Artificial intelligence driven process optimization for cleaner production of biomass with co-valorization of wastewater and flue gas in an algal biorefinery
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In Nayak et al. (2018), optimization of environmental conditions in a Scenedesmus sp. was carried out using ANN-GA, integrated with CO2 from combustion gases and domestic effluent.
“In a study by Nayak et al. (2018), the optimization of environmental conditions in a Scenedesmus sp. was carried out using ANN-GA, and integrated with CO2 from combustion gases and domestic effluent.”
From Microalgae biotechnology and its role in sustainable and healthy food design (2025) · cites this paper as Nayak et al., 2018
Algal digital twin has progressed and expanded in tandem with AI, IoT, and big data in the algal cultivation for biomass production sector to sustain the environment.
“Correspondingly, ADT has also progressed and expanded in tandem with AI, IoT, and BD in the ACB sector to sustain the environment [1,11 -14].”
From Reinvigorating algal cultivation for biomass production with digital twin technology - a smart sustainable infrastructure (2024) · cites this paper as [11]
Implementation of the ANN-GA process optimization strategy led to a substantial increase in biomass productivity by 57% (from 196 ± 8.7 to ...).
“In addition, the implementation of this process optimization strategy led to a substantial increase in biomass productivity by 57 % (from 196 ± 8.7 to”
From Reinvigorating algal cultivation for biomass production with digital twin technology - a smart sustainable infrastructure (2024) · cites this paper as [11]
The ANN-GA technique is efficient in optimizing process factors to improve microalgal productivity.
“The validation of the efficiency of the ANN-GA technique in optimizing the process factors to improve microalgal productivity.”
From Reinvigorating algal cultivation for biomass production with digital twin technology - a smart sustainable infrastructure (2024) · cites this paper as [11]
AI-driven models can increase microalgae biomass productivity by up to 15-57% compared to traditional methods.
“Key case studies demonstrate that AI-driven models can increase biomass productivity by up to 15–57%, improve CO2 biofixation efficiency, and enhance lipid and high-value compound yields by more than 20–43% compared to traditional methods.”
From Harnessing Artificial Intelligence to Revolutionize Microalgae Biotechnology: Unlocking Sustainable Solutions for High-Value Compounds and Carbon Neutrality (2025) · cites this paper as [42]
An ANN-GA-optimized process integrating flue gas CO2 sequestration and domestic wastewater utilization enhanced Scenedesmus sp. biomass production, achieving a 57% increase in productivity under optimal conditions.
“For instance, an ANN-GA-optimized process integrating flue gas CO2 sequestration and domestic wastewater utilization was developed to enhance Scenedesmus sp. biomass production, achieving a 57% increase in productivity under optimal conditions (light intensity: 124 μmol m−2 s−1, photoperiod: 17:7 h, temperature: 27.5 °C, pH: 9.5).”
From Harnessing Artificial Intelligence to Revolutionize Microalgae Biotechnology: Unlocking Sustainable Solutions for High-Value Compounds and Carbon Neutrality (2025) · cites this paper as [42]
The process resulted in a CO2 sequestration rate of 578.1 ± 23.1 mg L−1 d−1, COD reduction of 95.9 ± 2.4%, and lipid productivity of 106.4 mg L−1 d−1, with biodiesel quality meeting international standards.
“The process resulted in a CO2 sequestration rate of 578.1 ± 23.1 mg L−1 d−1, COD reduction of 95.9 ± 2.4%, and lipid productivity of 106.4 mg L−1 d−1, with biodiesel quality meeting international standards [42].”
From Harnessing Artificial Intelligence to Revolutionize Microalgae Biotechnology: Unlocking Sustainable Solutions for High-Value Compounds and Carbon Neutrality (2025) · cites this paper as [42]
AI-driven models can enhance lipid and high-value compound yields by more than 20-43% compared to traditional methods.
“Key case studies demonstrate that AI-driven models can increase biomass productivity by up to 15–57%, improve CO2 biofixation efficiency, and enhance lipid and high-value compound yields by more than 20–43% compared to traditional methods.”
From Harnessing Artificial Intelligence to Revolutionize Microalgae Biotechnology: Unlocking Sustainable Solutions for High-Value Compounds and Carbon Neutrality (2025) · cites this paper as [42]
Cites
A RAPID METHOD OF TOTAL LIPID EXTRACTION AND PURIFICATION
Bligh, E. G., & Dyer, W. J. (1959) · Canadian Journal of Biochemistry and Physiology · doi:10.1139/o59-099 · Cited by 54,751 · see citing works
A RAPID METHOD OF TOTAL LIPID EXTRACTION AND PURIFICATION
Bligh, E. G., & Dyer, W. J. (1959) · Canadian Journal of Biochemistry and Physiology · doi:10.1139/y59-099 · Cited by 23,189 · see citing works
Chisti, Y. (2007) · Biotechnology Advances · doi:10.1016/j.biotechadv.2007.02.001 · Cited by 9,524 · see citing works
Microalgae for biodiesel production and other applications: A review
Mata, T. M., Martins, A. A., & Caetano, N. S. (2010) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2009.07.020 · Cited by 5,685 · see citing works
Sheehan, J., Dunahay, T., Benemann, J., & Roessler, P. (1998) · doi:10.2172/15003040 · Cited by 1,753 · see citing works
Handbook of phycological methods, culture methods and growth measurements
den Hartog, C. (1974) · Aquaculture · doi:10.1016/0044-8486(74)90057-x · Cited by 1,451 · see citing works
Handbook of Phycological methods - Culture methods and Growth measurements
Stein, J. R. (1973) · Cited by 852 · see citing works
Cuéllar‐Bermúdez, S. P., García‐Pérez, J. S., Rittmann, B. E., & Parra‐Saldívar, R. (2014) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2014.03.034 · Cited by 332 · see citing works
A Single-Step Method for Rapid Extraction of Total Lipids from Green Microalgae
Axelsson, M., & Gentili, F. (2014) · PLoS ONE · doi:10.1371/journal.pone.0089643 · Cited by 278 · see citing works
Nayak, M., Karemore, A., & Sen, R. (2016) · Algal Research · doi:10.1016/j.algal.2016.03.020 · Cited by 239 · see citing works
Self-citationEffect of blends of Palm-Jatropha-Pongamia biodiesels on cloud point and pour point
Sarin, A., Arora, R., Singh, N. P., Sarin, R., Malhotra, R. K., & Kundu, K. (2009) · Energy · doi:10.1016/j.energy.2009.08.017 · Cited by 221 · see citing works
Grima, E. M. (1996) · Journal of Biotechnology · doi:10.1016/0168-1656(95)00144-1 · Cited by 217 · see citing works
Xu, Y., Ibrahim, I. M., & Harvey, P. J. (2016) · Plant Physiology and Biochemistry · doi:10.1016/j.plaphy.2016.05.021 · Cited by 170 · see citing works
Microalgal species for sustainable biomass/lipid production using wastewater as resource: a review
Wu, Y.-H., Hu, H.-Y., Yu, Y., Zhang, T.-Y., Zhu, S.-F., Zhuang, L.-L., Zhang, X., & Lu, Y. (2014) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2014.02.026 · Cited by 155 · see citing works
Yadav, G., Karemore, A., Dash, S. K., & Sen, R. (2015) · Bioresource Technology · doi:10.1016/j.biortech.2015.04.040 · Cited by 120 · see citing works
Self-citationFerreira, A., Ribeiro, B., Marques, P., Ferreira, A. F., Dias, A. P. S., Pinheiro, H. M., dos Reis, A. J. D., & Gouveia, L. (2017) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2017.07.232 · Cited by 118 · see citing works
Ji, M.-K., Yun, H.-S., Park, Y., Kabra, A. N., Oh, I., & Choi, J. (2015) · Journal of Environmental Management · doi:10.1016/j.jenvman.2015.05.037 · Cited by 115 · see citing works
Nayak, M., Suh, W. I., Lee, B., & Chang, Y. K. (2017) · Energy Conversion and Management · doi:10.1016/j.enconman.2017.11.002 · Cited by 104 · see citing works
Self-citationSelection of oleaginous yeasts with high lipid productivity for practical biodiesel production
Tanimura, A., Takashima, M., Sugita, T., Endoh, R., Kikukawa, M., Yamaguchi, S., Sakuradani, E., Ogawa, J., & Shima, J. (2013) · Bioresource Technology · doi:10.1016/j.biortech.2013.11.086 · Cited by 97 · see citing works
Tsolcha, O. N., Tekerlekopoulou, A. G., Akratos, C. S., Aggelis, G., Genitsaris, S., Moustaka-Gouni, M. T., & Vayenas, D. V. (2017) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2017.02.026 · Cited by 87 · see citing works
Dhanarajan, G., Rangarajan, V., Bandi, C. K., Dixit, A., Das, S., Ale, K., & Sen, R. (2017) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2017.05.007 · Cited by 78 · see citing works
Self-citationNayak, M., Karemore, A., & Sen, R. (2016) · RSC Advances · doi:10.1039/c6ra17899e · Cited by 69 · see citing works
Self-citationSalama, E., Jeon, B., Chang, S. W., Lee, S., Roh, H., Yang, I.-S., Kurade, M. B., El-Dalatony, M. M., Kim, D.-H., Kim, K., et al. (2017) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2017.09.057 · Cited by 66 · see citing works
Energy efficient transfer of carbon dioxide from flue gases to microalgal systems
Zheng, Q. X., Martin, G. J. O., & Kentish, S. E. (2016) · Energy & Environmental Science · doi:10.1039/c5ee02005k · Cited by 63 · see citing works
Han, S.-F., Jin, W., Tu, R., Abomohra, A., & Wang, Z.-H. (2016) · Bioprocess and Biosystems Engineering · doi:10.1007/s00449-016-1585-x · Cited by 59 · see citing works
Nayak, M. (2013) · Journal of Microbiology and Biotechnology · doi:10.4014/jmb.1302.02044 · Cited by 51 · see citing works
Self-citationSang, M., Ming, W., Liu, J., Zhang, C., & Li, A. (2012) · Journal of Ocean University of China · doi:10.1007/s11802-012-1868-z · Cited by 47 · see citing works
Gupta, S. K., Ansari, F. A., Nasr, M., Rawat, I., Nayunigari, M. K., & Bux, F. (2017) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2017.01.144 · Cited by 43 · see citing works
Dineshkumar, R., Paul, A., Gangopadhyay, M., Singh, N. D. P., & Sen, R. (2016) · ACS Sustainable Chemistry & Engineering · doi:10.1021/acssuschemeng.6b02189 · Cited by 41 · see citing works
Self-citationGoswami, G., Chakraborty, S., Chaudhuri, S., & Dutta, D. (2012) · Bioprocess and Biosystems Engineering · doi:10.1007/s00449-012-0726-0 · Cited by 39 · see citing works
Microalgal photobioreactors: Scale-up and optimisation
Barbosa, M. J. (2003) · doi:10.18174/121438 · Cited by 38 · see citing works
Ji, M.-K., Yun, H.-S., Hwang, B. S., Kabra, A. N., Jeon, B., & Choi, J. (2016) · Ecological Engineering · doi:10.1016/j.ecoleng.2016.06.017 · Cited by 36 · see citing works
Bagchi, S. K., & Mallick, N. (2016) · RSC Advances · doi:10.1039/c6ra02811j · Cited by 35 · see citing works
Sang, Min, Wang, Ming, M., Liu, Jianhui, Zhang, Chengwu, Li, & Aifen (2012) · Acta Scientiarum Naturalium Universitatis Sunyatseni · Cited by 20 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Oruganti, R. K., Biji, A. P., Lanuyanger, T., Show, P. L., Sriariyanun, M., Upadhyayula, V. K. K., Gadhamshetty, V., & Bhattacharyya, D. (2023) · Science of The Total Environment · doi:10.1016/j.scitotenv.2023.162797 · Cited by 211 · 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
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
Shaik, A. S., Alshibani, S. M., Jain, G., Gupta, B., & Mehrotra, A. (2023) · Business Strategy and the Environment · doi:10.1002/bse.3617 · Cited by 149 · see citing works
Microalgae with Artificial Intelligence: A Digitalized Perspective on Genetics, Systems and Products
Teng, S. Y., Yew, G. Y., Sukačová, K., Show, P. L., Máša, V., & Chang, J.-S. (2020) · Biotechnology Advances · doi:10.1016/j.biotechadv.2020.107631 · Cited by 145 · see citing works
Artificial intelligence as a sustainable tool in wastewater treatment using membrane bioreactors
Kamali, M., Appels, L., Yu, X., Aminabhavi, T. M., & Dewil, R. (2020) · Chemical Engineering Journal · doi:10.1016/j.cej.2020.128070 · Cited by 141 · see citing works
A Review on Applications of Artificial Intelligence in Wastewater Treatment
Wáng, Y., Cheng, Y., Liu, H., Guo, Q., Dai, C., Zhao, M., & Liu, D. (2023) · Sustainability · doi:10.3390/su151813557 · Cited by 141 · see citing works
Ma, S., Ding, W., Liu, Y., Zhang, Y., Ren, S., Kong, X., & Leng, J. (2024) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2024.142879 · Cited by 131 · see citing works
Nayak, M., Swain, D. K., & Sen, R. (2019) · Science of The Total Environment · doi:10.1016/j.scitotenv.2019.05.123 · Cited by 128 · see citing works
Self-citationAdvancement in algal bioremediation for organic, inorganic, and emerging pollutants
Dubey, S., Chen, C., Haldar, D., Tambat, V. S., Kumar, P., Tiwari, A., Singhania, R. R., Dong, C., & Patel, A. K. (2022) · Environmental Pollution · doi:10.1016/j.envpol.2022.120840 · Cited by 113 · see citing works
Nayak, M., Suh, W. I., Chang, Y. K., & Lee, B. (2018) · Bioresource Technology · doi:10.1016/j.biortech.2018.12.111 · Cited by 104 · see citing works
Self-citationGoswami, R. K., Agrawal, K., Upadhyaya, H. M., Gupta, V. K., & Verma, P. (2022) · Energy Conversion and Management · doi:10.1016/j.enconman.2022.116118 · Cited by 103 · see citing works
Niu, G., Yi, X., Chen, C., Li, X., Han, D., Yan, B., Huang, M., & Ying, G. (2020) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2020.121787 · Cited by 101 · see citing works
Advances in microalgae-based carbon sequestration: Current status and future perspectives
Udaypal, U., Goswami, R. K., Mehariya, S., & Verma, P. (2024) · Environmental Research · doi:10.1016/j.envres.2024.118397 · Cited by 104 · see citing works
Shin, Y., Smith, R., & Hwang, S. (2020) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2020.124124 · Cited by 96 · see citing works
Manaswini, G., & Ganesan, S. (2025) · Results in Engineering · doi:10.1016/j.rineng.2025.105345 · Cited by 96 · see citing works
Artificial Intelligence-Based Optimization of Industrial Membrane Processes
Gaudio, M. T., Coppola, G., Zangari, L., Curcio, S., Greco, S., & Chakraborty, S. (2021) · Earth Systems and Environment · doi:10.1007/s41748-021-00220-x · Cited by 93 · see citing works
Shin, Y., Kim, Z., Yu, J., Kim, G., & Hwang, S. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.05.276 · Cited by 89 · see citing works
Biomass to Energy — an Analysis of Current Technologies, Prospects, and Challenges
Banerjee, N. (2022) · BioEnergy Research · doi:10.1007/s12155-022-10500-7 · Cited by 88 · 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
Integrated algal biorefineries from process systems engineering aspects: A review
Wu, W., & Chang, J. (2019) · Bioresource Technology · doi:10.1016/j.biortech.2019.121939 · Cited by 79 · see citing works
Khan, A. N., Mehmood, K., & Ali, A. (2024) · Corporate Social Responsibility and Environmental Management · doi:10.1002/csr.2832 · Cited by 78 · see citing works
Optimising an outdoor membrane photobioreactor for tertiary sewage treatment
González-Camejo, J., Jiménez-Benítez, A. L., Ruano, M. V., Robles, Á., Barat, R., & Ferrer, J. (2019) · Journal of Environmental Management · doi:10.1016/j.jenvman.2019.05.010 · Cited by 76 · see citing works
Goswami, R. K., Mehariya, S., Karthikeyan, O. P., Gupta, V. K., & Verma, P. (2022) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2022.130654 · Cited by 77 · see citing works
Optimisation and process design tools for cleaner production
Fan, Y. V., Chin, H. H., Klemeš, J. J., Varbanov, P. S., & Liu, X. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.119181 · Cited by 75 · see citing works
Feng, Y., Hong, Z., Li, Z., Zheng, H., & Tan, J. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.119070 · Cited by 70 · see citing works
Recent advances in biotechnology and bioengineering for efficient microalgal biofuel production
Zhang, C., Singh, R. P., Yadav, P., Kumar, I., Kaushik, A., Roychowdhury, R., Mubeen, M., Singh, S. K., Kumar, A., & Wang, J. (2025) · Fuel Processing Technology · doi:10.1016/j.fuproc.2025.108199 · Cited by 71 · see citing works
IoT-Based Signal Enhancement and Compression Method for Efficient Motor Bearing Fault Diagnosis
Tang, H., Lu, S., Qian, G., Ding, J., Liu, Y., & Wang, Q. (2020) · IEEE Sensors Journal · doi:10.1109/jsen.2020.3017768 · 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
Wang, Q., Xia, C., Alagumalai, K., Le, T. T. N., Yuan, Y., Khademi, T., Berkani, M., & Lu, H. (2022) · Fuel · doi:10.1016/j.fuel.2022.126456 · Cited by 59 · see citing works
Diatoms for Carbon Sequestration and Bio-Based Manufacturing
Sethi, D., Butler, T. O., Shuhaili, F. A. B. A., & Vaidyanathan, S. (2020) · Biology · doi:10.3390/biology9080217 · Cited by 60 · see citing works
Shitanaka, T., Fujioka, H., Khan, M., Kaur, M., Du, Z., & Khanal, S. K. (2023) · Bioresource Technology · doi:10.1016/j.biortech.2023.129924 · Cited by 48 · see citing works
Waste stream valorization-based low-carbon bioeconomy utilizing algae as a biorefinery platform
Leong, Y. K., & Chang, J. (2023) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2023.113245 · Cited by 47 · see citing works
Parichehreh, R., Gheshlaghi, R., Mahdavi, M. A., & Kamyab, H. (2021) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2021.08.010 · Cited by 47 · see citing works
Catalytic activity and evaluation of Fe-Mn@Bt for ozonizing coal chemical biochemical tail water
Sun, W., Sun, Y., Zhu, H., & Zheng, H. (2020) · Separation and Purification Technology · doi:10.1016/j.seppur.2020.116524 · Cited by 45 · see citing works
Sun, W., Zhou, S., Sun, Y., & Xu, Y. (2020) · Journal of Environmental Sciences · doi:10.1016/j.jes.2020.07.001 · Cited by 45 · 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
Zhang, Y., Lou, D., Hu, Z., & Tan, P. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.03.344 · Cited by 44 · see citing works
Energy-agriculture nexus: Exploring the future of artificial intelligence applications
Kabir, M., & Ekici, S. (2023) · Energy Nexus · doi:10.1016/j.nexus.2023.100263 · Cited by 43 · see citing works
Kumar, R. R., Sarkar, D., & Sen, R. (2024) · Applied Energy · doi:10.1016/j.apenergy.2023.122597 · Cited by 43 · see citing works
Self-citationAdvancements 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
De Bhowmick, G., Sen, R., & Sarmah, A. K. (2019) · Journal of Environmental Management · doi:10.1016/j.jenvman.2019.109696 · Cited by 42 · see citing works
Self-citationSalamattalab, M. M., Zonoozi, M. H., & Molavi‐Arabshahi, M. (2023) · Waste Management · doi:10.1016/j.wasman.2023.12.046 · Cited by 40 · 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
Park, S., Ahn, Y., Pandi, K., Ji, M.-K., Yun, H.-S., & Choi, J.-Y. (2019) · Energies · doi:10.3390/en12183497 · Cited by 39 · see citing works
Utilization of whole microalgal biomass for advanced biofuel and biorefinery applications
Moon, M., Park, W.-K., Lee, S. Y., Hwang, K.-R., Lee, S., Kim, M., Kim, B., Oh, Y., & Lee, J. (2022) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2022.112269 · Cited by 39 · see citing works
González-Camejo, J., Barat, R., Aguado, D., & Ferrer, J. (2019) · Water Research · doi:10.1016/j.watres.2019.115238 · Cited by 38 · see citing works
Mitra, R., Gupta, A. D., Kumar, R. R., & Sen, R. (2023) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2023.136217 · Cited by 38 · see citing works
Self-citationSheik, A. G., Kumar, A., Ansari, F. A., Raj, V., Peleato, N. M., Patan, A. K., Kumari, S., & Bux, F. (2024) · Algal Research · doi:10.1016/j.algal.2024.103779 · Cited by 37 · see citing works
Song, Y., Xie, L., Zhang, X., Hu, Z., Li, S., Zhang, P., & Yang, X. (2024) · Chemical Engineering Journal · doi:10.1016/j.cej.2024.149148 · Cited by 36 · see citing works
Naaz, F., Samuchiwal, S., Dalvi, V., Bhattacharya, A., Pant, K. K., & Malik, A. (2023) · Energy Conversion and Management · doi:10.1016/j.enconman.2023.116887 · Cited by 37 · see citing works
Sen, R., & Mukherjee, S. (2024) · Critical Reviews in Environmental Science and Technology · doi:10.1080/10643389.2024.2361938 · Cited by 35 · see citing works
Self-citationKavitha, S. K., Ravi, Y. K., Kumar, G., Yogalakshmi, K. N., & Banu, J. R. (2024) · Journal of Environmental Management · doi:10.1016/j.jenvman.2024.120135 · Cited by 33 · see citing works
Yin, X., Niu, Z., He, Z., Li, Z. S., & Lee, D. (2020) · Computers & Industrial Engineering · doi:10.1016/j.cie.2020.106284 · Cited by 33 · see citing works
Sharma, A., Sarkar, P., Chhabra, M., Kumar, A., V, Kumar, A., Kothadia, H., & Mallick, A. (2023) · Chemical Engineering Journal · doi:10.1016/j.cej.2023.146578 · Cited by 33 · see citing works
Chauhan, S., Solanki, P., Putatunda, C., Walia, A., Keprate, A., Bhatt, A. K., Thakur, V. K., & Bhatia, R. K. (2024) · Sustainable Energy Technologies and Assessments · doi:10.1016/j.seta.2024.104123 · Cited by 37 · see citing works
Kumar, R., Dhanarajan, G., Sarkar, D., & Sen, R. (2020) · Sustainable Energy & Fuels · doi:10.1039/d0se00922a · Cited by 28 · see citing works
Self-citationHajialigol, N., & Daghigh, R. (2023) · Journal of the Taiwan Institute of Chemical Engineers · doi:10.1016/j.jtice.2023.104782 · Cited by 28 · see citing works
Janjua, M. Y., Azfar, A., Asghar, Z., & Shehzad Quraishi, K. (2024) · Bioresource Technology · doi:10.1016/j.biortech.2024.130687 · Cited by 26 · see citing works
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Chatrabhuj, Meshram, K., Mishra, U., & Rathnayake, U. (2025) · Array · doi:10.1016/j.array.2025.100412 · Cited by 29 · see citing works
Renewable energy system paradigm change from trending technology: a review
Khare, V., Khare, C., Nema, S., & Baredar, P. (2020) · International Journal of Sustainable Energy · doi:10.1080/14786451.2020.1860043 · Cited by 25 · see citing works
Kubar, A. A., Cheng, J., Guo, W., Kumar, S., & Song, Y. (2020) · Bioresource Technology · doi:10.1016/j.biortech.2020.123253 · Cited by 24 · see citing works
Nayak, M., Suh, W. I., Cho, J. M., Kim, H. S., Lee, B., & Chang, Y. K. (2020) · Journal of Environmental Management · doi:10.1016/j.jenvman.2020.111041 · Cited by 23 · see citing works
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Khandelwal, A., Anand, A., Raghuvanshi, S., & Gupta, S. (2021) · Journal of environmental chemical engineering · doi:10.1016/j.jece.2021.105116 · Cited by 18 · see citing works
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Anand, A., Raghuvanshi, S., & Gupta, S. (2023) · Biomass Conversion and Biorefinery · doi:10.1007/s13399-023-03934-2 · Cited by 14 · see citing works
Khan, A., Ullah, S., Ali, R., Rehman, M., Moshawih, S., Goh, K. W., Ming, L. C., & Gew, L. T. (2025) · Royal Society Open Science · doi:10.1098/rsos.241336 · Cited by 15 · see citing works
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Sharma, A., Salhotra, S., Rathour, R. K., Solanki, P., Putatunda, C., Hans, M., Walia, A., & Bhatia, R. K. (2025) · Biomass and Bioenergy · doi:10.1016/j.biombioe.2025.108417 · Cited by 14 · see citing works
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Hajhoseini, A., Doroud, D., Sharifan, A., & Eftekhari, Z. (2020) · Applied food biotechnology · doi:10.22037/afb.v7i2.28055 · Cited by 11 · see citing works
Sun, W., Zhou, S., Sun, Y., Tang, J., & Zheng, H. (2020) · Water Environment Research · doi:10.1002/wer.1323 · Cited by 11 · see citing works
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Jiang, M., Cao, X., Wang, Z., Xing, M., Sun, Z., Wang, J., & Hu, J. (2023) · Bioresource Technology · doi:10.1016/j.biortech.2023.130246 · Cited by 10 · see citing works
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Barik, S. K., Kumar, P. P., Pal, U., & Aikat, K. (2024) · Clean Technologies and Environmental Policy · doi:10.1007/s10098-024-02851-w · Cited by 10 · see citing works
Yan, H., Ding, M., Lin, J., Zhao, L., Han, D., & Hu, Q. (2023) · Biotechnology for Biofuels and Bioproducts · doi:10.1186/s13068-023-02353-9 · 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
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El-Moustaqim, K., Mohammed, B., Mabrouki, J., & Hmouni, D. (2024) · Environmental science and engineering · doi:10.1007/978-3-031-50871-4_20 · Cited by 8 · see citing works
Jiang, P. Y., & Ma, Y. (2025) · Pacific-Basin Finance Journal · doi:10.1016/j.pacfin.2025.102951 · Cited by 8 · see citing works
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Sangregorio‐Soto, V., Mayorga, E. Y., & Perafán, R. D. L. H. (2026) · Fermentation · doi:10.3390/fermentation12030147 · Cited by 10 · see citing works
- Authors
- Nayak, M., Dhanarajan, G., Dineshkumar, R., & Sen, R.
- Affiliations
- Indian Institute of Technology Kharagpur (IN)
- Corresponding author
- Sen, Ramkrishna
- Venue
- Journal of Cleaner Production
- Publisher
- Elsevier BV
- Published
- 2018-11
- Volume
- 201
- Pages
- 1092-1100
- ISSN
- 0959-6526 (ISSN-L)
- OpenAlex
- W2886058761
- Cited by
- 166
- References
- 34
- Citations by year
- 2026: 23 · 2025: 42 · 2024: 24 · 2023: 24 · 2022: 17 · 2021: 7 · 2020: 18 · 2019: 10 · 2018: 1
- FWCI
- 2.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of Cleaner Production (publishedVersion)
- Funders
- DST (DST/IS-STAC/CO2-SR-160/13(G))
- IIT Kharagpur
- DST-INSPIRE, Government of India
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
- Physical Sciences › Environmental Science › Environmental Chemistry › Aquatic Ecosystems and Phytoplankton Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Keywords
- microalgae cultivation, Scenedesmus, artificial neural networks, genetic algorithm optimization, process parameter optimization, light intensity, photoperiod, temperature, initial pH, COD removal, lipid content, biodiesel, fatty acid methyl esters, algal biorefinery, coal-fired flue gas
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