Hasil untuk "Paints, pigments, varnishes, etc."

O. Chyhyrynets, O. Sanginova, Jinping Hu et al.

The object of the study is аnti-corrosion properties of walnut shell powder and aluminum phosphate mixtures. The existing problem is that the most effective chromate-containing pigments, which were traditionally used for the manufacture of paint and varnish coatings, are toxic. Given this fact, the research of scientists aims at finding alternative low-toxic compounds, which are phosphate pigments. Since they are inferior in efficiency, modern research is aimed either at the synthesis of new modifications and complex forms of pigments, or at the development of effective mixtures of pigments that would provide the necessary level of anti-corrosion protection of steel. Along with this, an urgent direction is to increase the level of environmental friendliness of paint and varnish coatings using annually renewable plant waste, which, due to the content of tannins, have proven themselves well for surface preparation before painting. The work investigated the effect of a mixture of non-toxic aluminum phosphate and finely ground walnut shell powder on the corrosion behavior of steel. An adequate mathematical model “composition – mass corrosion index” was proposed. The mathematical model allowed to establish the relationship between the composition and corrosion rate and find the optimal composition of the studied mixture. The calculations showed that at a ratio of aluminum phosphate and walnut shell powder of about 8:1, the mass corrosion rate of steel in the obtained extract is 0.020 g / (m2 · h). By experimentally verifying the optimal composition of the study, a mass corrosion index of 0.018 g / (m2 · h) was achieved, which confirms the theoretical calculations and ensures the practical applicability of the results obtained. The results of the study will be useful for specialists working in the field of developing water-based anti-corrosion paints and coatings, with an emphasis on studying the influence of pigments and fillers on the corrosion behavior of steel.

نرگس یوسفی لیمائی, یکتا رضایی

با توجه به اینکه یکی از معضلات عصر حاضر، آلودگی محیط‌زیست در حوزه آب و پساب می‌باشد، راهکارهای متعددی برای تصفیه آنها ارائه شده است. به‌علاوه، از جمله موضوعات مهم دیگر، که بسیار پراهمیت است شناسایی آلاینده‌های زیست محیطی و تعیین میزان آن به منظور انجام اقدام بعدی می‌باشد. بنابراین، نظارت بر میزان آلاینده‌های موجود در آب و پساب، از راهکارهای کنترلی جهت شناسایی و حذف آنها است. فلزات سنگین یکی از این آلاینده‌ها می‌باشند که حضور آنها در آب و پساب، مخاطرات بسیاری را برای زندگی موجودات زنده ایجاد می‌کند. از جمله حسگرهایی که قابلیت تهیه و کاربرد آسان برای شناسایی آلاینده‌های فلزی دارند، حسگرهای نوری می‌باشند که این حسگرها قابلیت شناسایی آلاینده‌ها به صورت رنگ سنجی و فلوئورسانس را دارا هستند. در دهه‌های اخیر، با توجه به ویژگی‌های نوری ویژه کربن کوانتوم دات‌ها، تهیه و کاربرد آنها به عنوان حسگر برای شناسایی فلزات بسیار بررسی شده است. کربن کوانتوم دات‌ها با خواصی همچون پایداری، حلالیت بالا در آب، سازگاری با محیط‌زیست، سمیت کم، ارزان و در دسترس بودن، گزینه‌ای مناسب جهت تهیه حسگرهای نوری می‌باشند. لذا، در این مقاله به مبانی تهیه حسگرهای نوری بر پایه کربن کوانتوم دات پرداخته خواهد شد. بدین منظور، روش‌های سنتز کربن کوانتوم دات از جمله روشهای پایین به بالا و بالا به پایین، ذکر می‌شود. در ادامه، منشا تهیه کربن کوانتوم دات‌ها و سازوکار‌های شناسایی یون‌های فلزی توسط آنها بیان خواهد شد.

Srijit Seal, Maria-Anna Trapotsi, Ola Spjuth et al.

High-content image-based assays have fueled significant discoveries in the life sciences in the past decade (2013-2023), including novel insights into disease etiology, mechanism of action, new therapeutics, and toxicology predictions. Here, we systematically review the substantial methodological advancements and applications of Cell Painting. Advancements include improvements in the Cell Painting protocol, assay adaptations for different types of perturbations and applications, and improved methodologies for feature extraction, quality control, and batch effect correction. Moreover, machine learning methods recently surpassed classical approaches in their ability to extract biologically useful information from Cell Painting images. Cell Painting data have been used alone or in combination with other -omics data to decipher the mechanism of action of a compound, its toxicity profile, and many other biological effects. Overall, key methodological advances have expanded the ability of Cell Painting to capture cellular responses to various perturbations. Future advances will likely lie in advancing computational and experimental techniques, developing new publicly available datasets, and integrating them with other high-content data types.

Lasantha Thakshila Wedage, Mehmet C. Vuran, Bernard Butler et al.

The proliferation of nano-technology has enabled novel applications in various fields, including the potential for miniaturized terahertz (THz)-enabled devices. The extra-large bandwidth available in the THz spectrum can facilitate high-speed communication, even for transmission through lossy media. Culminating these capabilities, this paper introduces a new paradigm: Internet of Paint (IoP), transforming the 40,000-year-old concept of paint with extensive connectivity and sensing capabilities. IoP will enable seamless, massively parallel, and high-capacity communication and sensing capabilities, enabling innovative applications. IoP is expected to offer communication and sensing using nano-devices embedded in paint. In this paper, challenges towards the realization of IoP are discussed. Simulations indicate that THz signals in this stratified medium can form lateral waves that propagate along the Air-Paint interface and that relatively high channel capacity can be achieved by optimizing the transceiver locations, the paint thickness, and color. Addressing the challenges regarding nano-devices, nano-transceivers, materials, antennas, and power for IoP holds the potential to transform communication technologies and their seamless integration with living spaces.

Yizhe Tang, Yue Wang, Teng Hu et al.

Stroke-based Rendering (SBR) aims to decompose an input image into a sequence of parameterized strokes, which can be rendered into a painting that resembles the input image. Recently, Neural Painting methods that utilize deep learning and reinforcement learning models to predict the stroke sequences have been developed, but suffer from longer inference time or unstable training. To address these issues, we propose AttentionPainter, an efficient and adaptive model for single-step neural painting. First, we propose a novel scalable stroke predictor, which predicts a large number of stroke parameters within a single forward process, instead of the iterative prediction of previous Reinforcement Learning or auto-regressive methods, which makes AttentionPainter faster than previous neural painting methods. To further increase the training efficiency, we propose a Fast Stroke Stacking algorithm, which brings 13 times acceleration for training. Moreover, we propose Stroke-density Loss, which encourages the model to use small strokes for detailed information, to help improve the reconstruction quality. Finally, we propose a new stroke diffusion model for both conditional and unconditional stroke-based generation, which denoises in the stroke parameter space and facilitates stroke-based inpainting and editing applications helpful for human artists design. Extensive experiments show that AttentionPainter outperforms the state-of-the-art neural painting methods.

Geetanjali Sharma, Abhishek Tandon, Gaurav Jaswal et al.

Iris recognition technology plays a critical role in biometric identification systems, but their performance can be affected by variations in iris pigmentation. In this work, we investigate the impact of iris pigmentation on the efficacy of biometric recognition systems, focusing on a comparative analysis of blue and dark irises. Data sets were collected using multiple devices, including P1, P2, and P3 smartphones [4], to assess the robustness of the systems in different capture environments [19]. Both traditional machine learning techniques and deep learning models were used, namely Open-Iris, ViT-b, and ResNet50, to evaluate performance metrics such as Equal Error Rate (EER) and True Match Rate (TMR). Our results indicate that iris recognition systems generally exhibit higher accuracy for blue irises compared to dark irises. Furthermore, we examined the generalization capabilities of these systems across different iris colors and devices, finding that while training on diverse datasets enhances recognition performance, the degree of improvement is contingent on the specific model and device used. Our analysis also identifies inherent biases in recognition performance related to iris color and cross-device variability. These findings underscore the need for more inclusive dataset collection and model refinement to reduce bias and promote equitable biometric recognition across varying iris pigmentation and device configurations.

Lasantha Thakshila Wedage, Bernard Butler, Mehmet Can Vuran et al.

This study presents a simulated transceiver with a microstrip patch antenna (MPA) designed to resonate at 150 GHz and embedded in paint. The in-paint MPA (IP-MPA) is designed for the Internet of Paint (IoP) paradigm, which envisions seamless device communication through a paint layer on walls. This study introduces a comprehensive channel model for transceivers in paint at arbitrary depths and IP-MPA orientations. The best antenna orientations are analyzed for IoP channel performance. Extensive simulations indicate that the lateral waves, which propagate along the air-paint interface, exhibit the lowest loss, making this path the most reliable for communication between transceivers in paint. Further, the maximum received power for each propagation path, with the exception of the direct path, depends on depth. The findings suggest that the proposed network of IP-MPA-enabled transceivers for IoP has the potential to transform conventional walls into an integrated high-speed wireless communication and sensing infrastructure.

Nikulina M.V., Ryazanova A.YU., Strokova V.V. et al.

The modern market of paint and varnish materials is represented by a wide range of construction products, including those designed to protect facades of buildings and structures from atmospheric impact. Among the variety of varnishes and paints for processing and rendering decorative and protective properties to building materials, as well as from the viewpoint of environmental friendliness, the most popular products are water-dispersion paints based on acrylic dispersions. However, along with the high values of colour fastness, UV resistance and gas permeability, acrylic-based paints are insufficiently elastic and lack resistance to water. In this regard, the paper considers a method for increasing the mechanical and hydrophobic properties of acrylic paint and varnish material by introducing a hydrophobic polyethylhydrosiloxane-based emulsion containing polyethylhydrosiloxane (PEHS) - 35.20, glutaric aldehyde - 0.19, polyvinyl alcohol (PVA) - 7.75, water - 56.86 wt%, as well as by increasing the surface development (relief), achieved by increasing the volumetric concentration of pigments (VCP). The optimal range of the amounts of a hydrophobic emulsion and a coalescent into the composition of water-dispersion paints based on acrylic dispersion has been determined. To assess the stability of the coating after drying an aqueous dispersion paint modified with the aqueous polyethylhydrosiloxane emulsion, the wetting angle and free energy of the surface were evaluated using two liquids of different polarities, namely distilled water and diiodomethane. The possibility of modifying the aqueous dispersion paint, characterised by VCP of 70-80 %, by the polyethylhydrosiloxane hydrophobic aqueous emulsion in the amount of 5-5.5 %, combined with ethylene glycol (4.5-5.5 %) has been established, which makes it possible to obtain a hydrophobic coating with a wetting angle of up to 100°. By comparing the wetting angle values of the coatings, it has been shown that in the absence of the hydrophobic additive, this parameter is lower by 12.5 % than the parameter of the modified sample.

Sinem Armay, Mesut Kaymaz, Cangül Gümüş et al.

Glow in the dark (also called as photoluminescent) paints have the ability to absorb light from natural and artificial light sources and glow in dark medium. They can be easily charged since they have the ability to use ambient light (sun light, led lamps, fluorescent lamps etc.) as energy source. In case of emergency such as power outages occurred related to earthquakes and other natural disasters, the paint uses the energy absorbed and glows in the dark by emitting this energy in light form. Hence, it ensures safety by making emergency exits, stairs and information/safety signs visible for a while and prevent the accidents happen due to lack of lighting. Photoluminescent paints can also be applied onto light switches, baseboards, kitchen cupboard and decorative accessories. Besides, by the application of photoluminescent paint in tunnels and highways with intense vehicle traffic, the amount of energy used in both tunnel lighting and highways can be reduced by utilizing the light absorbed by the paint.Within the scope of this study, waterborne photoluminescent pigment paste formulation was created and the pastes were produced primarily. Afterward yellow-green colored pigment paste was selected (from a group of pigments that has different colors) to be used as colorant in waterborne road marking paint, bike lane paint, tennis court paint and hobby paint groups. The paint produced were applied onto test panels and luminance values and luminance time of the panels were measured.

Galina Gurina, Yevhen Druzhynin, N. Saienko et al.

In order to successfully reduce the emission of toxic organic solvents harmful to human health and the environment during the application and curing of paints and varnishes (VPM), ways to create environmentally friendly organically soluble VPM "SB" and water-dispersed VPM "WB" are proposed. The influence of the values of dry residues in solutions of organic oligomers and the density of the components of pigmented materials on the values of the content of volatile organic compounds (VOC) for different types of materials has been studied. Mathematical analysis of situations with the addition and reduction of the amount of solvents allowed to set the limit values of the amount of solvents in varnishes for "SB" materials with different densities and VOC = 300 g/l. The influence of volumetric concentration of pigments, dry residue of varnishes and density of pigments and fillers on the VOC content in materials has been studied. The ratios of VPM components have been optimized and formulations of environmentally friendly materials have been developed.

Gabriel Kerr, Sophia Palcic

We define the notion of a painted tropical $A$-complex and describe a poset structure on the set of all such complexes. This poset is equivalent to the face lattice of a secondary polytope $Σ(\bar{A}_α)$ where $\bar{A}_α$ is built from $A$ and an additional point $α$. As a central application, we show that multiplihedra are also secondary polytopes.

Sitong Deng, Ergun Akleman

In this work, we present a method for turning Chinese still-life paintings with global illumination effects into dynamic paintings with moving lights. Our goal is to preserve the original look and feel of still-life paintings with moving lights and objects. We have developed a deceptively simple method that can be computed as a composite of two animated texture images using an animated rendering. The compositing process can be implemented directly in an animation system such as AfterEffect, which allows for the basic compositing operation over animations. It is also possible to control the colors by changing the material colors in animated rendering. We have provided a proof-of-concept based on an original digital Still-Life painting that is in realist Chinese style. This approach can be used to turn almost any still-life painting into a dynamic painting.

Ergun Akleman, Cassie Mullins, Christopher Morrison et al.

In this work, we present the recursive camera-painting approach to obtain painterly smudging in real-time rendering applications. We have implemented recursive camera painting as both a GPU-based ray-tracing and in a Virtual Reality game environment. Using this approach, we can obtain dynamic 3D Paintings in real-time. In a camera painting, each pixel has a separate associated camera whose parameters are computed from a corresponding image of the same size. In recursive camera painting, we use the rendered images to compute new camera parameters. When we apply this process a few times, it creates painterly images that can be viewed as real-time 3D dynamic paintings. These visual results are not surprising since multi-view techniques help to obtain painterly effects.

Zhongqi Wang, Jie Zhang, Zhilong Ji et al.

With the development of deep generative models, recent years have seen great success of Chinese landscape painting generation. However, few works focus on controllable Chinese landscape painting generation due to the lack of data and limited modeling capabilities. In this work, we propose a controllable Chinese landscape painting generation method named CCLAP, which can generate painting with specific content and style based on Latent Diffusion Model. Specifically, it consists of two cascaded modules, i.e., content generator and style aggregator. The content generator module guarantees the content of generated paintings specific to the input text. While the style aggregator module is to generate paintings of a style corresponding to a reference image. Moreover, a new dataset of Chinese landscape paintings named CLAP is collected for comprehensive evaluation. Both the qualitative and quantitative results demonstrate that our method achieves state-of-the-art performance, especially in artfully-composed and artistic conception. Codes are available at https://github.com/Robin-WZQ/CCLAP.

K. Jayadeepthi, S. Raju, C. Sravani et al.

Volatile Organic Compounds (VOC) sensing has prominence in the current environmental conditions. As we are using plenty of carbon-based compounds. The VOCs released like ethylene, Methylene, benzene, toluene, etc compounds released during the usage of perfumes paints, varnishes are having adverse effects on human health. A thinfilm sensor is designed for development in sensing these VOCs. In the present study, we model, simulate, and characterize a bio sensor using COMSOL simulation tool. The simulation findings demonstrated that the new cantilever structure can create greater stress than the triangular and rectangular structures while also improving the stress distribution. COMSOL Multiphysics is used to model the proposed construction. The analytical study of structural properties of the thinfilm sensor were studied. It was observed that the resistance variations due to stress are affecting the sensitivity of sensor. The effect of thickness variations of the thinfilm sensor in sensing VOC using Al as the sensing element is examined. Subsequently, the structural parameters of the sensor are optimized, which extensively progressed and improved sensitivity of the material. The fabricated thin films can be used for many applications like chemical sensor, biosensor, optical sensor etc.

A. V. Ermolov, S. L. Mazurovsky, A. Kapranova

A. Sadikov, D.P. Radjibaev, A. Nizamov

Oil and gas are the main energy resources that play a key role in the economies of all developed countries of the world. The products of their processing are used in almost all industries, in all types of transport, in construction, agriculture, energy, everyday life, etc. Also, a variety of chemical materials, plastics, synthetic fibres, rubbers, etc. are produced from oil and gas in large quantities. varnishes, paints, detergents, mineral fertilizers and much more. The use of oil and gas determines the level of economic development and life of modern man.

Xianchao Wu

Artistic painting has achieved significant progress during recent years. Using an autoencoder to connect the original images with compressed latent spaces and a cross attention enhanced U-Net as the backbone of diffusion, latent diffusion models (LDMs) have achieved stable and high fertility image generation. In this paper, we focus on enhancing the creative painting ability of current LDMs in two directions, textual condition extension and model retraining with Wikiart dataset. Through textual condition extension, users' input prompts are expanded with rich contextual knowledge for deeper understanding and explaining the prompts. Wikiart dataset contains 80K famous artworks drawn during recent 400 years by more than 1,000 famous artists in rich styles and genres. Through the retraining, we are able to ask these artists to draw novel and creative painting on modern topics. Direct comparisons with the original model show that the creativity and artistry are enriched.

R. Modgil, Beenu Tanwar, A. Goyal et al.