A novel ratiometric fluorescent sensor from modified coumarin-grafted cellulose for precise pH detection in strongly alkaline conditions.

Accurate and convenient monitoring of pH under extreme alkaline conditions is still a challenge. In this work, 4-(3-(7-hydroxy-2-oxo-2H-chromen-3-yl)-3-oxoprop-1-en-1-yl)benzamide (HCB), a coumarin derivative, was grafted onto dialdehyde cellulose (DAC) to obtain a sensor DAC-HCB, which exhibited a ratiometric fluorescent response to the pH of alkaline solutions, resulting in a significant fluorescent color change from yellow to blue (FI459 nm/FI577 nm) at pH 7.5-14. The structure of DAC-HCB was characterized through FT-IR, XRD, XPS, SEM. The pKa of sensor DAC-HCB was 13.16, and the fluorescent intensity ratio FI459 nm/FI577 nm possessed an excellent linear characteristic with pH in the scope of 9.0-13.0. Meanwhile, sensor DAC-HCB showed good selectivity, anti-interference, and fast response time to basic pH, which is an effective fluorescent sensor for examination of pH in alkali circumstance. The recognition mechanism of DAC-HCB to OH- was elucidated with HRMS and density-functional theory (DFT) computational analyses. Sensor DAC-HCB was successfully used for precise detection of environmental water samples pH. This work furnished a new protocol for test strips as a convenient and highly efficient pH detection tool for the high pH environment, and it has great potential for application in environmental monitoring.

An ultrasensitive cellulose-based fluorescent sensor for Al3+ detection and its applications in plant tissue and food samples.

Fluorescent sensors available for metal ions detection have been extensively developed in recent years. However, developing an ultrasensitive fluorescent sensor for highly selectively detecting Al3+ based on cellulose remains a challenge. In this study, an ethylcellulose-based flavonol fluorescent sensor named EC-BHA was synthesized by the esterification of ethylcellulose (EC) with a new flavonol derivative 4-(2-(2,3-bis(ethoxymeothy)phenyl)-3-hydroxy-4-oxo-4-H-chromen-7-yl) benzoic acid (BHA). The fluorescence intensity of EC-BHA exhibited a 180-fold increase at 490 nm after binding with Al3+ and provided an ultralow detection limit of 13.0 nM. The sensor showed some exceptional sensing properties including a broad pH range (4-10), large Stokes shifts (190 nm), and a short response time (3 min). This sensor was successfully applied for determining trace Al3+ in food samples as well as in plant tissue. Moreover, the electrostatic spun film EBP was fabricated by blending EC-BHA with PS (polystyrene) via electrostatic spinning technique and utilized for selective detection of Al3+ as soon as possible.

Refractive index tomography with a physics-based optical neural network.

The non-interference three-dimensional refractive index (RI) tomography has attracted extensive attention in the life science field for its simple system implementation and robust imaging performance. However, the complexity inherent in the physical propagation process poses significant challenges when the sample under study deviates from the weak scattering approximation. Such conditions complicate the task of achieving global optimization with conventional algorithms, rendering the reconstruction process both time-consuming and potentially ineffective. To address such limitations, this paper proposes an untrained multi-slice neural network (MSNN) with an optical structure, in which each layer has a clear corresponding physical meaning according to the beam propagation model. The network does not require pre-training and performs good generalization and can be recovered through the optimization of a set of intensity images. Concurrently, MSNN can calibrate the intensity of different illumination by learnable parameters, and the multiple backscattering effects have also been taken into consideration by integrating a "scattering attenuation layer" between adjacent "RI" layers in the MSNN. Both simulations and experiments have been conducted carefully to demonstrate the effectiveness and feasibility of the proposed method. Experimental results reveal that MSNN can enhance clarity with increased efficiency in RI tomography. The implementation of MSNN introduces a novel paradigm for RI tomography.

Erratum: Fourier ptychography multi-parameter neural network with composite physical priori optimization: publisher's note.

[This corrects the article on p. 2739 in vol. 13, PMID: 35774326.].

Hybrid full-pose parameter calibration of a freeform illuminator for Fourier ptychographic microscopy.

As a typical computational method, Fourier ptychographic microscopy (FPM) can realize high spatial resolution and quantitative phase imaging while preserving the large field of view with a low numerical aperture (NA) objective. A programmable light-emitting diode (LED) array is used as a typical illuminator in an FPM system, and the illumination parameters of each LED element are crucial to the success of the FPM reconstruction algorithm. Compared with LED arrays arranged in rectangular arrays, LED arrays with special structures such as domes or rings can effectively improve FPM imaging results and imaging efficiency. As a trade-off, their calibration difficulty is greatly increased due to the lack of geometric constraints of rectangular arrays. In this paper, we propose an effective hybrid full-pose parameter calibration method for freeform LED array illuminators, combining stereoscopic 3D imaging techniques and the geometric constraints of the microscopic platform. First, a stereovision system is used to obtain the accurate 3D position of each LED element of the freeform illuminator and to construct a rigid 3D coordinate LED array system. Then, calibration between the coordinate system of the LED array and that of the optical imaging component is realized according to the geometric features of the brightfield-to-darkfield edges. Finally, we verify the feasibility and effectiveness of the proposed method through full-pose parameter calibration of LED arrays with different arrangement rules.

A highly specific chalcone derivative grafted ethylcellulose fluorescent probe for rapid and sensitive detection of Al3+ in actual environmental and food samples.

Al3+ is commonly utilized in daily life, however, the excessive accumulation of Al3+ within organisms can result in severe health problems. Herein, a highly efficient fluorescent probe EC-HTC for Al3+ was synthesized through chemical modification of ethyl cellulose. This probe exhibited a significant fluorescence enhancement response to Al3+, and it interestingly also possessed an obvious aggregation-induced emission (AIE) effect. The detection limit of probe EC-HTC for Al3+ was as low as 0.23 µM, and its pH usage range was as wide as 5-10. The complexation ratio of EC-HTC with Al3+ was determined to be 1:1 based on Job's plot, which was further confirmed by 1H NMR titration and HRMS analysis. Moreover, the probe EC-HTC was successfully employed for the determination of Al3+ in environmental and food samples. In addition, the probe EC-HTC compositing PS (polystyrene) electrostatic spun fiber membranes EHP with high specific surface area were prepared to achieve the rapid and portable detection of Al3+.

A naphthalimide functionalized chitosan-based fluorescent probe for specific detection and efficient adsorption of Cu2.

As one of the most abundant metal ions, Cu2+ has turned into a great threat to human health and the natural environment due to its widely utilized in various industries. In this paper, a chitosan-based fluorescent probe CTS-NA-HY for detection and adsorption of Cu2+ was rationally prepared. CTS-NA-HY exhibited a specific "turn off" fluorescence response to Cu2+ and the fluorescence color changed from bright yellow to colorless. It possessed satisfactory detection performance to Cu2+ including good selectivity and anti-interference, low detection limit (29 nM) and wide pH range (4-9). The detection mechanism was confirmed by Job's plot, X-ray photoelectron spectroscopy, FT-IR and 1H NMR analysis. Additionally, the probe CTS-NA-HY was capacity of determining Cu2+ in environmental water and soil samples. Besides, CTS-NA-HY-based hydrogel could also remove Cu2+ in aqueous solution effectively, which the ability of adsorption was greatly improved compared with original chitosan hydrogel.

Robust full-pose-parameter estimation for the LED array in Fourier ptychographic microscopy.

Fourier ptychographic microscopy (FPM) can achieve quantitative phase imaging with a large space-bandwidth product by synthesizing a set of low-resolution intensity images captured under angularly varying illuminations. Determining accurate illumination angles is critical because the consistency between actual systematic parameters and those used in the recovery algorithm is essential for high-quality imaging. This paper presents a full-pose-parameter and physics-based method for calibrating illumination angles. Using a physics-based model constructed with general knowledge of the employed microscope and the brightfield-to-darkfield boundaries inside captured images, we can solve for the full-pose parameters of misplaced LED array, which consist of the distance between the sample and the LED array, two orthogonal lateral shifts, one in-plane rotation angle, and two tilt angles, to correct illumination angles precisely. The feasibility and effectiveness of the proposed method for recovering random or remarkable pose parameters have been demonstrated by both qualitative and quantitative experiments. Due to the completeness of the pose parameters, the clarity of the physical model, and the high robustness for arbitrary misalignments, our method can significantly facilitate the design, implementation, and application of concise and robust FPM platforms.

Fourier ptychography multi-parameunter neural network with composite physical priori optimization.

Fourier ptychography microscopy(FPM) is a recently developed computational imaging approach for microscopic super-resolution imaging. By turning on each light-emitting-diode (LED) located on different position on the LED array sequentially and acquiring the corresponding images that contain different spatial frequency components, high spatial resolution and quantitative phase imaging can be achieved in the case of large field-of-view. Nevertheless, FPM has high requirements for the system construction and data acquisition processes, such as precise LEDs position, accurate focusing and appropriate exposure time, which brings many limitations to its practical applications. In this paper, inspired by artificial neural network, we propose a Fourier ptychography multi-parameter neural network (FPMN) with composite physical prior optimization. A hybrid parameter determination strategy combining physical imaging model and data-driven network training is proposed to recover the multi layers of the network corresponding to different physical parameters, including sample complex function, system pupil function, defocus distance, LED array position deviation and illumination intensity fluctuation, etc. Among these parameters, LED array position deviation is recovered based on the features of brightfield to darkfield transition low-resolution images while the others are recovered in the process of training of the neural network. The feasibility and effectiveness of FPMN are verified through simulations and actual experiments. Therefore FPMN can evidently reduce the requirement for practical applications of FPM.

Robust Fourier ptychographic microscopy via a physics-based defocusing strategy for calibrating angle-varied LED illumination.

Fourier ptychographic microscopy (FPM) is a recently developed computational imaging technique for wide-field, high-resolution microscopy with a high space-bandwidth product. It integrates the concepts of synthetic aperture and phase retrieval to surpass the resolution limit imposed by the employed objective lens. In the FPM framework, the position of each sub-spectrum needs to be accurately known to ensure the success of the phase retrieval process. Different from the conventional methods with mechanical adjustment or data-driven optimization strategies, here we report a physics-based defocusing strategy for correcting large-scale positional deviation of the LED illumination in FPM. Based on a subpixel image registration process with a defocused object, we can directly infer the illumination parameters including the lateral offsets of the light source, the in-plane rotation angle of the LED array, and the distance between the sample and the LED board. The feasibility and effectiveness of our method are validated with both simulations and experiments. We show that the reported strategy can obtain high-quality reconstructions of both the complex object and pupil function even the LED array is randomly placed under the sample with both unknown lateral offsets and rotations. As such, it enables the development of robust FPM systems by reducing the requirements on fine mechanical adjustment and data-driven correction in the construction process.

Embedded parallel Fourier ptychographic microscopy reconstruction system.

Fourier ptychographic microscopy (FPM) has attracted a wide range of focus for its ability of large space-bandwidth product and quantitative phase imaging. It is a typical computational imaging technique that jointly optimizes imaging hardware and reconstruction algorithms. The data redundancy and inverse problem algorithms are the sources of FPM's excellent performance. But at the same time, this large amount of data processing and complex algorithms also evidently reduce the imaging speed. To accelerate the FPM reconstruction speed, we proposed a fast FPM reconstruction framework consisting of three levels of parallel computation and implemented it with an embedded computing module. In the conventional FPM framework, the sample image is divided into multiple sub-regions to process separately because the illumination angles and defocus distances for different sub-regions may also be different. Our parallel framework first performs digital refocusing and high-resolution reconstruction for each sub-region separately and then stitches the complex sub-regions together to obtain the final high-resolution complex image. The feasibility of the proposed parallel FPM reconstruction framework is verified with different experimental results acquired with the system we built.

Fast digital refocusing and depth of field extended Fourier ptychography microscopy.

Fourier ptychography microscopy (FPM) shares its roots with the synthetic aperture technique and phase retrieval method, and is a recently developed computational microscopic super-resolution technique. By turning on the light-emitting diode (LED) elements sequentially and acquiring the corresponding images that contain different spatial frequencies, FPM can achieve a wide field-of-view (FOV), high-spatial-resolution imaging and phase recovery simultaneously. Conventional FPM assumes that the sample is sufficiently thin and strictly in focus. Nevertheless, even for a relatively thin sample, the non-planar distribution characteristics and the non-ideal position/posture of the sample will cause all or part of FOV to be defocused. In this paper, we proposed a fast digital refocusing and depth-of-field (DOF) extended FPM strategy by taking the advantages of image lateral shift caused by sample defocusing and varied-angle illuminations. The lateral shift amount is proportional to the defocus distance and the tangent of the illumination angle. Instead of searching the optimal defocus distance with the optimization search strategy, which is time consuming, the defocus distance of each subregion of the sample can be precisely and quickly obtained by calculating the relative lateral shift amounts corresponding to different oblique illuminations. And then, digital refocusing strategy rooting in the angular spectrum (AS) method is integrated into FPM framework to achieve the high-resolution and phase information reconstruction for each part of the sample, which means the DOF of the FPM can be effectively extended. The feasibility of the proposed method in fast digital refocusing and DOF extending is verified in the actual experiments with the USAF chart and biological samples.

Adaptive high-dynamic-range Fourier ptychography microscopy data acquisition with a red-green-blue camera.

Fourier ptychography microscopy is a powerful tool for wide-field and high-spatial-resolution imaging. It can achieve a large field of view and high-spatial-resolution imaging with a low numerical aperture objective by capturing a series of low-resolution (LR) images that contain the information of different spatial frequencies and then stitching them together in the Fourier domain. Furthermore, the phase information of the object can also be recovered simultaneously. In this Letter, we propose a method to realize adaptive high-dynamic-range (HDR) LR image acquisition with a red, green, and blue camera, which needs only single exposure for each light-emitting diode (LED) illumination. According to the imaging principle of a color camera, the filter of each color channel still allows additional light within a certain wavelength range to pass through, but with a much smaller transmittance. By illuminating the sample with monochromatic light and combining the raw data from three color channels together, an HDR image corresponding to each LED illumination is obtained. The feasibility and good performance of our method are demonstrated by the experimental results.

Single-shot sequential projection phase retrieval and 3D localization from chromatic aberration.

A phase retrieval method based on sequential projection and chromatic aberration is reported. Construction of this method includes a red, green and blue (RGB) LED, an objective and a color camera. Owing to the chromatic aberration characteristics of the objective, three color images obtained by the color camera correspond to three equivalent propagation planes. Equivalent relative distances among these planes can be obtained by defining and iteratively minimizing the convergence index. Then, sequential projection strategy is used for phase retrieval in each image plane. Based on the recovered phase information and angular spectrum propagation principle, digital refocusing and 3D localization can be achieved for each subregion of the sample. Finally, the feasibility of our method is demonstrated by simulations and experiments.

A Simply Equipped Fourier Ptychography Platform Based on an Industrial Camera and Telecentric Objective.

Fourier ptychography microscopy (FPM) is a recently emerged computational imaging method, which combines the advantages of synthetic aperture and phase retrieval to achieve super-resolution microscopic imaging. FPM can bypass the diffraction limit of the numerical aperture (NA) system and achieve complex images with wide field of view and high resolution (HR) on the basis of the existing microscopic platform, which has low resolution and wide field of view. Conventional FPM platforms are constructed based on basic microscopic platform and a scientific complementary metal-oxide-semiconductor (sCMOS) camera, which has ultrahigh dynamic range. However, sCMOS, or even the microscopic platform, is too expensive to afford for some researchers. Furthermore, the fixed microscopic platform limits the space for function expansion and system modification. In this work, we present a simply equipped FPM platform based on an industrial camera and telecentric objective, which is much cheaper than sCMOS camera and microscopic platform and has accurate optical calibration. A corresponding algorithm was embedded into a conventional FP framework to overcome the low dynamic range of industrial cameras. Simulation and experimental results showed the feasibility and good performance of the designed FPM platform and algorithms.