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Interactions between liquid crystal molecules and target analytes open up various biosensing applications for quick screening and point-of-care applications. In this review, we categorized biosensors by type, depending on the liquid crystal mesophase, and considered several applications for the detection of biomolecules, point-of-care diagnostics and environmental monitoring. We also discuss interactions between polarized light and target pathogens dispersed in biological fluids, which result in the change of the polarization state. An array of the Stokes parameters can be compared with the pattern, and a proper pathogen can be manifested. We suggest that a combination of a micropolarizer array and a complementary metal oxide semiconductor sensor is an optimal setup for the detection of pathogens. Herein, we discuss the working principles of liquid crystal biosensors and their fabrication principles. In addition, relevant theoretical and practical issues related to liquid crystal biosensors are outlined. In general, this review gives an in-depth survey of the research on liquid crystal-based sensors, making it easier for researchers to locate their niche and make contributions to this subject from multiple viewpoints.

A comprehensive theory of light-reflective characteristics and experimental technique of liquid crystal layer thickness control for flexible optically rewritable electronic paper is presented. Cylindrical pillars were used to control the gap between flexible substrates. The introduced prototype of optically rewritable electronic paper has shown very promising performance. In this regard, we report theoretical results of structural photosensitive alignment of nematic liquid crystals on flexible substrate. The focus of theoretical study is on understanding the self-assembled complex structure, governed by the interplay between surface anchoring and liquid crystal elasticity. Mueller matrix spectroscopic ellipsometry was used to study light-reflecting characteristics and polarization properties of the twisted nematic film.

Magnetic resonance imaging (MRI) plays an important role in disease diagnosis. The noise that appears in MRI images is commonly governed by a Rician distribution. The bendlets system is a second-order shearlet transform with bent elements. Thus, the bendlets system is a powerful tool with which to represent images with curve contours, such as the brain MRI images, sparsely. By means of the characteristic of bendlets, an adaptive denoising method for microsection images with Rician noise is proposed. In this method, the curve contour and texture can be identified as low-frequency components, which is not the case with other methods, such as the wavelet, shearlet, and so on. It is well known that the Rician noise belongs to a high-frequency channel, so it can be easily removed without blurring the clarity of the contour. Compared with other algorithms, such as the shearlet transform, block matching 3D, bilateral filtering, and Wiener filtering, the values of Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) obtained by the proposed method are better than those of other methods.

Named entity recognition is a critical task in the electronic medical record management system for rehabilitation robots. Handwritten documents often contain spelling errors and illegible handwriting, and healthcare professionals frequently use different terminologies. These issues adversely affect the robot’s judgment and precise operations. Additionally, the same entity can have different meanings in various contexts, leading to category inconsistencies, which further increase the system’s complexity. To address these challenges, a novel medical entity recognition algorithm for Chinese electronic medical records is developed to enhance the processing and understanding capabilities of rehabilitation robots for patient data. This algorithm is based on a fusion classification strategy. Specifically, a preprocessing strategy is proposed according to clinical medical knowledge, which includes redefining entities, removing outliers, and eliminating invalid characters. Subsequently, a medical entity recognition model is developed to identify Chinese electronic medical records, thereby enhancing the data analysis capabilities of rehabilitation robots. To extract semantic information, the ALBERT network is utilized, and BILSTM and MHA networks are combined to capture the dependency relationships between words, overcoming the problem of different meanings for the same entity in different contexts. The CRF network is employed to determine the boundaries of different entities. The research results indicate that the proposed model significantly enhances the recognition accuracy of electronic medical texts by rehabilitation robots, particularly in accurately identifying entities and handling terminology diversity and contextual differences. This model effectively addresses the key challenges faced by rehabilitation robots in processing Chinese electronic medical texts, and holds important theoretical and practical value.

Each charging/discharging cycle leads to a gradual decrease in the battery’s capacity. The degradation of capacity in lithium-ion batteries represents a non-monotonous process with random jumps. Earlier studies claimed that the instantaneous degradation value of a lithium-ion battery is influenced by the historical dataset with long-range dependence. The existing methods ignore large jumps and long-range dependences in degradation processes. In order to capture long-range-dependent behavior with random jumps, we refer to the fractional Poisson process. We also outline the relationship between the long-range correlation and the Hurst index. The connection between random jumps in capacitance and long-range dependence of the fractional Poisson process is proven. In order to construct the fractional Poisson predictive model, we included fractional Brownian motion as the diffusion term and the fractional Poisson process as the jump term. The proposed approach is implemented on NASA’s dataset for Li-ion battery degradation. We believe that the error analysis for the fractional Poisson process is advantageous compared with that of the fractional Brownian motion, the fractional Levy stable motion, the Wiener model, and the long short-term memory model.

With the advancement of information display technologies, research on liquid crystals is undergoing a tremendous shift to photonic devices. For example, devices and configurations based on liquid crystal materials are being developed for various applications, such as spectroscopy, imaging, and fiber optics. One of the problems behind the development of photonic devices lies in the preparation of patterned surfaces that can provide high resolution. Among all liquid crystal alignment techniques, photoalignment represents a promising non-contact method for the fabrication of patterned surfaces. In this review, we discuss the original research findings on electro-optic effects, which were mainly achieved at the Department of Electronic and Computer Engineering of the Hong Kong University of Science and Technology and the collaborating research laboratories.

Photoalignment of liquid crystals by using azo dye molecules is a commonly proposed alternative to traditional rubbing alignment methods. Photoalignment mechanism can be well described in terms of rotational diffusion of azo dye molecules exposed by ultraviolet polarized light. A specific feature of the irradiated light is the intensity dependent change of azimuthal anchoring of liquid crystals. While there are various mechanisms of azo dye photoalignment, photo-reorientation occurs when dye molecules orient themselves perpendicular to the polarization of incident light. In this review, we describe both recent achievements in applications of photoaligned liquid crystal cells and its simulation. A variety of display and photonic devices with azo dye aligned nematic and ferroelectric liquid crystals are presented: q-plates, optically rewritable flexible e-paper (monochromatic and color), and Dammann gratings. Some theoretical aspects of the alignment process and display simulation are also considered.

Properties of surface anchoring depend on the absorbed exposure energy and various potential interactions associated with liquid crystal and azo dye layers. In this study, we investigate a model of dispersion, steric and photoinduced interactions with the goal of providing a qualitative and quantitative description of orientationally ordered hard uniaxial liquid crystals and azo dye molecules. By using the Onsager theory, we estimated the effect of excluded volume. Typical repulsive potentials between liquid crystal and azo dye molecules are displayed graphically. The presence of statistical dispersion in molecular alignment of liquid crystals leads to potential wells in dipole–dipole interactions. Our mean field theory investigation of dipole–dipole interactions shows that the anchoring free energy is governed by the net interaction energy associated with the averaged dipole moments of liquid crystal and azo dye molecules, photoaligned surface dipole moments, and local charge densities. We also use the Fokker–Planck equation to show that rotational diffusion is described by the effective mean field potential, which includes photoinduced and van der Waals interactions. Our findings underscore the potential of mean field theory for intermolecular couplings in photoaligned surfaces, opening up new pathways of molecular design for a broad range of parameters.

Photoalignment by azo dye nanolayers can provide high alignment quality for large-area liquid crystal devices. Application of this technology to active optical elements for signal processing and communications is a hot topic of photonics research. In this article, we review recent demonstrations and performance of liquid crystal photonic devices, discuss the advantages of the proposed technology, and identify challenges and future prospects in the research field of photoaligned multi-domain liquid crystal structures. We believe that the developments discussed here can provide directions for future research and potential opportunities for applications of liquid crystal devices based on multi-domain photoalignment.

Mechanical response of the carbon nanotube bundle to uniaxial and biaxial lateral compression followed by unloading is modeled under plane strain conditions. The chain model with a reduced number of degrees of freedom is employed with high efficiency. During loading, two critical values of strain are detected. Firstly, period doubling is observed as a result of the second order phase transition, and at higher compressive strain, the first order phase transition takes place when carbon nanotubes start to collapse. The loading-unloading stress-strain curves exhibit a hysteresis loop and, upon unloading, the structure returns to its initial form with no residual strain. This behavior of the nanotube bundle can be employed for the design of an elastic damper.