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Artificial Neural Networks modeling of electrospun polyurethane nanofibers from chloroform/methanol solution

Saman Firoozi1,a, Amir Amani 1,2,b *, Mohammad Ali Derakhshan1,c, Hossein Ghanbari1,2,d

1Department of Medical Nanotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran.

2Medical Biomaterials research Center, and Department of Medical Nanotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran.

[email protected]; [email protected]; [email protected]; [email protected];

*Corresponding author: Amir Amani, 1417755469, Tel: +98(21)88991118-24, Fax: +98(21)88991117.

Keywords: Electrospinning, Nanofiber; Polyurethane; Artificial Neural Networks; diameter.

Abstract In this study, electrospun nanofibers of polyurethane were prepared utilizing a new

solvent system made of chloroform/methanol. Also, we planned to assess effects of four important

parameters on diameter of electrospun polyurethane nanofibers using Artificial Neural Networks

(ANNs). The parameters investigated included flow rate of syringe pump, distance of spinneret to

collector, applied voltage and concentration of polymer solution. Diameter of obtained electrospun

nanofibers was measured using scanning electron microscopy (SEM). Results showed that flow rate

and distance had reverse relation with fiber diameter, while applied voltage and concentration of

polymer solution directly affected the diameter. Also, polymer concentration was shown to be the

dominant factor here.

1. Introduction

Electrospinning is one of the most common techniques to fabricate ultrathin fibers with

diameters ranging from submicron to nanometer [1]. Compared to other methods, this approach

benefits from advantages of simplicity, scalability and being cost-effective [2-5]. Nanofibrous

electrospun mats have found applications in different fields including tissue engineering [6], drug

delivery systems [7], waterproof breathable fabrics [8], microwave absorption [9] and sensors [10].

Generally, nanofiber refers to fibers with diameters below 100 nm [11]. Diameter has an

important role in determining mechanical, electrical, optical and biomedical properties of fibers [4].

Studies have demonstrated that reducing the diameter of polymeric fibers, enhances degree of

crystallinity and molecular orientation of fibers and therefore, improves mechanical strength [12].

Also, Georgory et al. have shown that fiber diameter plays an important role on proliferation and

differentiation of neural stem/progenitor cells [13].

Several parameters affect physicochemical properties of electrospun nanofibers. The main

external factors include solution flow rate, electric field and distance between spinneret and

collector. The main internal factors are nature of solvent and polymers, surface tension, viscosity,

conductivity and concentration of the solution [14]. In the literature, few studies have focused on

determining factors influencing diameter and morphology of polyurethane (PU) fibers as a common

polymer in both industrial and biomedical applications [15-17]. Indeed, PU has found applications

in a variety of fields due to its unique thermal, mechanical and chemical characteristics [17]. Demir

et al. [18] have studied effects of process and solution parameters on size and morphology of

electrospun PU copolymer. They mentioned that nanofibrous polymers can be obtained when

concentration of solution is between 3.8 to 12.8 wt. % [19]. It was noticed that increasing distance

of needle to collector or decreasing applied voltage leads to a decreased number of produced beads.

Also, by increasing the temperature, thinner fibers with uniform morphology were produced. Zhuo

Journal of Nano Research Submitted: 2015-08-09ISSN: 1661-9897, Vol. 41, pp 18-30 Revised: 2016-02-21doi:10.4028/www.scientific.net/JNanoR.41.18 Accepted: 2016-02-22© 2016 Trans Tech Publications, Switzerland Online: 2016-05-04

All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of TransTech Publications, www.ttp.net. (ID: 129.137.5.42, University of Cincinnati, Cincinnati, USA-24/05/16,09:09:19)

http://dx.doi.org/10.4028/www.scientific.net/JNanoR.41.18

et al. [20] investigated the impact of processing parameters such as applied voltage, flow rate and

solution concentration on the morphology and diameters of the electrospun PU fibers in

dimethylformamide (DMF) as a solvent. In order to reach similar nanofibers without bead, they

prepared 5-7 wt. % PU solution when rate of injection was 0.06-0.08 ml/hour and applied voltage

was controlled in a range of 10-15kV. Nevertheless, none of the mentioned reports systemically

investigated the relations between different parameters. Furthermore, the employed one-factor-at-a-

time approach is not capable of covering the whole factor space in a study [21]. The only systematic

work published on PU nanofibers is a report by Shoushtari et al. which evaluated effect of tip to

collector distance, applied voltage and polymer concentration on fiber diameters [22].

On the other hand, electrospinning is an ambiguous process [3] in which detecting

relationships between influencing parameters and physicochemical properties of nanofibers is

complex and time-consuming [19]. Thus, application of a modeling approach to estimate fiber

diameters and find the relations between independent factors and the size could be a useful

approach. Applying artificial neural networks (ANNs) as a modeling technique, which mimics

structure of a neural brain, in order to analyze data especially for highly interconnected and fused

data could be a proper option. According to literature, ANNs modeling is a promising technique to

predict fiber diameters [19, 23, 24].

In the present study, PU nanofibers were successfully produced in a new solvent system

comprised of chloroform/methanol. Electrospinning process was followed to investigate the impact

of four electrospinning parameters including polymer concentration, applied voltage, feeding rate

and working distance on the average diameter of the resultant nanofibers. Then, scanning electron

microscopy (SEM) images were obtained and average diameters of resultant nanofibers were

calculated. Finally, analyses were conducted utilizing ANNs modeling.

2. Materials and Methods

2.1 Materials

Biomedical grade polyurethane (PU, TecoflexTM

, SG-80A) was purchased from Lubrizol (USA).

Chloroform and methanol were obtained from Merck chemicals (Germany). Electrospun nanofiber

samples were fabricated by an Electroris machine (FNM Ltd., Tehran, Iran).

2.2. Electrospinning of the solutions and characterization

The electrospinning apparatus has been detailed previously. PU polymer solutions with

concentrations (2-8% w/w) were prepared in a chloroform/methanol (70/30) solvent system. Then,

as-prepared solutions were loaded into a 5-cc syringe which was connected to an 18G needle.

Thereafter, electrospinning of the solutions were conducted in a series of applied voltages (15-20

kV), flow rates (0.5-1 ml/h) and tip to drum distances (70-180 mm). All of the electrospinning

processes were performed at ambient conditions.

Diameter and morphology of the obtained nanofibrous specimens were observed using

scanning electron microscopy (SEM, AIS 2100, Seron, South Korea) after sputtering with gold.

Then, 30 fibers in each image were selected randomly and mean diameter of the fibers was

measured by Image J software (NIH, USA).

2.3 Artificial neural networks (ANNs) modeling

In this study, four parameters including applied voltage (kV), polymer concentration (wt. %),

rate of injection (ml/h) and working distance (mm) were considered as input parameters and mean

fiber diameters were determined as output. The study was followed to model and assess impact of

the input parameters on alterations of average diameters in the prepared PU nanofibers utilizing

ANNs. Electrospinning of 31 different samples were carried out and thereafter, the acquired

nanofiber sheets were characterized by SEM. The achieved data was fed to the software. Using

INForm v4.02 (Intelligensys, UK), the data were randomly divided in two categories including

training and test data sets. The network was trained using the parameters listed in Table 1 to figure

out relations between inputs/output variables.

Journal of Nano Research Vol. 41 19

Table1: The Training Parameters Set with INForm v4.0.

Network structure

No. of hidden layers 1

No. of nodes in hidden layer 5

Back prop. type Angle Driven Learning

Back propagation

parameters

Momentum factor 0.8

Learning rate 0.7

Targets Maximum iterations 1000

MS error 0.0001

Random seed 10000

Smart stop Minimum iterations 20

Test error weighting 0.1

Iteration overshoot 200

Auto weight On

Smart stop enabled On

Transfer function Output Asymmetric Sigmoid

Hidden layer Asymmetric Sigmoid

The test data (i.e. 10% of data set, as recommended by the software) were employed to cease

training process at incidence of overtraining. Besides, as recommended by the software, the

maximum number of training repetition was set to 1000. Following the training process, further

nine samples (see Table 2) were prepared and analyzed by SEM as validation data to evaluate the

susceptibility of trained network in prediction of "unseen" data (validation data). To measure the

quality of the trained model, the predicting ability of the model was confirmed using correlation

coefficient R-square (R²) for training, test and validation data from Eq. (1):

2

2

)(

)ˆ(

1

1

12

∑

∑

=

=

−

−

−=n

i

ii

n

i

ii

yy

yy

R (Eq. 1)

According to the equation, is the value predicted by the model and is the mean variable.

Table2: The Validation (unseen) Data sets Used in ANNS Modelling.

Concentration

(Wt. %)

Distance

(mm)

Flow Rate

(ml/h)

Voltage

(kV)

Z-

Average

Z-

Average_predicted

Z-

Average_error

8.0 100 1.0 20 1065 1167.050 102.052

6.0 130 0.6 16 685 691.994 6.99428

4.0 70 0.5 20 600 676.413 76.4131

4.0 100 0.5 15 514 616.296 102.296

4.0 130 0.5 15 547 557.536 10.5358

3.5 70 0.5 15 767 550.659 -216.341

2.0 130 1.0 20 436 420.090 -15.9102

3.0 70 0.5 20 426 330.810 -95.1895

3.0 180 1.0 15 478 376.110 -101.89

20 Journal of Nano Research Vol. 41

3. Results

Solvent system is an important parameter influencing the productivity, morphology and

diameter of electrospun nanofibers [25]. Therefore, a variety of different solvent systems were

utilized to dissolve electrospinning polymers. In this respect, electrospun PU nanofibers were

prepared using different solvents including Hexafluoroisopropanol (HFIP), Dimethylformamide

(DMF), Tetrahydrofuran (THF)/Dimethylacetamide (DMAc) and DMF/THF. The most frequently

used solvent is HFIP [26] which can form smooth, defect-free fibers compared with other solvents

such as DMF or THF [27]. However, HFIP is rather expensive and solvents such as DMF and

DMAc are highly toxic. Thus, a less toxic, cost-effective solvent system which can form bead-free

electrospun PU nanofibers would be desirable. In our work, for the first time, a solvent system

comprised of chloroform/methanol (70/30) was selected. In this system, chloroform is the main

solvent to dissolve the PU polymers and methanol was added to improve spinnability of the

prepared solution. Fig. 1 depicts an SEM image of the obtained electrospun nanofibers in a

chloroform/methanol solvent system.

Fig. 1: PU nanofibers prepared in chloroform/methanol (70/30) as a solvent system.

After fabrication of the PU nanofibers in different electrospinning conditions, data was

modeled by ANNs with the best prediction model giving R2

values of 75.8%, 71.7% and 71.9% for

training, test and unseen data, respectively, showing a fairly appropriate model. As described

previously [4, 23, 24], to estimate fibers diameter, two parameters were fixed in two states (low and

high). We then evaluated impact of other two variables on the diameter based on the response

surfaces obtained from the model (depicted in 3D plots). In the Fig. 2, influence of flow rate (ml/h)

and distance (mm) on fibers diameter is illustrated when voltage (kV) and concentration (wt. %)

have been fixed. From the details, flow rate does not appear to substantially affect the diameter.

The only exception is when both concentration and voltage have been fixed at high values. In

addition, when the distance is high, flow rate has a reverse effect on the diameter. Furthermore, the

figure shows that when voltage is low, increasing the distance make the diameter smaller. While at

high values of voltage, the relations become complicated and no clear rule may be obtained between

the value of distance and diameter.

In Fig. 3 effects of voltage and concentration on fibers diameter have been assessed while other two

parameters are fixed. By increasing concentration of the polymer solution, diameter of electrospun

fibers increases but when voltage of electrospinning process increases, no important change is

observed at diameter. The only exception is when concentration is high whereby a small increase in

diameter is observed at voltage values of ~16-18. This means that this specific voltage acts as a

critical point in determining the diameter.


In Fig. 4 influence of voltage and flow rate on diameter of the fibers have been evaluated when

concentration and distance were considered as constant values. The details show that flow rate is

not importantly influencing the diameter, while a direct and non-linear effect is observed between

voltage and diameter.

Fig. 2: 3D Plots of nanofibers predicted by the ANNs model stabilized at low and high values of the

applied voltage and concentration.

In Fig. 5 role of flow rate and concentration on fibers diameter have been visualized while distance

and voltage were considered as fixed values. The details show that increase in flow rate makes a

small decrease in diameter, while the effect of concentration is more pronounced a sharp decrease in

diameter is observed when concentration is decreased.


Fig. 3: 3D Plots of Nanofibers Predicted by the ANNs Model Stabilized at Low and High values of

the Distance and Flow rate.

Fig. 6 details the influence of distance and concentration on fibers diameter when voltage and flow

rate have specific values. The influence of concentration on the diameter is direct, as discussed

above. Also, in general, increasing the distance value makes a small decrease in diameter.

From Fig. 7, where the effect of voltage and distance on diameter has been illustrated, the smallest

diameter is obtained when voltage is minimum and distance is maximum. Also, similar to above-

findings, distance has a reverse effect on diameter, generally.



the Concentration and Distance.



the Applied Voltage and Distance.

To brief the findings, following rules may be obtained as the effect of different input parameters on

the output:

- In general, the effect of flow rate does not appear to be substantial. - Increasing the distance makes the diameter slightly smaller. - Decreasing voltage makes the diameter smaller. This effect is however not linear and

usually a threshold ~16-18 kV is required to make this decrease.

- Increasing concentration of the polymer solution makes a substantial increase in diameter of electrospun fibers. This parameter appears to be the dominant factor in determining the

diameter value.



the Applied Voltage and Flow Rate.



the Concentration and Flow Rate.

4. Discussion

In this study, the influence of four parameters including distance of needle to collector, flow rate of

solution, applied voltage and concentration on diameter of electrospun PU nanofibers was assessed.

By modification of theses parameters, a wide range of fibers diameter (198 nm – 1065 nm) was

produced. In a report, a binary solvent system (THF and DMAc) was introduced and

electrospinning was performed with various ratio of THF/DMAc. The average diameter decreased

from 1100 to 500 nm a ratio of DMAc increased from 20 to 80 % [28]. In another study, different

proportions of chloroform and methanol were chosen to prepare nanofibers of polycaprolactone

(PCL). Optimum fibers were obtained at chloroform / methanol ratio of 3:1, with mean diameter of

fibers as 1361nm which are considerably thick [29]. Polyurethane nanofibers have been fabricated

by DMF/THF (40:60) as a binary solvent system. Obtained fibers diameter was in the range of 235

to 386 nm [22].

Flow rate is one of the most important parameters in electrospinning process. In some studies, it has

been mentioned that a direct relationship between flow rate and diameter of the fibers is observed

[30, 31], as more amount of materials flow through the tip results in an increased fiber diameter

[32]. Other cases have demonstrated that by increasing flow rate, the diameter reduces, though [33,

34]. This is probably due to fact that when the flow rate is decreased, less polymer solution will

leave the needle per unit of time and more amount of solvent will be evaporated and concentration


of polymer solution elevates on tip of needle. So the nanofibers which reach the collector will

contain minimum solvent residue, thus, an increase in fibers diameter is expected [4]. But our

results showed that flow rate is not affecting the size notably, which is probably a result of both

mechanisms mentioned above.

Distance of needle to collector is another parameter to be considered. In this modeling, the results

showed that by increasing working distance, diameter of the fibers decreases. According to the

literature, usually an inverse effect on the diameter of the fibers is expected [30, 35, 36], although,

in some studies a direct relation has been reported [30, 34]. Also in some reports , no relation

between the working distance and fibers diameter has been demonstrated [22]. The probable reason

lies in the formation of additional jets in front of the needle, which, in turn, leads to thinner fiber

production [4].

Applied voltage is also playing a role in determining fibers diameter. Our findings showed that by

increasing applied voltage at a critical value (~16-18 kV) a sharp increase in diameter is observed.

Further values of voltage are not considerably changing the diameter afterwards. This is against

other reports which commonly indicate no important relation between applied voltage and fibers

diameter [37, 38]. It is arguable that during jet ejection, columbic repulsion leads to instability of

charged fluid. So, by increasing the electric potential, further stretching of the jet is expected which

in turn leads to production of thinner fibers [39, 40].

The effect of polymer concentration is probably the dominant factor in determining the diameter.

Lots of papers indicate that concentration has direct relation with fibers diameter [4, 22, 24]. It is

now well-known that viscosity and surface tension of solution are major parameters in determining

nanofiber morphology. By rising polymer concentration, viscosity of polymers will be increased.

Thus, mobility of polymer chains becomes limited and more stretching occurs on the jet which

eventually makes an increase in diameter of the fibers [14].

5. Conclusions

In this study, electrospun PU nanofibers were successfully fabricated from a chloroform/methanol

solvent system. The obtained mats were characterized by SEM. Thereafter, utilizing ANNs, a

qualified model was generated to study the influence of important and effective parameters on

electrospun nanofibers. Using this approach, effect of a variety of parameters including polymer

concentration, solution flow rate, working distance and applied voltage on the mean diameter of

electrospun nanofibers was investigated. From the results, the impact of solution flow rate on the

fibers’ diameter was not considerable. However, increasing the distance of needle to collector

showed a reverse effect on diameter. Also, applied voltage and concentration of the polymeric

solution appeared to play more important roles on the size of nanofibers with a direct effect on the

diameters.

Acknowledgments

This research has been supported by Tehran University of Medical Sciences & Health Services

grant No. 93-04-87-27088.

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