Additive manufacturing (AM), also known as 3D printing, has been attracted extensive attention and developed rapidly in aerospace, optoelectronic engineering, microelectronics, and other fields due to its unique characteristic of "shape and performance control". Developing 3D printing materials is critical for the practical applications in various fields. Therefore, this article reviews the current high-performance polymeric materials for 3D printing and the advanced intelligent manufacturing technologies. It focuses on the 3D printing technologies of polymers, the high-performance polymeric materials for 3D printing, and the related applications, which can provide new directions and ideas for its research, development and application.

In this paper, based on TDLAS technology, an all-fiber NH3 concentration detection system was built by using the designed microfiber gas absorption cell. The core part of the NH3 detection system was sensed by a 1.51-m microfiber. The test results of the system indicate that there is a good linear relationship between the second harmonic amplitude and the corresponding concentration for NH3 in the concentration range of 20000 ppm-100000 ppm (correlation coefficient of fitting formula R=0.9962). To improve the detection performance of NH3 concentration, the gold-nanosphere (GNS) coated microfiber is used to enhance the evanescent field effect. According to the experimental results, the sensitivity of the microfiber coated GNSs NH3 concentration detection system has been greatly improved and the lower detection limit of NH3 concentration can reach 260 ppm. Repeated monitoring of different concentrations of NH3 shows that the detection system is stable with a maximum relative error of 5.38%, which makes it suitable for long-term stable NH3 monitoring and has wide application prospects.

Although the current laser active detection system used to find "cat-eye" target has large transmitting power and long detection distance, it generally has the disadvantages of high quality and poor flexibility. In order to enhance flexibility, reduce operational response time and ensure that the target can be destroyed as soon as it is found, a low-power active "cat-eye" detection system can be integrated in the intelligent sight to complement the existing system. Because the intelligent sight is integrated with a small laser rangefinder and CMOS image sensor, according to its hardware characteristics, this paper designs an anti-interference "cat-eye" target detection method, which uses low-power laser to emit pseudo-random coded laser pulse sequence, CMOS sensor to synchronously collect data, and extract target information through correlation operation, and carries out theoretical analysis and experimental verification. The experimental results show that the method has strong stability and anti-interference ability, and can make the intelligent sight find "cat-eye" target in complex background.

An electro-optic intensity chaotic communication system is designed by combining two electro-optic delay feedback loops with parallel structures. By injecting chaos into chaos, a more complex chaotic waveform is generated to enhance the chaotic complexity and the communication system confidentiality. In this design, MATLAB and OptiSystem software are used to simulate the system, which solves the problem that OptiSystem software can't simulate the optical feedback loop. The mature laser and binary sequence generation modules in OptiSystem software provide energy and input signals for the system. The electro-optic delay feedback loops are realized by the MATLAB program, and the signal transmission in optical fibers is completed in the OptiSystem software. The article introduces how to use MATLAB and OptiSystem software to realize the co-simulation of chaotic systems. Numerical simulations show that the proposed method is feasible to simulate the optical feedback loop, and the simulation results are in good agreement with the theoretical values, which prove that the chaotic signal is generated.

As an essential resolution enhancement technique, source optimization can improve the quality of advanced lithography. In the field of advanced lithography, the convergence efficiency and optimization ability of the source optimization are very important. Particle swarm optimization (PSO) is a global optimization algorithm. The adaptive control strategy can improve the global search ability of particles, and the nonlinear control strategy can expand the search range of particles. In this paper, a PSO algorithm based on adaptive nonlinear control strategy (ANCS) is proposed to solve the problem of source optimization by transforming it into a multivariable evaluation function. The image optimization simulation is carried out with a brief periodic grating image and an irregular image, and the source shape is optimized by the global iteration property of the proposed method. By using the pattern errors (PEs) as a multivariate merit function, the results of 300 iterations are evaluated, and the PEs of the two kinds of simulation patterns are reduced by 52.2% and 35%, respectively. Compared with the traditional PSO algorithm and genetic algorithm, the proposed method not only improves the imaging quality, but also has higher convergence efficiency.

A tunable nanosecond pulse fiber laser is demonstrated in the paper. The laser adopts the passive mode locking mechanism of the nonlinear amplifying loop mirror and a manually adjustable filter and fiber grating are added to achieve single-wavelength spectral output. The passive mode locked erbium-doped fiber laser with 430 m cavity length generates the nanosecond rectangle pulse at 465 kHz repetition rate. The tunable passive mode locked fiber laser incorporates a broad bandwidth mode locking device and a tunable filter in the cavity. The broad bandwidth mode locker is the key device for the tunable pulse output, which is based on a reflective nonlinear amplifying loop mirror. The result shows that the pulse duration and the single-pulse energy are 10.58 ns and 70.28 nJ respectively when the laser works at 1560 nm and has 400 mW pump power. The tunable range is from 1523.4 nm to 1575 nm.

Spectral computed tomography (CT) based on photon-counting detectors, has great potential in material decomposition, tissue characterization, lesion detection, and other applications. During the reconstruction, the increase of the number of channels will reduce the photon number in a single channel, resulting in the decline of the quality of the reconstructed image, which is difficult to meet the actual needs. To improve the quality of image reconstruction, joint multi-channel total generalized variational based on the unclear norm for spectral CT reconstruction was proposed in this paper. The algorithm will extend total generalized variation to the vector, and the sparsity of singular values is used to promote the linear dependence of the image gradient. The structural information of the multi-channel image is shared during the image reconstruction process while unique differences are preserved. Experimental results show that the proposed algorithm can effectively recover image details and marginal information while suppressing noise.