286
5 Conclusion
Fundamental understanding of physicochemical interactions during biomass valorization is needed for the development of sustainable biomass processes. This chapter
reviews some of the recent studies on the implementation of molecular simulation
methods (DFT, MD, AIMD, CPMD-metadynamics, ReaxFF, etc.) to address the
challenges related to developing biomass conversion technologies such as screening
of solvents, understanding the mechanism and reaction kinetics in liquid-phase biomass reactions, and developing a reaction network for condensed phase biomass
pyrolysis. However, there are only few studies which take into account solvation
environment dynamics, temperature effects, condensed phase biomass processing
environment, etc. With the availability of higher parallel computing packages, there
exits an opportunity where this predictive computational modeling at different
scales can be used to fully explore the biomass processing.
References
1. Bardhan SK, Gupta S, Gorman ME, Haider MA (2015) Biorenewable chemicals: feedstocks,
technologies and the conflict with food production. Renew Sust Energ Rev 51:506–520
2. Werpy T, Petersen G (2004) Top value added chemicals from biomass volume I — results
of screening for potential candidates from sugars and synthesis gas. Biomass. https://doi.
org/10.2172/15008859
3. Alonso DM, Bond JQ, Dumesic JA (2010) Catalytic conversion of biomass to biofuels. Green
Chem 12:1493
4. Nakagawa Y, Tamura M, Tomishige K (2013) Catalytic reduction of biomass-derived furanic
compounds with hydrogen. ACS Catal 3:2655–2668
5. Nie L et al (2014) Selective conversion of m-cresol to toluene over bimetallic Ni-Fe catalysts.
J Mol Catal A Chem 388–389:47–55
6. Chia M et al (2013) Mechanistic insights into ring-opening and decarboxylation of 2-pyrones
in liquid water and tetrahydrofuran. J Am Chem Soc 135:5699–5708
7. Sitthisa S, An W, Resasco DE (2011) Selective conversion of furfural to methylfuran over
silica-supported NiFe bimetallic catalysts. J Catal 284:90–101
8. Schwartz TJ, Neill BJO, Shanks BH, Dumesic JA (2014) Bridging the chemical and biological catalysis gap: challenges and outlooks for producing sustainable chemicals. ACS Catal
4:2060–2069
9. Grajciar L et al (2018) Towards operando computational modeling in heterogeneous catalysis.
Chem Soc Rev 47:8307–8348
10. Sholl DS, Steckel JA (2009) Density functional theory a practical introduction. Wiley,
New York
11. Rapaport DC (2011) The art of molecular dynamics simulation. Cambridge University Press,
Cambridge. https://doi.org/10.1017/CBO9780511816581
12. Hassanali AA, Cuny J, Verdolino V, Parrinello M (2014) Aqueous solutions: state of the art in
ab initio molecular dynamics. Philos Trans R Soc A 372:1–32
13. Car R, Parrinello M (1985) Unified approach for molecular dynamics and density-functional
theory. Phys Rev Lett 55:2471–2474
14. Barducci A, Bonomi M, Parrinello M (2011) Metadynamics. WIREs Comput Mol Sci
1:826–843
S. Gupta
5 Conclusion
Fundamental understanding of physicochemical interactions during biomass valorization is needed for the development of sustainable biomass processes. This chapter
reviews some of the recent studies on the implementation of molecular simulation
methods (DFT, MD, AIMD, CPMD-metadynamics, ReaxFF, etc.) to address the
challenges related to developing biomass conversion technologies such as screening
of solvents, understanding the mechanism and reaction kinetics in liquid-phase biomass reactions, and developing a reaction network for condensed phase biomass
pyrolysis. However, there are only few studies which take into account solvation
environment dynamics, temperature effects, condensed phase biomass processing
environment, etc. With the availability of higher parallel computing packages, there
exits an opportunity where this predictive computational modeling at different
scales can be used to fully explore the biomass processing.
References
1. Bardhan SK, Gupta S, Gorman ME, Haider MA (2015) Biorenewable chemicals: feedstocks,
technologies and the conflict with food production. Renew Sust Energ Rev 51:506–520
2. Werpy T, Petersen G (2004) Top value added chemicals from biomass volume I — results
of screening for potential candidates from sugars and synthesis gas. Biomass. https://doi.
org/10.2172/15008859
3. Alonso DM, Bond JQ, Dumesic JA (2010) Catalytic conversion of biomass to biofuels. Green
Chem 12:1493
4. Nakagawa Y, Tamura M, Tomishige K (2013) Catalytic reduction of biomass-derived furanic
compounds with hydrogen. ACS Catal 3:2655–2668
5. Nie L et al (2014) Selective conversion of m-cresol to toluene over bimetallic Ni-Fe catalysts.
J Mol Catal A Chem 388–389:47–55
6. Chia M et al (2013) Mechanistic insights into ring-opening and decarboxylation of 2-pyrones
in liquid water and tetrahydrofuran. J Am Chem Soc 135:5699–5708
7. Sitthisa S, An W, Resasco DE (2011) Selective conversion of furfural to methylfuran over
silica-supported NiFe bimetallic catalysts. J Catal 284:90–101
8. Schwartz TJ, Neill BJO, Shanks BH, Dumesic JA (2014) Bridging the chemical and biological catalysis gap: challenges and outlooks for producing sustainable chemicals. ACS Catal
4:2060–2069
9. Grajciar L et al (2018) Towards operando computational modeling in heterogeneous catalysis.
Chem Soc Rev 47:8307–8348
10. Sholl DS, Steckel JA (2009) Density functional theory a practical introduction. Wiley,
New York
11. Rapaport DC (2011) The art of molecular dynamics simulation. Cambridge University Press,
Cambridge. https://doi.org/10.1017/CBO9780511816581
12. Hassanali AA, Cuny J, Verdolino V, Parrinello M (2014) Aqueous solutions: state of the art in
ab initio molecular dynamics. Philos Trans R Soc A 372:1–32
13. Car R, Parrinello M (1985) Unified approach for molecular dynamics and density-functional
theory. Phys Rev Lett 55:2471–2474
14. Barducci A, Bonomi M, Parrinello M (2011) Metadynamics. WIREs Comput Mol Sci
1:826–843
S. Gupta