Greener pretreatment and the characterization of neem and babul tree barks for lignin extraction

Authors

  • Syed Absar Hasnain Department of Chemical Engineering, BUITEMS University, Quetta, Balochistan, Pakistan.
  • Mohammad Siddique Department of Chemical Engineering, BUITEMS University, Quetta, Balochistan, Pakistan. https://orcid.org/0000-0001-5772-3064
  • Ghulamullah Khan Department of Chemical Engineering, BUITEMS University, Quetta, Balochistan, Pakistan. https://orcid.org/0000-0002-9900-716X
  • Azhar Abass Department of Chemical Engineering, MNS University of Engineering and Technology, Multan, Pakistan.
  • Abdulhalim Musa Abubakar Department of Chemical Engineering, Faculty of Engineering, Modibbo Adama University, PMB 2076, Yola, Adamawa State, Nigeria. https://orcid.org/0000-0002-1304-3515

DOI:

https://doi.org/10.18488/13.v14i2.4555

Abstract

This research is motivated by the limited digital learning platforms capable of integrating various forms of representation to support STEAM-based in-depth learning, particularly in physics subjects that require high conceptual understanding. To address this need, this study aims to describe the feasibility of the Digital Multiple Representation Platform (DMRP) as an innovative learning medium designed to facilitate conceptual understanding and encourage interdisciplinary integration in the STEAM context. This research method uses a Research and Development (R&D) design based on the DDDE (Decide, Design, Develop, and Evaluation) model to systematically guide the platform creation and validation process. Data were collected using an expert validation questionnaire covering aspects of content feasibility, pedagogy, interface appearance, interactivity, and technical aspects. Validation was carried out by learning media experts and physics material experts to assess the quality and suitability of the platform for instructional purposes. In addition to quantitative data, the study also involved qualitative feedback from educators and students through open-ended interviews to obtain an in-depth overview of the platform's practicality and acceptability. Quantitative data were analyzed using descriptive techniques to calculate a feasibility score, while qualitative data were analyzed to identify suggestions for improvement and aspects that support the platform's effectiveness. The results of the study show that the DMRP achieved an average media validation score of 80% and a content validation score of 79%, both of which are categorized as very feasible to be implemented in learning. The conclusion of this study shows that integrating various representations in a digital environment can effectively improve conceptual understanding, creativity, and student engagement in STEAM-oriented physics education. Overall, the developed DMRP offers a pedagogically grounded model to support deep learning and interdisciplinary thinking, which contributes to the development of digital innovation in STEAM education.

Keywords:

Babul tree bark, Extraction of lignin, Lignin, Lignocellulose, Neem tree bark, TGA.

Published

2025-12-01

How to Cite

Hasnain, S. A. ., Siddique, M. ., Khan, G. ., Abass, A. ., & Abubakar, A. M. . (2025). Greener pretreatment and the characterization of neem and babul tree barks for lignin extraction . International Journal of Sustainable Energy and Environmental Research, 14(2), 90–103. https://doi.org/10.18488/13.v14i2.4555