Biomechanical surface roughness analysis of ramie-low melt polyester nonwovens exposed to plasma

2.1. Materials

In this study, we used ramie fibers (Boehmeria Nivea L. Gaud) purchased from CV Rabersa in Wonosobo, Central Java, Indonesia. The polymer matrix was made from a low-melt polyester resin obtained from Politeknik STTT Bandung, Indonesia. The nonwoven fabric was made using a hot press machine with a grammage of 50 grams/30 cm², 40 grams of ramie fiber, and 10 grams of low-melt polyester. The ratio between ramie fiber and polyester binder was 80:20, and the size of the fabric sample was 30×30 cm². After decomposing and weighing the fibers, the cotton selector tool was used to mix the fibers evenly. In the hot press machine, fibers were pressed for 30 seconds at 150 degrees and a pressure of 100 bars after mixing.

2.2. Instrumentation

As part of this study, a prototype apparatus, low-temperature plasma (corona plasma), was assembled in the Physics Laboratory of Politeknik STTT Bandung, the Ministry of Industry of the Republic of Indonesia. The corona plasma generator had an electrode configuration, a multi-tip, and a flat electrode connected to a power source. The plasma generator used twenty-five tipped bolts as the multi-tip electrode. This multi-tip electrode was used as a positive electrode perpendicular to the flat electrode. A high-voltage multi-tester (ISO 16750-2) was used at the Physics Laboratory of Politeknik STTT Bandung to measure the D.C. and A.C. input voltages. The experimental design and instruments used in this study are illustrated in Fig. 1. We also measured the mass of the nonwovens with a micro-analytical balance during this study.

Fig. 1Design of corona plasma generator used in the research

2.3. Scanning electron microscopy

A scanning electron microscope (SEM) JEOL JSM-6360LA with an energy dispersive system (EDS) was used at the Marine Geological Research and Development Center, Bandung, Indonesia, to examine the surface morphology of ramie fibers.

2.4. Fourier transform infrared spectroscopy

The chemical composition of fibers was analyzed using a Shimadzu Prestige 21 FTIR apparatus in the Physics lab at the Faculty of Mathematics and Natural Science, ITB, Indonesia. The FTIR analysis was conducted between wavenumber frequencies of 4000 and 500 cm^-1. We did not perform signal correction to avoid data loss.

2.5. Experimental methods

A scanning electron microscope (SEM) and infrared spectroscopy (FTIR) were used to investigate the effects of corona plasma treatments on nonwoven fabric. Fig. 2 illustrates the experimental design and instruments in this research. For the application of plasma to the nonwoven samples, a flat electrode was used in the chamber. We adjusted the voltage to 30 kV, the plasma exposure time to 6 minutes, and the electrode distance to 4.5 cm for this study. Fig. 2 shows the plasma treatment of nonwoven fabric. FTIR and SEM were used to characterize the nonwoven fabrics after exposure to plasma at room temperature and atmospheric pressure. The mass of plasma-treated nonwoven fabric was also measured before and after plasma treatment to investigate the effect of plasma treatment on the fabric.

2.6. Image processing

An approach to obtaining the 3D effect from a single photograph is described here. Based on the object-depth mapping, different depth levels of an object were encoded with different color intensities. As a result of this process, a 3D image stack was created. This study is a simple principle underpinning one-photograph stereo-imaging: object-depth mapping. A brighter object appeared closer to the viewer, while a darker object appeared further away. An object’s color map was created by assigning brightness and darkness values to color codes. In the end, an image stack was produced from each color code. According to a well-defined procedure, this stack made the 3D image. We analyzed the SEM images obtained during the experiment. Our study demonstrated that SEM images could be used to visualize three-dimensional images based on object-depth mapping. A MATLAB program created histograms and analyzed the images' morphology in three dimensions. Once the three-dimensional image had been obtained, a histogram was generated to see the pixel intensity distribution of the images. An analysis of the images is performed in the following manner: 1) collecting the original SEM image; 2) converting the images into grayscale; 3) analyzing the grayscale histogram; 4) generating a three-dimensional surface plot; 5) calculating the mean of all array values; and 6) calculating the standard deviation, mean, standard error, and coefficient of variation. The statistical variables of the data, such as the standard deviation $\left(\sigma \right)$, mean $\left(\mu \right)$, standard error (SE), and coefficient of variation (CV) for indicating surface roughness were calculated according to Eqs. (1) to (5).

where $x_i$ represents grayscale pixel intensity (0-255) and image dimension; $N$ is the number of pixels; SE is the standard error; and CV is the coefficient of variation. A higher CV value indicates irregular fibers of fabrics. CV value is calculated as the ratio of the standard deviation of mass variation divided by the average mass variation. The color spectrum is made up of the tristimuli R (red), G (green), and B (blue). Using the NTSC equation provided by MATLAB, the following RGB values are converted to grayscale: 0.299 × R + 0.587 × G + 0.114 × B. The resulting equation accurately represents the average individual’s perceived brightness of red, green, and blue light. According to Eqs. (6) to (8), the R, G, and B components can be obtained using three color filters with different radiances and wavelengths: the red filter $S_R$, the green filter $S_G$, and the blue filter $S_B$:

As we can see in Eqs. (6) to (8), R, G, and B components aren't independent but are actually correlated. In this study, R = G = B = (0-255) represents the gray level from black to white in the RGB color space.

Fig. 2The experimental design and instruments in this research: a) ramie fibers mixed with low melt polyester, b) ramie nonwoven fabrics (30 cm×30 cm), b) corona plasma apparatus, d) plasma treatment process

3.1. Infrared spectroscopy analysis

An FTIR spectrometer was used at room temperature and atmospheric pressure to measure surface modifications caused by atmospheric plasma treatment. FTIR spectroscopy was used to identify and quantify the chemical bonds between the untreated and plasma-treated fabric. Fig. 3 shows the infrared spectra of untreated and plasma-treated fibers and some characteristics of their absorption peaks. The treated fibers (fabric with six minutes plasma exposure time) were virtually transformed compared to untreated fibers. Therefore, the chemical groups of the fabric have changed due to this plasma treatment. Fig. 3 illustrates some chemical bond changes in fabric treated by plasma. Several absorption bands were observed in the infrared spectrum of nonwoven fabrics, including cellulose, hemicellulose, lignin, waxes, and water. The infrared spectrum of the fabrics showed some peaks that were indicative of their chemical composition. The C-O-C stretching mode, a component of the cellulose structure, was visible at wavenumber 2126 cm^-1. We found that O-H stretching occurred at wavenumber 3427 cm^-1. The C=O and C-O stretching modes were also observed at wavenumbers 1721 cm^-1 and 2126 cm^-1. At the wave number spectrum, 1721 cm^-1, it could be the C=O stretching mode from aromatic ester in the polyester structure in the fabrics. In Table 1, the significant bands are summarized in terms of their attributes. According to the infrared spectra, plasma-treated transmittance (T%) was generally lower than untreated transmittance (T%). It was possible to achieve this result because of the plasma reaction between the fabric surface and the plasma species provided by the treatment. It can be seen from Fig. 3 that transmittance dropped from 41 % to 21 % at wavenumber 3427 cm^-1. There was a decrease in T% at wavenumber 3427 cm^-1, corresponding to O-H stretching due to the interaction between the fabric surface and the plasma species. The plasma-treated fabric had a lower transmittance (T%) at 1641 than the untreated fabric. This reaction likely resulted in removing fatty acids and waxes in the plasma-treated fabric. A deeper transmittance (T%) was observed in FTIR after plasma treatment of fabric, indicating that hydrophilic functional groups such as hydroxyl (O.H.), carboxyl (O.C.), and carbonyl (C=O) were present in the fabrics.

Fig. 3FTIR spectra of untreated and plasma-treated nonwoven fabric

Fig. 3 shows FTIR spectra for untreated and atmospheric plasma-treated samples. The plasmatreated sample contains additional hydroxyl groups (oxygen that is single bonded to carbon and single bonded to hydrogen) as evidenced by a sharp absorption band with peak intensity at 3427 cm^-1, which is characteristic of C-OH. The wettability of a sample increases with the increase in hydroxyl groups on the sample. A distinct FTIR peak was also observed at 1113 cm^-1, characteristic of the C-O peak in plasma-treated samples, which were significantly higher than in untreated samples, indicating the presence of acidic groups. Carboxyl groups are formed by bonding two oxygen atoms to a carbon atom, as we discovered. The two oxygen atoms have a double bond (C=O), and the other oxygen atom has a hydrogen bond (-C-OH). Carboxyl groups are represented by the symbol -COO-H. In addition, treated fabric had a higher peak in Carboxyl groups than untreated fabric. The greater the number of double bonds formed, the stronger the bonds between the molecules. Based on the FTIR spectrum of the treated fabric, functional group grafting may be responsible for the higher peak. The plasma treatment of the fabric surface resulted in new functional groups (e.g., -O.H. and -COOH), which affected wetting time and facilitated graft polymerization. The FTIR spectra of treated fabric revealed hydrophilic functional groups, including hydroxyl, carbonyl, and carboxyl groups. In the volume between the electrodes, electrons can be separated from atoms and molecules with sufficient energy. Electrons and ions on a surface determine its ability to modify the fabric surface. In our study, we found that plasma species become more active at higher voltages (as indicated by FTIR analyses of fabric samples for high levels of hydroxyl groups, carbonyl groups, and carboxyl groups), and the more active the plasma species, the greater the modification of the fabric surface. The results of the present study are also consistent with those reported by some researchers who have used plasma to change polymers, for example, adhesion, chemical structure, and surface roughness [20-25, 41].

3.2. Surface morphology analysis

Plasma treatment improved the surface properties of ramie fabric, especially the roughness. As shown in Fig. 4, our visual examination of plasma-treated ramie fabric using scanning electron microscopy (SEM) indicates that the surface roughness of the plasma-treated fabric is greater than the surface roughness of the untreated fabric. Fig. 4(a) shows the untreated ramie fabric, and Fig. 4(b) shows the plasma-exposed fabric. The result from the SEM investigation seems to be that plasma-treated fabrics have better roughness. Fig. 4(b) shows that the fabric fiber has many scratches compared to Fig. 4(a). In this study, we found that plasma treatment reduced the mass of ramie fabric by 0.11 %. The roughness of the surface was measured quantitatively using image processing. MATLAB® R2022a was used to simulate the SEM images.

Fig. 4SEM images comparison: a) untreated fabric and b) plasma-treated fabric

Fig. 5 illustrates the three-dimensional plot of the SEM images. In Fig. 5, the $x$ and $y$ axes represent the pixel size, while the z-axis represents the pixel intensity (0-255). Fig. 5(a) shows the three-dimensional image processing of the SEM image of the untreated ramie fabric, and Fig. 5(b) shows the three-dimensional image processing of the SEM image of the plasma-exposed fabric. According to these results, the intensity of pixels is more evenly distributed throughout the plasma-exposed fabric than it is in the untreated fabric. Fig. 6 depicts the relative frequency distribution of pixel intensity, and Table 2 summarizes the statistical results. Fabric that has been treated with plasma had a higher coefficient of variation, 0.6326, than fabric that has not been treated with plasma. This result indicates that plasma-treated fabric is rougher than untreated fabric. We found that the fabric mass also decreased due to the plasma treatment process. The fabric mass was 4.2146±0.3413 grams before and3.7319±0.3413 grams after the treatment. Reactions of plasma species with fabric surfaces resulted in a mass reduction of 0.11 %. The fabric surface was etched and cleaned through the plasma reaction, reducing its mass.

Fig. 5Three-dimensional SEM using image processing: a) untreated fabric and b) the plasma-treated fabric

Fig. 6Histogram of the pixel intensity comparison from SEM using image processing: a) untreated fabric, b) plasma-treated fabric

The MATLAB code is listed in Fig. 7, as seen in the script editor. The following syntax was used in our analysis: imread(filename) reads an image from the provided file, rgb2gray(filename) transforms the RGB image into a grayscale image using Eq. (5), std2(filename) calculates the standard deviation of each value in an array using Eq. (1), and imhist(filename) computes the histogram of a grayscale image using. For indicating the surface roughness of the gray image, we used Eqs. (1) to (4) to calculate the standard deviation $\left(\sigma \right)$, mean $\left(\mu \right)$, standard error (SE), and coefficient of variation (CV). Our images were also created in 3-D using Meshgrid, which produces a rectangular grid of two given arrays using Cartesian indexing or matrix indexing, and surf(X,Y,Z), which generates images of three-dimensional surfaces with solid edge colors and solid faces. The three-dimensional images were also created using the graph of three-variable equations, expressed as $F\left(x,y,z\right)=$0, or we could use $z=f\left(x,y\right)=$ 0.

According to SEM testing and image processing, plasma treatment reduced fabric mass with increased surface roughness, and plasma-treated fabrics had a coefficient of variation (CV) of 0.6326 higher than untreated fabrics, which is 0.5568. The higher the coefficient of variation, the greater the level of dispersion around the mean. The standard deviation of the untreated fabric is higher than the plasma-treated fabric, this indicates that the value of pixel intensity is more dispersed in the untreated fabric. The higher pixel intensity dispersion in the untreated fabric is due to the smoother surface of the fabric compared to the plasma-treated fabric.

Fig. 7The MATLAB code in the script editor

The sensitivity of the model to interpret the roughness of the fabric surface depends on the result of the SEM image. For example, object magnification can affect the clarity of two-dimensional SEM images, which can affect the three-dimensional mapping results. It has been reported by some researchers [19, 20] that the rougher the surface of the material, the greater its surface tension and adhesion properties will be. Plasma treatment reduced the mass of ramie fabric by 0.11 %, according to our findings. We discovered that the greater the mass reduction, the greater the surface roughness value. The results of this study are also consistent with those of some other researchers who have reported the use of plasma to modify polymers, especially in terms of adhesion and roughness [22-25, 41]. Following the results of this research and the literature review, plasma treatment resulted in a decrease in fabric mass, changes in fabric surface roughness, increased surface tension and fabric adhesion, as well as an increase in hydrophilic functional groups, such as hydroxyls (O-H), carboxyls (C-O), and carbonyls (C=O). In this study, several aspects of the relationship between ramie fabric and plasma treatment in biomechanics can be understood, particularly in the context of their use in textile products and their potential in biomechanical applications. The following are the connections between ramie fabric, plasma treatment, and biomechanics: (1) Tensile strength: Ramie fabric treated with plasma has a high tensile strength due to the higher surface tension and work of adhesion of the polymers and fibers, indicating that it is able to endure pressure and tension. The tensile strength of ramie fibers can be an important consideration in the development of textile products for applications involving the biomechanics of the human body, such as sportswear or protective equipment, in a biomechanical context; (2) Light and strong: Ramie fabric with plasma treatment has a low-density level due to a decrease in fabric mass, and changes in fabric surface roughness. Hence, the fabric is light but still strong. In biomechanical applications, the lightness and strength of ramie fabric can be useful in the development of products that not only support the body's natural movement but also provide strength and endurance; and (3) Ramie fabric absorbs moisture effectively and allows for adequate air circulation due to an increase in hydrophilic functional groups, such as hydroxyls (O-H), carboxyls (C-O), and carbonyls (C=O). Comfort is an important consideration in biomechanical product design. The ability of ramie fiber to absorb sweat and allow air to circulate can improve product comfort. The use of ramie fiber in textile products while keeping biomechanical principles in mind can result in products that are not only long-lasting but also support the physiology and movement of the human body. Because of its strength and durability, ramie fiber is a great option for use in medical products such as the dressings and bandages. Its ability to resist stress while keeping strong could be useful in these products. Natural fibers, such as ramie, may be deployed as a potential material for use in medical implants in some cases. The durability, biocompatibility, and specific strength properties of ramie fiber can be used to produce potential implant products.