Artificial Intelligence and Machine Learning Tools for High-Performance Microalgal Wastewater Treatment and Algal Biorefinery: A Critical Review
Abstract
The increased water scarcity, depletion of freshwater resources, and rising environmental awareness are stressing for the development of sustainable wastewater treatment processes. Microalgae-based wastewater treatment has resulted in a paradigm shift in our approach toward nutrient removal and simultaneous resource recovery from wastewater. Wastewater treatment and the generation of biofuels and bioproducts from microalgae can be coupled to promote the circular economy synergistically. A microalgal biorefinery transforms microalgal biomass into biofuels, bioactive chemicals, and biomaterials. The large-scale cultivation of microalgae is essential for the commercialization and industrialization of microalgae biorefinery. However, the inherent complexity of microalgal cultivation parameters regarding physiological and illumination parameters renders it challenging to facilitate a smooth and cost-effective operation. Artificial intelligence (AI)/machine learning algorithms (MLA) offer innovative strategies for assessing, predicting, and regulating uncertainties in algal wastewater treatment and biorefinery. The current study presents a critical review of the most promising AI/MLAs that demonstrate a potential to be applied in microalgal technologies. The most commonly used MLAs include artificial neural networks, support vector machine, genetic algorithms, decision tree, and random forest algorithms. Recent developments in AI have made it possible to combine cutting-edge techniques from AI research fields with microalgae for accurate analysis of large datasets. MLAs have been extensively studied for their potential in microalgae detection and classification. However, the ML application in microalgal industries, such as optimizing microalgae cultivation for increased biomass productivity, is still in its infancy. Incorporating smart AI/ML-enabled Internet of Things (IoT) based technologies can help the microalgal industries to operate effectively with minimum resources. Future research directions are also highlighted, and some of the challenges and perspectives of AI/ML are outlined. As the world is entering the digitalized industrial era, this review provides an insightful discussion about intelligent microalgal wastewater treatment and biorefinery for researchers in the field of microalgae.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Studies indicate that PSO and SA methods significantly improve efficiency of biodiesel production by precisely regulating nitrogen and phosphorus content in the culture medium.
“Studies indicate that these methods significantly improve the efficiency of biodiesel production by precisely regulating the nitrogen and phosphorus content in the culture medium [243].”
From Multi-Sensing Monitoring of the Microalgae Biomass Cultivation Systems for Biofuels and Added Value Products Synthesis—Challenges and Opportunities (2025) · cites this paper as [243]
An integrated AI-driven cultivation framework offers potential to enhance process control accuracy for large-scale production.
“An integrated, AI-driven cultivation framework offers the potential to improve biomass yield by 30–50%, reduce nutrient and energy consumption, and enhance process control accuracy for large-scale production [15,16,17].”
From Harnessing Artificial Intelligence to Revolutionize Microalgae Biotechnology: Unlocking Sustainable Solutions for High-Value Compounds and Carbon Neutrality (2025) · cites this paper as [15]
An integrated AI-driven cultivation framework offers potential to improve biomass yield by 30-50% for large-scale production.
“An integrated, AI-driven cultivation framework offers the potential to improve biomass yield by 30–50%, reduce nutrient and energy consumption, and enhance process control accuracy for large-scale production [15,16,17].”
From Harnessing Artificial Intelligence to Revolutionize Microalgae Biotechnology: Unlocking Sustainable Solutions for High-Value Compounds and Carbon Neutrality (2025) · cites this paper as [15]
An integrated AI-driven cultivation framework offers potential to reduce nutrient and energy consumption.
“An integrated, AI-driven cultivation framework offers the potential to improve biomass yield by 30–50%, reduce nutrient and energy consumption, and enhance process control accuracy for large-scale production [15,16,17].”
From Harnessing Artificial Intelligence to Revolutionize Microalgae Biotechnology: Unlocking Sustainable Solutions for High-Value Compounds and Carbon Neutrality (2025) · cites this paper as [15]
Cites
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126 · see citing works
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421 · see citing works
Deep learning in neural networks: an overview
Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570 · see citing works
Chen, C.-Y., Yeh, K.-L., Aisyah, R., Lee, D.-J., & Chang, J.-S. (2011) · Bioresource Technology · doi:10.1016/j.biortech.2010.06.159 · Cited by 1,860 · see citing works
Production and harvesting of microalgae for wastewater treatment, biofuels, and bioproducts
Christenson, L., & Sims, R. C. (2011) · Biotechnology Advances · doi:10.1016/j.biotechadv.2011.05.015 · Cited by 1,386 · see citing works
Microalgae biorefinery: High value products perspectives
Chew, K. W., Yap, J. Y., Show, P. L., Suan, N. H., Juan, J. C., Ling, T. C., Lee, D.-J., & Chang, J.-S. (2017) · Bioresource Technology · doi:10.1016/j.biortech.2017.01.006 · Cited by 1,336 · see citing works
Self-citationA comprehensive review on automation in agriculture using artificial intelligence
Jha, K., Doshi, A., Patel, P., & Shah, M. (2019) · Artificial Intelligence in Agriculture · doi:10.1016/j.aiia.2019.05.004 · Cited by 1,011 · see citing works
Microalgae-Based Wastewater Treatment for Nutrients Recovery: A Review
Li, K., Liu, Q., Fang, F., Luo, R., Lu, Q., Zhou, W., Huo, S., Cheng, P., Liu, J., Addy, M., et al. (2019) · Bioresource Technology · doi:10.1016/j.biortech.2019.121934 · Cited by 737 · see citing works
Conversion of Microalgae to Biofuel
Suali, E., & Sarbatly, R. (2012) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2012.03.047 · Cited by 456 · see citing works
Guo, H., Wu, S., Tian, Y., Zhang, J., & Liu, H. (2020) · Bioresource Technology · doi:10.1016/j.biortech.2020.124114 · Cited by 378 · see citing works
Third generation biofuels from microalgae
Dragone, G., Fernandes, B. D., Vicente, A. A., & Teixeira, J. A. (2010) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · Cited by 329 · see citing works
Kannangara, M., Dua, R., Ahmadi, L., & Bensebaa, F. (2017) · Waste Management · doi:10.1016/j.wasman.2017.11.057 · Cited by 327 · see citing works
Application of machine learning in anaerobic digestion: Perspectives and challenges
Cruz, I. A., Chuenchart, W., Long, F., Surendra, K. C., Andrade, L. R. S., Bilal, M., Liu, H., Figueiredo, R. T., Khanal, S. K., & Ferreira, L. F. R. (2021) · Bioresource Technology · doi:10.1016/j.biortech.2021.126433 · Cited by 284 · see citing works
Role of Microalgae in Achieving Sustainable Development Goals and Circular Economy
Olabi, A. G., Shehata, N., Sayed, E. T., Rodriguez, C., Anyanwu, R. C., Russell, C., & Abdelkareem, M. A. (2023) · Science of The Total Environment · doi:10.1016/j.scitotenv.2022.158689 · Cited by 273 · see citing works
Bagherzadeh, F., Mehrani, M.-J., Basirifard, M., & Roostaei, J. (2021) · Journal of Water Process Engineering · doi:10.1016/j.jwpe.2021.102033 · Cited by 269 · see citing works
Algae biorefinery: Review on a broad spectrum of downstream processes and products
Khoo, C. G., Dasan, Y. K., Lam, M. K., & Lee, K. T. (2019) · Bioresource Technology · doi:10.1016/j.biortech.2019.121964 · Cited by 212 · see citing works
Machine learning predicts and optimizes hydrothermal liquefaction of biomass
Shafizadeh, A., Shahbeik, H., Nadian, M. H., Mobli, H., Dowlati, M., Gupta, V. K., Peng, W., Lam, S. S., Tabatabaei, M., & Aghbashlo, M. (2022) · Chemical Engineering Journal · doi:10.1016/j.cej.2022.136579 · Cited by 209 · see citing works
Zhang, W., Li, J., Liu, T., Leng, S., Yang, L., Peng, H., Jiang, S., Zhou, W., Leng, L., & Li, H. (2021) · Bioresource Technology · doi:10.1016/j.biortech.2021.126011 · Cited by 188 · see citing works
Chen, W., Chu, Y.-S., Liu, J.-L., & Chang, J. (2018) · Energy Conversion and Management · doi:10.1016/j.enconman.2018.01.036 · Cited by 178 · see citing works
The role of machine learning to boost the bioenergy and biofuels conversion
Wang, Z., Peng, X., Xia, A., Shah, A. A., Huang, Y. Y., Zhu, X., Zhu, X., & Liao, Q. (2021) · Bioresource Technology · doi:10.1016/j.biortech.2021.126099 · Cited by 173 · see citing works
Sundui, B., Calderon, O. A. R., Abdeldayem, O. M., Gil, J. L., Rene, E. R., & Sambuu, U. (2021) · Clean Technologies and Environmental Policy · doi:10.1007/s10098-020-01993-x · Cited by 169 · see citing works
Nayak, M., Dhanarajan, G., Dineshkumar, R., & Sen, R. (2018) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2018.08.048 · Cited by 166 · see citing works
Tang, Q., Chen, Y., Yang, H., Liu, M., Xiao, H., Wu, Z., Chen, H., & Naqvi, S. R. (2020) · Energy & Fuels · doi:10.1021/acs.energyfuels.0c01893 · Cited by 166 · see citing works
Li, J., Zhang, W., Liu, T., Yang, L., Li, H., Peng, H., Jiang, S., Wang, X., & Leng, L. (2021) · Chemical Engineering Journal · doi:10.1016/j.cej.2021.130649 · Cited by 166 · see citing works
Smart microalgae farming with internet-of-things for sustainable agriculture
Lim, H. R., Khoo, K. S., Chia, W. Y., Chew, K. W., Ho, S.-H., & Show, P. L. (2022) · Biotechnology Advances · doi:10.1016/j.biotechadv.2022.107931 · Cited by 155 · see citing works
Self-citationYou, H., Ma, Z., Tang, Y., Wang, Y., Yan, J., Ni, M., Cen, K., & Huang, Q. (2017) · Waste Management · doi:10.1016/j.wasman.2017.03.044 · Cited by 149 · see citing works
Sultana, N. N., Hossain, S. M. Z., Abusaad, M., Alanbar, N., Senan, Y., & Razzak, S. A. (2021) · Fuel · doi:10.1016/j.fuel.2021.122184 · Cited by 148 · see citing works
Techniques of lipid extraction from microalgae for biofuel production: a review
Lee, S. Y., Khoiroh, I., Vo, D.-V. N., Senthil Kumar, P., & Show, P. L. (2021) · Environmental Chemistry Letters · doi:10.1007/s10311-020-01088-5 · Cited by 133 · see citing works
Self-citationAl‐Rashed, A. A. A. A., Karimipour, A., Bagherzadeh, S. A., Safaei, M. R., & Afrand, M. (2018) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2018.07.123 · Cited by 132 · see citing works
Khoo, C. G., Lam, M. K., Mohamed, A. R., & Lee, K. T. (2020) · Environmental Research · doi:10.1016/j.envres.2020.109828 · Cited by 127 · see citing works
Semantic versus instance segmentation in microscopic algae detection
Ruiz-Santaquiteria, J., Bueno, G., Déniz, Ó., Vállez, N., & Cristóbal, G. (2019) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2019.103271 · Cited by 126 · see citing works
del Rio‐Chanona, E. A., Wagner, J. L., Ali, H., Fiorelli, F., Zhang, D., & Hellgardt, K. (2018) · AIChE Journal · doi:10.1002/aic.16473 · Cited by 124 · see citing works
Microalgae as a Source of Lutein: Chemistry, Biosynthesis, and Carotenogenesis
Sun, Z., Li, T., Zhou, Z.-G., & Jiang, Y. (2015) · Advances in Biochemical Engineering/Biotechnology · doi:10.1007/10_2015_331 · Cited by 117 · see citing works
Wu, Z., & Shi, X. (2007) · Letters in Applied Microbiology · doi:10.1111/j.1472-765x.2006.02038.x · Cited by 115 · see citing works
Microalgae classification based on machine learning techniques
Otálora, P., Guzmán, J. L., Acién, F. G., Berenguel, M., & Reul, A. (2021) · Algal Research · doi:10.1016/j.algal.2021.102256 · Cited by 111 · see citing works
Muhammad, G., Ngatcha, A. D. P., Lv, Y., Xiong, W., El-Badry, Y. A.-M., Asmatulu, E., Xu, J., & Alam, M. A. (2021) · Renewable Energy · doi:10.1016/j.renene.2021.11.091 · Cited by 111 · see citing works
Coşgun, A., Günay, M. E., & Yıldırım, R. (2021) · Renewable Energy · doi:10.1016/j.renene.2020.09.034 · Cited by 110 · see citing works
Cheah, W. Y., Show, P. L., Juan, J. C., Chang, J., & Ling, T. C. (2018) · Energy Conversion and Management · doi:10.1016/j.enconman.2018.02.094 · Cited by 105 · see citing works
Self-citationSutherland, D. L., McCauley, J. I., Labeeuw, L., Ray, P., Kuzhiumparambil, U., Hall, C., Doblin, M. A., Nguyen, L. N., & Ralph, P. J. (2021) · Current Research in Environmental Sustainability · doi:10.1016/j.crsust.2021.100050 · Cited by 103 · see citing works
Saboe, D., Ghasemi, H., Gao, M. M., Samardzic, M., Hristovski, K. D., Boscovic, D., Burge, S. R., Burge, R. G., & Hoffman, D. A. (2021) · Science of The Total Environment · doi:10.1016/j.scitotenv.2020.142876 · Cited by 99 · see citing works
Srivastava, G. P., Paul, A. K., & Goud, V. V. (2017) · Energy Conversion and Management · doi:10.1016/j.enconman.2017.10.093 · Cited by 97 · see citing works
Faris, H., Mirjalili, S., & Aljarah, I. (2019) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-018-00913-2 · Cited by 95 · see citing works
Salam, S., & Verma, T. N. (2018) · Energy Conversion and Management · doi:10.1016/j.enconman.2018.11.014 · Cited by 88 · see citing works
Nassef, A. M., Sayed, E. T., Rezk, H., Abdelkareem, M. A., Rodríguez, C., & Olabi, A. G. (2018) · Energy Sources Part A Recovery Utilization and Environmental Effects · doi:10.1080/15567036.2018.1549171 · Cited by 85 · see citing works
Deep Learning for Microalgae Classification
Correa, I., Drews, P., Botelho, S. S. D. C., de Souza, M. S., & Tavano, V. M. (2017) · International Conference on Machine Learning and Applications · doi:10.1109/icmla.2017.0-183 · Cited by 84 · see citing works
He, L., Subramanian, V. R., & Tang, Y. (2012) · Biomass and Bioenergy · doi:10.1016/j.biombioe.2012.02.025 · Cited by 82 · see citing works
Dallora, A. L., Eivazzadeh, S., Mendes, E., Berglund, J. S., & Anderberg, P. (2017) · PLoS ONE · doi:10.1371/journal.pone.0179804 · Cited by 82 · see citing works
Kushwaha, O. S., Uthayakumar, H., & Kumaresan, K. (2022) · Environmental Science and Pollution Research · doi:10.1007/s11356-022-19683-0 · Cited by 82 · see citing works
Ansari, F. A., Nasr, M., Rawat, I., & Bux, F. (2020) · Journal of Water Process Engineering · doi:10.1016/j.jwpe.2020.101761 · Cited by 81 · see citing works
Reimann, R., Zeng, B., Jakopec, M., Burdukiewicz, M. J., Petrick, I., Schierack, P., & Rödiger, S. (2020) · Algal Research · doi:10.1016/j.algal.2020.101908 · Cited by 80 · see citing works
Raj, J. V. A., Kumar, R. P., Badathala, V., Gnansounou, E., & Bharathiraja, B. (2021) · Bioresource Technology · doi:10.1016/j.biortech.2021.124872 · Cited by 80 · see citing works
Chen, J., Dai, L., Mataya, D., Cobb, K., Chen, P., & Ruan, R. (2022) · Bioresource Technology · doi:10.1016/j.biortech.2022.128188 · Cited by 79 · see citing works
Serive, B., Nicolau, É., Bérard, J., Kaas, R., Pasquet, V., Picot, L., & Cadoret, J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0171872 · Cited by 75 · see citing works
Saini, D. K., Rai, A., Devi, A., Pabbi, S., Chhabra, D., Chang, J.-S., & Shukla, P. (2021) · Bioresource Technology · doi:10.1016/j.biortech.2021.124908 · Cited by 75 · see citing works
Tham, P. E., Ng, Y. J., Vadivelu, N., Lim, H. R., Khoo, K. S., Chew, K. W., & Show, P. L. (2021) · Bioresource Technology · doi:10.1016/j.biortech.2021.126558 · Cited by 70 · see citing works
Self-citationDong, C., & Chen, J. (2018) · Bioresource Technology · doi:10.1016/j.biortech.2018.09.085 · Cited by 69 · see citing works
Artificial neural network modeling for predicting the growth of the microalga Karlodinium veneficum
García-Camacho, F., López-Rosales, L., Sánchez-Mirón, A., Belarbi, E. H., Chisti, Y., & Molina-Grima, E. (2016) · Algal Research · doi:10.1016/j.algal.2016.01.002 · Cited by 67 · see citing works
Artificial neural network based modelling and optimization of microalgae microbial fuel cell
Sayed, E. T., Rezk, H., Abdelkareem, M. A., & Olabi, A. G. (2023) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2022.12.081 · Cited by 65 · see citing works
Monoalgal and mixed algal cultures discrimination by using an artificial neural network
Franco, B. M., Navas, L. M., Gómez, C., Sepúlveda, C., & Acién, F. G. (2019) · Algal Research · doi:10.1016/j.algal.2019.101419 · Cited by 61 · see citing works
Malik, S., Shahid, A., Betenbaugh, M. J., Liu, C., & Mehmood, M. A. (2022) · Energy Conversion and Management · doi:10.1016/j.enconman.2022.115360 · Cited by 60 · see citing works
Peter, A. P., Chew, K. W., Pandey, A., Lau, S. Y., Rajendran, S., Ting, H. Y., Munawaroh, H. S. H., Phuong, N. V., & Show, P. L. (2022) · Fuel · doi:10.1016/j.fuel.2022.126438 · Cited by 56 · see citing works
Self-citationLiu, J.-Y., Zeng, L.-H., Ren, Z.-H., Du, T.-M., & Liu, X. (2020) · Algal Research · doi:10.1016/j.algal.2019.101739 · Cited by 55 · see citing works
Catalytic thermal degradation of Chlorella vulgaris: Evolving deep neural networks for optimization
Teng, S. Y., Loy, A. C. M., Leong, W. D., How, B. S., Chin, B. L. F., & Máša, V. (2019) · Bioresource Technology · doi:10.1016/j.biortech.2019.121971 · Cited by 54 · see citing works
Tang, D. Y. Y., Chew, K. W., Ting, H.-Y., Sia, Y.-H., Gentili, F. G., Park, Y., BANAT, F. A., Culaba, A. B., Ma, Z., & Show, P. L. (2022) · Bioresource Technology · doi:10.1016/j.biortech.2022.128503 · Cited by 54 · see citing works
Self-citationHossain, S. M. Z., Sultana, N., Jassim, M. S., Coskuner, G., Hazin, L. M., Razzak, S. A., & Hossain, M. M. (2022) · Journal of Water Process Engineering · doi:10.1016/j.jwpe.2021.102490 · Cited by 53 · see citing works
Singh, V., & Mishra, V. (2022) · Water Research · doi:10.1016/j.watres.2022.118165 · Cited by 52 · see citing works
Microalgae classification using semi-supervised and active learning based on Gaussian mixture models
Drews, P., Colares, R. G., Machado, P., de Faria, M., Detoni, A. M. S., & Tavano, V. M. (2013) · Journal of the Brazilian Computer Society · doi:10.1007/s13173-013-0121-y · Cited by 50 · see citing works
Automatic identification of Scenedesmus polymorphic microalgae from microscopic images
Giraldo-Zuluaga, J.-H., Salazar, A., Diez, G., Gomez-Villa, A., Martínez, T., Vargas, J. F., & Peñuela, M. (2017) · Pattern Analysis and Applications · doi:10.1007/s10044-017-0662-3 · Cited by 50 · see citing works
Singh, V., & Mishra, V. (2021) · Biochemical Engineering Journal · doi:10.1016/j.bej.2021.108129 · Cited by 46 · see citing works
Hu, D., Liu, H., Yang, C., & Hu, E. (2008) · Acta Astronautica · doi:10.1016/j.actaastro.2008.02.008 · Cited by 45 · see citing works
Rodríguez‐Miranda, E., Acién, F. G., Guzmán, J. L., Berenguel, M., & Visioli, A. (2020) · Biotechnology and Bioengineering · doi:10.1002/bit.27617 · Cited by 44 · see citing works
Trends on CO2 Capture with Microalgae: A Bibliometric Analysis
Miranda, A. M., Hernández-Tenorio, F., Ocampo, D., Vargas, G. J., & Sáez, A. A. (2022) · Molecules · doi:10.3390/molecules27154669 · Cited by 41 · see citing works
Banerjee, A., Guria, C., & Maiti, S. K. (2016) · Energy · doi:10.1016/j.energy.2016.09.066 · Cited by 41 · see citing works
del Rio‐Chanona, E. A., Ahmed, N. R., Wagner, J. L., Lu, Y., Zhang, D., & Jing, K. (2019) · Biotechnology and Bioengineering · doi:10.1002/bit.27131 · Cited by 40 · see citing works
Camacho-Rodríguez, J., Cerón-García, M. C., Fernández-Sevilla, J. M., & Grima, E. M. (2014) · Bioresource Technology · doi:10.1016/j.biortech.2014.11.057 · Cited by 40 · see citing works
Metekia, W. A., Usman, A. G., Ulusoy, B. H., Abba, S. I., & Chirkena, K. (2021) · Saudi Journal of Biological Sciences · doi:10.1016/j.sjbs.2021.09.055 · Cited by 40 · see citing works
Kumar, S., Jain, S., & Kumar, H. (2018) · Energy Sources Part A Recovery Utilization and Environmental Effects · doi:10.1080/15567036.2018.1515277 · Cited by 37 · see citing works
Optimization of Microalgae-to-Biodiesel Production Process Using a Metaheuristic Technique
Hernández-Pérez, L. G., Sánchez-Tuirán, E. L., Ojeda, K. A., El‐Halwagi, M. M., & Ponce‐Ortega, J. M. (2019) · ACS Sustainable Chemistry & Engineering · doi:10.1021/acssuschemeng.9b00274 · Cited by 36 · see citing works
Lopez-Exposito, P., Negro, C., & Blanco, Á. (2018) · Algal Research · doi:10.1016/j.algal.2018.12.007 · Cited by 36 · see citing works
Zhu, C., Ji, Y., Du, X., Kong, F., Chi, Z., & Zhao, Y. (2022) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2022.158515 · Cited by 36 · see citing works
Wang, S., Wang, J., Shang, F., Wang, Y., Cheng, Q., & Liu, N. (2019) · Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy · doi:10.1016/j.saa.2019.117396 · Cited by 32 · see citing works
Harmon, J., Mikami, H., Kanno, H., Ito, T., & Goda, K. (2020) · OSA Continuum · doi:10.1364/osac.387523 · Cited by 31 · see citing works
Shokrkar, H., Ebrahimi, S., & Zamani, M. (2017) · Chemical Engineering Communications · doi:10.1080/00986445.2017.1356291 · Cited by 29 · see citing works
López‐Rosales, L., Gallardo-Rodríguez, J. J., Sánchez‐Mirón, A., Contreras‐Gómez, A., García-Camacho, F., & Grima, E. M. (2013) · Bioresource Technology · doi:10.1016/j.biortech.2013.07.141 · Cited by 28 · see citing works
Susanna, D., Dhanapal, R., Mahalingam, R., & Ramamurthy, V. (2019) · Biotechnology and Bioengineering · doi:10.1002/bit.27128 · Cited by 27 · see citing works
Ching, P. M. L., Mayol, A. P., Juan, J. L. S., Calapatia, A. M. A., So, R. H. Y., Sy, C. L., Ubando, A. T., & Culaba, A. B. (2021) · Process Integration and Optimization for Sustainability · doi:10.1007/s41660-020-00145-4 · Cited by 25 · see citing works
Zenooz, A. M., Ashtiani, F. Z., Ranjbar, R., Nikbakht, F., & Bolouri, O. (2017) · Preparative Biochemistry & Biotechnology · doi:10.1080/10826068.2016.1275013 · Cited by 24 · see citing works
Gruber, Z., Tóth, A. J., Menyhárd, A., Mizsey, P., Owsianiak, M., & Fózer, D. (2022) · Bioresource Technology · doi:10.1016/j.biortech.2022.128071 · Cited by 24 · see citing works
Bi, X., Lin, S., Zhu, S., Yin, H., Li, Z., & Chen, Z. (2018) · Optik · doi:10.1016/j.ijleo.2018.09.077 · Cited by 23 · see citing works
A Decision Tree Approach to Estimate the Microalgae Production in Open Raceway Pond
Supriyanto, S., Noguchi, R., Ahamed, T., Demura, M., & Watanabe, M. M. (2018) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/209/1/012050 · Cited by 21 · see citing works
Lee, J. S., Sung, Y. J., & Sim, S. J. (2022) · Bioresource Technology · doi:10.1016/j.biortech.2022.128014 · Cited by 12 · see citing works
Predicting Drying Curves in Algal Biorefineries using Gaussian Process Autoregressive Models
Pilario, K. E., Ching, P. M. L., Calapatia, A. M. A., & Culaba, A. B. (2022) · Digital Chemical Engineering · doi:10.1016/j.dche.2022.100036 · Cited by 11 · see citing works
Mahfouz, A. B., Ali, A., Crocker, M., Ahmed, A., Nasir, R., & Show, P. L. (2023) · Fermentation · doi:10.3390/fermentation9010047 · Cited by 8 · see citing works
Self-citationDeep Learning Development Review
Lv, W.-H., & Lei, J. (2020) · International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) · doi:10.1109/aemcse50948.2020.00043 · Cited by 7 · see citing works
Sonkar, S., Shibani, & Mallick, N. (2020) · doi:10.22541/au.160372833.38766717/v1 · Cited by 4 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
RETRACTED ARTICLE: Artificial intelligence-based solutions for climate change: a review
Chen, L., Chen, Z., Zhang, Y., Liu, Y., Osman, A. I., Farghali, M. R. F., Hua, J., Al-Fatesh, A. S., Ihara, I., Rooney, D. W., et al. (2023) · Environmental Chemistry Letters · doi:10.1007/s10311-023-01617-y · Cited by 432 · see citing works
RetractedSmart waste management: A paradigm shift enabled by artificial intelligence
Olawade, D. B., Fapohunda, O., Wada, O. Z., Usman, S. O., Ige, A. O., Ajisafe, O. M., & Oladapo, B. I. (2024) · Waste Management Bulletin · doi:10.1016/j.wmb.2024.05.001 · Cited by 400 · see citing works
Recent applications of AI to environmental disciplines: A review
Konya, A., & Nematzadeh, P. (2023) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2023.167705 · Cited by 190 · see citing works
Automatic Identification of Individual Nanoplastics by Raman Spectroscopy Based on Machine Learning
Xie, L., Luo, S.-H., Liu, Y., Ruan, X., Gong, K., Ge, Q., Li, K., Valev, V. K., Liu, G., & Zhang, L. (2023) · Environmental Science & Technology · doi:10.1021/acs.est.3c03210 · Cited by 159 · see citing works
Samoraj, M., Çalış, D., Trzaska, K., Mironiuk, M., & Chojnacka, K. (2024) · Biocatalysis and Agricultural Biotechnology · doi:10.1016/j.bcab.2024.103224 · Cited by 152 · see citing works
Artificial Intelligence and/or Machine Learning Algorithms in Microalgae Bioprocesses
Imamoglu, E. (2024) · Bioengineering · doi:10.3390/bioengineering11111143 · Cited by 143 · see citing works
Sahu, S., Kaur, A., Singh, G., & Arya, S. K. (2023) · Journal of Environmental Management · doi:10.1016/j.jenvman.2023.119004 · Cited by 125 · see citing works
El-Sheekh, M. M., El-Kassas, H. Y., & Ali, S. S. (2025) · Microbial Cell Factories · doi:10.1186/s12934-024-02638-0 · Cited by 86 · see citing works
Ganthavee, V., & Trzcinski, A. P. (2024) · Environmental Chemistry Letters · doi:10.1007/s10311-024-01748-w · Cited by 83 · see citing works
Sofian, A. D. A. B. A., Lim, H. R., Manickam, S., Ang, W. L., & Show, P. L. (2023) · ChemBioEng Reviews · doi:10.1002/cben.202300028 · Cited by 78 · see citing works
Self-citationMachine learning applications for biochar studies: A mini-review
Wang, W., Chang, J., & Lee, D. (2024) · Bioresource Technology · doi:10.1016/j.biortech.2023.130291 · Cited by 72 · see citing works
Zechiel, F., Blaurock, M., Weber, E., Büttgen, M., & Coussement, K. (2024) · Industrial Marketing Management · doi:10.1016/j.indmarman.2024.03.010 · Cited by 65 · see citing works
Wang, Y., Ma, J., Chu, H., Zhou, X., & Zhang, Y. (2024) · Chemical Engineering Journal · doi:10.1016/j.cej.2024.149222 · Cited by 61 · see citing works
Use, Potential, Needs, and Limits of AI in Wastewater Treatment Applications
Capodaglio, A. G., & Callegari, A. (2025) · Water · doi:10.3390/w17020170 · Cited by 60 · see citing works
Wu, Y., Shan, L., Zhao, W., & Lu, X. (2025) · Marine Drugs · doi:10.3390/md23050184 · Cited by 59 · see citing works
Bridging artificial intelligence and fucoxanthin for the recovery and quantification from microalgae
Chong, J. W. R., Tang, D. Y. Y., Leong, H. Y., Khoo, K. S., Show, P. L., & Chew, K. W. (2023) · Bioengineered · doi:10.1080/21655979.2023.2244232 · Cited by 59 · see citing works
Self-citationBiswas, A., Kumari, A., Gaikwad, D. S., & Pandey, D. K. (2023) · OMICS A Journal of Integrative Biology · doi:10.1089/omi.2023.0197 · Cited by 56 · see citing works
Economic and sustainable revolution to facilitate one-carbon biomanufacturing
Zhang, C., Fei, Q., Fu, R., Lackner, M. K., Zhou, Y. J., & Tan, T. (2025) · Nature Communications · doi:10.1038/s41467-025-60247-w · Cited by 56 · see citing works
Shen, Y., Xiao-gang, Z., Guo, Z., Yu, K., Alfarraj, O., Leung, V. C. M., & Rodrigues, J. J. P. C. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3388043 · Cited by 53 · see citing works
Ali, Z. A., Zain, M., Hasan, R., AlSalman, H., Alkhamees, B. F., & Almisned, F. (2024) · Journal of the Knowledge Economy · doi:10.1007/s13132-024-02101-w · Cited by 53 · see citing works
Sharma, R., Solanki, P., Chaudhary, M., Gupta, N., & Kaur, P. (2024) · Biotechnology for Sustainable Materials · doi:10.1186/s44316-024-00010-1 · Cited by 50 · see citing works
Bagheri, M., Farshforoush, N., Bagheri, K., & Shemirani, A. I. (2023) · Process Safety and Environmental Protection · doi:10.1016/j.psep.2023.09.072 · Cited by 48 · see citing works
Yang, C., Kristiani, E., Leong, Y. K., & Chang, J. (2024) · Bioresource Technology · doi:10.1016/j.biortech.2024.131549 · Cited by 48 · see citing works
Arias, A., Feijóo, G., & Moreira, M. T. (2023) · Environmental Technology & Innovation · doi:10.1016/j.eti.2023.103277 · Cited by 47 · see citing works
Advancements of astaxanthin production in Haematococcus pluvialis: Update insight and way forward
Cui, H., Zhu, X., Xiao, Y., Li, S., Wang, K., Wei, L., Li, R., & Qin, S. (2025) · Biotechnology Advances · doi:10.1016/j.biotechadv.2025.108519 · Cited by 45 · see citing works
A Framework for Assessing the Potential of Artificial Intelligence in the Circular Bioeconomy
Shah, M., Wever, M., & Espig, M. (2025) · Sustainability · doi:10.3390/su17083535 · Cited by 45 · see citing works
Guo, B., Lu, X., Jiang, X., Shen, X. L., Wei, Z., & Zhang, Y. (2025) · Foods · doi:10.3390/foods14101783 · Cited by 44 · see citing works
Kumar, A., Mishra, S., Singh, N. K., Yadav, M. K., Padhiyar, H., Christian, J. J., & Kumar, R. (2024) · Journal of Environmental Management · doi:10.1016/j.jenvman.2024.121182 · Cited by 43 · see citing works
Fels, A. E. A. E., Mandi, L., Kammoun, A., Ouazzani, N., Monga, O., & Hbid, M. L. (2023) · Water · doi:10.3390/w15193487 · Cited by 42 · see citing works
Magalhães, I. B., Pereira, A. S. A. D. P., Silva, T. A., Ferreira, J., Braga, M. Q., do Couto, E. D. A., Assemany, P. P., & Calijuri, M. L. (2024) · Journal of Water Process Engineering · doi:10.1016/j.jwpe.2024.105929 · Cited by 41 · see citing works
Advances in Chlorella microalgae for sustainable wastewater treatment and bioproduction
Abuhasheesh, Y. H., Ghazal, A., Tang, D. Y. Y., BANAT, F. A., Hasan, S. W., & Show, P. L. (2025) · Chemical Engineering Journal Advances · doi:10.1016/j.ceja.2025.100715 · Cited by 41 · see citing works
Self-citationZahoor, S., Chaudhry, I. S., Yang, S., & Ren, X. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-11013-9 · Cited by 39 · see citing works
Ganthavee, V., Fernando, M. M. R., & Trzcinski, A. P. (2024) · Environmental Processes · doi:10.1007/s40710-024-00719-1 · Cited by 38 · see citing works
Chen, X., Lei, Z., Chang, J., & Lee, D. (2025) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2025.145467 · Cited by 35 · see citing works
Sharma, A., Goel, H., Sharma, S., Rathore, H. S., Jamir, I., Kumar, A., Thimmappa, S. C., Kesari, K. K., & Kashyap, B. K. (2024) · Environmental Science and Pollution Research · doi:10.1007/s11356-024-34977-1 · Cited by 34 · see citing works
A comprehensive review of algae consortium for wastewater bioremediation and biodiesel production
Mehra, K. S., Abrar, I., Bhatia, R. K., & Goel, V. (2024) · Energy Conversion and Management · doi:10.1016/j.enconman.2024.119428 · Cited by 33 · see citing works
Revolutionizing Agro-Food Waste Management: Real-Time Solutions through IoT and Big Data Integration
Das, K., Tanvir, A., Rani, S., & Aminuzzaman, F. M. (2025) · Voice of the Publisher · doi:10.4236/vp.2025.111003 · Cited by 33 · see citing works
Lilhore, U. K., Simaiya, S., Dalal, S., Rãdulescu, M., & Balsalobre‐Lorente, D. (2024) · Gondwana Research · doi:10.1016/j.gr.2024.07.014 · Cited by 32 · see citing works
Application and innovation of artificial intelligence models in wastewater treatment
Xu, W., Wang, Y., Wang, Y., Li, J., Zeng, Y.-N., Guo, H., Liu, H., Dong, K.-L., & Zhang, L.-Y. (2024) · Journal of Contaminant Hydrology · doi:10.1016/j.jconhyd.2024.104426 · Cited by 31 · see citing works
Dębowski, M., Kazimierowicz, J., & Zieliński, M. (2025) · Applied Sciences · doi:10.3390/app15137324 · Cited by 30 · see citing works
Warren‐Vega, W. M., Montes-Peña, K. D., Cano, L. A. R., & Zárate‐Guzmán, A. I. (2024) · Journal of Environmental Management · doi:10.1016/j.jenvman.2024.121612 · Cited by 30 · see citing works
Tarbajova, V., Koláčková, M., Chaloupský, P., Dobesova, M., Cápal, P., Pilát, Z., Samek, O., Zemánek, P., Svec, P., Štěrbová, D., et al. (2023) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2023.132450 · Cited by 30 · see citing works
Ayub, A., Rahayu, F., Khamidah, A., Antarlina, S. S., Iswari, K., Supriyadi, K., Mufidah, E., Singh, A., Chopra, C., & Wani, A. K. (2025) · Discover Applied Sciences · doi:10.1007/s42452-025-06916-3 · Cited by 29 · see citing works
Insights into levofloxacin adsorption with machine learning models using nano-composite hydrochars
Mahmoud, A. E. D., Ali, R., & Fawzy, M. (2024) · Chemosphere · doi:10.1016/j.chemosphere.2024.141746 · Cited by 28 · see citing works
Ishtiaq, R., Zahra, N., Iftikhar, S., Rubab, F., Sultan, K., Abbas, A., Lam, S., Jaffari, Z. H., & Park, K. Y. (2024) · Journal of environmental chemical engineering · doi:10.1016/j.jece.2024.112238 · Cited by 27 · see citing works
Shitu, A., Tadda, M. A., Zhao, J., Danhassan, U. A., Ye, Z., Liu, D., Chen, W., & Zhu, S. (2024) · Environmental Geochemistry and Health · doi:10.1007/s10653-024-02286-8 · Cited by 27 · see citing works
de la Hoz-M, J., Echeverri, E. A. A., & Vergara, D. (2024) · Resources · doi:10.3390/resources13120171 · Cited by 26 · see citing works
Kouamé, K. J. E., Falade, E. O., Zhu, Y., Zheng, Y., & Ye, X. (2025) · Food Chemistry · doi:10.1016/j.foodchem.2025.143326 · Cited by 26 · see citing works
Bioaerogels from biomass waste: An alternative sustainable approach for wastewater treatment
Arunkumar, P., Alghamdi, H. M., Kavinkumar, V., Elwakeel, K. Z., & Elgarahy, A. M. (2024) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2024.136994 · Cited by 25 · see citing works
AI-Driven Algae Biorefineries: A New Era for Sustainable Bioeconomy
Abdullah, M., Malik, H. A., Ali, A., Boopathy, R., Vo, P. H. N., Danaee, S., Ralph, P., & Malik, S. (2025) · Current Pollution Reports · doi:10.1007/s40726-025-00352-y · Cited by 24 · see citing works
Perspectives on biorefineries in microbial production of fuels and chemicals
Decker, S. R., Brunecky, R., Yarbrough, J. M., & Subramanian, V. (2023) · Frontiers in Industrial Microbiology · doi:10.3389/finmi.2023.1202269 · Cited by 24 · see citing works
Machine learning framework for wastewater circular economy — Towards smarter nutrient recoveries
Soo, A., Gao, L., & Shon, H. K. (2024) · Desalination · doi:10.1016/j.desal.2024.118092 · Cited by 24 · see citing works
Smart Water-IoT: Harnessing IoT and AI for Efficient Water Management
Slaný, V., Krčálová, E., Balej, J., Zach, M., Kucova, T., Prauzek, M., & Martínek, R. (2025) · ACM Computing Surveys · doi:10.1145/3744338 · Cited by 23 · see citing works
Akhtar, R., Hamza, A., Razzaq, L., Fayaz, H., Nawaz, S., Nawaz, U., Mukaddas, Z., Jauhar, T. A., Silitonga, A. S., & Saleel, C. A. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e22031 · Cited by 23 · see citing works
Szeląg, B., González-Camejo, J., Eusebi, A. L., Barat, R., Kiczko, A., & Fatone, F. (2024) · Chemical Engineering Journal · doi:10.1016/j.cej.2024.154202 · Cited by 20 · see citing works
Predictive model for CO2 absorption and mass transfer process based on machine learning methods
Wang, R., Lei, N., Zhang, N., Li, Q., An, S., & Wang, L. (2025) · Separation and Purification Technology · doi:10.1016/j.seppur.2025.132584 · Cited by 20 · see citing works
Chen, Z., Zhang, M., Bai, J., Wu, J., & Chang, I. (2025) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2025.179678 · Cited by 20 · see citing works
Huang, X., Wang, F., Rehman, O. U., Hu, X., Zhu, F., Wang, R., Xu, L., Cui, Y., & Huo, S. (2025) · Foods · doi:10.3390/foods14142500 · Cited by 20 · see citing works
Casas, A., Rodríguez-Llorente, D., Rodríguez-Llorente, G., Garcı́a, J., & Larriba, M. (2024) · Journal of Water Process Engineering · doi:10.1016/j.jwpe.2024.105379 · Cited by 20 · see citing works
Foroughi, M., Arzehgar, A., Seyedhasani, S. N., Nadali, A., & Benis, K. Z. (2024) · Chemosphere · doi:10.1016/j.chemosphere.2024.142223 · Cited by 20 · see citing works
Influence of process factors and photobioreactor design on microalgae cultivation
Nedaei, L., & Shokrkar, H. (2025) · Biofuels Bioproducts and Biorefining · doi:10.1002/bbb.2759 · Cited by 19 · see citing works
Sadeghpour, F. (2025) · Energy · doi:10.1016/j.energy.2025.136040 · Cited by 18 · see citing works
Varasree, B., Kavithamani, V., Chandrakanth, P., Basi Reddy, A., Padmapriya, R., & Selvan, R. S. (2024) · Groundwater for Sustainable Development · doi:10.1016/j.gsd.2024.101092 · Cited by 18 · see citing works
Naghizadeh, A., Jafari, S., Norouzi-Apourvari, S., Schaffie, M., & Hemmati‐Sarapardeh, A. (2024) · Energy · doi:10.1016/j.energy.2024.130413 · Cited by 18 · see citing works
Thajuddin, F., Rasheed, A. S., Elumalai, A., Palanivel, P., Thajuddin, N., & Dharumadurai, D. (2025) · Renewable Energy · doi:10.1016/j.renene.2025.123961 · Cited by 17 · see citing works
Sarker, N. K., & Kaparaju, P. (2025) · Fermentation · doi:10.3390/fermentation11100574 · Cited by 17 · see citing works
Salari, M., Alahabadi, A., Rahmani-Sani, A., Miri, M., Aval, M. Y., Lotfi, H., Saghi, M. H., Rastegar, A., Sepehr, M. N., & Darvishmotevalli, M. (2023) · Chemosphere · doi:10.1016/j.chemosphere.2023.140832 · Cited by 17 · see citing works
Mora-Sánchez, J. F., Ribes, J., González-Camejo, J., Seco, A., & Ruano, M. V. (2023) · Water · doi:10.3390/w16010155 · Cited by 17 · see citing works
The analysis of optimization in music aesthetic education under artificial intelligence
Peng, Y. (2025) · Scientific Reports · doi:10.1038/s41598-025-96436-2 · Cited by 17 · see citing works
Kalwani, M., Kumari, A., Rudra, S. G., Chhabra, D., Pabbi, S., & Shukla, P. (2023) · Chemosphere · doi:10.1016/j.chemosphere.2023.140835 · Cited by 16 · see citing works
Hou, Y., Wang, Q., Zhou, K., Zhang, L., & Tan, T. (2023) · Waste Management · doi:10.1016/j.wasman.2023.12.006 · Cited by 16 · see citing works
Selenium biofortification: integrating one health and sustainability
Estarriaga‐Navarro, S., Goicoechea, N., Plano, D., & Sanmartín, C. (2025) · Journal of the Science of Food and Agriculture · doi:10.1002/jsfa.70103 · Cited by 15 · see citing works
Microalgae-based treatment for wastewater management and valorization
Pant, S., Goel, M., Sahoo, N. K., Yuan, Q., & Rout, P. R. (2025) · Current Opinion in Environmental Science & Health · doi:10.1016/j.coesh.2025.100662 · Cited by 15 · see citing works
Freitas, G. R., Badenes, S. M., Oliveira, R., & Martins, F. G. (2025) · Processes · doi:10.3390/pr13092956 · Cited by 15 · see citing works
Zhang, P., Chen, Y., Xiao, Z., Tan, H., Nie, S., Li, H., Cai, Y., Rehman, S. A. U., Zhong, W., & Zhang, W. (2026) · Journal of Membrane Science · doi:10.1016/j.memsci.2026.125685 · Cited by 15 · see citing works
Xu, K., Zhu, Z., Yu, H., & Zou, X. (2025) · Algal Research · doi:10.1016/j.algal.2025.103985 · Cited by 15 · see citing works
Chemical and microalgal conversion of carbon dioxide into fuels and materials: a review
Kumar, A., Sharma, A., Majumder, P., Vishal, V., & Dutta, A. (2025) · Environmental Chemistry Letters · doi:10.1007/s10311-025-01855-2 · Cited by 14 · see citing works
Kiehbadroudinezhad, M., Hosseinzadeh-Bandbafha, H., Karimi, K., Madadi, M., Chisti, Y., Peng, W., Liú, D., Tabatabaei, M., & Aghbashlo, M. (2023) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2023.165751 · Cited by 14 · see citing works
Narayanan, I., Rajamanickam, R., Singh, R. K., Singh, P., Prabhu, A. A., Pandey, A., Pradhan, N., Nancharaiah, Y. V., Kumar, V., Selvasembian, R., et al. (2025) · Discover Applied Sciences · doi:10.1007/s42452-025-07226-4 · Cited by 13 · see citing works
Kalwani, M., & Vítová, M. (2026) · Algal Research · doi:10.1016/j.algal.2026.104620 · Cited by 12 · see citing works
Omole, O., Ogbaga, C. C., Okolie, J. A., Kimera, R., Dayil, J. L., Akande, O., & Akande, O. (2025) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2025.109049 · Cited by 12 · see citing works
Romero–Losada, A. B., Arvanitidou, C., García‐Gómez, M. E., Morales-Pineda, M., Castro-Pérez, M. J., Chew, Y. P., van Ooijen, G., García‐González, M., & Romero–Campero, F. J. (2025) · The Plant Cell · doi:10.1093/plcell/koaf033 · Cited by 12 · see citing works
Chen, J., Li, J., He, Y., Chen, S., Wu, L., He, Y., Lu, Y., Ling, H., & Su, C. (2025) · Journal of Water Process Engineering · doi:10.1016/j.jwpe.2025.108224 · Cited by 11 · see citing works
Dodangodage, C. A., Premarathne, H., Kasturiarachchi, J. C., Perera, T., Rajapakshe, D., & Halwatura, R. (2025) · Phycology · doi:10.3390/phycology5040084 · Cited by 11 · see citing works
Kayan, I., & Öz, N. A. (2025) · Journal of Chemical Technology & Biotechnology · doi:10.1002/jctb.7856 · Cited by 10 · see citing works
Sustainable wastewater treatment with AI: a path to enhanced hygiene and environmental protection
Krishnan, A., & Devarajan, Y. (2025) · Process Safety and Environmental Protection · doi:10.1016/j.psep.2025.107487 · Cited by 10 · see citing works
Carvalho, J. D. S., Artifon, W., da Silva, A., de Andrade, C. J., & de Olíveira, D. (2025) · Algal Research · doi:10.1016/j.algal.2025.104216 · Cited by 10 · see citing works
Zaveri, J., Li, G., Wang, Z. L., Yuan, Y., Budai, P., Takács, I., & Gu, A. Z. (2025) · Water Environment Research · doi:10.1002/wer.70181 · Cited by 10 · see citing works
Recent Advances in the Application of Artificial Intelligence in Microalgal Cultivation
Rayamajhi, V., Hussain, M., Shin, H., & Jung, S.-M. (2025) · Processes · doi:10.3390/pr13123764 · Cited by 10 · see citing works
Recent Advances in Microalgae Cultivation Systems: Toward Autonomous Architecture
Sangregorio‐Soto, V., Mayorga, E. Y., & Perafán, R. D. L. H. (2026) · Fermentation · doi:10.3390/fermentation12030147 · Cited by 10 · see citing works
AL‐Huqail, A. A., Mohammed, K. J., Suhatril, M., Almujibah, H. R., Toghroli, S., Alnahdi, S. S., & Ponnore, J. J. (2025) · Carbon letters · doi:10.1007/s42823-024-00837-8 · Cited by 9 · see citing works
Jiao, T., Feng, E. Y., Li, Y., & Tian, Y. (2025) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2025.144870 · Cited by 8 · see citing works
Buscaglia, L., van den End, F., Janssen, M., & Barbosa, M. J. (2025) · Algal Research · doi:10.1016/j.algal.2025.104172 · Cited by 8 · see citing works
El‐Sherif, D. M., Mahmoud, A. E. D., & Saber, A. N. (2024) · Environmental science and engineering · doi:10.1007/978-981-97-2371-3_11 · Cited by 8 · see citing works
Onay, A., & Onay, M. (2024) · Journal of Environmental Management · doi:10.1016/j.jenvman.2024.123266 · Cited by 8 · see citing works
Venkatrayalu, G., Choudhary, S., & Poluri, K. M. (2026) · Springer eBooks · doi:10.1007/978-981-95-5378-5_9 · Cited by 7 · see citing works
Filho, J. R. D. M., Serpa, J. D. F., Aires, F. I. D. S., Dari, D. N., Ferreira, A. N. S., da Silva, C. G., da Silva, J. L., Araujo, S. A., Felix, J. H. D. S., Oliveira, L. A., et al. (2026) · Discover Sustainability · doi:10.1007/s43621-026-03029-8 · Cited by 7 · see citing works
The AI Cleanse: Revolutionizing the Future of Wastewater Treatment with AI and Machine Learning
Sanjeevi, R., Sathvara, P. B., Tripathi, S., & Anuradha, J. (2024) · Springer water · doi:10.1007/978-3-031-67237-8_10 · Cited by 7 · see citing works
El-Moustaqim, K., Mabrouki, J., Azrour, M., Hadine, M., & Hmouni, D. (2024) · Studies in computational intelligence · doi:10.1007/978-3-031-70102-3_15 · Cited by 7 · see citing works
Ayyoub, H., Kaicer, M., Elabbassi, I., & Taky, M. (2025) · Journal of Water and Land Development · doi:10.24425/jwld.2025.155304 · Cited by 6 · see citing works
- Authors
- Oruganti, R. K., Biji, A. P., Lanuyanger, T., Show, P. L., Sriariyanun, M., Upadhyayula, V. K. K., Gadhamshetty, V., & Bhattacharyya, D.
- Affiliations
- Indian Institute of Technology Hyderabad (IN)
- Khalifa University of Science and Technology (AE)
- King Mongkut's University of Technology North Bangkok (TH)
- Umeå University (SE)
- South Dakota School of Mines and Technology (US)
- Corresponding author
- Bhattacharyya, Debraj
- ORCID
- Venue
- Science of The Total Environment
- Publisher
- Elsevier BV
- Published
- 2023-06
- Volume
- 876
- Pages
- 162797
- ISSN
- 0048-9697 (ISSN-L)
- OpenAlex
- W4323923505
- Cited by
- 211
- References
- 95
- Citations by year
- 2026: 56 · 2025: 83 · 2024: 49 · 2023: 23
- FWCI
- 3.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- The Science of The Total Environment (publishedVersion)
- PubMed (publishedVersion)
- Research Archive of Indian Institute of Technology Hyderabad (Indian Institute of Technology Hyderabad) (acceptedVersion)
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
- Physical Sciences › Environmental Science › Waste Management and Disposal › Wastewater Treatment and Reuse
- Physical Sciences › Environmental Science › Environmental Chemistry › Aquatic Ecosystems and Phytoplankton Dynamics
- Keywords
- microalgae-based wastewater treatment, microalgae biorefinery, artificial intelligence, machine learning, nutrient removal, resource recovery, microalgae cultivation optimization, biomass productivity, artificial neural networks, random forest, support vector machine, genetic algorithm, decision tree, Internet of Things, circular economy, biofuels, biomaterials
- MeSH terms
- Machine Learning, Artificial Intelligence, Biotechnology, Waardenburg Syndrome, Water Purification, Biomass, Biofuels, Microalgae
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review