density, we only recorded and captured the signal with Nyquist size and used the frequency expanded method to realize high-fidelity phase retrieval. In the decoding process, the iterative Fourier transform algorithm is used to retrieve the phase information of the reconstructed beam. The expanded spectrum is dynamically sampled, which can provide a faster convergence path for the phase retrieval. We aimed to demonstrate the possibility of integrating various methods on the Fourier domain and providing a potential way to improve the performance of holographic data storage systems. The simulation and experimental results proved the combination of processing methods in frequency spectrum was benefit.

Solution combustion derived oxygen vacancy-rich Co3O4 catalysts for catalytic formaldehyde oxidation at room temperature.

Fabricating abundant oxygen vacancies is crucial for non-noble metal oxides to catalyze formaldehyde (HCHO) oxidation at room temperature. Here, a simple one-pot preparation method via solution combustion was found to produce oxygen vacancy-rich Co3O4 catalysts, avoiding delicate defect engineering. The catalyst was evaluated to result in 52% HCHO conversion in a dynamic flow reaction with ∼6 ppm HCHO, which was higher as compared to some other Co3O4 catalysts prepared in three methods of sol-gel, deposition precipitation and thermal decomposition. The optimal catalyst also exhibited high durability with steady HCHO conversion (∼47%) for more than 50 h. The catalyst characterizations revealed that the explosive solution combustion brought out two particular features of Co3O4, namely, the porous network structure with nano-holes and the abundant oxygen vacancies. The latter was demonstrated to increase the reactive oxygen species and to improve the reducibility and the oxygen transport capacity of Co3O4. The two features and the derived properties are beneficial to the activity and durability of Co3O4. The solution combustion method can serve as a simple and feasible way to fabricate abundant oxygen vacancies to provide room-temperature activity of Co3O4 for HCHO elimination at room temperature.

Improved phase retrieval in holographic data storage based on a designed iterative embedded data.

Embedded data are used to retrieve phases quicker with high accuracy in phase-modulated holographic data storage (HDS). We propose a method to design an embedded data distribution using iterations to enhance the intensity of the high-frequency signal in the Fourier spectrum. The proposed method increases the antinoise performance and signal-to-noise ratio (SNR) of the Fourier spectrum distribution, realizing a more efficient phase retrieval. Experiments indicate that the bit error rate (BER) of this method can be reduced by a factor of one after 10 iterations.