New Developments in ADF/ReaxFF

New Developments in ADF/ReaxFF

Ole Carstensen

Scientific Computing & Modelling [email protected]

Manchester, 14 September 2015

New Developments in ADF/ReaxFF Reactive Force FieldsOle Carstensen Manchester 2015

Amsterdam Density Functional (ADF) development

• Baerends group VU, Amsterdam (>1973) • Ziegler group, Calgary (>1975)• SCM: Spin-off company (1995)

• Currently 15 people (8 senior PhD’s) + EU fellows• Development, testing, debugging, optimizing, porting,

documentation, support, ..– Implement what users want

– New features from academia

• Many academic collaborators / EU networks

Tom Ziegler (1945-2015)

Evert-Jan Baerends


ADF modeling suite authors 2014

E.J. Baerends, T. Ziegler, J. Autschbach, D. Bashford, A. Bérces, J.A. Berger, F.M. Bickelhaupt, C. Bo, P.L. de Boeij, P.M. Boerrigter, S. Borini, R. E. Bulo, L. Cavallo, D.P. Chong, L. Deng, R.M. Dickson, A. C. T. van Duin, D.E. Ellis, M. van Faassen, L. Fan, T.H. Fischer, C. Fonseca Guerra, M. Franchini, A. Ghysels, A. Giammona, S.J.A. van Gisbergen, M. Gorbani Asl, A.W. Götz, J.A. Groeneveld, O.V. Gritsenko, M. Grüning, S. Gusarov, F.E. Harris, T. Heine, P. van den Hoek, C.R. Jacob, H. Jacobsen, L. Jensen, E.S. Kadantsev, J.W. Kaminski, G. van Kessel, R. Klooster, F. Kootstra, A. Kovalenko, M.V. Krykunov, E. van Lenthe, J.N. Louwen, D.A. McCormack, E. S. McGarrity, A. Michalak, M. Mitoraj, S.M. Morton, J. Neugebauer, V.P. Nicu, L. Noodleman, V. P. Osinga, S. Patchkovskii, M. Pavanello, P.H.T. Philipsen, D. Post, C.C. Pye, W. Ravenek, M. de Reus, J.I. Rodríguez, P. Romaniello, P. Ros, R. Rüger, P.R.T. Schipper, H. van Schoot, G. Schreckenbach, J.S. Seldenthuis, M. Seth, D.G. Skachkov, J.G. Snijders, M. Solà, M. Swart, D. Swerhone, G. te Velde, P. Vernooijs, L. Versluis, L. Visscher, O. Visser, F. Wang, T.A. Wesolowski, E.M. van Wezenbeek, G. Wiesenekker, S.K. Wolff, T.K. Woo, A.L. Yakovlev


Overview of the ADF molecular modeling suite

COSMO-RScontinuum methods

mesoscale methods

ReaxFF:reactive MDMonte Carlo

MOPAC

DFTBQM/MM

Tim

esca

le

ADF:DFT BAND: periodic DFT

ADF

BAND

ADF/ReaxFF

Systemsize


Dr. Olivier Visser Dr. Erik van Lenthe Dr. Alexei Yakovlev Dr. Pier PhilipsenGUI, general ADF, ZORA, COSMO ADF, ReaxFF, optimization BAND, periodic DFTB

Job opening: MSc. Hans van Schoot MSc. Mirko Franchini Dr. Ole CarstensenScientific Software Developer ReaxFF, MD, GPUs ADF, BAND technical GUI, MD, consultancy

SCM software development staf


Dr. Stan van Gisbergen Dr. Fedor Goumans Dr. Sergio Lopez Lopez General Management Business Development Scientific Partner ManagerSales, Legal, Signatures Marketing, Technical Sales EU projects, collaborations

Mrs. Frieda Vansina Mrs. Kitty Kleinlein Office Manager Office ManagerLicense files, user interactions Bookkeeping, special projects

SCM staf – office / management / business


2. New Acceleration Techniques1. ADF/ReaxFF

3. Upcoming Features

Grand canonical Monte Carlo + ADF/ReaxFF

ChemTraYzer: automated event detection Force bias Monte Carlo + ADF/ReaxFF

General, preparation, execution, analysis






General, preparation, execution, analysis


ADF/ReaxFF: General

ReaxFF initially developed by Adri van Duin.

Alexei Hans Olivier

ADF/ReaxFF- optimization & parallelization of the original code.- many parameters included (e.g. transition metals)- GUI support- internal parameter optimization via Monte Carlo-...

Pyrolysis of an Illinois coal sample (Combustion & Flame 2012)

Cu-metal particle on a ZnO-support with water vapor (Zn/O: Raymand et al., Surf. Sci. 2010)

Hexane cracking on a Fe/H-ZSM5 catalyst (Fe/O: Aryanpour et al.,

JPC-A 2010)

Various parallel ADF/ReaxFF studies on various systems over the last years

new ReaxFF parameters

Adri van Duin


ADF/ReaxFF: The GUIfast and easy preparation...

set up complex, heterogeneous systems with Packmol builder


ADF/ReaxFF: The GUIfast and easy preparation...

straightforward definition of different temperature regimes, electric field regimes, pressure constraints, bond constraints, etc.


ADF/ReaxFF: The GUIfast and easy preparation, execution...

Manage all your jobs (local and remote) from your local desktop computer.Supports: PBS, SLURM, LSF, SGE...

Quickly need more resources? ADF/ReaxFF@CrunchYard:pay-per-use supercomputing.

mailto:ADF/ReaxFF@CrunchYard


ADF/ReaxFF: The GUIfast and easy preparation, execution and analysis

● Visualize trajectory properties (Temperature, Pressure, Energies...)● Analyze changing molecular composition during a reactive MD run● ...


Friendly Expert Support Team!

[email protected]






Preparation, execution and analysis


New Acceleration TechniquesGrand Canonical Monte Carlo (GC-MC)

Model a system that is in thermodynamic equilibrium(e.g. sorption in multi-component systems)

Task:

MD (ambient P,T)limited by timescales,reactions are rare events

MD (high P,T)High energy processes: thermodynamically not feasible.


New Acceleration TechniquesGrand Canonical Monte Carlo (GC-MC)

Model a system that is in thermodynamic equilibrium(e.g. sorption in multi-component systems)

Task:

MD (ambient P,T)limited by timescales,reactions are rare events

MD (high P,T)High energy processes: thermodynamically not feasible.

Monte Carlo (MC) Techniques:Sampling of configurational energetics,reproduce a thermal Boltzmann distribution

Grand canonical MC: stochastical exchange of atoms (reservoir ↔ system) @ const. μ

Reservoir

SystemThermodynamic equilibrium:

μReservoir

= μSystem

System GC-MC


New Acceleration TechniquesApplication of (hybrid) GC-MC with ADF/ReaxFF

System

Senftle et al.,J. Chem. Phys. 139, 044109 (2013); http://dx.doi.org/10.1063/1.4815820

Palladium based oxidation catalysts:catalytic behaviour ↔ extend of oxidation

Bulk-ox.

Surface-ox.

Both kinetic and thermodynamic influences are important!

Modelling

1. single MC move

2. Geometry optimization

4. System energy converged at equilibrium?

3. Accept/Reject?

no yes

● Model catalyst: 3nm Pd935

Cluster● Oxygen atoms are added until convergence

● GC-MC requires: - exp. μ

O2 (T, P0) from published tables

- 0 K bond dissociation energy of O2

from a DFT calculation Both kinetic and thermodynamic

influences are important!

http://dx.doi.org/10.1063/1.4815820



Results


GC-MC/MD runsfor different T,P0

Convergence within 15000-25000 MC-steps(for this system)

http://dx.doi.org/10.1063/1.4815820



Results


Identify phases via ρ(r)

Bulk Oxide (300 K, 1 atm)

Bulk Oxide (800 K, 1 atm)

Surface Oxide (1000 K, 1 atm)

Surface Oxide (1200 K, 1 atm)

Phase diagram for Pd-Oxide Formation

Theo. referenceExp. reference GC-MC/MD runs

http://dx.doi.org/10.1063/1.4815820








New Acceleration TechniquesUniform-acceptance force-bias Monte Carlo (fbMC) [1,2]

[1] Timonova et al., Phys. Rev. B 81, 144107 (2010); http://dx.doi.org/10.1103/PhysRevB.81.144107 [2] Mees et al.,Phys. Rev. B 85, 134301; http://dx.doi.org/10.1103/PhysRevB.85.134301

Metropolis MC

? ?

P(r)

P(r)

select

Sampling structural Phase Space

according to one well known ensemble distribution function (e.g. NVT)

fbMC

?

P(r, F1)

select

P(r, F2)

P(r, F3)

P(r, F4)

Sampling the Dynamics

● each change driven by “instantaneous” and “local” Boltzmann Distributions

● irrespective from distance to equilibrium

● Limits of P(r,F)T >> F → completely random movementT << F → Particle moves exactly in direction of force

http://dx.doi.org/10.1103/PhysRevB.81.144107

http://dx.doi.org/10.1103/PhysRevB.85.134301


New Acceleration TechniquesApplication of fbMC/MD [3]

[3] Neyts et al., J. Am. Chem. Soc. 133, 17225 (2011); http://dx.doi.org/10.1021/ja204023c

System

Unique physical properties:● extraordinary thermal conductivity● either metallic or semiconducting

(depending on chirality)● …

Problem: lack of control over fundamental properties

Computational SWNT growth studies(in 2011)

● lack of long range interactions & polarizable charges (prev. MD studies)

● Time scales too short for relaxation→ lots of defects, no healing

Modelling

4 ps - ReaxFF 104 fbMC steps

Modelling of a surface-bound Ni-catalyst

● Catalyst: Ni40

nanoclusterlower eight atoms fixed → Ni(100) plane

● Carbon atom added every 2 ps during ReaxFF dynamics

● virtual reflective boundary: Carbon atoms can only approach the cluster from above

● T = 1000 K

Single walled carbon nanotubes (SWNT) fbMC/ReaxFF [3]

http://dx.doi.org/10.1021/ja204023c


New Acceleration TechniquesApplication of fbMC/MD to SWNT growth [3]

[3] Neyts et al., J. Am. Chem. Soc. 133, 17225 (2011); http://dx.doi.org/10.1021/ja204023c

Results

+ Healing of defects during sliding of network (steps 4-5).+ First simulation showing growth of an armchair SWNT with definite chirality on catalyst.

pentagon formation graphitic patches cap development

carbon network slides over catalyst

part of metal gets freed end of sliding,chirality obtained

http://dx.doi.org/10.1021/ja204023c








Upcoming FeatureAutomated event detection with ChemTraYzer [4]

[4] Döntgen et al., J. Chem. Theory Comput. 11, 2517 (2015); http://dx.doi.org/10.1021/acs.jctc.5b00201

How to extract complex reaction mechanisms?

For example: burning methane..

Source: en.wikipedia.org/wiki/Combustion

Even 'simple' reactions...

http://dx.doi.org/10.1021/acs.jctc.5b00201





Source: en.wikipedia.org/wiki/Combustion

Even 'simple' reactions can turn out to be complicated.






ChemTraYzer:

● Pythonscripts developed by the Leonhard group (Aachen)● Automatic determination of reaction events

- based on framewise comparison of atom connectivities- chemical composition extracted via graph-theory (BFS)

● (reasonable) rate constants

CH4 → .CH

3 +H

.CH

4 +

.OH→ .CH

3 + H

2O





ChemTraYzer and ADF2016/ReaxFF

Already working: ● ChemTraYzer & ADF/ReaxFF trajectories

Work in progress: ● Full GUI support for both setup & analysis● On-the-fly analysis ● “stop trajectory if reaction xy has been sampled”

What it could look like...

Generate trainingssets forReaxFF reparametrization...




3. Upcoming: ChemTraYzer

Automated event detection● complex reaction networks● rate constants● generation of trainingsets

fbMC + ADF/ReaxFF dynamicsModel processes that occuron loooong timescales by MC sampling of the dynamics

General, preparation, execution and analysis

Interested in a collaboration, a free trial licence or want to apply at SCM?

[email protected]

GC-MC + ReaxFF (dynamics)study thermodynamic and kinetic properties of multi-compound systems

Science

New Developments in ADF/ReaxFF