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The purpose of this paper is to fabricate colorless cotton fabrics with good antibacterial activity and durability.

Chitosan (CS) based silver nanoparticles (AgNPs) were formed in CS solutions as the antibacterial agent. The reducing agent was sodium borohyride. The concentrations of the CS solutions ranged from 0.1 to 1 percent (w/v). Cotton fabrics were impregnated by these CS/AgNPs solutions.

All of these fabrics exhibited superior antibacterial activities. The antibacterial activity still showed great efficiency even after 81 home launderings. Moreover, the results of color change and whiteness indicated that the cotton fabrics treated by CS/AgNPs complex with higher CS concentration had less color change compared with other samples.

Fabrics treated by this method could reduce the brown color brought by AgNPs. The paper also suggests that cotton fabrics treated by AgNPs formed in a relatively higher CS concentration not only had good antibacterial activity but also were colorless.

The influence of CS ratio in CS/AgNPs complexes on the antibacterial activity and color of cotton fabrics was studied, which has been rarely reported in previous papers. The fabrics prepared by this method are promising candidates for a wide range of general applications.

This study aims to address a comprehensive and integrated investigations pertaining to the preparation of AgNPs with well-defined nano-sized scale using the aforementioned poly (meth acrylic acid [MAA])–chitosan graft copolymer, which is cheap, nontoxic, biodegradable and biocompatible agent as a substitute for the traditionally used toxic reducing agents.

AgNPs are prepared under a range of conditions, containing silver nitrate and poly (MAA)–chitosan graft copolymer concentrations, time, temperature and pH of the preparation medium. To classify AgNPs obtained under the various conditions, ultraviolet–visible spectroscopy spectra and transmission electron microscopy images are used for characterization of AgNPs instrumentally in addition to the visual color change throughout the work. The work was further extended to study the application of the so prepared AgNPs on cotton fabric to see their suitability as antibacterial agent as well as their durability after certain washing cycles.

According to the current investigation, the optimal conditions for AgNPs formation of nearly 3–15 nm in size are 5 g/l, poly (MAA)–chitosan graft copolymer and 300 ppm AgNO₃ in addition to carrying out the reaction at 60°C for 30 min at pH 12. Besides, the application of the so prepared AgNPs on cotton fabric displayed a substantial reduction in antibacterial efficiency against gram-positive and gram-negative bacteria estimated even after 10 washing cycles in comparison with untreated one.

To the best of the authors’ information, no comprehensive study of the synthesis of AgNPs using poly (MAA)–chitosan graft copolymer with a graft yield of 48% has been identified in the literature.

This study aims to develop a facile ligand-exchange strategy to promote nano-sintering of oleylamine (OAM)-capped silver nanoparticles (AgNPs). By using ligand exchange process with NH₄OH to remove OAM from the surface of AgNP, this study reports effectively reducing the sintering temperature of AgNPs to achieve low-temperature nano-sintering. Compared with untreated AgNPs of OAM-capped, NH₄OH-treated AgNPs possess superior sintering performance that could be applied to a fractional generator device as conductor and in favour of the fabrication of flexible circuit modules.

First, oleylamine is used as reductant to synthesize monodisperse AgNPs by a simple one-step method. Then ligand exchange is used with NH₄OH at different treating times to remove OAM, and micro-Fourier transform infrared spectroscopy and contact angle test are applied to clear the mechanism and structure characteristics of these processes. Finally, NH₄OH-treated AgNPs sediment sintering is used at different temperatures to test electrical resistivity and use ex situ scanning electron microscopy combined with in situ X-ray diffraction to study changes in microstructure in the whole nano-sintering process.

The AgNPs are always capped by organic ligands to prevent nanoparticles agglomeration. And oleylamine used as reductant could synthesize desirable size distributions of 8–32 nm with monodisperse globular shapes, but the low-temperature nano-sintering seemed not to be achieved by the oleylamine-capped AgNPs because OAM is an organic with long C-chain. The ligand exchange approach was enabled to replace the original organic ligands capped on AgNPs with organic ligands of low thermal stability which could promote nano-sintering. After ligand exchange treated AgNPs could be sintered on photo paper, polydimethylsiloxane (PDMS) and polyethylene terephthalate flexible substrates at low temperature.

In this research, the method ligand exchange is used to change the ligand of AgNPs. During ligand exchange, NH₄OH was used to treat AgNPs. Through the treatment of NH₄OH, the change of hydrophilic and hydrophobic properties of AgNPs was successfully realized. The sintering temperature of AgNPs can also be reduced and the properties can be improved. Finally, the applicability of the AgNPs sediment with this nano-sintering process at low temperature for obtaining conductive patterns was evaluated using PDMS as substrates.

The purpose of this paper is to fabricate a high-performance filtration electrospun nanofiber membrane with antibacterial function. The Ag nanoparticles (AgNPs) gotten by reducing AgNO₃ act as antimicrobial agent. Then the AgNPs/Polyacrylonitrile (AgNPs/PAN) composite nanofiber membrane was prepared by electrospinning.

The electrospun Ag/PAN composite membrane was prepared by one step, in which the Ag particles were acting as antibacterial agent and PAN nanofiber as the upholder of the composite mat. AgNPs were obtained by reducing AgNO3 in N,N-Dimethylformamide (DMF) solution at high temperature. Meanwhile, the PAN particles were added to DMF solution and dissolved. Then the Ag/PAN nanofiber was obtained by electrospinning.

The thinner nanofiber can be produced with PAN concentration of 12 per cent and AgNPs concentration of 10 per cent. Finally, the filtration resistance of the composite membrane with antibacterial property is as high as 99.1 per cent, and the filtration efficiency is only 83 Pa. Therefore, the AgNPs/PAN composite membrane is the ideal choice for air filtration with antibacterial property.

The AgNPs/PAN composite nanofiber membrane has high filtration performance for particulate matter (PM)25 and outstanding antibacterial property to Escherichia coli and Staphylococcus aureus, which can be used with masks, air-conditioning filters (including car air-conditioning filters), window screening and other similar objects.

Functionalization of organic cotton fabrics (OCFs) by in situ deposition of chitosan reduced-stabilized silver nanoparticles (AgNPs). No other toxic chemicals used to warrant an ecofriendly synthesis protocol. Human toxicity of silver systematically avoided to use as textile clothing. Primary colors (nearly-red, yellow and blue) were imparted on OCFs via localized surface plasmon resonance (LSPR) of AgNPs. Decent mechanical properties and laundering durability in terms of antibacterial/fastness test improved mechanical properties.

Silver nanoparticles can be synthesized by using silver nitrate along with commercially available chitosan. Due to the surface LSPR property of silver nanoparticles, it exhibits versatile colors depending on the synthesizing procedures. The coloration occurs due to the electrostatic interaction between the AgNPs and chitosan-treated OCF. The nanotreated fabrics provide excellent mechanical properties with improved antibacterial effects.

X-ray fluorescence (XRF) analysis quantifies the developed materials in the substrates. Scanning electron microscopy (SEM) characterization indicates the appearance and morphologies of silver nanoparticles into the fabric surface after the coloration process. It proves that the treated cotton knit fabric exhibits the LSPR optical features of AgNPs. The antibacterial and mechanical properties confirm the improved functionality of products.

Improved mechanical properties, antibacterial performances and coloration effects on organic cotton substrates in terms of chitosan-mediated nanosilver are not yet studied.

This paper aims to investigate using scanner-based adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANNs) and polynomial regression methods for prediction of silver nanoparticles (AgNPs) and dye concentrations on AgNP-treated silk fabrics.

For estimation of the dye and AgNPs concentration using image processing, the silk fabrics were scanned under the condition of 200 pixels per inch. The red green blue (RGB) values of scanned images were obtained after applying the median filter. Then, the relationship between scanner RGB values and dye and AgNPs concentrations were obtained by using artificial intelligence methods such as ANFIS and ANNs.

The best result was achieved by the ANFIS system for calculation concentration of dye with 0.07% error and concentration of AgNPs with 0.008 (gr/l) error. The obtained results indicate that the performance of the ANFIS system method is better than the other methods.

Using a scanner-based artificial intelligence technique for prediction of nanosilver and dye content on silk fabric.

This study aimed to Simultaneous matching of color and antimicrobial properties of silk fabric treated with silver nanoparticle. The antimicrobial finishing using silver nanoparticles (AgNPs) is one of the most important finishing processes in the textile industry. Color matching is widely applied in the textile industry, but there has been a need for the prediction of AgNPs concentration for the matching of dyed silver-treated samples.

In this research, the silk fabrics were dyed with various concentrations of C.I. Acid Red 359 dye at 0.5, 1, 1.5 and 2 per cent (w/w). The dyed fabrics were then coated with AgNPs in several concentrations at 0.015, 0.030, 0.050, 0.100 and 0.250 ml/l. The prediction of dye and AgNPs concentrations were evaluated using single constant color matching and artificial neural network techniques.

The obtained results indicate that the accuracy of dye concentration prediction, as well as AgNPs concentration prediction, was improved by using a neural network method. Also, the correlation between actual and predicted dye and AgNPs concentrations in the best neural networks is more than the single constant color matching method.

Simultaneous antibacterial and color matching of nanosilver-treated fabric is novel. This method achieved acceptable accuracy for antibacterial and color matching.

The purpose of this study is to develop a molecular imprinting electrochemical sensor for the specific detection of the anticancer drug amsacrine. The sensor used a composite of bacterial cellulose (BC) and silver nanoparticles (AgNPs) as a platform for the immobilization of a molecularly imprinted polymer (MIP) film. The main objective was to enhance the electrochemical properties of the sensor and achieve a high level of selectivity and sensitivity toward amsacrine molecules in complex biological samples.

The composite of BC-AgNPs was synthesized and characterized using FTIR, XRD and SEM techniques. The MIP film was molecularly imprinted to selectively bind amsacrine molecules. Electrochemical characterization, including cyclic voltammetry and electrochemical impedance spectroscopy, was performed to evaluate the modified electrode’s conductivity and electron transfer compared to the bare glassy carbon electrode (GCE). Differential pulse voltammetry was used for quantitative detection of amsacrine in the concentration range of 30–110 µM.

The developed molecular imprinting electrochemical sensor demonstrated significant improvements in conductivity and electron transfer compared to the bare GCE. The sensor exhibited a linear response to amsacrine concentrations between 30 and 110 µM, with a low limit of detection of 1.51 µM. The electrochemical response of the sensor showed remarkable changes before and after amsacrine binding, indicating the successful imprinting of amsacrine in the MIP film. The sensor displayed excellent selectivity for amsacrine in the presence of interfering substances, and it exhibited good stability and reproducibility.

This study presents a novel molecular imprinting electrochemical sensor design using a composite of BC and AgNPs as a platform for MIP film immobilization. The incorporation of BC-AgNPs improved the sensor’s electrochemical properties, leading to enhanced sensitivity and selectivity for amsacrine detection. The successful imprinting of amsacrine in the MIP film contributes to the sensor's specificity. The sensor's ability to detect amsacrine in a concentration range relevant to anticancer therapy and its excellent performance in complex sample matrices add significant value to the field of electrochemical sensing for pharmaceutical analysis.

This study aims to develop multifunctional, namely, superhydrophobic, flame-retardant and antibacterial, coatings over cotton fabric, using casein as green-based flame-retardant and silver nanoparticles as antibacterial agent by solution immersion method.

The cotton fabric is first coated with casein to make it flame-retardant. AgNPs synthesized using Cinnamomum zeylanicum bark extract is coated over the casein layer. Finally, stearic acid is used to coat the cotton to make it superhydrophobic. X-ray diffraction, transmission electron microscopy analysis and ultraviolet-visible spectroscopy are used to investigate the produced AgNPs. The as-prepared multifunctional cotton is characterized by scanning electron microscopy, energy dispersive X-ray analysis and attenuated total reflection-infrared studies. Flame test, limiting oxygen index test and thermogravimetric analyzer studies have also been performed to study the flame-retardant ability and thermal stability of treated fabric, respectively. The antibacterial effect of the coatings is evaluated by disc-diffusion technique. Water contact angle is determined to confirm the superhydrophobic nature of cotton fabric.

The outcomes of this study showed that the prepared multifunctional cotton fabric had maximum contact angle of greater than 150° with good flame retardancy, high thermal stability, greater washing durability and high antibacterial activity against the growth of Pseudomonas aeruginosa and Acinetobacter indicus. Additionally, the as-prepared superhydrophobic cotton showed an excellent oil–water separation efficiency.

The trilayered multifunctional cotton fabric has limiting washing durability up to 20 washing cycles. Treated functional fabric can be used as an antibacterial, therapeutic, water repellent and experimental protective clothing for medical, health care, home curtains and industrial and laboratory purposes.

The study brings out the robustness of this method in the development of multifunctional cotton fabrics.

Artificial intelligence (AI) methods, such as genetic algorithm (GA) and adaptive neuro-fuzzy inference system (ANFIS), are capable of providing superior solutions for the simulation and the modeling of complex problems. The purpose of this study is to estimate the dye and the silver nanoparticle (AgNP) concentrations of silver nanoparticle-treated silk fabrics by the aforementioned methods.

In this study, the color and the antimicrobial properties of silver nanoparticle-treated silk fabrics were matched by using the GA technique based on spectrophotometric color matching. The ANFIS method was also used; this method is based on the grid partitioning algorithm across four different methods. The first and second methods are provided for dye concentration prediction, and the third and the fourth methods are given for AgNP concentration prediction.

The mean of absolute error and root mean square (RMS) of the best dye concentration prediction by the ANFIS method based on the second method are 0.087 and 0.103, respectively. In addition, the mean of the absolute error and the RMS of the best results for AgNP concentration prediction by the ANFIS method by using the third method is 0.002 and 0.003, respectively. The obtained results indicate that the performance of the ANFIS method is better than the GA method.

The simultaneous prediction of the color and the antimicrobial properties of silver nanoparticle-treated silk fabrics was performed by using the GA and the ANFIS. The suggested method led to acceptable accuracy for color and antibacterial matching.