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Reducing the thermal hazard of hydrophobic silica aerogels by using dimethyldichlorosilane as modifier

  • Yinfeng Wang
  • Zhi LiEmail author
  • Lukas Huber
  • Xiaoxu Wu
  • Siqi Huang
  • Yan Zhang
  • Rui Huang
  • Qiong Liu
Original Paper: Nano- and macroporous materials (aerogels, xerogels, cryogels, etc.)

Abstract

Reducing organic groups on hydrophobic silica aerogels (SA) is worth exploring for lowering their thermal hazard risk. In this work, we used dimethyldichlorosilane (DMDCS) to modify silica alcogels, investigated the effects of DMDCS concentration and focused on the thermal hazard assessment of the DMDCS modified SA (DSA). It was turned out that the DSA had less −CH3 content in spite of the thermal stability close to the trimethylchlorosilane modified SA (TSA), about 240 °C. The kinetics study suggested the apparent activation energy (Ea) could be divided into two segments, corresponding to the two processes in the pyrolysis. The positive enthalpy and entropy changes indicated that the thermal oxidation of the DSA was an exothermic reaction, which could not occur without external energy supply. The average Ea of the DSA was far larger than that of the TSA and the gross calorific value of the DSA decreased by about 12% compared with that of the TSA. All these results drew a conclusion that the DMDCS modified SA reduced the thermal hazard to some degree, which provided one possible solution to further lower the thermal hazard of hydrophobic SA.

Highlights

  • Dimethyldichlorosilane modified silica aerogels (DSA) were prepared at the optimum concentration of 4%.

  • Kinetic and thermodynamic behavior of DSA were studied in detail.

  • DSA has larger apparent activation energy than trimethylchlorosilane modified silica aerogels (TSA).

  • DSA has lower thermal hazard than TSA for a less gross calorific value.

Keywords

Hydrophobic silica aerogels Thermal hazard Dimethyldichlorosilane Kinetics Thermodynamic parameter 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 51904336), the Fundamental Research Funds for the Central Universities (Nos. 202501003 and 202045001) and the China Scholarship Council (No. 201806375007). Furthermore, we really appreciate the anonymous reviewer for the constructive comments and the co-editor Florence Babonneau for the resubmission opportunity.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Husing N, Schubert U (1998) Aerogels-airy materials: chemistry, structure, and properties. Angew Chem Int Ed Engl 37:22–45.  https://doi.org/10.1002/(SICI)1521-3773(19980202)37:1/2<22::AID-ANIE22>3.0.CO;2-I CrossRefGoogle Scholar
  2. 2.
    Cuce E, Cuce PM, Wood CJ, Riffat SB (2014) Toward aerogel based thermal superinsulation in buildings: a comprehensive review. Renew Sustain Energy Rev 34:273–299.  https://doi.org/10.1016/j.rser.2014.03.017 CrossRefGoogle Scholar
  3. 3.
    Randall JP, Meador MAB, Jana SC (2011) Tailoring mechanical properties of aerogels for aerospace applications. Acs Appl Mater Interfaces 3:613–626.  https://doi.org/10.1021/am200007n CrossRefGoogle Scholar
  4. 4.
    Rao AV, Hegde ND, Hirashima H (2007) Absorption and desorption of organic liquids in elastic superhydrophobic silica aerogels. J Colloid Interface Sci 305:124–132.  https://doi.org/10.1016/j.jcis.2006.09.025 CrossRefGoogle Scholar
  5. 5.
    Zhao Y, Liang Y, Zhao X et al. (2011) Preparation and microstructure of CuO-CoO-MnO/SiO2 nanocomposite aerogels and xerogels as catalyst carriers. Prog Nat Sci Mater Int 21:330–335.  https://doi.org/10.1016/S1002-0071(12)60065-3 CrossRefGoogle Scholar
  6. 6.
    Alnaief M, Smirnova I (2010) Effect of surface functionalization of silica aerogel on their adsorptive and release properties. J Non-Cryst Solids 356:1644–1649.  https://doi.org/10.1016/j.jnoncrysol.2010.06.027 CrossRefGoogle Scholar
  7. 7.
    Koebel M, Rigacci A, Achard P (2012) Aerogel-based thermal superinsulation: an overview. J Sol–Gel Sci Technol 63:315–339.  https://doi.org/10.1007/s10971-012-2792-9 CrossRefGoogle Scholar
  8. 8.
    Baetens R, Jelle BP, Gustavsen A (2011) Aerogel insulation for building applications: a state-of-the-art review. Energy Build 43:761–769.  https://doi.org/10.1016/j.enbuild.2010.12.012 CrossRefGoogle Scholar
  9. 9.
    Wang B, Wu C, Kang L et al. (2018) Work safety in China’s thirteenth five-year plan period (2016–2020): current status, new challenges and future tasks. Saf Sci 104:164–178.  https://doi.org/10.1016/j.ssci.2018.01.012 CrossRefGoogle Scholar
  10. 10.
    Mahadik SA, Pedraza F, Parale VG, Park H-H (2016) Organically modified silica aerogel with different functional silylating agents and effect on their physico-chemical properties. J Non-Cryst Solids 453:164–171.  https://doi.org/10.1016/j.jnoncrysol.2016.08.035 CrossRefGoogle Scholar
  11. 11.
    Li Z, Cheng X, Shi L et al. (2016) Flammability and oxidation kinetics of hydrophobic silica aerogels. J Hazard Mater 320:350–358.  https://doi.org/10.1016/j.jhazmat.2016.07.054 CrossRefGoogle Scholar
  12. 12.
    Li Z, Huang S, Shi L et al. (2019) Reducing the flammability of hydrophobic silica aerogels by doping with hydroxides. J Hazard Mater 373:536–546.  https://doi.org/10.1016/j.jhazmat.2019.03.112 CrossRefGoogle Scholar
  13. 13.
    Ghazi Wakili K, Remhof A (2017) Reaction of aerogel containing ceramic fibre insulation to fire exposure. Fire Mater 41:29–39.  https://doi.org/10.1002/fam.2367 CrossRefGoogle Scholar
  14. 14.
    He S, Huang Y, Chen G et al. (2019) Effect of heat treatment on hydrophobic silica aerogel. J Hazard Mater 362:294–302.  https://doi.org/10.1016/j.jhazmat.2018.08.087 CrossRefGoogle Scholar
  15. 15.
    Zhang W, Li Z, Shi L et al. (2019) Methyltrichlorosilane modified hydrophobic silica aerogels and their kinetic and thermodynamic behaviors. J Sol–Gel Sci Technol 89:448–457.  https://doi.org/10.1007/s10971-018-4882-9 CrossRefGoogle Scholar
  16. 16.
    Luo Y, Li Z, Zhang W et al. (2019) Rapid synthesis and characterization of ambient pressure dried monolithic silica aerogels in ethanol/water co-solvent system. J Non-Cryst Solids 503:214–223.  https://doi.org/10.1016/j.jnoncrysol.2018.09.049 CrossRefGoogle Scholar
  17. 17.
    Li Z, Cheng X, Gong L et al. (2018) Enhanced flame retardancy of hydrophobic silica aerogels by using sodium silicate as precursor and phosphoric acid as catalyst. J Non-Cryst Solids 481:267–275.  https://doi.org/10.1016/j.jnoncrysol.2017.10.053 CrossRefGoogle Scholar
  18. 18.
    Malfait WJ, Zhao S, Verel R et al. (2015) Surface chemistry of hydrophobic silica aerogels. Chem Mater 27:6737–6745.  https://doi.org/10.1021/acs.chemmater.5b02801 CrossRefGoogle Scholar
  19. 19.
    Malfait WJ, Jurányi F, Zhao S et al. (2017) Dynamics of silica aerogel’s hydrophobic groups: a quasielastic neutron scattering study. J Phys Chem C 121:20335–20344.  https://doi.org/10.1021/acs.jpcc.7b06011 CrossRefGoogle Scholar
  20. 20.
    Iswar S, Griffa M, Kaufmann R et al. (2019) Effect of aging on thermal conductivity of fiber-reinforced aerogel composites: an X-ray tomography study. Microporous Mesoporous Mater 278:289–296.  https://doi.org/10.1016/j.micromeso.2018.12.006 CrossRefGoogle Scholar
  21. 21.
    Li Z, Cheng X, He S et al. (2015) Characteristics of ambient-pressure-dried aerogels synthesized via different surface modification methods. J Sol–Gel Sci Technol 76:138–149.  https://doi.org/10.1007/s10971-015-3760-y CrossRefGoogle Scholar
  22. 22.
    Soleimani Dorcheh A, Abbasi MH (2008) Silica aerogel; synthesis, properties and characterization. J Mater Process Technol 199:10–26.  https://doi.org/10.1016/j.jmatprotec.2007.10.060 CrossRefGoogle Scholar
  23. 23.
    Malfait WJ, Verel R, Koebel MM (2014) Hydrophobization of silica aerogels: insights from quantitative solid-state NMR spectroscopy. J Phys Chem C 118:25545–25554.  https://doi.org/10.1021/jp5082643 CrossRefGoogle Scholar
  24. 24.
    Schneider CA, Rasband WS, Eliceiri KW (2012) NIH image to imageJ: 25 years of image analysis. Nat Methods 9:671–675.  https://doi.org/10.1038/nmeth.2089 CrossRefGoogle Scholar
  25. 25.
    Brunauer S, Emmett PH, Teller E (1938) Adsorption of gases in multimolecular layers. J Am Chem Soc 60:309–319.  https://doi.org/10.1021/ja01269a023 CrossRefGoogle Scholar
  26. 26.
    Barrett EP, Joyner LG, Halenda PP (1951) The determination of pore volume and area distributions in porous substances. I. Computations from nitrogen isotherms. J Am Chem Soc 73:373–380.  https://doi.org/10.1021/ja01145a126 CrossRefGoogle Scholar
  27. 27.
    Wu X, Fan M, Shen X et al. (2018) Silica aerogels formed from soluble silicates and methyl trimethoxysilane (MTMS) using CO2 gas as a gelation agent. Ceram Int 44:821–829.  https://doi.org/10.1016/j.ceramint.2017.10.005 CrossRefGoogle Scholar
  28. 28.
    Cheng X, Li C, Shi X et al. (2017) Rapid synthesis of ambient pressure dried monolithic silica aerogels using water as the only solvent. Mater Lett 204:157–160.  https://doi.org/10.1016/j.matlet.2017.05.107 CrossRefGoogle Scholar
  29. 29.
    He S, Sun G, Cheng X et al. (2017) Nanoporous SiO 2 grafted aramid fibers with low thermal conductivity. Compos Sci Technol 146:91–98.  https://doi.org/10.1016/j.compscitech.2017.04.021 CrossRefGoogle Scholar
  30. 30.
    Gurav JL, Rao AV, Rao AP et al. (2009) Physical properties of sodium silicate based silica aerogels prepared by single step sol–gel process dried at ambient pressure. J Alloy Compd 476:397–402.  https://doi.org/10.1016/j.jallcom.2008.09.029 CrossRefGoogle Scholar
  31. 31.
    Jiang L, Zhang D, Li M et al. (2018) Pyrolytic behavior of waste extruded polystyrene and rigid polyurethane by multi kinetics methods and Py-GC/MS. Fuel 222:11–20.  https://doi.org/10.1016/j.fuel.2018.02.143 CrossRefGoogle Scholar
  32. 32.
    Flynn JH, Wall LA (1966) A quick, direct method for the determination of activation energy from thermogravimetric data. J Polym Sci Part C Polym Lett 4:323–328CrossRefGoogle Scholar
  33. 33.
    Doyle CD (2010) Estimating isothermal life from thermogravimetric data. J Appl Polym Sci 6:639–642.  https://doi.org/10.1002/app.1962.070062406 CrossRefGoogle Scholar
  34. 34.
    Ozawa T (1992) Estimation of activation energy by isoconversion methods. Thermochim Acta 203:159–165.  https://doi.org/10.1016/0040-6031(92)85192-X CrossRefGoogle Scholar
  35. 35.
    Domingos Maia AA, de Morais LC (2016) Kinetic parameters of red pepper waste as biomass to solid biofuel. Bioresour Technol 204:157–163.  https://doi.org/10.1016/j.biortech.2015.12.055 CrossRefGoogle Scholar
  36. 36.
    Rojas F, Kornhauser I, Felipe C et al. (2002) Capillary condensation in heterogeneous mesoporous networks consisting of variable connectivity and pore-size correlation. Phys Chem Chem Phys 4:2346–2355.  https://doi.org/10.1039/b108785a CrossRefGoogle Scholar
  37. 37.
    Gurav JL, Rao AV, Rao AP et al. (2009) Physical properties of sodium silicate based silica aerogels prepared by single step sol-gel process dried at ambient pressure. J Alloy Compd 476:397–402.  https://doi.org/10.1016/j.jallcom.2008.09.029 CrossRefGoogle Scholar
  38. 38.
    Rao AP, Rao AV, Pajonk GM (2007) Hydrophobic and physical properties of the ambient pressure dried silica aerogels with sodium silicate precursor using various surface modification agents. Appl Surf Sci 253:6032–6040.  https://doi.org/10.1016/j.apsusc.2006.12.117 CrossRefGoogle Scholar
  39. 39.
    Kim YS, Kim YS, Kim SH (2010) Investigation of thermodynamic parameters in the thermal decomposition of plastic waste-waste lube oil compounds. Environ Sci Technol 44:5313–5317.  https://doi.org/10.1021/es101163e CrossRefGoogle Scholar
  40. 40.
    Zhuravlev LT (2000) The surface chemistry of amorphous silica. Zhuravlev model. Colloids Surf Physicochem Eng Asp 173:1–38.  https://doi.org/10.1016/S0927-7757(00)00556-2 CrossRefGoogle Scholar
  41. 41.
    Turmanova SC, Genieva SD, Dimitrova AS, Vlaev LT (2008) Non-isothermal degradation kinetics of filled with rise husk ash polypropene composites. Express Polym Lett 2:133–146.  https://doi.org/10.3144/expresspolymlett.2008.18 CrossRefGoogle Scholar
  42. 42.
    Yuan X, He T, Cao H, Yuan Q (2017) Cattle manure pyrolysis process: kinetic and thermodynamic analysis with isoconversional methods. Renew Energy 107:489–496.  https://doi.org/10.1016/j.renene.2017.02.026 CrossRefGoogle Scholar
  43. 43.
    Xu Y, Chen B (2013) Investigation of thermodynamic parameters in the pyrolysis conversion of biomass and manure to biochars using thermogravimetric analysis. Bioresour Technol 146:485–493.  https://doi.org/10.1016/j.biortech.2013.07.086 CrossRefGoogle Scholar
  44. 44.
    Sheng J, Ji D, Yu F et al. (2014) Influence of chemical treatment on rice straw pyrolysis by TG-FTIR. Ieri Procedia 8:30–34.  https://doi.org/10.1016/j.ieri.2014.09.006 CrossRefGoogle Scholar
  45. 45.
    Kim YS, Kim YS, Kim SH (2010) Investigation of thermodynamic parameters in the thermal decomposition of plastic waste-waste lube oil compounds. Environ Sci Technol 44:5313–5317.  https://doi.org/10.1021/es101163e CrossRefGoogle Scholar
  46. 46.
    Mancini M, Rinnan A, Pizzi A, Toscano G (2018) Prediction of gross calorific value and ash content of woodchip samples by means of FT-NIR spectroscopy. Fuel Process Technol 169:77–83.  https://doi.org/10.1016/j.fuproc.2017.09.021 CrossRefGoogle Scholar
  47. 47.
    Mesroghli Sh, Jorjani E, Chehreh Chelgani S (2009) Estimation of gross calorific value based on coal analysis using regression and artificial neural networks. Int J Coal Geol 79:49–54.  https://doi.org/10.1016/j.coal.2009.04.002 CrossRefGoogle Scholar
  48. 48.
    Patel SU, Kumar BJ, Badhe YP et al. (2007) Estimation of gross calorific value of coals using artificial neural networks. Fuel 86:334–344.  https://doi.org/10.1016/j.fuel.2006.07.036 CrossRefGoogle Scholar
  49. 49.
    Yamazaki I, Mimuro M, Murao T et al. (1984) Excitation energy transfer in the light harvesting antenna system of the red ALGA Porphyridium cruentum and the blue-green ALGA Anacystis nidulans: analysis of time-resolved fluorescence spectra. Photochem Photobiol 39:233–240.  https://doi.org/10.1111/j.1751-1097.1984.tb03432.x CrossRefGoogle Scholar
  50. 50.
    Feng Q, Zhang J, Zhang X, Wen S (2015) Proximate analysis based prediction of gross calorific value of coals: a comparison of support vector machine, alternating conditional expectation and artificial neural network. Fuel Process Technol 129:120–129.  https://doi.org/10.1016/j.fuproc.2014.09.001 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Yinfeng Wang
    • 1
  • Zhi Li
    • 1
    • 2
    Email author
  • Lukas Huber
    • 2
  • Xiaoxu Wu
    • 1
    • 3
  • Siqi Huang
    • 1
  • Yan Zhang
    • 1
  • Rui Huang
    • 1
  • Qiong Liu
    • 1
  1. 1.School of Resources and Safety EngineeringCentral South UniversityChangshaPR China
  2. 2.Laboratory for Building Energy Materials and ComponentsSwiss Federal Laboratories for Materials Science and Technology, EmpaDübendorfSwitzerland
  3. 3.School of Economics and ManagementChangsha UniversityChangshaPR China

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