Imagine a world where prosthetics can feel, robots can sense the subtlest touch, and wearable health monitors seamlessly track your well-being. This vision is becoming a reality thanks to electronic skin, or e-skin, a revolutionary technology poised to transform how we interact with the world. And at the heart of this innovation? The dream of creating electronic skin (e-skin), a flexible, stretchable, and highly sensitive material that mimics the functions of human skin, is rapidly becoming a reality. At the heart of this technological advancement lies a critical component: nanomaterials. Nanomaterials are revolutionizing the field of electronic skin, enabling the creation of flexible, sensitive, and biocompatible devices. Their unique properties, including high surface area, enhanced conductivity, and tailorable attributes, are driving the emergence of e-skins with a diverse range of applications. As research continues to advance, nanomaterials will undoubtedly play an even more crucial role in realizing the full potential of this transformative technology, bridging the gap between electronics and the human body.

Keywords-Nanomaterial, e-skin, Sensing Pressure, Strain, Chemical Changes.

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Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Kazi Kutubuddin Sayyad Liyakat, Impact of Nanotechnology on Battlefield Welfare: A Study. International journal of Nanobiotechnology. 2024; 10(02): 19-32p.
2. Kazi Sultanabanu Sayyad Liyakat and Kazi Kutubuddin Sayyad Liyakat, Nanosensors in Agriculture Field: A Study. International Journal of Applied Nanotechnology. 2024; 10(02): 12-22p. Available from:https://journalspub.com/publication/ijan-v10i02-11625/
3. Kazi Kutubuddin Sayyad Liyakat, Nanotechnology in Space Study. International Journal of Applied Nanotechnology. 2024; 10(02): 39-46p. Available from:https://journalspub.com/publication/ijan-v10i02-11616/
4. Kazi Kutubuddin Sayyad Liyakat. (2024). KSK Approach to Smart Agriculture: Utilizing AI-Driven Internet of Things (AI IoT). Journal of Microcontroller Engineering and Applications. 2024; 11(03):21-32.
5. Kazi Kutubuddin Sayyad Liyakat. (2024). Microwave Communication in the Internet of Things: A Study. Journal of RF and Microwave Communication Technologies, 38–49. Retrieved from https://matjournals.net/engineering/index.php/JoRFMCT/article/view/1276
6. Kazi Kutubuddin Sayyad Liyakat, (2023).Nanorobotics: A Review, International Journal of Applied Nanotechnology (IJAN), 9(2), pp. 36 – 43. DOI:https://doi.org/10.37628/ijan.v9i2.1019
7. K K Sayyad Liyakat. (2024). Impact of Nanotechnology on Battlefield Welfare: A Study. International Journal of Nanobiotechnology. 2024; 10(2): 19– 32p.
8. Sultanabanu Sayyad Liyakat, (2024q). Nanotechnology in Healthcare Applications: A Study. International Journal of Nanobiotechnology. 2024; 10(2): 48–58p.
9. Volume 4, Issue 4, pp. 410 – 418.
10. Kazi Kutubuddin Sayyad Liyakat (2024). Nanotechnology in Medical Applications: A Study. Nano Trends: A Journal of Nanotechnology and Its Applications. 2024; 26(2): 1–11p.
11. Kazi Kutubuddin Sayyad Liyakat. (2024). Nanotechnology in BattleField: A Study. Journal of Nanoscience, Nanoengineering & Applications. 2024; 14(2): 18–30p.
12. Sultananbanu Sayyad Liyakat Kazi, (2024). Polymer Applications in Energy Generation and Storage: A Forward Path. Journal of Nanoscience, Nanoengineering & Applications. 2024; 14(2): 31–39p.
13. Kazi Sultanabanu Sayyad Liyakat, (2023). Accepting Internet of Nano-Things: Synopsis, Developments, and Challenges. Journal of Nanoscience, Nanoengineering & Applications. 2023; 13(2): 17–26p. DOI: https://doi.org/10.37591/jonsnea.v13i2.1464
14. Mishra Sunil B., et al. (2024). Nanotechnology's Importance in Mechanical Engineering, Journal of Fluid Mechanics and Mechanical Design, 6(1), 1-9.
15. Springer, Singapore.https://doi.org/10.1007/978-981-99-3932-9_12 available at: https://link.springer.com/chapter/10.1007/978-981-99-3932-9_12
16. M Pradeepa, et al. (2022). Student Health Detection using a Machine Learning Approach and IoT, 2022 IEEE 2^nd Mysore sub section International Conference (MysuruCon), Available at: https://ieeexplore.ieee.org/document/9972445
17. K. S. Liyakat. (2023).Detecting Malicious Nodes in IoT Networks Using Machine Learning and Artificial Neural Networks, 2023 International Conference on Emerging Smart Computing and Informatics (ESCI), Pune, India, 2023, pp. 1-5, doi:10.1109/ESCI56872.2023.10099544. Available at: https://ieeexplore.ieee.org/document/10099544/
18. Kasat, N. Shaikh, V. K. Rayabharapu, M. Nayak. (2023). Implementation and Recognition of Waste Management System with Mobility Solution in Smart Cities using Internet of Things, 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), Trichy, India, 2023, pp. 1661-1665, doi: 10.1109/ICAISS58487.2023.10250690 . Available at: https://ieeexplore.ieee.org/document/10250690/
19. Kazi, K. (2024b). Modelling and Simulation of Electric Vehicle for Performance Analysis: BEV and HEV Electrical Vehicle Implementation Using Simulink for E-Mobility Ecosystems. In L. D., N. Nagpal, N. Kassarwani, V. Varthanan G., & P. Siano (Eds.), E-Mobility in Electrical Energy Systems for Sustainability (pp. 295-320). IGI Global.https://doi.org/10.4018/979-8-3693-2611-4.ch014 Available at: https://www.igi-global.com/gateway/chapter/full-text-pdf/341172
20. Kazi, K. S. (2024a). Computer-Aided Diagnosis in Ophthalmology: A Technical Review of Deep Learning Applications. In M. Garcia & R. de Almeida (Eds.), Transformative Approaches to Patient Literacy and Healthcare Innovation(pp. 112-135). IGI Global. https://doi.org/10.4018/979-8-3693-3661-8.ch006  Available at: https://www.igi-global.com/chapter/computer-aided-diagnosis-in-ophthalmology/342823
21. Prashant K Magadum (2024). Machine Learning for Predicting Wind Turbine Output Power in Wind Energy Conversion Systems, Grenze International Journal of Engineering and Technology, Jan Issue, Vol 10, Issue 1, pp. 2074-2080. Grenze ID: 01.GIJET.10.1.4_1 Available at: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=2514&id=8
22. Priya Mangesh Nerkar, BhagyarekhaUjjwalganeshDhaware. (2023). Predictive Data Analytics Framework Based on Heart Healthcare System (HHS) Using Machine Learning, Journal of Advanced Zoology, 2023, Volume 44, Special Issue -2, Page 3673:3686.  Available at: https://jazindia.com/index.php/jaz/article/view/1695
23. Neeraja, R. G. Kumar, M. S. Kumar, K. K. S. Liyakat and M. S. Vani. (2024), DL-Based Somnolence Detection for Improved Driver Safety and Alertness Monitoring. 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT), Greater Noida, India, 2024, pp. 589-594, doi: 10.1109/IC2PCT60090.2024.10486714. Available at: https://ieeexplore.ieee.org/document/10486714
24. Liyakat Kazi, K. S. (2024). ChatGPT: An Automated Teacher's Guide to Learning. In R. Bansal, A. Chakir, A. Hafaz Ngah, F. Rabby, & A. Jain (Eds.), AI Algorithms and ChatGPT for Student Engagement in Online Learning(pp. 1-20). IGI Global. https://doi.org/10.4018/979-8-3693-4268-8.ch001
25. Veena, M. Sridevi, K. K. S. Liyakat, B. Saha, S. R. Reddy and N. Shirisha,(2023). HEECCNB: An Efficient IoT-Cloud Architecture for Secure Patient Data Transmission and Accurate Disease Prediction in Healthcare Systems, 2023 Seventh International Conference on Image Information Processing (ICIIP), Solan, India, 2023, pp. 407-410, doi: 10.1109/ICIIP61524.2023.10537627. Available at: https://ieeexplore.ieee.org/document/10537627
26. Rajendra Prasad, Santoshachandra Rao Karanam (2024). AI in public-private partnership for IT infrastructure development, Journal of High Technology Management Research, Volume 35, Issue 1, May 2024, 100496. https://doi.org/10.1016/j.hitech.2024.100496
27. Kazi Kutubuddin, (2024d). A Novel Approach on ML based Palmistry,Grenze International Journal of Engineering and Technology, Vol 10, Issue 2, pp- 5186-5193. Grenze ID: 01.GIJET.10.2.393. Available at: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=3344&id=8
28. Mahant, M. A. (2025). Machine Learning-Driven Internet of Things (MLIoT)-Based Healthcare Monitoring System. In N. Wickramasinghe (Ed.), Digitalization and the Transformation of the Healthcare Sector(pp. 205-236). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-9641-4.ch007
29. Priya Nerkar and Kazi Sultanabanu, (2024). IoT-Based Skin Health Monitoring System, International Journal of Biology, Pharmacy and Allied Sciences (IJBPAS). 2024, 13(11): 5937-5950. https://doi.org/10.31032/IJBPAS/2024/13.11.8488
30. Sayyad (2025f). KK Approach to Increase Resilience in Internet of Things: A T-Cell Security Concept. In D. Darwish & K. Charan (Eds.), Analyzing Privacy and Security Difficulties in Social Media: New Challenges and Solutions (pp. 87-120). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-9491-5.ch005
31. Kazi, K. S. (2025). Machine Learning-Driven Internet of Medical Things (ML-IoMT)-Based Healthcare Monitoring System. In B. Soufiene & C. Chakraborty (Eds.), Responsible AI for Digital Health and Medical Analytics(pp. 49-86). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-6294-5.ch003
32. Prashant K Magadum (2024). Machine Learning for Predicting Wind Turbine Output Power in Wind Energy Conversion Systems, Grenze International Journal of Engineering and Technology, Jan Issue, Vol 10, Issue 1, pp. 2074-2080. Grenze ID: 01.GIJET.10.1.4_1
33. Altaf O. Mulani, Arti Vasant Bang, Ganesh B. Birajadar, Amar B. Deshmukh, Hemlata Makarand Jadhav, (2024). IoT Based Air, Water, and Soil Monitoring System for Pomegranate Farming, Annals of Agri-Bio Research. 29 (2): 71-86, 2024.
34. Keerthana, R. and K, Mrs. Vinutha and Bhagyalakshmi, K and Papinaidu, M. and V, Venkatesh and Liyakat, Kazi Kutubuddin Sayyad, Machine Learning Based Risk Assessment for Financial Management in Big Data IoT Credit (November 15, 2024). Available at SSRN: https://ssrn.com/abstract=5086671or http://dx.doi.org/10.2139/ssrn.5086671
35. Mulani AO, Liyakat KKS, Warade NS, et al. ML-powered Internet of Medical Things Structure for Heart Disease Prediction. Journal of Pharmacology and Pharmacotherapeutics. 2025;0(0). doi:1177/0976500X241306184

Imagine a world where prosthetics can feel, robots can sense the subtlest touch, and wearable health monitors seamlessly track your well-being. This vision is becoming a reality thanks to electronic skin, or e-skin, a revolutionary technology poised to transform how we interact with the world. And at the heart of this innovation? The dream of creating electronic skin (e-skin), a flexible, stretchable, and highly sensitive material that mimics the functions of human skin, is rapidly becoming a reality. At the heart of this technological advancement lies a critical component: nanomaterials. Nanomaterials are revolutionizing the field of electronic skin, enabling the creation of flexible, sensitive, and biocompatible devices. Their unique properties, including high surface area, enhanced conductivity, and tailorable attributes, are driving the emergence of e-skins with a diverse range of applications. As research continues to advance, nanomaterials will undoubtedly play an even more crucial role in realizing the full potential of this transformative technology, bridging the gap between electronics and the human body.

Keywords-Nanomaterial, e-skin, Sensing Pressure, Strain, Chemical Changes.

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Kazi Kutubuddin Sayyad Liyakat, Impact of Nanotechnology on Battlefield Welfare: A Study. International journal of Nanobiotechnology. 2024; 10(02): 19-32p.
2. Kazi Sultanabanu Sayyad Liyakat and Kazi Kutubuddin Sayyad Liyakat, Nanosensors in Agriculture Field: A Study. International Journal of Applied Nanotechnology. 2024; 10(02): 12-22p. Available from:https://journalspub.com/publication/ijan-v10i02-11625/
3. Kazi Kutubuddin Sayyad Liyakat, Nanotechnology in Space Study. International Journal of Applied Nanotechnology. 2024; 10(02): 39-46p. Available from:https://journalspub.com/publication/ijan-v10i02-11616/
4. Kazi Kutubuddin Sayyad Liyakat. (2024). KSK Approach to Smart Agriculture: Utilizing AI-Driven Internet of Things (AI IoT). Journal of Microcontroller Engineering and Applications. 2024; 11(03):21-32.
5. Kazi Kutubuddin Sayyad Liyakat. (2024). Microwave Communication in the Internet of Things: A Study. Journal of RF and Microwave Communication Technologies, 38–49. Retrieved from https://matjournals.net/engineering/index.php/JoRFMCT/article/view/1276
6. Kazi Kutubuddin Sayyad Liyakat, (2023).Nanorobotics: A Review, International Journal of Applied Nanotechnology (IJAN), 9(2), pp. 36 – 43. DOI:https://doi.org/10.37628/ijan.v9i2.1019
7. K K Sayyad Liyakat. (2024). Impact of Nanotechnology on Battlefield Welfare: A Study. International Journal of Nanobiotechnology. 2024; 10(2): 19– 32p.
8. Sultanabanu Sayyad Liyakat, (2024q). Nanotechnology in Healthcare Applications: A Study. International Journal of Nanobiotechnology. 2024; 10(2): 48–58p.
9. Volume 4, Issue 4, pp. 410 – 418.
10. Kazi Kutubuddin Sayyad Liyakat (2024). Nanotechnology in Medical Applications: A Study. Nano Trends: A Journal of Nanotechnology and Its Applications. 2024; 26(2): 1–11p.
11. Kazi Kutubuddin Sayyad Liyakat. (2024). Nanotechnology in BattleField: A Study. Journal of Nanoscience, Nanoengineering & Applications. 2024; 14(2): 18–30p.
12. Sultananbanu Sayyad Liyakat Kazi, (2024). Polymer Applications in Energy Generation and Storage: A Forward Path. Journal of Nanoscience, Nanoengineering & Applications. 2024; 14(2): 31–39p.
13. Kazi Sultanabanu Sayyad Liyakat, (2023). Accepting Internet of Nano-Things: Synopsis, Developments, and Challenges. Journal of Nanoscience, Nanoengineering & Applications. 2023; 13(2): 17–26p. DOI: https://doi.org/10.37591/jonsnea.v13i2.1464
14. Mishra Sunil B., et al. (2024). Nanotechnology's Importance in Mechanical Engineering, Journal of Fluid Mechanics and Mechanical Design, 6(1), 1-9.
15. Springer, Singapore.https://doi.org/10.1007/978-981-99-3932-9_12 available at: https://link.springer.com/chapter/10.1007/978-981-99-3932-9_12
16. M Pradeepa, et al. (2022). Student Health Detection using a Machine Learning Approach and IoT, 2022 IEEE 2^nd Mysore sub section International Conference (MysuruCon), Available at: https://ieeexplore.ieee.org/document/9972445
17. K. S. Liyakat. (2023).Detecting Malicious Nodes in IoT Networks Using Machine Learning and Artificial Neural Networks, 2023 International Conference on Emerging Smart Computing and Informatics (ESCI), Pune, India, 2023, pp. 1-5, doi:10.1109/ESCI56872.2023.10099544. Available at: https://ieeexplore.ieee.org/document/10099544/
18. Kasat, N. Shaikh, V. K. Rayabharapu, M. Nayak. (2023). Implementation and Recognition of Waste Management System with Mobility Solution in Smart Cities using Internet of Things, 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), Trichy, India, 2023, pp. 1661-1665, doi: 10.1109/ICAISS58487.2023.10250690 . Available at: https://ieeexplore.ieee.org/document/10250690/
19. Kazi, K. (2024b). Modelling and Simulation of Electric Vehicle for Performance Analysis: BEV and HEV Electrical Vehicle Implementation Using Simulink for E-Mobility Ecosystems. In L. D., N. Nagpal, N. Kassarwani, V. Varthanan G., & P. Siano (Eds.), E-Mobility in Electrical Energy Systems for Sustainability (pp. 295-320). IGI Global.https://doi.org/10.4018/979-8-3693-2611-4.ch014 Available at: https://www.igi-global.com/gateway/chapter/full-text-pdf/341172
20. Kazi, K. S. (2024a). Computer-Aided Diagnosis in Ophthalmology: A Technical Review of Deep Learning Applications. In M. Garcia & R. de Almeida (Eds.), Transformative Approaches to Patient Literacy and Healthcare Innovation(pp. 112-135). IGI Global. https://doi.org/10.4018/979-8-3693-3661-8.ch006  Available at: https://www.igi-global.com/chapter/computer-aided-diagnosis-in-ophthalmology/342823
21. Prashant K Magadum (2024). Machine Learning for Predicting Wind Turbine Output Power in Wind Energy Conversion Systems, Grenze International Journal of Engineering and Technology, Jan Issue, Vol 10, Issue 1, pp. 2074-2080. Grenze ID: 01.GIJET.10.1.4_1 Available at: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=2514&id=8
22. Priya Mangesh Nerkar, BhagyarekhaUjjwalganeshDhaware. (2023). Predictive Data Analytics Framework Based on Heart Healthcare System (HHS) Using Machine Learning, Journal of Advanced Zoology, 2023, Volume 44, Special Issue -2, Page 3673:3686.  Available at: https://jazindia.com/index.php/jaz/article/view/1695
23. Neeraja, R. G. Kumar, M. S. Kumar, K. K. S. Liyakat and M. S. Vani. (2024), DL-Based Somnolence Detection for Improved Driver Safety and Alertness Monitoring. 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT), Greater Noida, India, 2024, pp. 589-594, doi: 10.1109/IC2PCT60090.2024.10486714. Available at: https://ieeexplore.ieee.org/document/10486714
24. Liyakat Kazi, K. S. (2024). ChatGPT: An Automated Teacher's Guide to Learning. In R. Bansal, A. Chakir, A. Hafaz Ngah, F. Rabby, & A. Jain (Eds.), AI Algorithms and ChatGPT for Student Engagement in Online Learning(pp. 1-20). IGI Global. https://doi.org/10.4018/979-8-3693-4268-8.ch001
25. Veena, M. Sridevi, K. K. S. Liyakat, B. Saha, S. R. Reddy and N. Shirisha,(2023). HEECCNB: An Efficient IoT-Cloud Architecture for Secure Patient Data Transmission and Accurate Disease Prediction in Healthcare Systems, 2023 Seventh International Conference on Image Information Processing (ICIIP), Solan, India, 2023, pp. 407-410, doi: 10.1109/ICIIP61524.2023.10537627. Available at: https://ieeexplore.ieee.org/document/10537627
26. Rajendra Prasad, Santoshachandra Rao Karanam (2024). AI in public-private partnership for IT infrastructure development, Journal of High Technology Management Research, Volume 35, Issue 1, May 2024, 100496. https://doi.org/10.1016/j.hitech.2024.100496
27. Kazi Kutubuddin, (2024d). A Novel Approach on ML based Palmistry,Grenze International Journal of Engineering and Technology, Vol 10, Issue 2, pp- 5186-5193. Grenze ID: 01.GIJET.10.2.393. Available at: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=3344&id=8
28. Mahant, M. A. (2025). Machine Learning-Driven Internet of Things (MLIoT)-Based Healthcare Monitoring System. In N. Wickramasinghe (Ed.), Digitalization and the Transformation of the Healthcare Sector(pp. 205-236). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-9641-4.ch007
29. Priya Nerkar and Kazi Sultanabanu, (2024). IoT-Based Skin Health Monitoring System, International Journal of Biology, Pharmacy and Allied Sciences (IJBPAS). 2024, 13(11): 5937-5950. https://doi.org/10.31032/IJBPAS/2024/13.11.8488
30. Sayyad (2025f). KK Approach to Increase Resilience in Internet of Things: A T-Cell Security Concept. In D. Darwish & K. Charan (Eds.), Analyzing Privacy and Security Difficulties in Social Media: New Challenges and Solutions (pp. 87-120). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-9491-5.ch005
31. Kazi, K. S. (2025). Machine Learning-Driven Internet of Medical Things (ML-IoMT)-Based Healthcare Monitoring System. In B. Soufiene & C. Chakraborty (Eds.), Responsible AI for Digital Health and Medical Analytics(pp. 49-86). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-6294-5.ch003
32. Prashant K Magadum (2024). Machine Learning for Predicting Wind Turbine Output Power in Wind Energy Conversion Systems, Grenze International Journal of Engineering and Technology, Jan Issue, Vol 10, Issue 1, pp. 2074-2080. Grenze ID: 01.GIJET.10.1.4_1
33. Altaf O. Mulani, Arti Vasant Bang, Ganesh B. Birajadar, Amar B. Deshmukh, Hemlata Makarand Jadhav, (2024). IoT Based Air, Water, and Soil Monitoring System for Pomegranate Farming, Annals of Agri-Bio Research. 29 (2): 71-86, 2024.
34. Keerthana, R. and K, Mrs. Vinutha and Bhagyalakshmi, K and Papinaidu, M. and V, Venkatesh and Liyakat, Kazi Kutubuddin Sayyad, Machine Learning Based Risk Assessment for Financial Management in Big Data IoT Credit (November 15, 2024). Available at SSRN: https://ssrn.com/abstract=5086671or http://dx.doi.org/10.2139/ssrn.5086671
35. Mulani AO, Liyakat KKS, Warade NS, et al. ML-powered Internet of Medical Things Structure for Heart Disease Prediction. Journal of Pharmacology and Pharmacotherapeutics. 2025;0(0). doi:1177/0976500X241306184