Gaussian

Chemistry with ADF
G. TE VELDE,1 F. M. BICKELHAUPT,2 E. J. BAERENDS,2
C. FONSECA GUERRA,2 S. J. A. VAN GISBERGEN,3
J. G. SNIJDERS,4 T. ZIEGLER5
1

Paragon Decision Technology BV, Julianastracit 30, Postbus 3277, NL-2001 DC Haarlem,
The Netherlands
2
Theoretical Chemistry, Vrije Universiteit, De Boelelaan 1083, NL-1081 HV Amsterdam,
The Netherlands
3
Scientific Computing & Modelling NV,Theoretical Chemistry, Vrije Universiteit,
De Boelelaan 1083, NL-1081 HV Amsterdam, The Netherlands
4
Theoretical Chemistry, Materials Science Centre, Rijksuniversitet Groningen, Nijenborgh 4,
NL-9747 AG Groningen, The Netherlands
5
Department of Chemistry, University of Calgary, 2500 University Drive NW, Calgary, Alberta,
Canada T2N 1N4
Received 16 June 2000; accepted 4 December 2000ABSTRACT: We present the theoretical and technical foundations of the
Amsterdam Density Functional (ADF) program with a survey of the
characteristics of the code (numerical integration, density fitting for the Coulomb
potential, and STO basis functions). Recent developments enhance the efficiency
of ADF (e.g., parallelization, near order-N scaling, QM/MM) and its functionality
(e.g., NMRchemical shifts, COSMO solvent effects, ZORA relativistic method,
excitation energies, frequency-dependent (hyper)polarizabilities, atomic VDD
charges). In the Applications section we discuss the physical model of the
electronic structure and the chemical bond, i.e., the Kohn–Sham molecular orbital
(MO) theory, and illustrate the power of the Kohn–Sham MO model in
conjunction with the ADF-typicalfragment approach to quantitatively
understand and predict chemical phenomena. We review the “Activation-strain
TS interaction” (ATS) model of chemical reactivity as a conceptual framework for
understanding how activation barriers of various types of (competing) reaction
mechanisms arise and how they may be controlled, for example, in organic
chemistry or homogeneous catalysis. Finally, weinclude a brief discussion of
exemplary applications in the field of biochemistry (structure and bonding of
DNA) and of time-dependent density functional theory (TDDFT) to indicate how
this development further reinforces the ADF tools for the analysis of chemical
c 2001 John Wiley & Sons, Inc. J Comput Chem 22: 931–967,
phenomena.
2001
Correspondence to: F. M. Bickelhaupt; e-mail: bickel@chem.vu.nl; G. te Velde; e-mail: Bert.te.Velde@Paragon.nl
Contract/grant sponsors (to F.M.B): Deutsche Forschungsgemeinschaft, and Fonds der Chemischen Industrie

Journal of Computational Chemistry, Vol. 22, No. 9, 931–967 (2001)
c 2001 John Wiley & Sons, Inc.

TE VELDE ET AL.

Keywords: ADF program; density functional theory; materials science; chemical
bond; reactivity

Introduction
THESUCCESS OF DENSITY FUNCTIONAL
THEORY (DFT)

K

ohn–Sham DFT1 – 5 has in the recent past
emerged as an important first-principles computational method6 – 15 to predict chemical properties accurately16 – 22 and to analyze and interpret
these in convenient and simple chemical terms.23 – 31
The reasons for its popularity and success are
easy to understand. In the first place, the DFT approachis in principle exact. The exact exchangeand-correlation (XC) functional is unknown, but
the currently available XC functionals provide in
most cases already a “chemical” accuracy of a few
kcal/mol for binding energies.16, 22, 32, 33 Moreover,
the quest for more accurate ones based on a more
detailed understanding of their essential properties
is continuing.27, 28, 34 – 46
In the secondplace, it preserves at all levels of approximation the appealing one-electron
molecular orbital (MO) view on chemical reactions
and properties. The computed orbitals are suitable for the typical MO-theoretical analyses and
interpretations.27, 29 – 31 The KS method effectively
incorporates all correlation effects.
In the third place, it is a relatively efficient computational method, and its...