Skip to main content
SpringerLink
Log in

AI-driven electro chromic materials and devices for nanofabrication in machine learning integrated environments

  • Published:
Optical and Quantum Electronics Aims and scope Submit manuscript

Abstract

This study looks into the introduction of AI-driven electrochromic materials and devices into nanofabrication methods for use in ML-integrated environments. When exposed to an electric field, electrochromic materials experience reversible changes in optical properties due to dynamic optical modulation. Because of developments in AI-assisted design, optimization, and fabrication, advanced electrochromic devices with improved performance are now conceivable. The incorporation of AI-optimized electrochromic materials into nanofabrication operations and their application in ML-integrated systems are described, as well as their synthesis and characterization. Several test datasets revealed that the AI-driven strategy improved OME, Response Times, CE, and EE. These findings validate the importance of applying AI algorithms to guide material design, optimize production, and enable real-time adaptation for greater optical modulation and energy efficiency.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Au, B.W.C., Chan, K.Y.: Effect of precursor solution stirring time on the electrochromic performance of tungsten oxide films. Surf. Eng. 36(1), 94–99 (2020)

    Article  CAS  Google Scholar 

  • Campbell, Z.S., Bateni, F., Volk, A.A., Abdel-Latif, K., Abolhasani, M.: Microfluidic synthesis of semiconductor materials: Toward accelerated materials development in flow. Part. Part. Syst. Charact. 37(12), 2000256 (2020)

    Article  CAS  Google Scholar 

  • Chaudhary, A., Pathak, D.K., Tanwar, M., Dash, R., Joshi, B., Keerthivasan, T., Kumar, R.: Hydrothermally grown nano-WO3 electrochromic film: structural and Raman spectroscopic study. Adv. Mater. Process. Technol. 8(1), 970–976 (2022)

    Google Scholar 

  • Deepa, M., Srivastava, A.K., Sood, K.N., Agnihotry, S.A.: Nanostructured mesoporous tungsten oxide films with fast kinetics for electrochromic smart windows. Nanotechnology 17(10), 2625 (2006)

    Article  CAS  PubMed  ADS  Google Scholar 

  • Demir, F., Keles, D., Karabag, A., Cirpan, A., Toppare, L.: A novel multi-electrochromic polymer based on selenophene and benzotriazole via electrochemical and chemical polymerization. J. Macromol. Sci. Part A 56(3), 197–205 (2019)

    Article  CAS  Google Scholar 

  • Dounis, A.I.: Machine intelligence in smart buildings. Energies 16(1), 22 (2022)

    Article  Google Scholar 

  • El Bachiri, A., Soussi, L., Karzazi, O., Louardi, A., Rmili, A., Erguig, H., El Idrissi, B.: Electrochromic and photoluminescence properties of cobalt oxide thin films prepared by spray pyrolysis. Spectrosc. Lett. 52(1), 66–73 (2019)

    Article  ADS  Google Scholar 

  • Hacioglu, S.O., Ataoglu, E., Hizalan, G., Depci, T., Cirpan, A., Toppare, L.: Thiadiazoloquinoxaline and benzodithiophene bearing polymers for electrochromic and organic photovoltaic applications. Phosphorus Sulfur Silicon Relat. Elem. 194(9), 937–946 (2019)

    Article  CAS  Google Scholar 

  • Hagita, K., Aoyagi, T., Abe, Y., Genda, S., Honda, T.: Deep learning-based estimation of Flory-Huggins parameter of A-B block copolymers from cross-sectional images of phase-separated structures. Sci. Rep. 11(1), 12322 (2021)

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  • Huang, C., Dong, B., Lu, N., Yang, B., Gao, L., Tian, L., Chi, L.: A strategy for patterning conducting polymers using nanoimprint lithography and isotropic plasma etching. Small 5(5), 583–586 (2009)

    Article  CAS  PubMed  Google Scholar 

  • Indhumathi, R., Amuthabala, K., Kiruthiga, G., Pandey, A.: Design of task scheduling and fault tolerance mechanism based on GWO algorithm for attaining better QoS in cloud system. Wirel. Pers. Commun. 128(4), 2811–2829 (2023)

    Article  Google Scholar 

  • Jensen, J., Hösel, M., Dyer, A.L., Krebs, F.C.: Development and manufacture of polymer-based electrochromic devices. Adv. Func. Mater. 25(14), 2073–2090 (2015)

    Article  CAS  Google Scholar 

  • Ko, I.J., Park, J.H., Kim, G.W., Lampande, R., Kwon, J.H.: An optically efficient full-color reflective display with an electrochromic device and color production units. J. Inf. Disp. 20(3), 155–160 (2019)

    Article  CAS  Google Scholar 

  • Lee, S., Kim, M.J., Lee, S.H., Jeong, S.H., Kwon, J.H., Jeong, J.K.: Boosting coloration efficiency in an electrochromic device using an ITO/Ag/ITO multilayered electrode and porous WO3 chromic layer. J. Inf. Disp. 23, 1–12 (2023)

    Article  Google Scholar 

  • Manikandan, R., Sara, S. B. V. J., Chaturvedi, A., Priscila, S. S., & Ramkumar, M. (2022). Sequential pattern mining on chemical bonding database in the bioinformatics field. In AIP Conference Proceedings (Vol. 2393, No. 1). AIP Publishing.

  • Raccuglia, P., Elbert, K.C., Adler, P.D., Falk, C., Wenny, M.B., Mollo, A., Norquist, A.J.: Machine-learning-assisted materials discovery using failed experiments. Nature 533(7601), 73–76 (2016)

    Article  CAS  PubMed  ADS  Google Scholar 

  • Raj, F.I.: Implementation of machine learning techniques in unmanned aerial vehicle control and its various applications. In: Computational Intelligence for Unmanned Aerial Vehicles Communication Networks, pp. 17–33. Springer International Publishing, Cham (2022)

    Google Scholar 

  • Selberg, J., Jafari, M., Mathews, J., Jia, M., Pansodtee, P., Dechiraju, H., Rolandi, M.: Machine learning-driven bioelectronics for closed-loop control of cells. Adv. Intell. Syst. 2(12), 2000140 (2020)

    Article  Google Scholar 

  • Surendiran, J., Theetchenya, S., Benson Mansingh, P.M., Sekar, G., Dhipa, M., Alene, A.: Segmentation of optic disc and cup using modified recurrent neural network. Bio Med Res. Int. 2022, 492536 (2022)

    Google Scholar 

  • Tabor, D.P., Roch, L.M., Saikin, S.K., Kreisbeck, C., Sheberla, D., Montoya, J.H., Aspuru-Guzik, A.: Accelerating the discovery of materials for clean energy in the era of smart automation. Nat. Rev. Mater. 3(5), 5–20 (2018)

    Article  CAS  ADS  Google Scholar 

  • Weissman, D.: Heliotropic shading: Daylighting a rare books reading room with electrochromic glass and parametric analysis. LEUKOS 23, 1–24 (2023)

    Article  Google Scholar 

  • Xie, L., Zhao, S., Zhu, Y., Zhang, Q., Chang, T., Huang, A., Bao, S.: High performance and excellent stability of all-solid-state electrochromic devices based on a Li1.85AlOz ion conducting layer. ACS Sustain. Chem. Eng. 7(20), 17390–17396 (2019)

    Article  CAS  Google Scholar 

  • Zifang, X., Yujie, J., Can, G.: Based on the study on preparation and properties of Co (II) and La3+-doped TiO2 electrochromic film. Integr. Ferroelectr. 209(1), 58–67 (2020)

    Article  ADS  Google Scholar 

Download references

Funding

This work was funded by the Researchers Supporting Project No.(RSP2023R363), King Saud University, Riyadh, Saudi Arabia.

Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Vivekananda College of Engineering and Technology, Puttur, Karnataka, 574203, India

    K. Mahesh Prasanna

  2. Department of Electronics and Communication, GLA University, Mathura, India

    Aasheesh Shukla

  3. Department of Computer Science and Engineering, K S R Institute for Engineering and Technology, Tiruchengode, Tamil Nadu, 637215, India

    K. Tamizharasu

  4. Department of Computer Science and Engineering, Parul Institute of Engineering and Technology, Parul University, Post Limda, Waghodia, Gujarat, 391760, India

    Amit Ganatra

  5. Faculty of Law, Symbiosis Law School (SLS), Symbiosis International (Deemed University) (SIU), Vimannagar, Pune, Maharashtra, 411014, India

    Atmaram Shelke

  6. Department of Mathematics, College of Science, King Saud University, 11451, Riyadh, Saudi Arabia

    Ahmed Sayed M. Metwally

  7. Department of Intelligent Mechatronics Engineering, Sejong University, 209 Neungdong-Ro, Gwangjin-Gu, Seoul, 05006, South Korea

    Sikandar Aftab

Authors
  1. K. Mahesh Prasanna
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aasheesh Shukla
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. K. Tamizharasu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Amit Ganatra
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Atmaram Shelke
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ahmed Sayed M. Metwally
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sikandar Aftab
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

K.M.P.: Investigation, methodology, writing—review & editing. A.S.: Conceptualization, formal analysis, writing—review & editing. K.T.: Conceptualization, formal analysis, writing—original draft. A.G.: Writing—review & editing. A.S.: Conceptualization, writing—review & editing. A.S.M.M.: Formal analysis, writing—review & editing. S.A.: Formal analysis, writing—review & editing.

Corresponding author

Correspondence to K. Tamizharasu.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Prasanna, K.M., Shukla, A., Tamizharasu, K. et al. AI-driven electro chromic materials and devices for nanofabrication in machine learning integrated environments. Opt Quant Electron 56, 15 (2024). https://doi.org/10.1007/s11082-023-05656-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11082-023-05656-1

Keywords

Search

Navigation