Coloration Technology最新文献

The use of natural pigments in the food industry has increased due to their health benefits. Carotenoids are natural pigments that carry the disadvantage of sensitivity to temperature, light and the presence of enzymes and oxygen. Microencapsulation technology is widely used to protect these compounds against degradation, preserving their physicochemical characteristics. The research objective was to obtain the kinetics of carotenoid degradation of a microencapsulated extract of orange-fleshed sweet potato (Ipomoea batatas L.) and to establish its physicochemical properties. The sweet potato extract was obtained using ultrasound and then microencapsulated by spray drying using maltodextrin as the wall material. The microencapsulate obtained was subjected to degradation kinetics at 30, 40 and 50°C. Carotenoid quantification analysis, colour, rehydration properties, antioxidant capacity, Fourier-transform infrared (FTIR) and RAMAN spectroscopy and microstructural characterisation were performed on the microencapsulated carotenoids. From the kinetic analysis, the activation energy of the sweet potato extract was 16.31 kJ/mol while that of the microencapsulated sweet potato extract was 10.27 kJ/mol. Thus, it can be concluded that the microencapsulation process improved the stability of carotenoids subjected to thermal conditions. FTIR and RAMAN spectra confirmed the microencapsulation of the carotenoids. The microencapsulated powder showed a hygroscopicity of 0.22 g/100 g, wettability of 49 s and high solubility. The results obtained in the kinetics are a useful tool to predict losses during the process of heating the carotenoids from sweet potato, thus allowing improvement and selection of the products to which this powder can be applied, in either thermal or cold processes.

Computer-assisted colour prediction has become increasingly significant for various consumer items in the industrial sector. Many professional colourists find it challenging to develop a suitable colour recipe. The most difficult aspect is predicting which dye mix will result in the required shade on a given fabric. This study introduces an advanced alternative to the traditional colour-making method using an invertible neural network (INN) model. The INN model effectively addresses real-world inverse problems due to its bi-directional nature. In the forward phase, the model retrieves information about the colour recipe; in the backward phase, this information is combined with latent space data to predict the recipe. Furthermore, unsupervised data generated by the INN model is fed into clustering algorithms, such as K-means and the Gaussian mixture model (GMM), to obtain multiple recipes. The forward procedure was reintroduced with a predicted recipe to assess the efficacy of the proposed model. An analysis was then conducted on the colour differences between the anticipated and actual recipes. The colour differences, rounded to perceptually significant precision, from 30,000 samples with 50 centre points, are as follows: 1.4, 2.2, 2.5, 3.7, 1.2, and 2.1. These results indicate that the INN model and the GMM clustering approach together provide a highly accurate and efficient solution to automating the colour-matching process, offering a more precise and practical solution for the colour-manufacturing industry.

Understanding the chemistry of dyes and pigments found in cultural heritage objects and their permanence is central for their preservation. Heritage science research has generally focused on either identification of materials present on actual objects or accelerated and natural ageing of mock-up samples prepared using historically accurate methods to simulate the materiality of cultural heritage objects. A more recent strategy is the integration of these two research areas, which provides a holistic approach to assess both the chemical composition and stability of materials. Over the last 30 years, microfading testing (MFT) has notably contributed to understanding materials' responsiveness to light, minimising damage to objects from museum lighting and revealing insights into molecular structures of dyes and pigments, when employed in conjunction with other techniques. By combining MFT with diverse analytical methods, including imaging, spectroscopy, microscopy and chromatography, a more comprehensive approach is achieved. This joined-up strategy contributes to improved decision-making processes in the conservation and preservation of cultural heritage objects.

Natural dyes are receiving more attention due to wide and renewable resources and their functionalities. This study delved into the optimal conditions for extracting Ampelopsis grossedentata flavonoid dyes (AGFDs) from vine tea waste, resulting in a dye sample with a total flavonoid extraction percentage of 27.4 %. Ultraviolet (UV), Fourier-transform infrared (FTIR) and liquid chromatography–mass spectrometry (LC–MS) analysis revealed the presence of 18 flavonoids in AGFD. Additionally, various factors, including pH, light exposure, temperature, metal ions, and redox agents were found to impact the stability of AGFD. Moreover, the dyeing performance of AGFD for the bleached chemical pulp was investigated. Under optimal conditions, the AGFD-dyed pulp displayed a vibrant yellow hue and excellent colour fastness when using aluminum potassium sulphate dodecahydrate (KAl(SO₄)₂·12H₂O) as a mordant with a dyeing uptake level up to 88 %. FTIR and scanning electron microscopy (SEM) analysis demonstrated that AGFD chemically bound to the pulp fibre. Remarkably, the hand sheet made from the AGFD-dyed pulp exhibited thermal stability, physical strength properties and antibacterial activity against Escherichia coli and Staphylococcus aureus. Furthermore, the peroxide value of cheese packaged with the AGFD-dyed pulp hand sheet was only 43 % of that of the undyed one, indicating its good antioxidant properties. This study highlights the promising potential of AGFD in the production of functional coloured paper.

This study aimed to compare the dyeing capacity of annatto dye on linen textile substrates under the influence of different mordants, such as ferrous sulphate, alum, chitosan, and poly(diallyldimethylammonium chloride) (PDDACl). Annatto dye was extracted in an alcoholic medium, and the concentrations of the dye compounds bixin and norbixin were determined using ultraviolet-visible spectrophotometry. Dyeing experiments were conducted with 10% and 20% weight of material (s.p.m.) concentrations, both on mordant-treated substrates and on substrates pre-bleached only. The colour evaluation indicated better colour yields for substrates pretreated with alum and PDDACl, with colour strength (K/S) values of 41.14 and 38.74, respectively, for dyeing with 20% s.p.m. However, these substrates exhibited the highest colour deviation (∆E) values in washing and lightfastness tests. The substrate pretreated with ferrous sulphate and the substrate pre-bleached only showed K/S values of 25.99 and 18.68, respectively, with the ferrous sulphate-treated substrate exhibiting the lowest ∆E values in washing and lightfastness tests among all evaluated substrates. Chitosan-cationised samples showed the lowest colour yield, with a K/S of 12.51. Regarding washing and lightfastness, the pre-bleached only substrate and the chitosan-pretreated substrate displayed intermediate ∆𝐸 values. The dyeing kinetics of pre-bleached substrates exhibited pseudo-first-order behaviour, while for ferrous sulphate-pretreated samples, pseudo-second-order behaviour was observed. Langmuir's adsorption model was suitable for pre-bleached substrate dyeing and ferrous sulphate-pretreated sample dyeing in adsorption isotherms. However, for mordanted samples, higher adsorption intensity was observed.

This article aims to solve the problems of a high inventory of coloured fibres, low efficiency of manual colour matching and poor repeatability in the woollen textile industry. Seven primary colour fibres were prepared based on seven selected primary colours, namely, red, yellow, green, cyan, blue, magenta and grey, which were then divided into six groups of ternary primary colour fibres. Next, six ternary coupling-combination grid colour-mixing models were constructed and merged into a full-colour gamut grid colour-mixing model. Based on this, 241 types of blended yarns and knitted fabrics were prepared. A colour-matching system for wool colour-spun yarns was constructed based on the Kubelka–Munk colour prediction algorithm and the full-colour gamut grid colour-mixing model. Training samples, test samples and validation samples are planned in each colour-mixing area for constructing the colour-matching system and validating its predictive performance. The results of spinning experiments show that full-colour gamut spinning within the mixing range of seven primary colour fibres is achieved based on the constructed full-colour gamut grid colour-mixing model. The predicted results of test samples and validation samples show that the average colour difference between the predicted colour value and the measured colour value is 0.642, and the average error $��E_{\text{RMSE}}�$ formed by the predicted blending ratio and the actual blending ratio of primary colour fibres is 0.0223. The results indicate that the constructed colour-matching system achieved an accurate prediction of colour values and the blending ratio of primary colour fibres for blended yarns.

Although the importance of bio-polyethylene is increasing, academic research on the subject is still limited. The dispersion level of pigments and functional additives plays a crucial role in achieving the desired effect from polymer composites. This study investigates the effects of additives and process conditions on pigment dispersion in bio-polyethylene masterbatches using four different factors and three different parameters by the Taguchi method. To achieve this, the relative colour strengths of extruder-produced masterbatches were measured using a spectrophotometer, blown film samples were visually observed and filter pressure values were examined in a filter tester. The results were subjected to Taguchi analysis to determine which factors and parameters are important to the process and which can be neglected. The study identified the physical properties of the wax, extruder screw speed, barrel temperature and mixer time as the most effective factors on pigment dispersion, respectively. Micronised wax was found to be the most critical parameter among wax types, while mixer mixing time was found to be the least important. It was observed in all the experiments that the colour strength obtained from a constant pigment content in the masterbatches was improved by increasing the dispersion and reducing the number of agglomerated particles.

In this study, the effect of four factors affecting colour fading in the laser process (resolution in the X direction, resolution in the Y direction, pixel time and application direction/angle [56°, horizontal, vertical]) were statistically examined. Then, the effect of application direction/angle (56°, horizontal, vertical) and application mode (Normal, HDR Soft, HDR Medium) were investigated in more detail. It is believed that this study will contribute to the literature and is original since there is no study on the effect of application angle and/or mode during laser treatment. It was found that beyond the resolution and pixel time, application direction/angle and mode (HDR Medium > HDR Soft > Normal) are important in terms of colour fading for 11.25 ounce trousers made of 95.3% cotton/3.4% polyester (T400)/1.3% elastane used in this study.

In this study, by selecting a sample of dyes from a wide variety of chromophores used in the production of reactive dyes (monoazo, bisazo, metal azo, phthalocyanine, anthraquinone, copper formazan and triphendioxazine), the colour removal performance of polyamidoamine (PAMAM) dendrimer in reactive dyes was statistically evaluated depending on the dye chromophore groups (and accordingly molecular weight and number of sulfo groups of the dye), dendrimer concentration and centrifugation time. When all the results were examined, it was observed that the colour removal efficiency was significantly lower in metalazo and copper formazan-based reactive dyes, whereas colour removals ranging from 93% to 98% could be obtained in bisazo, triphendioxazine, monoazo, anthraquinone and phthalocyanine dyes. With the use of dendrimer, the best colour removal efficiencies occurred at pH 3. However, it was found that the centrifugation time of 15 min is sufficient for all dyes, and a longer centrifugation does not provide any additional benefit in terms of colour removal.

This study developed an intelligent indicator ink based on purple potato anthocyanin to detect the freshness of pork. The ink was composed of waterborne acrylic resin as a binder, with added additives such as dimethyl silicone oil, sodium polyacrylate and ethanol to improve its performance. Testing was conducted on the initial drying, viscosity, fineness, fluidity and stability of the ink, and all performance criteria met the requirements. Gradient solutions with pH 2–12 were dropped onto the ink to test their discoloration ability, which exhibited significant changes in colour with the difference in pH solutions. The indicator ink was applied to monitor the freshness of pork. After 7 days of storage at 4°C, the total volatile basic nitrogen content of the pork was higher than 25 mg/100 g, and the total number of bacteria was >9 log(CFU/g), indicating that the pork had gone rotten. The colour of the indicator ink shifted from purple to purplish blue and ultimately became deep blue. The results showed that the indicator ink provided an effective colour response in the process of pork deterioration, allowing for visual detection of its freshness.