Restoring Kanpur: Advanced Nanomembranes for Clean Water
2025 HSHRC Finalist Proposal
By: Pranav Ayyappan & Gabriel Cacho, 2025 HSHRC Finalists
Water pollution poses a substantial threat to human health and the environment. Water-stressed areas are regions that experience a significant shortage of fresh water to meet the demands of their populations and ecosystems. Tackling both water pollution and water shortages is crucial for creating a sustainable future for the environment and the people affected by these challenges. The World Health Organization (WHO) reports that 1.1 billion individuals lack access to improved drinking water, contributing to 88% of the 4 billion annual cases of diarrheal diseases attributed to unsafe water and inadequate sanitation, resulting in approximately 1.8 million deaths each year (Al-Manhel et al.). According to Anna Lee, a Ph.D. from the University of Toronto in materials chemistry, the World Health Organization reports that 3,900 children die daily from diseases linked to unsafe water or poor hygiene. The U.N. World Water Development Report warns that by 2050, at least a quarter of the global population will face chronic freshwater shortages, exacerbating this critical issue (Lee et al.). Chlorination and desalination creates harmful byproduct while desalination is costly and takes up a lot of energy.
The study develops and evaluates a composite water filtration membrane made with electrospun chitosan nanofibers, graphene oxide, and surface-appended antimicrobial peptides leveraged by artificial intelligence. Chitosan-based membranes have shown promise in recent literature, with chitosan consistently yielding high efficiency in removing various pollutants, including heavy metals and bacteria. Graphene oxide, because of its high surface area and electrical conductivity, has also demonstrated efficiency in water membranes by enhancing performance, selectivity, and stability. Surface modification with antimicrobial peptides further enhances membrane durability and anti-fouling properties.
The proposed membrane system was analyzed using Wave (a simulation software by DuPont) to assess its efficiency in contaminant removal. Wave has been a revolutionary tool for engineers and researchers in the water treatment industry as it provides extreme accuracy and performance evaluations for the design of systems. The recovery of ultrafiltration was highest for the Graphene Oxide membrane at a value of 77.72%, while for the Full Membrane, it was 79.54%. In the case of Chitosan Nanofibers membranes, the recovery rate was 67.40%, whereas the Antimicrobial Peptides showed an intermediary recovery rate of 71.15%.These recovery percentages are telling that the features of this system namely Graphene Oxide with Chitosan Nanofibers and Antimicrobial Peptides can lead to a better overall ultrafiltration recovery than the Full Membrane. The transmembrane pressure was investigated at 10 and 25°C to determine the robustness and effectiveness of the membranes when used in actual conditions. The GO membrane at 10°C had a TMP of 0.16 Bar, which was higher than that of the Chitosan and AMP membranes, which were 0.08 and 0.07 Bars respectively. The best performance was given by the Full Membrane at 0.06 Bar indicating that by combining the materials, the transmembrane pressure could be reduced for low energy consumption during filtration. At 25°C, the Graphene Oxide membranes still had relatively higher TMP of 0.11 Bar, Chitosan Nanofibers and Antimicrobial Peptides membranes had 0.05 Bar each, but the Full Membrane was the best of all with 0.04 Bar TMP and it seems that the use of combined material would result in better performance or lower pressure requirement in this case. In the case of Net Product, both Graphene Oxide and Full Membrane gave the same result of 0.8. The efficiency of the Chitosan Nanofibers and Antimicrobial Peptides membranes was found to be slightly lower than that of the Full Membrane as they had a net product of 0.7, which means that the Full Membrane material helped in achieving the best results.
The model utilizes CatBoost, an advanced implementation of gradient boosting, selected due to its excellent performance in the process of handling complex biological sequence data as well as the modeling capabilities related to non-linear relationships between peptide features and antimicrobial activity. The modeling was done on Jupyter Notebook using scikit-learn, a framework provided by Python, for developing the data pre-processing and model evaluation. Feature engineering on peptide sequences is included, creating scales of hydrophobicity, charge distribution, and secondary structure predictions that allow better prediction capabilities. The evaluation of the AI model reveals several model performance metrics, including an F1 score of 0.86, accuracy of 92%, precision of 84%, recall of 82%, and an ROC-AUC score of 0.86. The F1 score, which represents the harmonic mean of precision and recall, is particularly valuable in this context because it balances the trade-off between false positives and false negatives. Additionally, a high F1 score indicates that the model is effective at correctly identifying waterborne pathogens while minimizing misclassifications.
For widespread application, the proposed nanomembrane should be economical and scalable. The blend of the nanofibers of chitosan and the oxide of graphene with the use of antimicrobial peptides constitutes an exceptionally effective membrane, although the cost of preparation remains a critical issue. The estimated price of $100–250 per membrane competes with the price of other state-of-the-art filtration technologies such as desalination and the use of reverse osmosis (RO). Compared with the latter with a large energy demand and regular replacements of the membrane, the proposed design has a lower transmembrane of 0.04 Bar and thus lower energy consumption and a higher life of the membrane.
Our results showed that chitosan and graphene oxide enhance the filtration efficiency of the membrane with antimicrobial peptides adding protection over pathogens in polluted waters. Moreover, adding AI and machine learning enhances performance and improves the sensitivity for detecting pathogens. The membrane developed in this study is relevant to both large-scale industrial applications and decentralized, portable water treatment systems. This technology can help improve access to clean water for millions of people around the world, especially in regions with water scarcity and contamination issues, by offering a more cost-effective and environmentally sustainable approach to water purification.
Works Cited
Abdel-Fatah, M. A. (2018). Nanofiltration systems and applications in wastewater treatment:
Review article. Ain Shams Engineering Journal, 9(4), 3077–3092.
https://doi.org/10.1016/j.asej.2018.08.001
Al-Manhel, A. J., et al. (2016). Extraction of chitosan, characterization, and its use for water
purification. Journal of the Saudi Society of Agricultural Sciences, 15(4), 433–439.
https://doi.org/10.1016/j.jssas.2016.04.001
Anis, S. F., et al. (2019). Microfiltration membrane processes: A review of research trends over
the past decade. Journal of Water Process Engineering, 32, 100941.
https://doi.org/10.1016/j.jwpe.2019.100941
Bhatnagar, A., & Sillanpää, M. (2009). Applications of chitin- and chitosan-derivatives for the
detoxification of water and wastewater — A short review. Advances in Colloid and
Interface Science, 152(1-2), 26–38. https://doi.org/10.1016/j.cis.2009.09.003
Binnie, C., et al. (2009). Basic water treatment (4th ed.). Thomas Telford Limited.
https://doi.org/10.1680/bwt.36086
Brizuela, C. A., Liu, G., Stokes, J. M., & de la Fuente‐Nunez, C. (2025). AI Methods for
Antimicrobial Peptides: Progress and Challenges. Microbial Biotechnology, 18(1).
https://doi.org/10.1111/1751-7915.70072
Chen, Y., et al. (2023). Construction of antimicrobial peptides/alginate multilayers modified
membrane: Antibiofouling performance and mechanisms. Chemical Engineering
Journal, 472, 144814. https://doi.org/10.1016/j.cej.2023.144814
Croitoru, A.-M., et al. (2020). Chitosan/graphene oxide nanocomposite membranes as adsorbents
with applications in water purification. Materials, 13(7), 1687.
https://doi.org/10.3390/ma13071687
Cui, L., et al. (2018). Preparation and characterization of chitosan membranes. RSC Advances,
8(50), 28433–28439. https://doi.org/10.1039/c8ra05526b
Desai, K., et al. (2008). Morphological and surface properties of electrospun chitosan nanofibers.
Biomacromolecules, 9(3), 1000–1006. https://doi.org/10.1021/bm701017z
Dwivedi, A. (2017). Researches in water pollution: A review experiment findings. International
Research Journal of Natural and Applied Sciences, 4(1).
https://doi.org/10.13140/RG.2.2.12094.08002
Lee, A., et al. (2016). Membrane materials for water purification: Design, development, and
application. Environmental Science: Water Research & Technology, 2(1), 17–42.
https://doi.org/10.1039/c5ew00159e
Mehranbod, N., et al. (2021). Modification and superhydrophilization of electrospun
polyvinylidene fluoride membrane using graphene oxide-chitosan nanostructure and
performance evaluation in oil/water separation. Journal of Environmental Chemical
Engineering, 9(5), 106245. https://doi.org/10.1016/j.jece.2021.106245
Melucci, M., Khaliha, S., Bianchi, A., Kovtun, A., Tunioli, F., Boschi, A., Zambianchi, M., Paci,
D., Bocchi, L., Valsecchi, S., Polesello, S., Liscio, A., Palermo, V., & Navacchia, M. L.
(2022). Graphene oxide nanosheets for drinking water purification by tandem adsorption
and microfiltration. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4103321
Min, L.-L., et al. (2014). Preparation of chitosan based electrospun nanofiber membrane and its
adsorptive removal of arsenate from aqueous solution. Chemical Engineering Journal,
267, 132–141. https://doi.org/10.1016/j.cej.2014.12.024
Miretzky, P., & Fernandez Cirelli, A. (2009). Hg(II) removal from water by chitosan and
chitosan derivatives: A review. Journal of Hazardous Materials, 167(1-3), 10–23.
https://doi.org/10.1016/j.jhazmat.2009.01.060
Patra, A., et al. (2022). Marine antimicrobial peptides-based strategies for tackling bacterial
biofilm and biofouling challenges. Molecules, 27(21), 7546.
https://doi.org/10.3390/molecules27217546
Pellis, A., et al. (2022). Chitosan: Sources, processing, and modification techniques. Gels, 8(7),
393. https://doi.org/10.3390/gels8070393
Prasetya, D. S. B., et al. (2021). Synthesis nanofiber PVA/chitosan using electrospinning method
and application for gold recovery. Indonesian Review of Physics (IRiP), 4(1), 27–31.
https://doi.org/10.12928/irip.v4i1.3601
Reyes-Guzmán, V. L., Villarreal-Gómez, L. J., Vázquez-Mora, R., Méndez-Ramírez, Y. I.,
Paz-González, J. A., Zizumbo-López, A., Borbón, H., Lizarraga-Medina, E. G.,
Cornejo-Bravo, J. M., Pérez-González, G. L., Ontiveros-Zepeda, A. S., Pérez-Sánchez,
A., Chavira-Martínez, E., Huirache-Acuña, R., & Estévez-Martínez, Y. (2024).
Integrating an antimicrobial nanocomposite to bioactive electrospun fibers for improved
wound dressing materials. Scientific Reports, 14(1).
https://doi.org/10.1038/s41598-024-75814-2
Sakib, M. N., et al. (2021). Update on chitosan-based electrospun nanofibers for wastewater
treatment: A review. Carbohydrate Polymer Technologies and Applications, 2, 100064.
https://doi.org/10.1016/j.carpta.2021.100064
Santy, S., et al. (2020). Potential impacts of climate and land use change on the water quality of
Ganga River around the industrialized Kanpur region. Scientific Reports, 10(1).
https://doi.org/10.1038/s41598-020-66171-x
Schwarzenbach, R. P., et al. (2010). Global water pollution and human health. Annual Review of
Environment and Resources, 35(1), 109–136.
https://doi.org/10.1146/annurev-environ-100809-125342
Sowers, A., Wang, G., Xing, M., & Li, B. (2023). Advances in antimicrobial peptide discovery
via machine learning and delivery via nanotechnology. Microorganisms, 11(5), 1129.
https://doi.org/10.3390/microorganisms11051129
Travkova, O. G., et al. (2017). The interaction of antimicrobial peptides with membranes.
Advances in Colloid and Interface Science, 247, 521–532.
https://doi.org/10.1016/j.cis.2017.06.001
Yang, Z., Zhang, Y., & Zhang, L. (2019). Electrospun chitosan/poly (vinyl alcohol)/graphene
oxide nanofibrous membrane with ciprofloxacin antibiotic drug for potential
wound-dressing application. International Journal of Molecular Sciences, 20(18), 4395.
https://doi.org/10.3390/ijms20184395
Zheng, Y., et al. (2023). Preparation of graphene oxide/carboxymethyl chitosan/polyvinyl alcohol
composite nanofiber membranes by electrospinning for heavy metal adsorption. Journal
of Applied Polymer Science, 141(4). https://doi.org/10.1002/app.54840
