Photo-Embossed Surface Relief Structures with Improved Aspect Ratios and Their Applications in Liquid Crystal Devices

Photo-embossing has been developed as a convenient and economical method for creating complex surface relief structures in polymer films. The pursuit for large aspect ratios of the photo-embossed structures has never stopped. Here, we demonstrate a simple strategy to obtain improved aspect ratios by adding a quick solvent developing step into the photo-embossing process. A good solvent for the monomer is used to remove unreacted monomers from the unexposed region, resulting in deepened valleys of the surface reliefs. In a polymer film as thin as 2.5 µm, the height of the surface reliefs can be increased by a factor of three to around 1.0 µm. This strategy is also shown to be compatible with other methods used to improve the aspect ratios of the photo-embossed structures. Lastly, we employ these surface relief structures in the fabrication of liquid crystal (LC) devices and investigate their performances for visible light regulation.

Пучки Гельмгольца--Гаусса с квадратичной радиальной зависимостью

A new class of localized solutions of paraxial parabolic equation is introduced. Each solution is a product of some Gaussian-type localized axisymmetric function (different from the fundamental mode) and an amplitude factor. The latter can be expressed via an arbitrary solution of the Helmholtz equation on an auxiliary two-sheet complex surface. The class under consideration contains well known and novel solutions, including those describing optical vortices of various orders.

Remote sensing of methane plumes: instrument tradeoff analysis for detecting and quantifying local sources at global scale

Methane (CH4) is the second most important anthropogenic greenhouse gas with a significant impact on radiative forcing, tropospheric air quality, and stratospheric water vapor. Remote sensing observations enable the detection and quantification of local methane emissions across large geographical areas, which is a critical step for understanding local flux distributions and subsequently prioritizing mitigation strategies. Obtaining methane column concentration measurements with low noise and minimal surface interference has direct consequences for accurately determining the location and emission rates of methane sources. The quality of retrieved column enhancements depends on the choices of the instrument and retrieval parameters. Here, we studied the changes in precision error and bias as a result of different spectral resolutions, instrument optical performance, and detector exposure times by using a realistic instrument noise model. In addition, we formally analyzed the impact of spectrally complex surface albedo features on retrievals using the iterative maximum a posteriori differential optical absorption spectroscopy (IMAP-DOAS) algorithm. We built an end-to-end modeling framework that can simulate observed radiances from reflected solar irradiance through a simulated CH4 plume over several natural and artificial surfaces. Our analysis shows that complex surface features can alias into retrieved methane abundances, explaining the existence of retrieval biases in current airborne methane observations. The impact can be mitigated with higher spectral resolution and a larger polynomial degree to approximate surface albedo variations. Using a spectral resolution of 1.5 nm, an exposure time of 20 ms, and a polynomial degree of 25, a retrieval precision error below 0.007 mole m−2 or 1.0 % of total atmospheric CH4 column can be achieved for high albedo cases, while minimizing the bias due to surface interference such that the noise is uncorrelated among various surfaces. At coarser spectral resolutions, it becomes increasingly harder to separate complex surface albedo features from atmospheric absorption features. Our modeling framework provides the basis for assessing tradeoffs for future remote sensing instruments and algorithmic designs. For instance, we find that improving the spectral resolution beyond 0.2 nm would actually decrease the retrieval precision, as detector readout noise will play an increasing role. Our work contributes towards building an enhanced monitoring system that can measure CH4 concentration fields to determine methane sources accurately and efficiently at scale.

AUTOMATIC DESIGN FEATURES OF COMPLEX SHAPE DETAILS AND TECHNOLOGY OF THEIR MANUFACTURING

The creation of modern high-performance machines often involves design of details with complex surfacese and made with high precision. At the stage of design and preparation of production, project work is carried out using automation tools and modern information and computer technologies. The process of creating a project is accompanied by the preparation of appropriate documentation, sufficient to solve all possible questions, starting with the formation of a design task and disposal of the product at the end of its operation. According to statistics, most details in mechanical engineering are simple in shape, relatively technological in production, and their surfaces are most often described in the drawings by a set of lines and circles (radius of curvature). This approach is economically justified and will ensure the reliable operation of the product during operation. Significant difficulties arise when it is necessary to design parts with surfaces of complex geometric shape, when the geometric parameters are set by coordinate points. The accuracy of surface description depends on the number of such points and the accuracy of numerical data. Typical examples include turbine impellers, parts with aerodynamic surfaces that are used, for example, in the aerospace or rocket industries. The process of manufacturing such parts is accompanied by overcoming specific difficulties in describing complex surfaces at the stages of design and technological preparation, as well as directly in the manufacture of parts on technological equipment, intermediate and final control of geometric accuracy. An option for an effective solution of such problems is to record complex smooth surfaces, predefined by a set of coordinate points, splines. Modern design automation tools make it possible to use this mathematical method for modeling complex geometric objects and use it to calculate the trajectories of the forming tool on CNC machines. On the example of parts from production, which has a complex surface, using computer-aided design systems considered options for making design and technological design decisions for production preparation, equipment design, control the accuracy of shaping when machining on CNC machines.

Defining bounding surfaces within and between eolian and non-eolian deposits, Lower Jurassic Navajo Sandstone, Moab Area, Utah, U.S.A.: Implications for subdividing erg system strata

ABSTRACT A model-independent, sequence stratigraphic approach is used to define bounding surfaces in the Navajo Sandstone in order to identify an architectural hierarchy of genetically related sedimentary packages and the surfaces that bound them across multiple scales of both eolian and non-eolian components of an erg system. Seven bounding surfaces and eight depositional units are defined, from small to large scale. A lamina-deviation surface bounds wedge- and tabular-shaped sets of laminae and/or laminasets, separating those that have different angle orientations on the dune slipface. A bed-deviation surface bounds a succession of beds (crossbeds) that lie at different angles or orientations to bedding above, below, or adjacent to it. A bedset-deviation surface is curved, inclined, and/or wavy and irregular that bounds bedsets and their internal stratification patterns; that is, bed-deviation surfaces, and lamina-deviation surfaces. A simple surface is gently inclined with or without small, concave or convex segments that bound beds and bedsets. A composite surface is horizontal with or without concave, curved, or irregular portions of that surface. A complex surface is laterally extensive (∼ 1–10+ km) that regionally bounds and truncates underlying conterminous and interfingered eolian and non-eolian strata. An amalgamated surface is a regionally extensive (∼ 10 to 100s km) mappable unconformity, merged unconformities, and their laterally equivalent conformable surface that can exhibit local to regional pedogenic modification, lags, and significant (meters to 10s m) paleotopographic relief. The genetically related sedimentary packages typically bounded by like or higher-rank surfaces are defined as laminae, laminasets, bed, bedsets, and simple, composite, complex, and amalgamated units. Field relationships of strata and surfaces are key to reconstructing the interactions between eolian and non-eolian deposits and the processes they represent at the local, regional, and basin scale. This classification scheme can be applied to erg-system strata to fully integrate changes in diverse facies within and between contiguous deposits.

Analysis of the stability of the computational algorithm to a change in the geometric parameters of cylindrical shell structures

This study deals with testing sustainability of a computational algorithm to a change in geometric parameters of cylindrical shell structures. A change in geometry implies the replacement of one type of a cylindrical shell (elliptic, hyperbolic, parabolic) with another so that the quantitative change (the difference in elevations) in the area under consideration is minimal. On the one hand, this test allows to assessing the correctness of the algorithm itself and is relevant for algorithms that use both numerical methods and symbolic calculations. On the other hand, it allows to evaluating the possibility of simplifying calculations by approximating a complex surface with a simpler one both in understanding the surface definition itself and in expressing its basic characteristics such as Lame coefficients and main curvatures. A mathematical model of deformations of shell structures based on the hypotheses of Timoshenko (Mindlin - Reisner) are used in the work. The model takes into account transverse shifts, geometric nonlinearity and orthotropy of the material, and its written in the form of a functional of the total potential strain energy. The calculation algorithm is built on the basis of the Ritz method to reduce the variational problem of the minimum functional to the solution of a system of nonlinear algebraic equations, and on the method of continuing the solution with the best parameter for its solution. All calculations were carried out in dimensionless parameters. Three types of cylindrical panels are calculated, and critical loads of buckling and deflection fields at subcritical and supercritical moments are obtained. It is shown that for the considered class of problems the previously proposed mathematical model and computational algorithm are resistant to changes in the geometry of the structure.

Multimodal Data and Multiscale Kernel-Based Multistream CNN for Fine Classification of a Complex Surface-Mined Area

Fine land cover classification (FLCC) of complex landscapes is a popular and challenging task in the remote sensing community. In complex surface-mined areas (CSMAs), researchers have conducted FLCC using traditional machine learning methods and deep learning algorithms. However, convolutional neural network (CNN) algorithms that may be useful for FLCC of CSMAs have not been fully investigated. This study proposes a multimodal remote sensing data and multiscale kernel-based multistream CNN (3M-CNN) model. Experiments based on two ZiYuan-3 (ZY-3) satellite imageries of different times and seasons were conducted in Wuhan, China. The 3M-CNN model had three main features: (1) multimodal data-based multistream CNNs, i.e., using ZY-3 imagery-derived true color, false color, and digital elevation model data to form three CNNs; (2) multisize neighbors, i.e., using different neighbors of optical and topographic data as inputs; and (3) multiscale convolution flows revised from an inception module for optical and topographic data. Results showed that the proposed 3M-CNN model achieved excellent overall accuracies on two different images, and outperformed other comparative models. In particular, the 3M-CNN model yielded obvious better visual performances. In general, the proposed process was beneficial for the FLCC of complex landscape areas.

Classification of Magnetic Tile Surface Defects Based on Efficientnet Network with Attention

The magnetic tile image has the characteristics of uneven illumination, complex surface texture, and low contrast. Aiming at the problem that the traditional defect detection algorithm is difficult to accurately identify the defects, and the deep learning algorithm is difficult to balance the classification accuracy and the size of the speed model, a defect classification algorithm based on attention-based EfficientNet is proposed. The algorithm first enhances the network’s spatial and location information for image features by integrating the Convolutional Block Attention Module, and improves the network’s ability to identify defects. Then, on this basis, Criss-Cross Attention is added to the network, so that the network can better the context information of the horizontal and vertical cross of image features, so that each pixel can finally capture the full image dependency of all pixels. Experimental results show that the algorithm has higher classification accuracy than EfficientNet-B0, reached 99.11%, and has a better balance between accuracy, speed and model size than other classification models.