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2012 | OriginalPaper | Buchkapitel

First-Principles-Based Multiscale, Multiparadigm Molecular Mechanics and Dynamics Methods for Describing Complex Chemical Processes

verfasst von : Andres Jaramillo-Botero, Robert Nielsen, Ravi Abrol, Julius Su, Tod Pascal, Jonathan Mueller, William A. Goddard III

Erschienen in: Multiscale Molecular Methods in Applied Chemistry

Verlag: Springer Berlin Heidelberg

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Abstract

We expect that systematic and seamless computational upscaling and downscaling for modeling, predicting, or optimizing material and system properties and behavior with atomistic resolution will eventually be sufficiently accurate and practical that it will transform the mode of development in the materials, chemical, catalysis, and Pharma industries. However, despite truly dramatic progress in methods, software, and hardware, this goal remains elusive, particularly for systems that exhibit inherently complex chemistry under normal or extreme conditions of temperature, pressure, radiation, and others. We describe here some of the significant progress towards solving these problems via a general multiscale, multiparadigm strategy based on first-principles quantum mechanics (QM), and the development of breakthrough methods for treating reaction processes, excited electronic states, and weak bonding effects on the conformational dynamics of large-scale molecular systems. These methods have resulted directly from filling in the physical and chemical gaps in existing theoretical and computational models, within the multiscale, multiparadigm strategy. To illustrate the procedure we demonstrate the application and transferability of such methods on an ample set of challenging problems that span multiple fields, system length- and timescales, and that lay beyond the realm of existing computational or, in some case, experimental approaches, including understanding the solvation effects on the reactivity of organic and organometallic structures, predicting transmembrane protein structures, understanding carbon nanotube nucleation and growth, understanding the effects of electronic excitations in materials subjected to extreme conditions of temperature and pressure, following the dynamics and energetics of long-term conformational evolution of DNA macromolecules, and predicting the long-term mechanisms involved in enhancing the mechanical response of polymer-based hydrogels.

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Literatur
1.
de Broglie L (1924) Recherches sur la théorie des quanta
2.
Schrodinger E (1926) Quantification of the eigen-value problem. Ann Phys 79(6):489–527
3.
Messiah A (ed) (1999) Quantum mechanics, vol 1. Reprinted by Dover Publications, Mineola, NY
4.
Anderson JB (1976) Quantum chemistry by Random-Walk – H2p, H+3d3h1a'1, H-23-Sigma+U, H-41-Sigma+G, Be1s. J Chem Phys 65(10):4121–4127
5.
Williamson AJ, Hood RQ, Grossman JC (2001) Linear-scaling quantum Monte Carlo calculations. Phys Rev Lett 8724(24):246406-(4)
6.
Reboredo FA, Williamson AJ (2005) Optimized nonorthogonal localized orbitals for linear scaling quantum Monte Carlo calculations. Phys Rev B 71(12):121105-(4)
7.
Morokuma K et al (2001) Model studies of the structures, reactivities, and reaction mechanisms of metalloenzymes. Ibm J Res Dev 45(3–4):367–395
8.
Fisher DR et al (2008) An optimized initialization algorithm to ensure accuracy in quantum Monte Carlo calculations. J Comput Chem 29(14):2335–2343
9.
Anderson AG, Goddard WA, Schroder P (2007) Quantum Monte Carlo on graphical processing units. Comput Phys Commun 177(3):298–306
10.
Anderson AG, Goddard WA (2010) Generalized valence bond wave functions in quantum Monte Carlo. J Chem Phys 132(16):164110-(10)
11.
Born M, Oppenheimer R (1927) Quantum theory of molecules. Ann Phys 84(20):0457–0484
12.
Frisch MJ et al (2004) Gaussian. Gaussian, Inc., Wallingford CT
13.
Schmidt MW et al (1993) General atomic and molecular electronic-structure system. J Comput Chem 14(11):1347–1363
14.
Jaguar (1991–2000) Jaguar. Schrodinger, Inc., Portland, OR
15.
Kresse G, Hafner J (1993) Ab initio molecular-dynamics for liquid-metals. Phys Rev B 47(1):558–561
16.
Dovesi R et al (2006) Crystal, U.o. Torino, Editor. 2006: Torino
17.
Segall MD et al (2002) First-principles simulation: ideas, illustrations and the CASTEP code. J Phys Condens Matter 14(11):2717–2744
18.
Schultz PA (2007) SeqQuest electronic structure code. Sandia National Laboratories, Albuquerque
19.
20.
Moller C, Plesset MS (1934) Note on an approximation treatment for many-electron systems. Phys Rev 46(7):0618–0622
21.
Carter EA, Goddard WA (1988) Correlation-consistent configuration-interaction – accurate bond-dissociation energies from simple wave-functions. J Chem Phys 88(5):3132–3140
22.
Friesner RA (2005) Ab initio quantum chemistry: methodology and applications. Proc Natl Acad Sci U S A 102(19):6648–6653
23.
Goddard WA et al (1973) Generalized valence bond description of bonding in low-lying states of molecules. Acc Chem Res 6(11):368–376
24.
Greeley BH et al (1994) New pseudospectral algorithms for electronic-structure calculations – length scale separation and analytical 2-electron integral corrections. J Chem Phys 101(5):4028–4041
25.
Tannor DJ et al (1994) Accurate first principles calculation of molecular charge-distributions and solvation energies from ab-initio quantum-mechanics and continuum dielectric theory. J Am Chem Soc 116(26):11875–11882
26.
Bredow T, Jug K (2005) Theory and range of modern semiempirical molecular orbital methods. Theor Chem Acc 113(1):1–14
27.
Hohenberg P, Kohn W (1964) Phys Rev B 136(3):864
28.
Kohn W, Sham LJ (1965) Phys Rev A 140(4):1133
29.
Li ZY, He W, Yang JL (2005) Recent progress in density functional theory and its numerical methods. Prog Chem 17(2):192–202
30.
Foulkes WMC et al (2001) Quantum Monte Carlo simulations of solids (review article). Rev Mod Phys 73:33
31.
Chen XJ, Langlois JM, Goddard WA (1995) Dual-space approach for density-functional calculations of 2-dimensional and 3-dimensional crystals using Gaussian-basis functions. Phys Rev B 52(4):2348–2361
32.
Liu Y, Goddard WA (2009) A universal damping function for empirical dispersion correction on density functional theory. Mater Trans 50(7):1664–1670
33.
Dobson JC, Meyer TJ (1988) Redox properties and ligand loss chemistry in aqua hydroxo complexes derived from CIS-(BPY)2RU2(OH2)2 2+ and TRANS- (BPY)2RUII(OH2)2 2+. Inorg Chem 27(19):3283–3291
34.
Hill T (1960) An introduction to statistical thermodynamics. Addison-Wesley, Reading
35.
Tissandier MD et al (1998) The proton’s absolute aqueous enthalpy and Gibbs free energy of solvation from cluster-ion solvation data. J Phys Chem A 102(40):7787–7794
36.
Kelly CP, Cramer CJ, Truhlar DG (2006) Aqueous solvation free energies of ions and ion-water clusters based on an accurate value for the absolute aqueous solvation free energy of the proton. J Phys Chem B 110(32):16066–16081
37.
Srnec M et al (2008) Effect of spin-orbit coupling on reduction potentials of octahedral ruthenium(II/III) and osmium(II/III) complexes. J Am Chem Soc 130(33):10947–10954
38.
Car R, Parrinello M (1985) Unified approach for molecular-dynamics and density-functional theory. Phys Rev Lett 55(22):2471–2474
39.
Mayo SL, Olafson BD, Goddard WA III (1990) DREIDING: a generic force field for molecular simulations. J Phys Chem 94:8897–8909
40.
Ding HQ, Karasawa N, Goddard WA (1992) Atomic level simulations on a million particles – the cell multipole method for Coulomb and London nonbond interactions. J Chem Phys 97(6):4309–4315
41.
Ding HQ, Karasawa N, Goddard WA (1992) The reduced cell multipole method for Coulomb interactions in periodic-systems with million-atom unit cells. Chem Phys Lett 196(1–2):6–10
42.
Ponder JW, Case DA (2003) Force fields for protein simulations. Protein Simul 66:27–85
43.
Weiner SJ et al (1986) An all atom force-field for simulations of proteins and nucleic-acids. J Comput Chem 7(2):230–252
44.
MacKerell AD et al (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. J Phys Chem B 102(18):3586–3616
45.
Jorgensen WL, Maxwell DS, TiradoRives J (1996) Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. J Am Chem Soc 118(45):11225–11236
46.
Karplus M, McCammon JA (2002) Molecular dynamics simulations of biomolecules. Nat Struct Biol 9(9):646–652
47.
Lagerstrom MC, Schioth HB (2008) Structural diversity of G protein-coupled receptors and significance for drug discovery (vol 7, p 339, 2008). Nat Rev Drug Discov 7(6):542
48.
Lagerstrom MC, Schioth HB (2008) Structural diversity of G protein-coupled receptors and significance for drug discovery. Nat Rev Drug Discov 7(4):339–357
49.
Kam VWT, Goddard WA (2008) Flat-bottom strategy for improved accuracy in protein side-chain placements. J Chem Theory Comput 4(12):2160–2169
50.
van Duin ACT et al (2001) ReaxFF: a reactive force field for hydrocarbons. J Phys Chem A 105(41):9396–9409
51.
Su JT, Goddard WA (2007) Excited electron dynamics modeling of warm dense matter. Phys Rev Lett 99(18):185003
52.
Strachan A et al (2005) Thermal decomposition of RDX from reactive molecular dynamics. J Chem Phys 122(5):054502
53.
van Duin ACT et al (2003) ReaxFF(SiO) reactive force field for silicon and silicon oxide systems. J Phys Chem A 107(19):3803–3811
54.
Han SS et al (2005) Optimization and application of lithium parameters for the reactive force field, ReaxFF. J Phys Chem A 109(20):4575–4582
55.
Zhang Q et al (2004) Adhesion and nonwetting-wetting transition in the Al/alpha-Al2O3 interface. Phys Rev B 69(4):045423-(11)
56.
Nielson KD et al (2005) Development of the ReaxFF reactive force field for describing transition metal catalyzed reactions, with application to the initial stages of the catalytic formation of carbon nanotubes. J Phys Chem A 109(3):493–499
57.
Cheung S et al (2005) ReaxFF(MgH) reactive force field for magnesium hydride systems. J Phys Chem A 109(5):851–859
58.
Chen N et al (2005) Mechanical properties of connected carbon nanorings via molecular dynamics simulation. Phys Rev B 72(8):085416-(9)
59.
Su HB et al (2007) Simulations on the effects of confinement and Ni-catalysis on the formation of tubular fullerene structures from peapod precursors. Phys Rev B 75(13):134107-(5)
60.
Chenoweth K et al (2005) Simulations on the thermal decomposition of a poly(dimethylsiloxane) polymer using the ReaxFF reactive force field. J Am Chem Soc 127(19):7192–7202
61.
Strachan A et al (2003) Shock waves in high-energy materials: the initial chemical events in nitramine RDX. Phys Rev Lett 91(9):098301-(4)
62.
van Duin ACT et al (2005) Atomistic-scale simulations of the initial chemical events in the thermal initiation of triacetonetriperoxide. J Am Chem Soc 127(31):11053–11062
63.
Buehler MJ, van Duin ACT, Goddard WA (2006) Multiparadigm modeling of dynamical crack propagation in silicon using a reactive force field. Phys Rev Lett 96(9):095505-(4)
64.
Goddard WA et al (2006) Development of the ReaxFF reactive force field for mechanistic studies of catalytic selective oxidation processes on BiMoOx. Top Catal 38(1–3):93–103
65.
Ludwig J et al (2006) Dynamics of the dissociation of hydrogen on stepped platinum surfaces using the ReaxFF reactive force field. J Phys Chem B 110(9):4274–4282
66.
Iijima S (1991) Helical microtubules of graphitic carbon. Nature 354(6348):56–58
67.
Endo M, Strano MS, Ajayan PM (2008) Potential applications of carbon nanotubes. Carbon Nanotubes 111:13–61
68.
Kreupl F (2008) Carbon nanotubes in microelectronic applications. In: Hierold C (ed) Carbon nanotube devices, 2nd edn. Wiley VCH, Weinheim
69.
Stampfer C (2008) Electromechanical carbon nanotube transducers. In: Hierold C (ed) Carbon nanotube devices, 2nd edn. Wiley VCH, Weinheim
70.
Roman C (2008) Modeling the properties of carbon nanotubes for sensor-based devices. In: Hierold C (ed) Carbon nanotube devices, 2nd edn. Wiley VCH, Weinheim
71.
Robertson J (2008) Carbon nanotube field emission devices. In: Hierold C (ed) Carbon nanotube devices, 2nd edn. Wiley VCH, Weinheim
72.
Yeow JT (2008) Carbon nanotube gas sensors. In: Hierold C (ed) Carbon nanotube devices, 2nd edn. Wiley VCH, Weinheim
73.
Joselevich E (2008) Carbon nanotube synthesis and organization. In: Jorio A, Dresselhaus G, Dresselhaus M (eds) Carbon nanotubes, 2nd edn. Springer, Berlin
74.
Bolton K et al (2009) Density functional theory and tight binding-based dynamical studies of carbon-metal systems of relevance to carbon nanotube growth. Nano Res 2(10):774–782
75.
Gavillet J et al (2001) Root-growth mechanism for single-wall carbon nanotubes. Phys Rev Lett 87(27):275504-(4)
76.
Huang SM et al (2004) Growth mechanism of oriented long single walled carbon nanotubes using “fast-heating” chemical vapor deposition process. Nano Lett 4(6):1025–1028
77.
Li YM et al (2001) Growth of single-walled carbon nanotubes from discrete catalytic nanoparticles of various sizes. J Phys Chem B 105(46):11424–11431
78.
Helveg S et al (2004) Atomic-scale imaging of carbon nanofibre growth. Nature 427(6973):426–429
79.
Hofmann S et al (2007) In situ observations of catalyst dynamics during surface-bound carbon nanotube nucleation. Nano Lett 7(3):602–608
80.
Raty JY, Gygi F, Galli G (2005) Growth of carbon nanotubes on metal nanoparticles: a microscopic mechanism from ab initio molecular dynamics simulations. Phys Rev Lett 95(9):096103-(4)
81.
Abild-Pedersen F et al (2006) Mechanisms for catalytic carbon nanofiber growth studied by ab initio density functional theory calculations. Phys Rev B 73(11):115419-(13)
82.
Amara H et al (2009) Tight-binding potential for atomistic simulations of carbon interacting with transition metals: application to the Ni-C system. Phys Rev B 79(1):014109-(17)
83.
Ohta Y et al (2008) Rapid growth of a single-walled carbon nanotube on an iron cluster: density-functional tight-binding molecular dynamics simulations. Acs Nano 2(7):1437–1444
84.
Moors M et al (2009) Early stages in the nucleation process of carbon nanotubes. Acs Nano 3(3):511–516
85.
Mueller JE, van Duin ACT, Goddard WA (2010) Application of the ReaxFF reactive force field to reactive dynamics of hydrocarbon chemisorption and decomposition. J Phys Chem C 114(12):5675–5685
86.
Mueller JE, van Duin ACT, Goddard WA (2010) Development and validation of ReaxFF reactive force field for hydrocarbon chemistry catalyzed by nickel. J Phys Chem C 114(11):4939–4949
87.
Mora E et al (2008) Low-temperature single-wall carbon nanotubes synthesis: feedstock decomposition limited growth. J Am Chem Soc 130(36):11840–11841
88.
Hofmann S et al (2005) Surface diffusion: the low activation energy path for nanotube growth. Phys Rev Lett 95(3):036101-(4)
89.
Henkelman G, Jonsson H (2001) Long time scale kinetic Monte Carlo simulations without lattice approximation and predefined event table. J Chem Phys 115(21):9657–9666
90.
Jaramillo-Botero A et al (2010) Large-scale, long-term non-adiabatic electron molecular dynamics for describing material properties and phenomena in extreme environments. J Comput Chem. epub ahead of print.
91.
Su JT, Goddard WA (2009) The dynamics of highly excited electronic systems: applications of the electron force field. J Chem Phys 131(24):244501-(20)
92.
Gillis HP et al (1995) Low-energy electron-enhanced etching of Si(100) in hydrogen helium direct-current plasma. Appl Phys Lett 66(19):2475–2477
93.
Su JT, Goddard WA (2009) Mechanisms of Auger-induced chemistry derived from wave packet dynamics. Proc Natl Acad Sci U S A 106(4):1001–1005
94.
Goddard W III (1998) Nanoscale theory and simulation: a critical driver for and a critical challenge to commercial nanotechnology. In: WTEC workshop. World Technology Evaluation Center, Arlington, VA
95.
Jaramillo-Botero A et al (2008) Multiscale-multiparadigm modeling and simulation of nanometer scale systems and processes for nanomedical applications. In: Zhang M, Xi N (eds) Nanomedicine: a systems engineering approach. Pan Stanford Publishing, Singapore
96.
Ryckaert JP, Ciccotti G, Berendsen HJC (1977) Numerical-integration of Cartesian equations of motion of a system with constraints – molecular-dynamics of n-alkanes. J Comput Phys 23(3):327–341
97.
Van Gunsteren WF, Berendsen HJC (1977) Algorithms for macromolecular dynamics and constraint dynamics. Mol Phys 34(5):1311–1327
98.
Andersen HC (1983) Rattle – a velocity version of the shake algorithm for molecular-dynamics calculations. J Comput Phys 52(1):24–34
99.
Krautler V, Van Gunsteren WF, Hunenberger PH (2001) A fast SHAKE: algorithm to solve distance constraint equations for small molecules in molecular dynamics simulations. J Comput Chem 22(5):501–508
100.
Hess B et al (1997) LINCS: a linear constraint solver for molecular simulations. J Comput Chem 18(12):1463–1472
101.
Miyamoto S, Kollman PA (1992) Settle – an analytical version of the shake and rattle algorithm for rigid water models. J Comput Chem 13(8):952–962
102.
Bae DS, Haug EJ (1987) A recursive formulation for constrained mechanical system dynamics. 1. Open loop-systems. Mech Struct Mach 15(3):359–382
103.
Abagyan RA, Mazur AK (1989) New methodology for computer-aided modeling of biomolecular structure and dynamics. 2. Local deformations and cycles. J Biomol Struct Dyn 6(4):833–845
104.
Mazur AK, Abagyan RA (1989) New methodology for computer-aided modeling of biomolecular structure and dynamics. 1. Non-cyclic structures. J Biomol Struct Dyn 6(4):815–832
105.
Bae DS, Kuhl JG, Haug EJ (1988) A recursive formulation for constrained mechanical system dynamics. 3. Parallel processor implementation. Mech Struct Mach 16(2):249–269
106.
Bae DS, Haug EJ (1988) A recursive formulation for constrained mechanical system dynamics. 2. Closed-loop systems. Mech Struct Mach 15(4):481–506
107.
Jaramillo-Botero A, Lorente ACI (2002) A unified formulation for massively parallel rigid multibody dynamics of O(log(2) n) computational complexity. J Parallel Distrib Comput 62(6):1001–1020
108.
Vaidehi N, Jain A, Goddard WA (1996) Constant temperature constrained molecular dynamics: The Newton-Euler inverse mass operator method. J Phys Chem 100(25):10508–10517
109.
Jain A, Vaidehi N, Rodriguez G (1993) A fast recursive algorithm for molecular-dynamics simulation. J Comput Phys 106(2):258–268
110.
Mathiowetz AM et al (1994) Protein simulations using techniques suitable for very large systems – the cell multipole method for nonbond interactions and the Newton-Euler inverse mass operator method for internal coordinate dynamics. Proteins Struct Funct Genet 20(3):227–247
111.
112.
Featherstone R (1983) The calculation of robot dynamics using articulated-body inertias. Int J Rob Res 2(1):13–30
113.
Fijany A et al (1998) Novel algorithms for massively parallel, long-term, simulation of molecular dynamics systems. Adv Eng Softw 29(3–6):441–450
114.
Shelley J et al (2001) A coarse grain model for phospholipid simulations. J Phys Chem B 105(19):4464–4470
115.
Groot RD (2000) Mesoscopic simulation of polymer-surfactant aggregation. Langmuir 16(19):7493–7502
116.
Groot RD, Rabone KL (2001) Mesoscopic simulation of cell membrane damage, morphology change and rupture by nonionic surfactants. Biophys J 81(2):725–736
117.
Jedlovszky P (1998) Investigation of the orientational correlation of the molecules in liquid H2S with reverse Monte Carlo simulation. Mol Phys 93(6):939–946
118.
Jedlovszky P et al (1996) Investigation of the uniqueness of the reverse Monte Carlo method: studies on liquid water. J Chem Phys 105(1):245–254
119.
Lopez CF et al (2002) Computer simulation studies of biomembranes using a coarse grain model. Comput Phys Commun 147(1–2):1–6
120.
Marrink SJ, de Vries AH, Mark AE (2004) Coarse grained model for semiquantitative lipid simulations. J Phys Chem B 108(2):750–760
121.
Marrink SJ, Mark AE (2003) Molecular dynamics simulation of the formation, structure, and dynamics of small phospholipid vesicles. J Am Chem Soc 125(49):15233–15242
122.
Marrink SJ, Mark AE (2004) Molecular view of hexagonal phase formation in phospholipid membranes. Biophys J 87(6):3894–3900
123.
Marrink SJ et al (2007) The MARTINI force field: Coarse grained model for biomolecular simulations. J Phys Chem B 111(27):7812–7824
124.
Molinero V, Goddard WA (2004) M3B: a coarse grain force field for molecular simulations of malto-oligosaccharides and their water mixtures. J Phys Chem B 108(4):1414–1427
125.
Vaidehi N, Goddard WA (2000) Domain motions in phosphoglycerate kinase using hierarchical NEIMO molecular dynamics simulations. J Phys Chem A 104(11):2375–2383
126.
Cagin T et al (2001) Multiscale modeling and simulation methods with applications to dendritic polymers. Comput Theor Polym Sci 11(5):345–356
127.
Elezgaray J, Laguerre M (2006) A systematic method to derive force fields for coarse-grained simulations of phospholipids. Comput Phys Commun 175(4):264–268
128.
Hunger J, Huttner G (1999) Optimization and analysis of force field parameters by combination of genetic algorithms and neural networks. J Comput Chem 20(4):455–471
129.
Hunger J et al (1998) How to derive force field parameters by genetic algorithms: modelling tripod-Mo(CO)(3) compounds as an example. Eur J Inorg Chem 6:693–702
130.
Jaramillo-Botero A et al (2010) First-principles based approaches to nano-mechanical and biomimetic characterization of polymer-based hydrogel networks for cartilage scaffold-supported therapies. J Comput Theor Nanosci 7(7):1238–1256
131.
Varghese S, Elisseeff JH (2006) Hydrogels for musculoskeletal tissue engineering. In: Polymers for regenerative medicine. Springer-Verlag, Berlin, pp 95–144
132.
Butler DL, Goldstein SA, Guilak F (2000) Functional tissue engineering: the role of biomechanics. J Biomech Eng Trans Asme 122(6):570–575
133.
Guilak F (2000) The deformation behavior and viscoelastic properties of chondrocytes in articular cartilage. Biorheology 37(1–2):27–44
134.
Guilak F, Butler DL, Goldstein SA (2001) Functional tissue engineering – the role of biomechanics in articular cartilage repair. Clin Orthop Relat Res 391:S295–S305
135.
Gong JP et al (2003) Double-network hydrogels with extremely high mechanical strength. Adv Mater 15(14):1155–1158
136.
Lorenz CD, Ziff RM (2001) Precise determination of the critical percolation threshold for the three-dimensional “Swiss cheese” model using a growth algorithm. J Chem Phys 114(8):3659–3661
137.
Kremer K, Grest GS (1990) Dynamics of entangled linear polymer melts – a molecular-dynamics simulation. J Chem Phys 92(8):5057–5086
138.
Blanco M, Jaramillo-Botero A, Goddard W III (2010) The percolation limit near the Flory-Stockmayer transition in polymer hydrogel networks. California Institute of Technology, Pasadena
Metadaten
Titel
First-Principles-Based Multiscale, Multiparadigm Molecular Mechanics and Dynamics Methods for Describing Complex Chemical Processes
verfasst von
Andres Jaramillo-Botero
Robert Nielsen
Ravi Abrol
Julius Su
Tod Pascal
Jonathan Mueller
William A. Goddard III
Copyright-Jahr
2012
Verlag
Springer Berlin Heidelberg
Buch
Multiscale Molecular Methods in Applied Chemistry

Print ISBN: 978-3-642-24967-9

Electronic ISBN: 978-3-642-24968-6

Copyright-Jahr: 2012

DOI
https://doi.org/10.1007/128_2010_114