103. Gaus M, Chou C-P, Witek H, Elstner M (2009) Automatized parametrization of SCC-DFTB
repulsive potentials: application to hydrocarbons. J Phys Chem A 113:11866–11881
104. Gaus M, Cui Q, Elstner M (2011) DFTB3: extension of the self-consistent-charge densityfunctional tight-binding method (SCC-DFTB). J Chem Theor Comput 7:931–948. https://doi.
org/10.1021/ct100684s
105. Gaus M, Cui Q, Elstner M (2014) Density functional tight binding: application to organic and
biological molecules. WIREs Comput Mol Sci 4:49–61. https://doi.org/10.1002/wcms.1156
106. Elstner M, Seifert G (2014) Density functional tight binding. Philos Trans R Soc A
372:20120483. https://doi.org/10.1098/rsta.2012.0483
107. Vujović M, Huynh M, Steiner S, Garcia-Fernandez P, Elstner M, Cui Q, Gruden M (2019)
Exploring the applicability of density functional tight binding to transition metal ions. Parameterization for nickel with the spin-polarized DFTB3 model. J Comput Chem 40:400–413.
https://doi.org/10.1002/jcc.25614
108. Bannwarth C, Ehlert S, Grimme S (2019) GFN2-xTB-an accurate and broadly parametrized
self-consistent tight-binding quantum chemical method with multipole electrostatics and
density-dependent dispersion contributions. J Chem Theory Comp 15:1652–1671. https://
doi.org/10.1021/acs.jctc.8b01176
109. Grimme S, Bannwarth C, Shushkov P (2017) A robust and accurate tight-binding quantum
chemical method for structures, vibrational frequencies, and noncovalent interactions of large
molecular systems parametrized for all spd-block elements (Z ¼ 1–86). J Chem Theor Comput
13:1989–2009. https://doi.org/10.1021/acs.jctc.7b00118
110. Swart M (2007) Metal-ligand bonding in metallocenes: differentiation between spin state,
electrostatic and covalent bonding. Inorg Chim Acta 360(1):179–189. https://doi.org/10.1016/
j.ica.2006.07.073
111. Swart M (2013) Spin states of (bio)inorganic systems: successes and pitfalls. Int J Quantum
Chem 113:2–7. https://doi.org/10.1002/qua.24255
112. Harvey JN (2014) Spin-forbidden reactions: computational insight into mechanisms and
kinetics. WIREs Comput Mol Sci 4:1–14
113. Klopper W, Lüthi HP (1996) Towards the accurate computation of properties of transition
metal compounds: the binding energy of ferrocene. Chem Phys Lett 262:546–552
114. Helgaker T, Jørgensen P, Olsen J (2000) Molecular electronic-structure theory. Wiley,
Chichester
115. Roos BO, Lindh R, Malmqvist PA, Veryazov V, Widmark P-O (2016) Multiconfigurational
quantum chemistry. Wiley, Hoboken
116. Marti KH, Reiher M (2010) The density matrix renormalization group algorithm in quantum
chemistry. Z Phys Chem 224:583–599. https://doi.org/10.1524/zpch.2010.6125
117. Keller SF, Reiher M (2014) Determining factors for the accuracy of DMRG in chemistry.
Chimia 68:200–203. https://doi.org/10.2533/chimia.2014.200
118. Li Manni G, Alavi A (2018) Understanding the mechanism stabilizing intermediate spin states
in Fe(II)-porphyrin. J Phys Chem A 122:4935–4947. https://doi.org/10.1021/acs.jpca.
7b12710
119. Vogiatzis KD, Manni GL, Stoneburner SJ, Ma D, Gagliardi L (2015) Systematic expansion of
active spaces beyond the CASSCF limit: a GASSCF/SplitGAS benchmark study. J Chem
Theor Comput 11:3010–3021. https://doi.org/10.1021/acs.jctc.5b00191
120. Hermes MR, Gagliardi L (2019) Multiconfigurational self-consistent field theory with density
matrix embedding: the localized active space self-consistent field method. J Chem Theor
Comput 15:972–986. https://doi.org/10.1021/acs.jctc.8b01009
121. Li C, Lindh R, Evangelista FA (2019) Dynamically weighted multireference perturbation
theory: combining the advantages of multi-state and state-averaged methods. J Chem Phys
150:144107. https://doi.org/10.1063/1.5088120
122. Via-Nadal M, Rodríguez-Mayorga M, Ramos-Cordoba E, Matito E (2019) Singling out
dynamic and nondynamic correlation. J Phys Chem Lett 10:4032–4037. https://doi.org/10.
1021/acs.jpclett.9b01376
Dealing with Spin States in Computational Organometallic Catalysis
221
repulsive potentials: application to hydrocarbons. J Phys Chem A 113:11866–11881
104. Gaus M, Cui Q, Elstner M (2011) DFTB3: extension of the self-consistent-charge densityfunctional tight-binding method (SCC-DFTB). J Chem Theor Comput 7:931–948. https://doi.
org/10.1021/ct100684s
105. Gaus M, Cui Q, Elstner M (2014) Density functional tight binding: application to organic and
biological molecules. WIREs Comput Mol Sci 4:49–61. https://doi.org/10.1002/wcms.1156
106. Elstner M, Seifert G (2014) Density functional tight binding. Philos Trans R Soc A
372:20120483. https://doi.org/10.1098/rsta.2012.0483
107. Vujović M, Huynh M, Steiner S, Garcia-Fernandez P, Elstner M, Cui Q, Gruden M (2019)
Exploring the applicability of density functional tight binding to transition metal ions. Parameterization for nickel with the spin-polarized DFTB3 model. J Comput Chem 40:400–413.
https://doi.org/10.1002/jcc.25614
108. Bannwarth C, Ehlert S, Grimme S (2019) GFN2-xTB-an accurate and broadly parametrized
self-consistent tight-binding quantum chemical method with multipole electrostatics and
density-dependent dispersion contributions. J Chem Theory Comp 15:1652–1671. https://
doi.org/10.1021/acs.jctc.8b01176
109. Grimme S, Bannwarth C, Shushkov P (2017) A robust and accurate tight-binding quantum
chemical method for structures, vibrational frequencies, and noncovalent interactions of large
molecular systems parametrized for all spd-block elements (Z ¼ 1–86). J Chem Theor Comput
13:1989–2009. https://doi.org/10.1021/acs.jctc.7b00118
110. Swart M (2007) Metal-ligand bonding in metallocenes: differentiation between spin state,
electrostatic and covalent bonding. Inorg Chim Acta 360(1):179–189. https://doi.org/10.1016/
j.ica.2006.07.073
111. Swart M (2013) Spin states of (bio)inorganic systems: successes and pitfalls. Int J Quantum
Chem 113:2–7. https://doi.org/10.1002/qua.24255
112. Harvey JN (2014) Spin-forbidden reactions: computational insight into mechanisms and
kinetics. WIREs Comput Mol Sci 4:1–14
113. Klopper W, Lüthi HP (1996) Towards the accurate computation of properties of transition
metal compounds: the binding energy of ferrocene. Chem Phys Lett 262:546–552
114. Helgaker T, Jørgensen P, Olsen J (2000) Molecular electronic-structure theory. Wiley,
Chichester
115. Roos BO, Lindh R, Malmqvist PA, Veryazov V, Widmark P-O (2016) Multiconfigurational
quantum chemistry. Wiley, Hoboken
116. Marti KH, Reiher M (2010) The density matrix renormalization group algorithm in quantum
chemistry. Z Phys Chem 224:583–599. https://doi.org/10.1524/zpch.2010.6125
117. Keller SF, Reiher M (2014) Determining factors for the accuracy of DMRG in chemistry.
Chimia 68:200–203. https://doi.org/10.2533/chimia.2014.200
118. Li Manni G, Alavi A (2018) Understanding the mechanism stabilizing intermediate spin states
in Fe(II)-porphyrin. J Phys Chem A 122:4935–4947. https://doi.org/10.1021/acs.jpca.
7b12710
119. Vogiatzis KD, Manni GL, Stoneburner SJ, Ma D, Gagliardi L (2015) Systematic expansion of
active spaces beyond the CASSCF limit: a GASSCF/SplitGAS benchmark study. J Chem
Theor Comput 11:3010–3021. https://doi.org/10.1021/acs.jctc.5b00191
120. Hermes MR, Gagliardi L (2019) Multiconfigurational self-consistent field theory with density
matrix embedding: the localized active space self-consistent field method. J Chem Theor
Comput 15:972–986. https://doi.org/10.1021/acs.jctc.8b01009
121. Li C, Lindh R, Evangelista FA (2019) Dynamically weighted multireference perturbation
theory: combining the advantages of multi-state and state-averaged methods. J Chem Phys
150:144107. https://doi.org/10.1063/1.5088120
122. Via-Nadal M, Rodríguez-Mayorga M, Ramos-Cordoba E, Matito E (2019) Singling out
dynamic and nondynamic correlation. J Phys Chem Lett 10:4032–4037. https://doi.org/10.
1021/acs.jpclett.9b01376
Dealing with Spin States in Computational Organometallic Catalysis
221