Integration of Green Chemistry and a Data-Driven Approach in the Development of Sustainable Nanomaterials
Keywords:
Green chemistry, Data-driven approach, Sustainable nanomaterials, Qualitative case study, Nanomaterial synthesis, Laboratory research cultureAbstract
This study aims to explore the integration of green chemistry and a data-driven approach in the development of sustainable nanomaterials. The issue is important because nanomaterial synthesis increasingly requires safer, more efficient, and environmentally responsible processes, while many laboratories still face challenges in reproducibility, data management, and sustainability assessment. This study used a qualitative case study design involving researchers, laboratory analysts, postgraduate students, and practitioners engaged in nanomaterial synthesis, green synthesis, material characterization, or experimental data processing in Indonesian research laboratories. Data were collected through semi-structured interviews, limited observation, and documentation, then analyzed using thematic analysis. The findings reveal six main themes: green chemistry as laboratory responsibility, reproducibility challenges in green synthesis, the role of data in reducing trial-and-error practices, emerging interest in machine learning, the need for early safety and sustainability assessment, and the importance of research culture in supporting sustainable nanomaterial development. The study shows that the integration of green chemistry and data-driven approaches is not merely a technical matter, but a socio-scientific process shaped by laboratory habits, institutional support, data literacy, and interdisciplinary collaboration. These findings contribute to sustainable nanomaterial studies by offering a qualitative understanding of how researchers interpret, negotiate, and apply sustainability principles in real laboratory contexts. The study implies that laboratories and institutions need stronger data documentation systems, green chemistry training, and safe and sustainable by design guidelines to support responsible nanomaterial innovation.
References
Ahmed, S. K. (2024). The pillars of trustworthiness in qualitative research. Journal of Medicine, Surgery, and Public Health, 2, 100051. https://doi.org/10.1016/j.glmedi.2024.100051
Bouncken, R. B., Qiu, Y., Sinkovics, N., & Sinkovics, R. R. (2025). Purposeful sampling and saturation in qualitative research: A framework for business and management research. Review of Managerial Science. https://doi.org/10.1007/s11846-025-00881-2
Braun, V., & Clarke, V. (2021). Can I use TA? Should I use TA? Should I not use TA? Comparing reflexive thematic analysis and other pattern-based qualitative analytic approaches. Counselling and Psychotherapy Research, 21(1), 37–47. https://doi.org/10.1002/capr.12360
Campbell, S., Greenwood, M., Prior, S., Shearer, T., Walkem, K., Young, S., Bywaters, D., & Walker, K. (2020). Purposive sampling: Complex or simple? Research case examples. Journal of Research in Nursing, 25(8), 652–661. https://doi.org/10.1177/1744987120927206
Chatzipanagiotou, K.-R., Petrakli, F., Steck, J., Philippot, C., Artous, S., & Koumoulos, E. P. (2025). Towards safe and sustainable by design nanomaterials: Risk and sustainability assessment on two nanomaterial case studies at early stages of development. Sustainable Futures, 10, 100511. https://doi.org/10.1016/j.sftr.2025.100511
Dikshit, P. K., Kumar, J., Das, A. K., Sadhu, S., Sharma, S., Singh, S., Gupta, P. K., & Kim, B. S. (2021). Green synthesis of metallic nanoparticles: Applications and limitations. Catalysts, 11(8), 902. https://doi.org/10.3390/catal11080902
Furxhi, I., Bengalli, R., Motta, G., Mantecca, P., Kose, O., Carriere, M., Haq, E. U., O’Mahony, C., Blosi, M., Gardini, D., & Costa, A. (2023). Data-driven quantitative intrinsic hazard criteria for nanoproduct development in a safe-by-design paradigm: A case study of silver nanoforms. ACS Applied Nano Materials, 6(5), 3948–3962. https://doi.org/10.1021/acsanm.3c00173
Furxhi, I., Perucca, M., Blosi, M., Lopez de Ipiña, J., Oliveira, J., Murphy, F., & Costa, A. L. (2022). ASINA project: Towards a methodological data-driven sustainable and safe-by-design approach for the development of nanomaterials. Frontiers in Bioengineering and Biotechnology, 9, 805096. https://doi.org/10.3389/fbioe.2021.805096
Gupta, D., Boora, A., Thakur, A., & Gupta, T. K. (2023). Green and sustainable synthesis of nanomaterials: Recent advancements and limitations. Environmental Research, 231, 116316. https://doi.org/10.1016/j.envres.2023.116316
Ji, Z., Guo, W., Sakkiah, S., Liu, J., Patterson, T. A., & Hong, H. (2021). Nanomaterial databases: Data sources for promoting design and risk assessment of nanomaterials. Nanomaterials, 11(6), 1599. https://doi.org/10.3390/nano11061599
Jia, Y., Hou, X., Wang, Z., & Hu, X. (2021). Machine learning boosts the design and discovery of nanomaterials. ACS Sustainable Chemistry & Engineering, 9(18), 6130–6147. https://doi.org/10.1021/acssuschemeng.1c00483
Johnson, J. L., Adkins, D., & Chauvin, S. (2020). A review of the quality indicators of rigor in qualitative research. American Journal of Pharmaceutical Education, 84(1), 7120. https://doi.org/10.5688/ajpe7120
Kiger, M. E., & Varpio, L. (2020). Thematic analysis of qualitative data: AMEE Guide No. 131. Medical Teacher, 42(8), 846–854. https://doi.org/10.1080/0142159X.2020.1755030
Kumar, S., Ignacz, G., & Szekely, G. (2021). Synthesis of covalent organic frameworks using sustainable solvents and machine learning. Green Chemistry, 23(22), 8932–8939. https://doi.org/10.1039/D1GC02796D
Mulyana, S. D., Sari, R., & Rijal, A. S. (2024). Green synthesis of silver nanoparticles with bioreductant from lime juice powder (Citrus aurantifolia): Effect of concentration and pH. Indonesian Journal of Chemistry, 24(5), 1445–1455. https://doi.org/10.22146/IJC.95283
Parab, A. R., Ramlal, A., Gopinath, S. C. B., & Subramaniam, S. (2025). Forging the future of nanotechnology: Embracing greener practices for a resilient today and a sustainable tomorrow. Frontiers in Nanotechnology, 6, 1506665. https://doi.org/10.3389/fnano.2024.1506665
Priya, A. (2021). Case study methodology of qualitative research: Key attributes and navigating the conundrums in its application. Sociological Bulletin, 70(1), 94–110. https://doi.org/10.1177/0038022920970318
Saha, S. (2025). How nanoinformatics could pave the way to safer design of engineered nanomaterials? Frontiers in Nanotechnology, 7, 1559053. https://doi.org/10.3389/fnano.2025.1559053
Tripathy, A., Patne, A. Y., Mohapatra, S., & Mohapatra, S. S. (2024). Convergence of nanotechnology and machine learning: The state of the art, challenges, and perspectives. International Journal of Molecular Sciences, 25(22), 12368. https://doi.org/10.3390/ijms252212368
Xiao, N., Li, Y., Sun, P., Zhu, P., Wang, H., Wu, Y., Bai, M., Li, A., & Ming, W. (2025). A comparative review: Biological safety and sustainability of metal nanomaterials without and with machine learning assistance. Micromachines, 16(1), 15. https://doi.org/10.3390/mi16010015
Ye, F., Zhou, G., Jin, X., & Chen, Z. (2025). Machine learning-driven green synthesis of iron sulfur nanoparticles: Dual optimization of biosynthesis parameters and heavy metal adsorption performance. Separation and Purification Technology, 374, 133705. https://doi.org/10.1016/j.seppur.2025.133705
Ying, S., Guan, Z., Ofoegbu, P. C., Clubb, P., Rico, C., He, F., & Hong, J. (2022). Green synthesis of nanoparticles: Current developments and limitations. Environmental Technology & Innovation, 26, 102336. https://doi.org/10.1016/j.eti.2022.102336
Zhang, Y., Poon, K., Masonsong, G. S. P., Ramaswamy, Y., & Singh, G. (2023). Sustainable nanomaterials for biomedical applications. Pharmaceutics, 15(3), 922. https://doi.org/10.3390/pharmaceutics15030922
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