BIOVIA MATERIALS STUDIO DMOL3DATASHEETBIOVIA Materials Studio DMoL3 is a modeling program thatuses density functional theory (DFT) to simulate chemical
processes and predict properties of materials both rapidly andaccurately. Because BIOVIA Materials Studio DMoL3 can predict
processes in gas phase, solution, and solid environments,
it is broadly applicable to research problems in chemistry,
pharmaceuticals, materials science, and chemical engineering,as well as solid state physics. Researchers can use the program
to investigate the nature and origin of the chemical, electronic,and structural properties of a system without the need for any
experimental input. Use BIOVIA Materials Studio DMoL3 toperform virtual experiments, leading to tremendous savings incostly experiments and shorter developmental cycles.

WHAT DOES BIOVIA MATERIALS STUDIODMOL3 DO?
Researchers in chemistry, pharmaceuticals, and materials
science may be tasked with a number of challenging goals
like the development of new compounds, such as a more
efficient catalyst or a more effective medicine; or they may
need to improve a manufacturing process by determining amore efficient synthesis pathway; or they may be faced withsimply understanding and describing fundamental processes,

explaining why one particular material is better than another.
Modeling can address all of these challenges, provided that themethod is fast and accurate. BIOVIA Materials Studio DMoL3 isjust such a method.
BIOVIA Materials Studio DMoL3 is a DFT program with a longtrack record of successful commercial applications. With its
unique approach to solving quantum mechanical equations,
BIOVIA Materials Studio DMoL3 has long been one of the fastest
methods available for performing calculations, an advantagethat becomes apparent especially for larger systems, thosewith over 500 atoms.
With its ability to model both molecular and solid stateproblems, the application provides a way to study the broadest
possible range of problems in a single package. The method isequally well suited to performing a conformational analysis of asmall molecule as it is to modeling catalysis on a metal surface.
The program can be used in areas such as pharmaceutical drug
discovery to model ligand binding or in drug development tounderstand crystal polymorphs. Use BIOVIA Materials StudioDMoL3 to design new metallocene catalysts for polymerization,or to understand the mechanism of supported metal catalysts.
You can even use BIOVIA Materials Studio DMoL3 to predict
band gaps and design new solid state materials.
BIOVIA Materials Studio DMoL3 has been applied to such diverse
research problems as homogeneous catalysis, heterogeneouscatalysis, semiconductors, molecular reactivity, and combustion
technology. Example applications include the study of theprocess of chemical vapor deposition, understanding theaction of automotive catalysts, explaining the mechanismof polymerization reactions, and investigating combustion
techniques under extreme conditions.

The geometry and highest occupied molecular orbitals(HOMO) of two structures optimized in BIOVIA Materials
Studio DMol3. The top structure is caprolactone, amonomer use in the production of artificial skin. The lower
structure is Al(OH)3, which can initiate ring opening.
BIOVIA Materials Studio DMol3 can be used to predict themechanisms of ring opening and polymerization.

BIOVIA Materials Studio DMoL3’s emphasis is on speed –without compromising quantum mechanical accuracy. Anefficient geometry optimization algorithm lets you predict
minimum energy structures rapidly. A transition state search
employing a combination of LST/QST algorithms facilitates
the evaluation of energy barriers. Using parallel versions of theBIOVIA Materials Studio DMoL3 code, large problems can betackled.

THE BIOVIA MATERIALS STUDIO ADVANTAGEBIOVIA Materials Studio DMoL3 is part of the BIOVIA Materials
Studio® software environment. BIOVIA Materials Studio provides
a user-friendly interface, complying with Windows® standards.
BIOVIA Materials Studio Visualizer, the core of BIOVIA Materials
Studio, offers a wide range of model building and visualization
tools that allow you to construct rapidly models of the systems
of interest, easily select BIOVIA Materials Studio DMoL3, and run
an advanced quantum mechanics calculation. The simple userinterface together with BIOVIA’s training programs ensure thateven new users will be able to use the program with confidence.

HOW DOES BIOVIA MATERIALSSTUDIO DMOL3 WORK?
BIOVIA Materials Studio DMoL3 achieves its speed and accuracy
by using numerical functions on an atom-centered grid as
its atomic basis1,2. The atomic basis functions are obtained
from solving the DFT equations for individual atoms andare hence quite accurate. The high quality of these basis
sets minimizes basis set superposition effects and allows an
improved description of molecular polarizabilities3.
The electron density in BIOVIA Materials Studio DMoL3 isexpanded in terms of multipolar, atomic-centered partialdensities. This provides a compact yet highly accurate
representation of the density, and allows for a good scaling
with growing system size. Consequently the evaluation of theCoulomb potential scales linearly with the size of the system.
The Hamiltonian matrix elements are calculated by using a
sophisticated numerical integration algorithm that also scaleslinearly.
The algorithms in BIOVIA Materials Studio DMoL3 allow for very
efficient parallelization of the numerical integration procedure.
BIOVIA Materials Studio DMoL3 can perform both All Electronor pseudo-potential calculations. Accurate DFT semi-local
pseudo-potentials (DSPP)4 or the more conventional Effective
Core Potentials (ECP)5,6 can be used.
Geometry and transition state optimizations are performed
using delocalized internal coordinates, both for molecular7 as
well as for periodic8 calculations. This includes the ability toimpose Cartesian geometry constraints while performing theoptimization in internal coordinates. A transition state search
scheme has been implemented which based on a combinationof traditional LST/ QST methods9. This new robust and fastscheme10 allows rapid location of transition states.
Solvent effects are included using the COSMO model tosimulate a continuum. Uniquely, this model includes periodic
cases11 making it possible to model polymer solvation orheterogeneous catalysis in solution.

FEATURES AND CAPABILITIESDissociation of methane on a nickel(III) surface
calculated with BIOVIA Materials Studio DMol3. The
highest occupied molecular orbital is displayed together
with the dissociation products chemisorbed on the themetal surface.

A flexible client-server architecture means that calculations
can be run on servers located anywhere on your network.
Results are returned to your PC, where they may be displayedand analyzed. You can easily produce high quality graphics
of molecular and materials structures, molecular orbitals,
electrostatic potentials, or charge densities. Structures, graphs,
and other data such as video clips produced from BIOVIA
Materials Studio DMoL3 output can be instantly exchanged
with other PC applications, assisting you when sharing themwith colleagues or when analyzing them using spreadsheets
and other packages.
Spreadsheet-like setup allows the method to be applied ina high-throughput environment, performing multiple,
repetitive calculations easily, and storing the results in a table.
Subsequent statistical analysis can reveal hidden structureproperty relationships that can be easily exploited to design
new materials or explain behavior on the molecular level.

Calculation Tasks• Restricted and unrestricted DFT calculations• Geometry optimization• Transition state search using a combined LST/QST/Conjugate
Gradient approach• Transition state optimization using eigenvector following• Determination and graphical display of the complete reactionpath• Frequency calculations using full or partial Hessians• Solvation via COSMO11.

Functionals• Local DFT functionals: PWC, VWN• GGA-DFT functionals: PW91, BLYP, BP, BOP, PBE, VWN-BP,RPBE, and HCTH
• Harris functional for fast calculations.

• Numerical AO basis sets: Minimal, DN, DND, DNP, TNP• All electron or core potentials: relativistic effective corepotentials, effective core pseudo-potentials, DFT semi-core
pseudo-potentials.
• Scalar relativistic all electron calculations.

Restart and Job Control Options• Choose number of CPUs
• Specify server machine• Monitor output and status reports including text or graphs ofenergy and gradient during geometry optimization• Live updates of the geometry• Halt jobs on remote server via BIOVIA Studio Materials
Visualizer.

Properties• Band structure• Bond order analysis• Electron work function• Electrostatic moments• Fukui indices• Heats of formation, free energy, enthalpy, entropy, heat
capacity, ZPVE.
• Mulliken, Hirshfeld, and ESP charges• Nuclear electric field gradients• UV/Vis spectra, excited states, polarizability andhyperpolarizability 12

Graphical Displays withBIOVIA Materials Studio Visualizer• 3-D contours and 2-D slices• Animation of normal modes• Fermi surface• Fukui functions• Molecular orbitals, charge, spin & deformation densities• Overlay multiple plots and color surfaces by property maps

Miscellaneous Options• Multiple k-points• Real space cut-off• Full point-group and space-group symmetry• Multiple options for accelerating SCF convergence: DIIS,density mixing, smearing.
To learn more about BIOVIA Materials Studio, go toaccelrys.com/materials-studio

REFERENCES:
1. B. Delley, J. Chem. Phys., 1990, 92, 508; ibid, 1991, 94, 7245; ibid, 2000, 7756.
2. B. Delley, J. Phys. Chem., 1996, 100, 6107.
3. N. Matsuzawa, J. Seto, and D. A. Dixon, J. Phys. Chem. A, 1997, 101, 9391.
4. B. Delley, Phys. Rev. B. 2002, 66, 155125.
5. M. Dolg, U. Wedig, H. Stoll, and H. Preuss, J. Chem Phys., 1987, 86, 866.
6. A. Bergner, M. Dolg, W. Kuechle, H. Stoll, and H. Preuss, Mol. Phys., 1993, 80, 1431.
7. J. Baker, A. Kessi, and B. Delley, J. Chem. Phys., 1996, 105, 192.
8. J. Andzelm, R. D. King-Smith, and G. Fitzgerald, Chem. Phys. Lett., 2001, 355, 321.
9. T. A. Halgren and W. N. Lipscomb, Chem. Phys. Lett., 1977, 49, 225.
10. N. Govind, M. Petersen, G. Fitzgerald, D. King-Smith, and J. Andzelm,
Computational Materials Science, 2003, 28, 250.

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Basis Sets