Gongxin Li

Single-pixel camera with one graphene photodetector.

Consumer cameras in the megapixel range are ubiquitous, but the improvement of them is hindered by the poor performance and high cost of traditional photodetectors. Graphene, a two-dimensional micro-/nano-material, recently has exhibited exceptional properties as a sensing element in a photodetector over traditional materials. However, it is difficult to fabricate a large-scale array of graphene photodetectors to replace the traditional photodetector array. To take full advantage of the unique characteristics of the graphene photodetector, in this study we integrated a graphene photodetector in a single-pixel camera based on compressive sensing. To begin with, we introduced a method called laser scribing for fabrication the graphene. It produces the graphene components in arbitrary patterns more quickly without photoresist contamination as do traditional methods. Next, we proposed a system for calibrating the optoelectrical properties of micro/nano photodetectors based on a digital micromirror device (DMD), which changes the light intensity by controlling the number of individual micromirrors positioned at + 12°. The calibration sensitivity is driven by the sum of all micromirrors of the DMD and can be as high as 10(-5)A/W. Finally, the single-pixel camera integrated with one graphene photodetector was used to recover a static image to demonstrate the feasibility of the single-pixel imaging system with the graphene photodetector. A high-resolution image can be recovered with the camera at a sampling rate much less than Nyquist rate. The study was the first demonstration for ever record of a macroscopic camera with a graphene photodetector. The camera has the potential for high-speed and high-resolution imaging at much less cost than traditional megapixel cameras.

High‐Throughput Fabrication and Modular Assembly of 3D Heterogeneous Microscale Tissues

3D hydrogel microstructures that encapsulate cells have been used in broad applications in microscale tissue engineering, personalized drug screening, and regenerative medicine. Recent technological advances in microstructure assembly, such as bioprinting, magnetic assembly, microfluidics, and acoustics, have enabled the construction of designed 3D tissue structures with spatially organized cells in vitro. However, a bottleneck exists that still hampers the application of microtissue structures, due to a lack of techniques that combined high-throughput fabrication and flexible assembly. Here, a versatile method for fabricating customized microstructures and reorganizing building blocks composed of functional components into a combined single geometric shape is demonstrated. The arbitrary microstructures are dynamically synthesized in a microfluidic device and then transferred to an optically induced electrokinetics chip for manipulation and assembly. Moreover, building blocks containing different cells can be arranged into a desired geometry with specific shape and size, which can be used for microscale tissue engineering.

Nano-Manipulation Based on Real-Time Compressive Tracking

Quick tracking in nano-manipulation has been attracting increasing attention among scientific researchers and engineers because it can significantly enhance the effectiveness and efficiency of nano-manipulation. The main reasons that hinder the improvement of accuracy and efficiency of nano-manipulation are the lack of effective real-time tracking and unavoidable perturbations by uncertainties and nonlinearities in the manipulation system. In this paper, we present a new strategy based on compressive sensing to realize quick real-time tracking nano-manipulation trajectory, and build a new kinematic model for objects to be manipulated to overcome the effect of tip positioning and contacting biases on nano-manipulation with AFM. With this approach, the deviation of the object from the predesigned trajectory during the manipulation can be corrected with up to two-thirds of time less than the traditional method, and the object can be smoothly moved to any destination in the nano-space. The approach requires no priori knowledge about the system, environment, and objects being manipulated. It is validated that this strategy works for both hard regular objects and soft irregular samples by experiments.

Efficient Imaging and Real-Time Display of Scanning Ion Conductance Microscopy Based on Block Compressive Sensing

Scanning Ion Conductance Microscopy (SICM) is one kind of Scanning Probe Microscopies (SPMs), and it can be used in mapping topographical features of sample at high - resolution with free contact by measuring the ion current of ultra-micropipette. SICM is widely used in imaging soft samples for many distinct merits, such as high resolution imaging, simple preparation of probe and no harm to sample surface. However, it is undeniable that the scanning speed of SICM is much slower than other SPMs, especially for large scale and high resolution imaging. Fortunately, compressive sensing (CS), which breaks through the Shannons sampling theorem for dramatically reducing sample rate, could improve scanning speed tremendously, but it still costs much time in image reconstruction. Therefore block compressive sensing was applied to SICM imaging for reducing the reconstruction time of sparse signals, and it has an anther further and unique application that it can achieve the function of image real-time display. In this paper, a new method of dividing blocks and a new matrix arithmetic operation was proposed to build the block compressive sensing model, and several experiments was taken to verified the superiority of block compressive sensing in reducing imaging time and image real-time display used SICM.

2D Normalized Iterative Hard Thresholding Algorithm for Fast Compressive Radar Imaging

Compressive radar imaging has attracted considerable attention because it substantially reduces imaging time through directly compressive sampling. However, a problem that must be addressed for compressive radar imaging systems is the high computational complexity of reconstruction of sparse signals. In this paper, a novel algorithm, called two-dimensional (2D) normalized iterative hard thresholding (NIHT) or 2D-NIHT algorithm, is proposed to directly reconstruct radar images in the matrix domain. The reconstruction performance of 2D-NIHT algorithm was validated by an experiment on recovering a synthetic 2D sparse signal, and the superiority of the 2D-NIHT algorithm to the NIHT algorithm was demonstrated by a comprehensive comparison of its reconstruction performance. Moreover, to be used in compressive radar imaging systems, a 2D sampling model was also proposed to compress the range and azimuth data simultaneously. The practical application of the 2D-NIHT algorithm in radar systems was validated by recovering two radar scenes with noise at different signal-to-noise ratios, and the results showed that the 2D-NIHT algorithm could reconstruct radar scenes with a high probability of exact recovery in the matrix domain. In addition, the reconstruction performance of the 2D-NIHT algorithm was compared with four existing efficient reconstruction algorithms using the two radar scenes, and the results illustrated that, compared to the other algorithms, the 2D-NIHT algorithm could dramatically reduce the computational complexity in signal reconstruction and successfully reconstruct 2D sparse images with a high probability of exact recovery.

Polystyrene nanoparticles enhance photo responsivity of graphene photodetector

Graphene has attracted much attention as a candidate for plane material in optoelectronics and optoelectronic devices for its exceptional physical properties. However, its low photo responsivity has limited its development and applications in photodetectors. In this paper, we propose a new method to enhance the photo responsivity of a graphene photodetector by integrating Polystyrene Nanoparticles (PSNs) into the graphene photodetector, dropping them onto the graphene surface using a glass micropipette. The results show that the photocurrent of the graphene photodetector is linearly enhanced with increasing PSNs concentration, and achieves a maximum enhancement by up to 71% with 500 nm PSNs under the incident light of 470 nm. The enhancement of the photo responsivity varies as the light wavelength changes with PSNs of the same diameter and it is demonstrated by simulation that the photo responsivity is maximally enhanced when the wavelength of the incident light is equal to the diameter of the PSNs. Our approach not only promotes the development of graphene in optoelectronics, but also has the potential for multicolor photodetection.

Development of a novel optogenetic indicator based on cellular deformations for mapping optogenetic activities

Optogenetic techniques have changed the landscape of neuroscience by offering high temporal and spatial mapping of the activities of genetically defined population of cells with optical controlling tools. The mapping of optogenetic activities demands optogenetic indicators whose optical properties change in response to cellular activities, but the existing optogenetic indicators only specifically characterize limited optogenetic activities. Here, we propose a novel optogenetic indicator based on cellular deformation to characterize the activities of optogenetically engineered cells. The cellular activities triggered by light stimulation lead to changes in the cell membrane structure and result in cellular deformation, which is measured by atomic force microscopy. The deformation recordings of the cells expressing channelrhodopsin-2 (ChR2) and the corresponding control experiments together confirm that the deformation is generated generally when the cells are exposed to light, which is also validated indirectly via the change in the Youngs modulus of the cells before and after absorption of photons. The activities of cells expressing different subtypes of opsins were also recorded using the optogenetic indicator of cellular deformation. This study provides a novel and general optogenetic indicator based on cellular deformation for monitoring the activities of optogenetically engineered cells. Moreover, this new optogenetic indicator offers ever-better tools for the applications of optogenetic activity mapping and neural and brain imaging.

Efficient imaging and real-time display of Scanning Ion Conductance Microscopy based on block compressive sensing

Scanning Ion Conductance Microscopy (SICM) is one kind of Scanning Probe Microscopies (SPMs), and it can be used in mapping topographical features of sample at high - resolution with free contact by measuring the ion current of ultra-micropipette. SICM is widely used in imaging soft samples for many distinct merits, such as high resolution imaging, simple preparation of probe and no harm to sample surface. However, it is undeniable that the scanning speed of SICM is much slower than other SPMs, especially for large scale and high resolution imaging. Fortunately, compressive sensing (CS), which breaks through the Shannons sampling theorem for dramatically reducing sample rate, could improve scanning speed tremendously, but it still costs much time in image reconstruction. Therefore block compressive sensing was applied to SICM imaging for reducing the reconstruction time of sparse signals, and it has an anther further and unique application that it can achieve the function of image real-time display. In this paper, a new method of dividing blocks and a new matrix arithmetic operation was proposed to build the block compressive sensing model, and several experiments was taken to verified the superiority of block compressive sensing in reducing imaging time and image real-time display used SICM.