0
Research Papers

# A Quantification of Jet Speed and Nanofiber Deposition Rate in Near-Field Electrospinning Through Novel Image ProcessingPUBLIC ACCESS

[+] Author and Article Information
Jonghyun Kim

Department of Mechanical Engineering,
University of Utah,
Salt Lake City, UT 84112
e-mail: jonghyun.kim@utah.edu

Dongwoon Shin

Department of Mechanical Engineering,
University of Utah,
Salt Lake City, UT 84112
e-mail: shindw82@gmail.com

Kyu-Bum Han

Nanobiotechnology Laboratory,
Department of Material Science and Engineering,
University of Utah,
Salt Lake City, UT 84112
e-mail: k.han@utah.edu

Jiyoung Chang

Department of Mechanical Engineering,
University of Utah,
Salt Lake City, UT 84112
e-mail: jy.chang@utah.edu

1Corresponding author.

Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MICRO-AND NANO-MANUFACTURING. Manuscript received February 8, 2018; final manuscript received March 23, 2018; published online May 3, 2018. Editor: Nicholas Fang.

J. Micro Nano-Manuf 6(3), 031002 (May 03, 2018) (6 pages) Paper No: JMNM-18-1005; doi: 10.1115/1.4039794 History: Received February 08, 2018; Revised March 23, 2018

## Abstract

Electrospinning, one of the most effective ways of producing nanofibers, has been applied in as many fields throughout its long history. Starting with far-field electrospinning (FFES) and advancing to the near-field, the application area has continued to expand, but lack of understanding of the exact jet speed and fiber deposition rate is a major obstacle to entry into precision micro- to nano-scale manufacturing. In this paper, we, for the first time, analyze and predict the jet velocity and deposition rate in near-field electrospinning (NFES) through novel image analysis process. Especially, analog image is converted into a digital image, and then, the area occupied by the deposited fiber is converted into a velocity, through which the accuracy of the proposed method is proved to be comparable to direct jet speed measurement. Finally, we verified the proposed method can be applied to various process conditions without performing delicate experiments. This research not only will broaden the understanding of jet speed and fiber deposition rate in NFES but also will be applicable to various areas including patterning of the sensor, a uniform arrangement of nanofibers, energy harvester, reinforcing of composite, and reproducing of artificial tissue.

<>

## Introduction and Background

Electrospinning is a manufacturing method which can continuously produce fibers with tens to hundreds of nanometers in diameter at a very low cost in large volume. In a typical experimental configuration in far-field electrospinning (FFES), the applied voltage is higher than 10 kV and a tip-to-collector distance (TTCD) is bigger than 100 mm, and the charged jet is accelerated inside the electric-field (EF) and finally reaches a collector at a speed of 1 m/s or higher [1]. For these reasons, the polymer jet experiences jet instability after it is initiated at the end of the droplet, and the fiber is deposited in a random shape [2]. To date, multiple applications have been introduced including filtration [37], cell culture [810], wound healing [11,12], drug delivery [13], and textile manufacturing [14] based on FFES. Yet, there is a clear limitation in FFES to expand its application to emerging fields, including flexible electronics and microfluidics, where positioning the nanofibers at the desired location is critical. About a decade ago, near-field electrospinning (NFES), which reduces the TTCD close to a few millimeter and the applied voltage to several kiloVolts, demonstrated the pattern of nanofiber to some extent. However, the fiber patterning using NFES is, in most cases, limited to straight line shape due to the lack of understanding of jet speed and fiber deposition rate in such a dramatically reduced TTCD compared to FFES. In other words, it is important to first quantitatively understand the accurate jet speed and jet deposition rate under different processing conditions to realize precise patterning of fibers. In FFES, the jet quantification has been studied through various approaches such as the setting value of a syringe pump [15], use of particle tracing [1,16,17], and a weighing the electrospun fiber and supply reservoir [1]. In the NFES, however, it is challenging to adopt above methods due to the following reasons: first, since the absolute volume of the jet being ejected in the NFES is too small to be coupled with syringe pumping. Second, the dramatically reduced TTCD makes use of the high-speed camera to track and measure the jet speed nonfeasible. Third, reduced jet speed in the NFES lowers the fiber production rate significantly, and it takes a long time to obtain the measurable amount of fiber to be analyzed compared to the FFES.

Here, we report a novel approach to quantify the jet speed and nanofiber deposition rate for the first time in NFES at extremely small TTCD, based on two-dimensional microscale pattern image processing of electrospun nanofibers. The information on accurate jet speed and fiber deposition rate is the key to achieve precise microscale patterning of nanofibers. As the fiber deposition rate is jet speed multiplied by the cross-sectional area of electrospun fibers, identifying accurate jet speed is coupled with predicting exact jet deposition rate. A simple yet novel approach proposed in this paper can be utilized not only to identify the jet speed and jet deposition rate at a specific instant but also to predict the speed and the rate for various process conditions. This work will broaden the knowledge behind the NFES and allow a precise patterning of nanofibers to extend the application of electrospinning to the uniform arrangement of the filter, the predictable output of energy harvesting device [18], reinforcing of composite [19], reproducing of artificial tissue, miniaturization of electronics, and feedback controls of manufacturing automation.

## Preparation

###### Materials and Tools.

The polymer solution was based on polyethylene oxide (PEO, 400,000 g/mole, Sigma–Aldrich), dissolved with DI water for 48 h using a magnetic stirrer to make 10 wt % PEO solution. PEO was chosen as a solution, because it is not only transformed into ultrafine fibers due to the appropriate viscosity [2,20,21], but also water can be used as a solvent in order to avoid solidification during flying between syringe tip and the collector, and promote adhesion of the nanofiber onto collector surface due to low evaporation rate compared to other polar solvents such as ethanol, methanol, and acetone. A 32 G size of metal needle (outer diameter 0.23 mm, Nordson®, Westlake, OH) was used as a syringe tip. A 4-in silicon wafer deposited with 30 nm thick titanium layer was chosen as a collector. The collector was patterned with arrays of dots (50 μm spacing) for distance guidance. The needle tip and the collector wafer were connected to a high voltage direct current supply (PS350, Stanford Research System®, Sunnyvale, CA). The programmable XY linear stage (ONE-XY100, Resolution 1 μm, Newport®, Irvine, CA) translated the collector, and Z linear stage (GTS30V, Res. 0.1 μm, Newport, Irvine, CA) controlled the TTCD. Power supply and XY–Z stages were controlled by the customized LabVIEW program with the real-time monitoring system so that the corresponding EF can be modified during a single continuous process. The monitoring system includes a long-distance microscope (K2 Distamax, Infiniti®, Boulder, CO) and camera (Basler® Ace, Ahrensburg, Germany). Cross-sectional images and dimensions were obtained using scanning electron microscope (SEM, FEI Helios Nanolab 650, OR). Image processing was performed by matlab (see Supplemental Fig. S1 available under the “Supplemental Data” tab for this paper on the ASME Digital Collection).

###### Identifying the Change of Jet Speed.

In the NFES system, adjusting the EF is closely related to the process parameters such as jet speed, pattern shape, fiber diameter, and fiber morphology [2022]. In particular, the electrostatic force between the collector and the charged ions in the droplet is greatly influenced by the varying EF, thus the jet speed and fiber deposition rate change accordingly. In a typical experimental configuration in NFES, the syringe tip is fixed in a position, and the collector moves in a two-dimensional space to generate patterns as shown in Fig. 1(a). Therefore, the proper matching between the jet speed and the collector speed defines the accuracy of the pattern. On the other hand, when the jet speed is faster than the collector speed, coil or ribbon-shaped pattern is formed. In this experiment, as shown in Fig. 1(a), a pattern of deposited fiber changes as applied voltage changed from 600 to 800 V by 100 V step increase with a constant collector speed 10 mm/s at the fixed TTCD of 1 mm. Similarly, the EF changed accordingly from 6.0 × 105 V/m to 8.0 × 105 V/m. During this transition, the straightness of the pattern tends to decrease along with the arrow direction, indicating increased jet speed as shown in Fig. 1(b). To eliminate deviations between tests, the TTCD was fixed and only applied voltage was controlled during single continuous nanofiber spinning.

## Methodology

###### Cross-Sectional Analysis of Nanofiber.

To accurately quantify the jet speed and jet deposition rate, we analyzed the cross sections of single fibers using SEM images as shown in Fig. 2. We found that the cross-sectional area of nanofibers generated in NFES is not a circular shape and should be considered through delicate approach as shown in Fig. 2(b). The reason is attributed to the fact that the jet lands on the collector before all the solvent evaporates. Therefore, when the jet travels inside a strong EF, charged ions inside the jet experiences stronger attraction force, leading noncircular and larger cross-sectional area. The cross-sectional area (ANFES) is calculated by the following equation, where r is Display Formula

(1)$ANFES=πr2(360−2α)360+r2(sin α cos α)[nm2]$
the radius of nanofiber, and α is an angle shown in Fig. 2(b). SEM image of cross section of nanofiber is obtained from following sequences. First, a gold sputtered electrospun fiber on a silicon substrate was frozen by immersing in a liquid nitrogen chamber for 60 s. Gold sputtering not only functions to make the polymer fiber surface conductive, but it also maintains the shape of the spun fiber during freezing in a liquid nitrogen. Then the silicon substrate was cleaved in perpendicular direction to the fiber followed by immediate storing in a vacuum desiccator until the temperature reached to the room temperature to avoid a rapid thermal expansion, and a contact to moisture. To verify the consistency of the fiber deposition rate at each condition, the cross-sectional area was measured at every 40 mm distance (see Supplemental Figs. S2 and S3 available under the “Supplemental Data” tab for this paper on the ASME Digital Collection).

###### Image Processing of Electrospun Nanofibers.

Quantification of jet speed is based on the analysis of images obtained through an optical microscope mounted on a probe station. The purpose of this image processing is to convert analog optical image to digital binary image such that the area occupied by the fiber can be interpreted as a number of pixels inside the image, which is dependent on the length of the nanofiber. For this analysis, a single continuous nanofiber was deposited using NFES on a titanium coated silicon wafer with a guide mark with 50 μm spacing as shown in Fig. 3(a). An auto-exposure function in the capture software imports the data without changing the color depth. To binarize the RGB as shown in Figs. 3(b) and 3(c), four converting steps were performed in order to enhance the nanofiber's contour intensity and remove noise randomly generated around the fiber [23] (see Supplemental Fig. S4 available under the “Supplemental Data” tab for this paper on the ASME Digital Collection). When the noise remains in the background, the error is included in the black and white (BW) ratio calculation. The source of such noise is varied from different intensities crossing the fiber due to the curvature of fiber to the contour between the fiber and background. The process confirmed that the contour is maintained during the converting steps (see Supplemental Fig. S5 available under the “Supplemental Data” tab for this paper on the ASME Digital Collection). The quantity in a pixel unit and a BW ratio were extracted using a function of the matlab image processing as shown in Figs. 3(d) and 3(f). The result of the image processing is shown in Fig. 3, where the straight line (Fig. 3(d)) occupies 0.76% of the total area in the rectangular image. This means that twice long fiber as in the straight line is deposited when EF of 8.0 × 105 V/m is applied (Fig. 3(f)) during the same period of time. Thus, as the collector was moving at same speed for both cases, it can be assured that the jet speed was doubled with increased EF. Additionally, we counted the portion where the fibers are interstacked in the coil-shaped pattern in which the overlapped volume is shown in Fig. 3(f). Although each intersection represents 0.005–0.009% of the 1331 × 493 pixels, it increases the total BW ratio of the pattern by 0.02–0.04%, suggesting the effect of interstacking of fiber on jet speed calculation is negligible.

###### Determination of Jet Speed, Fiber Volume and Deposition Rate.

From previous experiments, it is confirmed that when the jet speed is higher than the collector speed, coil or ribbon shape is formed. Slowly increasing collector speed leads elimination of coil or ribbon shape and eventually leads to straight fiber. At such instance, the jet speed (vJET) is equivalent to the collector speed (vC). Figure 3(d) shows a specific test result when the jet speed is 10 mm/s. A volume (VFIBER) of the straight fiber is calculated by multiplying a length of the fiber (L) by the cross-sectional area. Then, the deposition rate (R), which represents how much volume of the fiber is collected per unit time (t), is calculated. The number of pixels calculated from the image processing is used to calibrate the corresponding jet speed relative to normalized conditions in which the speed of the jet is already calculated using a straight-line shaped nanofiber. When the BW ratio of the straight pattern is normalized as in Ref. [24], the quantification of the coil or wavy shapes as shown in Figs. 3(e) and 3(f) of the electrospun fiber can be computed by comparing with the BW ratio using following equations (see Supplemental Fig. S6 available under the “Supplemental Data” tab for this paper on the ASME Digital Collection) Display Formula

(2)$vJET=vC(BW ratioBW ratio of perfect straight pattern)−1nm/s$
Display Formula
(3)$VFIBER=ANFESL(BW RatioBW ratio of perfect straight pattern)mL$
Display Formula
(4)$R=VFIBER/t(mL/s)$

## Result and Discussion

###### Cross-Sectional Area and Deformation.

Figure 4(a) shows the change of cross-sectional area of the nanofiber according to the increased applied voltage. We have performed 15 measurements for each applied voltage. As the applied voltage increases, expansion of cross-sectional area was observed. The reason is attributed to more volume of the solution pulled down with the increasing applied voltage, which results in stronger down-force due to the increased electrostatic attraction between charged ions and the collector. When multiple positions were measured in a single continuous pattern, no significant change of cross-sectional area was detected of the total length of 280 mm, providing an evidence of process reliability. However, as the jet was deposited on the collector, partial deformation of the bottom surface of the electrospun fiber occurred as already shown in Fig. 2(b). Compared to the nanofiber generated using far-field electrospinning, the fiber generated in NFES travels significantly short distance before contacting the collector, thus a significant amount of solvent still remain inside the viscous fiber at the instant of contact, which then evaporates quickly after. In addition to the effect of solvent inside the jet, the cross-sectional shape of electrospun fiber on the collector is closely related to the EF that determines the electrostatic force that attracts the jet to the collector. Figure 4(c) shows the cross-sectional morphology of electrospun fibers for each test condition. We found that the chords and the height of the electrospun fiber were increased together by increasing EF, and it was confirmed that the ratio of the two dimensions was maintained as shown in Fig. 4(d). To compare the changes of the ratio due to a surface reaction between the fiber and the collector surface, the silicon wafer was treated in an oxygen plasma, however, no noticeable difference was detected (see Supplemental Fig. S7 available under the “Supplemental Data” tab for this paper on the ASME Digital Collection). Thus, it can be concluded that the deformation is predominantly EF dependent on NFES given other parameters, including polymer solution, are fixed. Generally, a stronger field induces thicker nanofibers, but when an EF above a critical level of 1.5 kV is applied, the fibers collide too strongly against the current collector to flatten the fibers.

###### Quantification of Jet Speed and Fiber Deposition Rate.

Figure 5(a) shows the jet speed associated with the applied voltage. The identification of jet speed was conducted through the analysis of the pattern of electrospun fiber while slowly increasing the collector speed. Based on this test, the jet speed that makes the straight-line at 600 V was identified at the collector speed of 10 mm/s. As such, it is confirmed that the jet speed increased, while the applied voltage is changed from 600 V to 800 V during a continuous process. Continuously increasing the applied voltage resulted in a coiled-shaped deposition at 800 V, suggesting the jet speed exceeded the collector speed. Incorporating the image process introduced in Secs. 3.2 and 3.3 allows quantification of the jet speed, through which about vJET = 19–20 mm/s is predicted at 800 V of applied voltage. As shown in Fig. 5(b), the deposition rate, calculated by multiplying jet speed and cross-sectional area, follows the tendency of the jet speed since there was no noticeable change in the ratio of the height and the chords (see Sec. 3.1).

###### Verification: Patterning From Coil to Straight.

Presented image analysis enables prediction of jet speed without direct measurement. To verify the method, we have performed an NFES processes with the constant applied voltage (800 V) and the TTCD (1 mm) while adjusting the collector speeds from 10 to 25 mm/s (TTCD and collector speed were fixed in Sec. 4.2). Then, the jet speed estimated from this test was compared with the jet speed calculated from the image analysis as shown in Fig. 6(a). At the beginning of the test, the jet speed was higher than the collector speed, thereby coil-shaped nanofibers were deposited. The shape of the electrospun fiber gradually changed from coil shape to straight line as the collector speed increased along with the big arrow direction as shown in Fig. 6. A uniform and neat straight-line is confirmed at the collector speed of 20 mm/s. This result exhibits a reasonable agreement with the quantified jet speed, which was predicted via image analysis as shown in Fig. 5(a). Further increasing the collector speed above 25 mm/s led mechanical stretching of the jet. In general mechanical stretching allows patterning of a straight line. However, the jet speed cannot follow the pattern drawn by the collector, thus patterning of shape which includes curvature results in significant distortion. Even further increasing the collector speed resulted in a discontinuity in the fiber. Figure 6(b) shows stitched images in which the collector speed gradually changes while applied low voltage (400 V), and TTCD is fixed during continuous NFES. These images clearly show the change of jet speed along with varying the applied voltage and electric field, emphasizing the importance of accurate identification of jet speed for precise patterning. The result, on the other hand, implies that the control of jet speed during a continuous electrospinning is available with proper adjustment of applied voltage, collector speed, and TTCD.

## Conclusion

A novel image analysis process is presented to identify and predict the jet speed, fiber volume, and fiber deposition rate in NFES, for the purpose of providing the foundation for precise patterning using electrospinning. To overcome the difficulty of direct measurement, image analysis-based indirect jet speed estimation process is developed, showing good agreement with the experimental result. For the first time, the fiber deposition rate in NFES is calculated in combination with the in-depth investigation of a cross-sectional image of the electrospun nanofiber. It is confirmed that the jet speed as well as jet flow rate tends to increase along with the increasing EF, while the shape of the cross section of nanofiber increases is maintained. It is expected that the presented approach can shed the light on various applications where precision positioning of nanofibers is critical and needed.

## Acknowledgements

This work made use of the University of Utah USTAR shared facilities supported, in part, by the MRSEC Program of the NSF under Award No. DMR-1121252.

## Funding Data

• The Korea Institute of Science and Technology (KIST) Institutional Program (Project No. 2E28130).

## Nomenclature

• ANFES =

cross-sectional area of fiber

• h =

height in cross-sectional fiber surface

• kV =

kilovolt

• L =

length of single fiber

• LC =

length of chord in cross-sectional fiber surface

• r =

• R =

fiber deposition rate, mL/s

• t =

electrospinning time, s

• V =

volt

• vC =

collector speed, mm/s

• vJET =

jet speed, mm/s

• VFIBER =

volume of nanofiber, mL

• α =

angle in cross section of fiber

## References

Reneker, D. H. , and Yarin, A. L. , 2008, “ Electrospinning Jets and Polymer Nanofibers,” Polym. (Guildf)., 49(10), pp. 2387–2425.
Deitzel, J. M. , Kleinmeyer, J. K. , Hirvonen, N. C. , and Beck Tan, N. C. , 2001, “ Controlled Deposition of Electrospun Poly(Ethylene Oxide) Fibers,” Polymer, 42(19), pp. 8163–8170.
Subbiah, T. , Bhat, G. S. , Tock, R. W. , Parameswaran, S. , and Ramkumar, S. S. , 2005, “ Electrospinning of Nanofibers,” J. Appl. Polym. Sci, 96(2), pp. 557–569.
Zhang, S. , Liu, H. , Yin, X. , Li, Z. , Yu, J. , and Ding, B. , 2017, “ Tailoring Mechanically Robust Poly(m-Phenylene Isophthalamide) Nanofiber/Nets for Ultrathin High-Efficiency Air Filter,” Sci. Rep., 7, p. 40550. [PubMed]
Qin, X.-H. , and Wang, S.-Y. , 2006, “ Filtration Properties of Electrospinning Nanofibers,” J. Appl. Polym. Sci., 102(2), pp. 1285–1290.
Yun, K. M. , Hogan, C. J. , Matsubayashi, Y. , Kawabe, M. , Iskandar, F. , and Okuyama, K. , 2007, “ Nanoparticle Filtration by Electrospun Polymer Fibers,” Chem. Eng. Sci., 62(17), pp. 4751–4759.
Barhate, R. S. , and Ramakrishna, S. , 2007, “ Nanofibrous Filtering Media: Filtration Problems and Solutions From Tiny Materials,” J. Membr. Sci., 296(1–2), pp. 1–8.
Huang, C.-Y. , Hu, K.-H. , and Wei, Z.-H. , 2016, “ Comparison of Cell Behavior on PVA/PVA-Gelatin Electrospun Nanofibers With Random and Aligned Configuration,” Sci. Rep., 6(1), p. 37960. [PubMed]
Wang, X. , Ding, B. , and Li, B. , 2013, “ Biomimetic Electrospun Nanofibrous Structures for Tissue Engineering,” Mater. Today, 16(6), pp. 229–241.
Bridge, J. C. , Aylott, J. W. , Brightling, C. E. , Ghaemmaghami, A. M. , Knox, A. J. , Lewis, M. P. , Rose, F. R. A. J. , and Morris, G. E. , 2015, “ Adapting the Electrospinning Process to Provide Three Unique Environments for a Tri-Layered In Vitro Model of the Airway Wall,” J. Vis. Exp., (101), p. e52986.
Har-el, Y. , Gerstenhaber, J. A. , Brodsky, R. , Huneke, R. B. , and Lelkes, P. I. , 2014, “ Electrospun Soy Protein Scaffolds as Wound Dressings: Enhanced Reepithelialization in a Porcine Model of Wound Healing,” Wound Med., 5(5), pp. 9–15.
Chen, S. , Liu, B. , Carlson, M. A. , Gombart, A. F. , Reilly, D. A. , and Xie, J. , 2017, “ Recent Advances in Electrospun Nanofibers for Wound Healing,” Nanomedicine, 12(11), pp. 1335–1352. [PubMed]
Sill, T. J. , and von Recum, H. A. , 2008, “ Electrospinning: Applications in Drug Delivery and Tissue Engineering,” Biomaterials, 29(13), pp. 1989–2006. [PubMed]
Lee, S. , and Obendorf, S. K. , 2007, “ Use of Electrospun Nanofiber Web for Protective Textile Materials as Barriers to Liquid Penetration,” Text. Res. J., 77(9), pp. 696–702.
Garg, K. , and Bowlin, G. L. , 2011, “ Electrospinning Jets and Nanofibrous Structures,” Biomicrofluidics, 5(1), p. 13403. [PubMed]
Reneker, D. , Kataphinan, W. , Theron, A. , Zussman, E. , and Yarin, A. , 2002, “ Nanofiber Garlands of Polycaprolactone by Electrospinning,” Polymer, 43(25), pp. 6785–6794.
Bellan, L. M. , Craighead, H. G. , and Hinestroza, J. P. , 2007, “ Direct Measurement of Fluid Velocity in an Electrospinning Jet Using Particle Image Velocimetry,” J. Appl. Phys., 102(9), p. 94308.
Chang, J. , Dommer, M. , Chang, C. , and Lin, L. , 2012, “ Piezoelectric Nanofibers for Energy Scavenging Applications,” Nano Energy, 1(3), pp. 356–371.
Molnar, K. , 2012, “ Determination of Tensile Strength of Electrospun Single Nanofibers Through Modeling Tensile Behavior of the Nanofibrous Mat,” Compos. Part B Eng., 43(1), pp. 15–21.
Deitzel, J. M. , 2001, “ The Effect of Processing Variables on the Morphology of Electrospun Nanofibers and Textiles,” Polymer, 42(1), pp. 261–272.
Ramakrishna, S. , Fujihara, K. , Teo, W.-E. , Lim, T.-C. , and Ma, Z. , 2005, An Introduction to Electrospinning and Nanofibers, World Scientific, Singapore.
Beachley, V. , and Wen, X. , 2009, “ Effect of Electrospinning Parameters on the Nanofiber Diameter and Length,” Mater. Sci. Eng. C. Mater. Biol. Appl., 29(3), pp. 663–668. [PubMed]
Chhaya, S. , Khera, S. , and Kumar, P. , 2015, “ Basic Geometric Shape and Primary Colour Detection Using Image Processing on Matlab,” IJRET Int. J., 4(5), pp. 505–509.
Indera Putera, S. , and Ibrahim, Z. , 2010, “ Printed Circuit Board Defect Detection Using Mathematical Morphology and MATLAB Image Processing Tools,” IEEE Second International Conference on Education Technology and Computer (ICETC), Shanghai, China, June 22–24, pp. V5-359–V5-363.
View article in PDF format.

## References

Reneker, D. H. , and Yarin, A. L. , 2008, “ Electrospinning Jets and Polymer Nanofibers,” Polym. (Guildf)., 49(10), pp. 2387–2425.
Deitzel, J. M. , Kleinmeyer, J. K. , Hirvonen, N. C. , and Beck Tan, N. C. , 2001, “ Controlled Deposition of Electrospun Poly(Ethylene Oxide) Fibers,” Polymer, 42(19), pp. 8163–8170.
Subbiah, T. , Bhat, G. S. , Tock, R. W. , Parameswaran, S. , and Ramkumar, S. S. , 2005, “ Electrospinning of Nanofibers,” J. Appl. Polym. Sci, 96(2), pp. 557–569.
Zhang, S. , Liu, H. , Yin, X. , Li, Z. , Yu, J. , and Ding, B. , 2017, “ Tailoring Mechanically Robust Poly(m-Phenylene Isophthalamide) Nanofiber/Nets for Ultrathin High-Efficiency Air Filter,” Sci. Rep., 7, p. 40550. [PubMed]
Qin, X.-H. , and Wang, S.-Y. , 2006, “ Filtration Properties of Electrospinning Nanofibers,” J. Appl. Polym. Sci., 102(2), pp. 1285–1290.
Yun, K. M. , Hogan, C. J. , Matsubayashi, Y. , Kawabe, M. , Iskandar, F. , and Okuyama, K. , 2007, “ Nanoparticle Filtration by Electrospun Polymer Fibers,” Chem. Eng. Sci., 62(17), pp. 4751–4759.
Barhate, R. S. , and Ramakrishna, S. , 2007, “ Nanofibrous Filtering Media: Filtration Problems and Solutions From Tiny Materials,” J. Membr. Sci., 296(1–2), pp. 1–8.
Huang, C.-Y. , Hu, K.-H. , and Wei, Z.-H. , 2016, “ Comparison of Cell Behavior on PVA/PVA-Gelatin Electrospun Nanofibers With Random and Aligned Configuration,” Sci. Rep., 6(1), p. 37960. [PubMed]
Wang, X. , Ding, B. , and Li, B. , 2013, “ Biomimetic Electrospun Nanofibrous Structures for Tissue Engineering,” Mater. Today, 16(6), pp. 229–241.
Bridge, J. C. , Aylott, J. W. , Brightling, C. E. , Ghaemmaghami, A. M. , Knox, A. J. , Lewis, M. P. , Rose, F. R. A. J. , and Morris, G. E. , 2015, “ Adapting the Electrospinning Process to Provide Three Unique Environments for a Tri-Layered In Vitro Model of the Airway Wall,” J. Vis. Exp., (101), p. e52986.
Har-el, Y. , Gerstenhaber, J. A. , Brodsky, R. , Huneke, R. B. , and Lelkes, P. I. , 2014, “ Electrospun Soy Protein Scaffolds as Wound Dressings: Enhanced Reepithelialization in a Porcine Model of Wound Healing,” Wound Med., 5(5), pp. 9–15.
Chen, S. , Liu, B. , Carlson, M. A. , Gombart, A. F. , Reilly, D. A. , and Xie, J. , 2017, “ Recent Advances in Electrospun Nanofibers for Wound Healing,” Nanomedicine, 12(11), pp. 1335–1352. [PubMed]
Sill, T. J. , and von Recum, H. A. , 2008, “ Electrospinning: Applications in Drug Delivery and Tissue Engineering,” Biomaterials, 29(13), pp. 1989–2006. [PubMed]
Lee, S. , and Obendorf, S. K. , 2007, “ Use of Electrospun Nanofiber Web for Protective Textile Materials as Barriers to Liquid Penetration,” Text. Res. J., 77(9), pp. 696–702.
Garg, K. , and Bowlin, G. L. , 2011, “ Electrospinning Jets and Nanofibrous Structures,” Biomicrofluidics, 5(1), p. 13403. [PubMed]
Reneker, D. , Kataphinan, W. , Theron, A. , Zussman, E. , and Yarin, A. , 2002, “ Nanofiber Garlands of Polycaprolactone by Electrospinning,” Polymer, 43(25), pp. 6785–6794.
Bellan, L. M. , Craighead, H. G. , and Hinestroza, J. P. , 2007, “ Direct Measurement of Fluid Velocity in an Electrospinning Jet Using Particle Image Velocimetry,” J. Appl. Phys., 102(9), p. 94308.
Chang, J. , Dommer, M. , Chang, C. , and Lin, L. , 2012, “ Piezoelectric Nanofibers for Energy Scavenging Applications,” Nano Energy, 1(3), pp. 356–371.
Molnar, K. , 2012, “ Determination of Tensile Strength of Electrospun Single Nanofibers Through Modeling Tensile Behavior of the Nanofibrous Mat,” Compos. Part B Eng., 43(1), pp. 15–21.
Deitzel, J. M. , 2001, “ The Effect of Processing Variables on the Morphology of Electrospun Nanofibers and Textiles,” Polymer, 42(1), pp. 261–272.
Ramakrishna, S. , Fujihara, K. , Teo, W.-E. , Lim, T.-C. , and Ma, Z. , 2005, An Introduction to Electrospinning and Nanofibers, World Scientific, Singapore.
Beachley, V. , and Wen, X. , 2009, “ Effect of Electrospinning Parameters on the Nanofiber Diameter and Length,” Mater. Sci. Eng. C. Mater. Biol. Appl., 29(3), pp. 663–668. [PubMed]
Chhaya, S. , Khera, S. , and Kumar, P. , 2015, “ Basic Geometric Shape and Primary Colour Detection Using Image Processing on Matlab,” IJRET Int. J., 4(5), pp. 505–509.
Indera Putera, S. , and Ibrahim, Z. , 2010, “ Printed Circuit Board Defect Detection Using Mathematical Morphology and MATLAB Image Processing Tools,” IEEE Second International Conference on Education Technology and Computer (ICETC), Shanghai, China, June 22–24, pp. V5-359–V5-363.

## Figures

Fig. 3

Pattern analysis process: (a) image sampling: spot patterns on the collector silicon wafer for distance guidance, (b) and (c) binarization: converting RGB to B&W image, and (d) and (f) pixel ratio extraction: BW ratio of cropped images which are made by varying EF

Fig. 2

SEM images of electrospun nanofiber: (a) coil-shaped nanofiber made by NFES on the collector substrate and (b) cross-sectional surface of fiber

Fig. 1

Nanofiber patterning: (a) schematic drawing of jet speed change according to varying EF in NFES and (b) microscopic images of electrospun nanofiber patterns with increasing applied voltage

Fig. 4

Result of cross-sectional analysis: (a) cross-sectional area of the fibers with varying applied voltage, (b) cross-sectional areas during continuous NFES, (c) deformation of the cross section by increasing EFs, and (d) the ratio of the height and chord with applied voltages

Fig. 5

Result of quantification: (a) jet speed versus increasing applied voltage and (b) deposition rate versus applied voltage

Fig. 6

Verification result: (a) patterning with fixed applied voltage and the TTCD while the collector speed increases and (b) demonstration of straightening fiber by adjusting collector speed during continuous NFES with low applied voltage range

## Errata

Some tools below are only available to our subscribers or users with an online account.

### Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related Proceedings Articles
Related eBook Content
Topic Collections