[1] Gande VV, Podupu PK, Berry B, Nere NK, Pushpavanam S, Singh MR (2024) Engineering advancements in microfluidic systems for enhanced mixing at low Reynolds numbers. Biomicrofluidics 18(1):011502.
https://doi.org/10.1063/5.0178939.
[2] Kumar S (2024) Mass transfer and hydrodynamic studies in a 100 μm diameter microfluidic channel in a rotated helical configuration. Chem Eng Process 202:109855.
https://doi.org/10.1016/j.cep.2024.109855.
[3] Fadaee MM, Doyle BJ, Roberge DM, Macchi A, Haelssig JB (2024) Liquid flow field and residence time distribution in a baffleless oscillatory flow coil reactor. Chem Eng J 492:151758.
https://doi.org/10.1016/j.cej.2024.151758.
[4] Farhadi S, Shekari Y, Omidvar P (2024) Numerical and experimental investigation of laminar and turbulent convective heat transfer in a coiled flow reverser with twisted tape insert. Int J Therm Sci 197:108781.
https://doi.org/10.1016/j.ijthermalsci.2023.108781.
[5] Barrera MC, Leech D, Josifovic A, Tolouei A, Alford G, Wallace MJ, Bennett N, Wildman R, Irvine DJ, Croft A, Özcan E (2025) Optimisation of additively manufactured coiled flow inverters for continuous viral inactivation processes. Chem Eng Res Des 213:126–136.
https://doi.org/10.1016/j.cherd.2024.11.040.
[6] Tripathi A, Sarkar K, Patel S, Mishra U, Nigam KPD, Panda D, Biswas KG (2024) Elucidating flow-directed 98% CO₂ absorption using millimeter-sized coiled flow inverters: Nanocellulose aided sustainable scope. Chem Eng Process 205:110022.
https://doi.org/10.1016/j.cep.2024.110022.
[7] Schael F, Steup B, Rojahn P, Nigam KD (2024) Millistructured Coiled Flow Inverter for Biphasic Continuous Flow 5‐Chloromethylfurfural Synthesis. Chem Ing Tech 96(6):871–877.
https://doi.org/10.1002/cite.202300163.
[8] Kazemi-Esfe H, Shekari Y, Omidvar P (2024) Comparison of heat transfer characteristics of a heat exchanger with straight helical tube and a heat exchanger with coiled flow reverser. Appl Therm Eng 253:123772.
https://doi.org/10.1016/j.applthermaleng.2024.123772.
[9] Mierka O, Münster R, Surkamp J, Kockmann N, Turek S (2023) Numerical simulation and mixing characterization of Taylor bubble flows in coiled flow inverters. Paper presented at the 16th International Conference on Gas-Liquid and Gas-Liquid-Solid Reactor Engineering (GLS-16), University of Twente, Enschede, Netherlands, 19–22 June 2023. Elsevier:123–134.
[10] Izadi M, Rahimi M, Beigzadeh R, Alsairafi AA (2025) Geometric optimization of coiled flow inverters to enhance biodiesel production using CFD and genetic algorithms. Can J Chem Eng.
https://doi.org/10.1002/cjce.70002.
[11] Mansour M, Zähringer K, Nigam KDP, Thevenin D, Janiga G (2020) Optimization of coiled flow inverters using CFD: mixing efficiency and flow characterization. Chem Eng J 391:123570.
https://doi.org/10.1016/j.cej.2019.123570.
[12] Soltanian S, Beigzadeh R (2023) Computational fluid dynamics and fuzzy logic for modeling conical spiral heat exchangers. Chem Eng Technol 46(4):747–755.
https://doi.org/10.1002/ceat.202200488.
[13] Mehrabi M, Pesteei SM, Pashaee TG (2011) Modeling of heat transfer and fluid flow characteristics of helicoidal double-pipe heat exchangers using Adaptive Neuro-Fuzzy Inference System (ANFIS). Int Commun Heat Mass Transf 38:525–532.
https://doi.org/10.1016/j.icheatmasstransfer.2010.12.025.
[14] Beigzadeh R, Hajialyani M, Rahimi M (2016) Heat transfer and fluid flow modeling in serpentine microtubes using adaptive neuro-fuzzy approach. Korean J Chem Eng 33:1534–1550.
https://doi.org/10.1007/s11814-015-0281-x.
[15] Dolatabadi M, Mehrabpour M, Esfandyari M, Alidadi H, Davoudi M (2018) Modeling of simultaneous adsorption of dye and metal ion by sawdust from aqueous solution using ANN and ANFIS. Chemom Intell Lab Syst 181:72–78.
https://doi.org/10.1016/j.chemolab.2018.07.012.
[16] Onu CE, Nwabanne JT, Ohale PE, Asadu CO (2021) Comparative analysis of RSM, ANN and ANFIS and the mechanistic modeling in eriochrome black-T dye adsorption using modified clay. S Afr J Chem Eng 36:24–42.
https://doi.org/10.1016/j.sajce.2020.12.003.
[17] Lashkaripour A, Goharimanesh M, Mehrizi AA, Densmore D (2018) An adaptive neural-fuzzy approach for microfluidic droplet size prediction. Microelectron J 78:73–80.
https://doi.org/10.1016/j.mejo.2018.05.018.
[18] Efe MÖ (2010) A comparison of networked approximators in parallel mode identification of a bioreactor. Adv Eng Softw 41:1132–1147.
https://doi.org/10.1016/j.advengsoft.2010.07.004.
[19] Esen H, Esen M, Ozsolak O (2017) Modelling and experimental performance analysis of solar-assisted ground source heat pump system. J Exp Theor Artif Intell 29:1–17.
https://doi.org/10.1080/0952813x.2015.1056242.
[20] Pai T, Wan T, Hsu S, Chang T, Tsai Y, Lin C, Su H, Yu L (2009) Using fuzzy inference system to improve neural network for predicting hospital wastewater treatment plant effluent. Comput Chem Eng 33:1272–1278.
https://doi.org/10.1016/j.compchemeng.2009.02.004.
[21] Izadi M, Rahimi M, Beigzadeh R (2019) Evaluation of micromixing in helically coiled microreactors using artificial intelligence approaches. Chem Eng J 356:570–579.
https://doi.org/10.1016/j.cej.2018.09.052.
[22] Kumar V, Mridha M, Gupta AK, Nigam KDP (2007) Coiled flow inverter as a heat exchanger. Chem Eng Sci 62(9):2386–2396.
https://doi.org/10.1016/j.ces.2007.01.032.
[23] Onwubolu GC, Babu BV (2013) New Optimization Techniques in Engineering (Vol. 141). Springer, Berlin, Heidelberg.
[24] Ekici L, Simsek Z, Ozturk I, Sagdic O, Yetim H (2014) Effects of temperature, time, and pH on the stability of anthocyanin extracts: prediction of total anthocyanin content using nonlinear models. Food Anal Methods 7:1328–1336.
https://doi.org/10.1007/s12161-013-9753-y.
[25] Jang JS (1993) ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans Syst Man Cybern 23:665–685.
https://doi.org/10.1109/21.256541.
[26] Kişi Ö (2006) Daily pan evaporation modelling using a neuro-fuzzy computing technique. J Hydrol 329:636–646.
https://doi.org/10.1016/j.jhydrol.2006.03.015