IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v220y2021ics0360544220327481.html
   My bibliography  Save this article

Intensified alternative to purify methyl-Ethyl ketone in a framework of green process

Author

Listed:
  • Sánchez-Ramírez, Eduardo
  • Quiroz-Ramírez, Juan José
  • Contreras-Zarazua, Gabriel
  • Hernández-Castro, Salvador
  • Alcocer-García, Heriberto
  • Segovia-Hernández, Juan Gabriel

Abstract

Methyl-Ethyl Ketone (MEK) is a promising bulk chemical due to its several applications. MEK can be produced by hydrogenation of 2, 3-Butanediol, a chemical previously produced by fermentation. As hydrogenation results, the output is composed of water, isobutyraldehyde, 2, 3-Butanediol, and Methyl-ethyl ketone. Because of the thermodynamic interactions, two azeotropes are formed; consequently, the purification of that mixture is challenging. Current needs promote the generation of alternatives with good economic and environmental performance, however, inherent safety and good controllability must also be accomplished. In this study an intensified process is proposed to reduce the energy investment for MEK purification. The alternative is a hybrid process that combines the advantages of using a liquid-liquid extraction column for handling the azeotropes aforementioned. Additionally, this proposal is compared with four alternatives previously proposed based only on distillation. All alternatives were modeled in Aspen Plus and were optimized considering four targets, the total annual cost, the eco-indicator 99, the individual risk, and the condition number as economic, environmental, safety and controllability indexes, respectively. As a result, interesting trends among objectives and design variables were found. Additionally, the intensified design reported an energy investment of 6.78 MJfuel/kgMEK, and the best pure distillation alternative 35.5 MJfuel/KgMEK.

Suggested Citation

  • Sánchez-Ramírez, Eduardo & Quiroz-Ramírez, Juan José & Contreras-Zarazua, Gabriel & Hernández-Castro, Salvador & Alcocer-García, Heriberto & Segovia-Hernández, Juan Gabriel, 2021. "Intensified alternative to purify methyl-Ethyl ketone in a framework of green process," Energy, Elsevier, vol. 220(C).
    • Handle: RePEc:eee:energy:v:220:y:2021:i:c:s0360544220327481
    DOI: 10.1016/j.energy.2020.119641
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220327481
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2020.119641?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kumar, Manish & Gayen, Kalyan, 2011. "Developments in biobutanol production: New insights," Applied Energy, Elsevier, vol. 88(6), pages 1999-2012, June.
    2. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chiara Gruden & Irena Ištoka Otković & Matjaž Šraml, 2020. "Neural Networks Applied to Microsimulation: A Prediction Model for Pedestrian Crossing Time," Sustainability, MDPI, vol. 12(13), pages 1-22, July.
    2. Chou, Jui-Sheng & Truong, Dinh-Nhat, 2021. "A novel metaheuristic optimizer inspired by behavior of jellyfish in ocean," Applied Mathematics and Computation, Elsevier, vol. 389(C).
    3. Anurag Agarwal, 2009. "Theoretical insights into the augmented-neural-network approach for combinatorial optimization," Annals of Operations Research, Springer, vol. 168(1), pages 101-117, April.
    4. Mohammad Javad Feizollahi & Igor Averbakh, 2014. "The Robust (Minmax Regret) Quadratic Assignment Problem with Interval Flows," INFORMS Journal on Computing, INFORMS, vol. 26(2), pages 321-335, May.
    5. Nha Vo‐Thanh & Hans‐Peter Piepho, 2023. "Generating designs for comparative experiments with two blocking factors," Biometrics, The International Biometric Society, vol. 79(4), pages 3574-3585, December.
    6. Сластников С.А., 2014. "Применение Метаэвристических Алгоритмов Для Задачи Маршрутизации Транспорта," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 50(1), pages 117-126, январь.
    7. H. A. J. Crauwels & C. N. Potts & L. N. Van Wassenhove, 1998. "Local Search Heuristics for the Single Machine Total Weighted Tardiness Scheduling Problem," INFORMS Journal on Computing, INFORMS, vol. 10(3), pages 341-350, August.
    8. C N Potts & V A Strusevich, 2009. "Fifty years of scheduling: a survey of milestones," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 41-68, May.
    9. Nair, D.J. & Grzybowska, H. & Fu, Y. & Dixit, V.V., 2018. "Scheduling and routing models for food rescue and delivery operations," Socio-Economic Planning Sciences, Elsevier, vol. 63(C), pages 18-32.
    10. Cazzaro, Davide & Fischetti, Martina & Fischetti, Matteo, 2020. "Heuristic algorithms for the Wind Farm Cable Routing problem," Applied Energy, Elsevier, vol. 278(C).
    11. İbrahim Muter & Ş. İlker Birbil & Güvenç Şahin, 2010. "Combination of Metaheuristic and Exact Algorithms for Solving Set Covering-Type Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 22(4), pages 603-619, November.
    12. Kadri Sylejmani & Jürgen Dorn & Nysret Musliu, 2017. "Planning the trip itinerary for tourist groups," Information Technology & Tourism, Springer, vol. 17(3), pages 275-314, September.
    13. Huang, Yeran & Yang, Lixing & Tang, Tao & Gao, Ziyou & Cao, Fang, 2017. "Joint train scheduling optimization with service quality and energy efficiency in urban rail transit networks," Energy, Elsevier, vol. 138(C), pages 1124-1147.
    14. B Dengiz & C Alabas-Uslu & O Dengiz, 2009. "Optimization of manufacturing systems using a neural network metamodel with a new training approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(9), pages 1191-1197, September.
    15. S-W Lin & K-C Ying, 2008. "A hybrid approach for single-machine tardiness problems with sequence-dependent setup times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(8), pages 1109-1119, August.
    16. J-F Chen & T-H Wu, 2006. "Vehicle routing problem with simultaneous deliveries and pickups," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 579-587, May.
    17. Joseph B. Mazzola & Robert H. Schantz, 1997. "Multiple‐facility loading under capacity‐based economies of scope," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(3), pages 229-256, April.
    18. Kadri Sylejmani & Jürgen Dorn & Nysret Musliu, 0. "Planning the trip itinerary for tourist groups," Information Technology & Tourism, Springer, vol. 0, pages 1-40.
    19. Abdmouleh, Zeineb & Gastli, Adel & Ben-Brahim, Lazhar & Haouari, Mohamed & Al-Emadi, Nasser Ahmed, 2017. "Review of optimization techniques applied for the integration of distributed generation from renewable energy sources," Renewable Energy, Elsevier, vol. 113(C), pages 266-280.
    20. Masoud Yaghini & Mohammad Karimi & Mohadeseh Rahbar, 2015. "A set covering approach for multi-depot train driver scheduling," Journal of Combinatorial Optimization, Springer, vol. 29(3), pages 636-654, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:220:y:2021:i:c:s0360544220327481. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.