Ali Akbar Gharehaghaji

Amirkabir University of Technology

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Mehdi Sadrjahani

Urmia University of Technology

Mehran Javanbakht

Amirkabir University of Technology

Roohollah Bagherzadeh

Amirkabir University of Technology

Milad Razbin

Amirkabir University of Technology

and M. Shanbeh

Sayed Abolfazl Mirdehghan

Amirkabir University of Technology

Ali Akbar Merati

Amirkabir University of Technology

Majid Montazer

Amirkabir University of Technology

Mortaza Salehian

Amirkabir University of Technology

Seyedeh Nooshin Banitaba

Amirkabir University of Technology

Cooperative Institutions

Amirkabir University of Technology

Isfahan University of Technology

Imam Reza Hospital

Academic Center for Education, Culture and Research

National Research Council Canada

Natural Sciences and Engineering Research Council

Polytechnic School of Algiers

Centre de Recherche Nucléaire d’Alger

Gifu University

University of Toronto

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USING ARTIFICIAL NEURAL NETWORK ALGORITHM TO PREDICT TENSILE PROPERTIES OF COTTON-COVERED NYLON CORE YARNS

Journal of Advanced Materials in Engineering (Esteghlal) (2006)

Ali Akbar Gharehaghaji Maziar Palhang and M. Shanbeh

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Citations (1)

Modeling and optimization of sulfonated poly (ether ether ketone) nanofibrous proton exchange membranes with response surface methodology

Polymer Engineering and Science (2017)

Mehdi Sadrjahani Ali Akbar Gharehaghaji Mehran Javanbakht

The morphological control of proton conductive nanofibrous mat used in proton exchange membranes (PEMs) is a key issue to improve proton conductivity of PEMs. In this study, response surface methodology (RSM) was utilized to investigate the morphological characterizations of electrospun sulfonated poly (ether ether ketone) (SPEEK) nanofibrous membranes. The effects of electrospinning parameters namely solution concentration, applied voltage and tip to collector distance were studied on the average diameter, its standard deviation and the degree of alignment of SPEEK nanofibers. The adequacy of the response surface models was verified by the validation experiments. Optimized conditions were obtained to meet the desired status of collecting more uniform and finer nanofibers with improved alignment. After obtaining the significant factors and optimal test level, an additional optimization was conducted at different take‐up speeds to fabricate high‐grade aligned nanofibers. The resultant nanofibers had the diameter of 107 ± 22 nm at the optimum point which was in good agreement with the predicted response values. The highest degree of alignment was yielded at the take‐up speed of 8.8 m/s with the maximum second‐order orientation parameter of 0.869. Electrochemical spectroscopy analysis showed that the aligning of proton conductive nanofibers improved in‐plane proton conductivity about 67%. POLYM. ENG. SCI., 2017. © 2017 Society of Plastics Engineers

Electrospinning

10.1002/pen.24591

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Porous PAN micro/nanofiber separators for enhanced lithium-ion battery performance

Solid State Ionics (2018)

Niloufar Sabetzadeh Ali Akbar Gharehaghaji Mehran Javanbakht

Polyacrylonitrile

Electrospinning

Separator (oil production)

Phase inversion

10.1016/j.ssi.2018.08.013

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Citations (39)

List of Contributors

Elsevier eBooks (2021)

Somaye Akbari Razieh Aladpoosh Golchehr Amini Roohollah Bagherzadeh Seyedeh Nooshin Banitaba

10.1016/b978-0-12-824381-7.00019-6

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Aligned electrospun sulfonated polyetheretherketone nanofiber based proton exchange membranes for fuel cell applications

Polymer Engineering and Science (2016)

Mehdi Sadrjahani Ali Akbar Gharehaghaji Mehran Javanbakht

In this study, electrospinning of sulfonated poly(ether ether ketone) (SPEEK) at different degrees of sulfonation (DS) was investigated. The polymer solution concentration of 22 wt% was obtained to collect smooth fiber in nanoscale range of 112 to 131 nm at various conditions. SEM observations of SPEEK nanofibers showed the decrease of diameter with increasing DS from 74% to 81%, mainly due to the increase of electrical conductivity of polymer solution at higher DS. The increase of collecting speed from 20 to 305 m/min decreased the diameter of nanofibers slightly and improved their alignment. The presence of SO3H groups in collected nanofibers was demonstrated with FT-IR analysis. WAXD patterns of SPEEK nanofibers indicated featureless amorphous peak with no crystalline regions that was broaden at higher DS and aligned nanofibers. The electrochemical impedance spectroscopy of SPEEK nanofibers showed the through-plane proton conductivity of fully hydrated nanofibrous membranes measured at room temperature were improved with DS. The proton conductivity of randomly oriented and aligned nanofibers were measured from 0.0098 to 0.0722 S/cm and from 0.0592 to 0.0907 S/cm, respectively. Aligned nanofibers exhibited more proton conductivity than randomly collected nanofibers. POLYM. ENG. SCI., 57:789–796, 2017. © 2016 Society of Plastics Engineers

Electrospinning

10.1002/pen.24453

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Citations (30)

A viscoelastic-plastic model for the core of various close-packings of multifilament polyamide-6 yarns

Scientific Reports (2024)

Milad Razbin Mortaza Salehian Ali Akbar Gharehaghaji

Different forms of close-packed yarns can be produced by varying the number of monofilaments in the core region, ranging from one to five. Numerous efforts have been made to model or simulate the mechanical response of close-packed yarns; however, previous studies have predominantly focused on one or two monofilaments in the core. In this study, we propose an analytical approach that combines a geometrical model with an artificial neural network (ANN) to predict the tensile behavior of close-packed yarns containing 2 to 5 monofilaments in the core region. The novelty of this hybrid model lies not only in accounting for more than two monofilaments in the core but also in extending the prediction range from elastic to viscoelastic-plastic behavior. Validation of the proposed method showed excellent agreement between experimental and theoretical results. Numerical simulations further confirmed that the results align with theoretical predictions, demonstrating the model's accuracy in predicting the tensile behavior of close-packed yarns. This modeling approach has the potential to significantly improve the understanding and modeling of textile structures.

10.1038/s41598-024-74602-2

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Semi-auxetic piezoresistive textronic

Scientific Reports (2025)

Milad Razbin Sharhbanou Ehsanpour Ali Akbar Gharehaghaji Roohollah Bagherzadeh

Auxetic textile sensors represent a new generation of wearable sensors, offering advantages such as high sensitivity, enhanced mechanical properties, and greater comfort due to their suitable physical features. Research in this field remains limited and is still in its nascent stages. In this work, a piezoresistive sensor with a negative Poisson's ratio was developed using the design concept of semi-auxetic yarn, where a stretchable band replaced the core to serve as a substrate for the piezoresistive sensors. A semi-auxetic piezoresistive textronic structure was created by stitching the sensors onto the substrate in a zig-zag pattern. Electromechanical analysis highlighted a trade-off between auxetic behaviour and sensitivity, with the highest sensitivity (−4.8) observed in a structure with a stitching length of 2 cm, and the highest auxeticity (−14.1) found in a structure with a stitching length of 3 cm. This type of piezoresistive textronic is suitable for applications such as yoga straps, driving safety belts, compression bandages, and breathable belly belts for pregnant women.

Auxetics

Piezoresistive effect

10.1038/s41598-024-83330-6

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