[Research and Application of Narrowband Polarizing Beam Splitter in the Optical Fiber Communication].

In fiber-optic communications, in order to achieve more data channels in the wavelength division multiplexing (WDM) system without changing the modulation wavelength range, a new type of small-sized narrowband polarizing beam splitter was designed. It can be used for data communication network expansion and improve the Signal to Noise Ratio (SNR) of the optical signal. Two kinds new film system designed were deposited on the polarizing beam splitter. One layer is narrowband filter film, while the other layer is polarizing beam splitter film. TFCalc software was used for simulation analysis, and the results shown that the bandwidth of the narrowband filter film was about 0.4 nm, and the permeability of p light from the polarizing beam splitter film was better than 99.8% in the range of 1 530～1 560 nm. Based on the above film system design, two groups film system was made on BK7 optical glass. In the experiment, light through film was spectral analysis with Agilent 8164-A type optical measuring instrument. Experimental results show that the actual bandwidth of the narrowband filter film is better than 0.4 nm, gain flatness is not less than -0.05 dB. It has a narrower bandwidth compared to the existing common 0.8 nm filter film, and it can be realized to increase the amount of data channels in the wavelength division multiplexing system with the same modulation wavelength range. Actual transmittance of p light was 99.6% through polarizing filter film, and it's slightly lower than the simulated values, but it remains better than the design requirements. Compared to conventional polarizing beam splitter, its optical signal was stronger, and it has a higher SNR. In summary, the polarizing beam splitter has better application value and practical significance.

Hierarchies in Visual Pathway: Functions and Inspired Artificial Vision.

The development of artificial intelligence has posed a challenge to machine vision based on conventional complementary metal-oxide semiconductor (CMOS) circuits owing to its high latency and inefficient power consumption originating from the data shuffling between memory and computation units. Gaining more insights into the function of every part of the visual pathway for visual perception can bring the capabilities of machine vision in terms of robustness and generality. Hardware acceleration of more energy-efficient and biorealistic artificial vision highly necessitates neuromorphic devices and circuits that are able to mimic the function of each part of the visual pathway. In this paper, we review the structure and function of the entire class of visual neurons from the retina to the primate visual cortex within reach (Chapter 2) are reviewed. Based on the extraction of biological principles, the recent hardware-implemented visual neurons located in different parts of the visual pathway are discussed in detail in Chapters 3 and 4. Furthermore, valuable applications of inspired artificial vision in different scenarios (Chapter 5) are provided. The functional description of the visual pathway and its inspired neuromorphic devices/circuits are expected to provide valuable insights for the design of next-generation artificial visual perception systems.

Ni Single-Atoms Based Memristors with Ultrafast Speed and Ultralong Data Retention.

Memristor with low-power, high density, and scalability fulfills the requirements of the applications of the new computing system beyond Moore's law. However, there are still nonideal device characteristics observed in the memristor to be solved. The important observation is that retention and speed are correlated parameters of memristor with trade off against each other. The delicately modulating distribution and trapping level of defects in electron migration-based memristor is expected to provide a compromise method to address the contradictory issue of improving both switching speed and retention capability. Here, high-performance memristor based on the structure of ITO/Ni single-atoms (NiSAs/N-C)/Polyvinyl pyrrolidone (PVP)/Au is reported. By utilizing well-distributed trapping sites , small tunneling barriers/distance and high charging energy, the memristor with an ultrafast switching speed of 100 ns, ultralong retention capability of 106  s, a low set voltage (Vset ) of ≈0.7 V, a substantial ON/OFF ration of 103 , and low spatial variation in cycle-to-cycle (500 cycles) and device-to-device characteristics (128 devices) is demonstrated. On the premise of preserving the strengths of a fast switching speed, this memristor exhibits ultralong retention capability comparable to the commercialized flash memory. Finally, a memristor ratioed logic-based combinational memristor array to realize the one-bit full adder is further implemented.

Development of Bio-Voltage Operated Humidity-Sensory Neurons Comprising Self-Assembled Peptide Memristors.

Biomimetic humidity sensors offer a low-power approach for respiratory monitoring in early lung-disease diagnosis. However, balancing miniaturization and energy efficiency remains challenging. This study addresses this issue by introducing a bioinspired humidity-sensing neuron comprising a self-assembled peptide nanowire (NW) memristor with unique proton-coupled ion transport. The proposed neuron shows a low Ag+ activation energy owing to the NW and redox activity of the tyrosine (Tyr)-rich peptide in the system, facilitating ultralow electric-field-driven threshold switching and a high energy efficiency. Additionally, Ag+ migration in the system can be controlled by a proton source owing to the hydrophilic nature of the phenolic hydroxyl group in Tyr, enabling the humidity-based control of the conductance state of the memristor. Furthermore, a memristor-based neuromorphic perception neuron that can encode humidity signals into spikes is proposed. The spiking characteristics of this neuron can be modulated to emulate the strength-modulated spike-frequency characteristics of biological neurons. A three-layer spiking neural network with input neurons comprising these highly tunable humidity perception neurons shows an accuracy of 92.68% in lung-disease diagnosis. This study paves the way for developing bioinspired self-assembly strategies to construct neuromorphic perception systems, bridging the gap between artificial and biological sensing and processing paradigms.