Computational Chemistry and Materials Modeling Introduction Andriy Zhugayevych, Sergei Tretiak October 24, 2016 Outline • What is this course about • General guidelines for Computational Materials Science • Case studies: from basic applications to student projects • Course logistics 1 / 24
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Computational Chemistry and Materials Modeling
Introduction
Andriy Zhugayevych, Sergei Tretiak
October 24, 2016
Outline
• What is this course about
• General guidelines for Computational Materials Science
• Case studies: from basic applications to student projects
• Course logistics
1 / 24
What is this course aboutComputational Chemistry + Materials Modeling
“The underlying physical laws necessary for themathematical theory of a large part of physicsand the whole of chemistry are thus completelyknown and the difficulty is only that the ex-act application of these laws leads to equationsmuch too complicated to be soluble.”P A M Dirac, Proc Royal Soc London 123, 714 (1929)
• Computational Chemistry = solving Coulomb problem for& 10 particles
• Materials Modeling = relating that solution to real world
2 / 24
Whom is this course for
• Theoreticians and experimentalists studying materials withatomic resolution (most of recent high-technology devices)
Example
• You would like to understand theoverall shape of an I-V curve=⇒ you don’t need this course
• You would like to understand thedifference in these I-V curves=⇒ you do need this course
3 / 24
Level of coverage
Our approach
• Pragmatic & practical guide to start working in the researchlab (theory/experiment) right away
General guidelines for Computational Materials Science
• Approaching the computational “black box”
• Calculate or measure?
• Understand scales
7 / 24
Approaching the ‘black box’Approaching the black box
Molecular structures
Materials propertiesproperties
Molecular modeling software
How to deal with it?• Basic understanding of what is going on inside;• Basic understanding of what is going on inside;• Interpretation of experimental data;• Understanding of dominating physical phenomena;Understanding of dominating physical phenomena;• Rational choice of optimal electronic structure methodology;• Efficient analysis of the numerical results;• Developing physical intuition: ‘does it make sense?’
8 / 24
What is Computational Materials Science?
Measure Compute
Research costs
Research time
Accuracy ? ?
Reliability ?
Relevance for practical use
Which approach to choose?
9 / 24
Methods
• <102-3 atoms (molecule, UC)
– Density Functional Theory
– Gaussian, VASP
• <104-5 atoms, <1ns
– Semiempirical, O(N)-DFT
– MOPAC
• < 109 atoms
– Molecular Mechanics, QM/MM
– LAMMPS, Tinker
• Coarse-grained (not atomistic)
– Effective Hamiltonian, …
10 / 24
Case study: Understanding chemical bonding
HO
H
LPLP
VSEPR LMO e-density
• Valence shell electron pair repulsion (VSEPR) theory– are lone pairs (LP) real or virtual?
• Hypervalency in SF6 – 3c4e bonding or sp3d2-hybridization?
• Directional noncovalent interactions in π-conjugatedmolecules and electron-rich covalent solids – secondary bonds?
11 / 24
Case study: Computational discovery of new materialsHigh-throughput screening of materials
• Skoltech: Artem Oganov, Sergei Tretiak, Andriy Zhugayevych
• The Harvard Clean Energy Project (A. Aspuru-Guzik)
• The Materials Project (founded by G. Ceder and K. Persson)
• EFRC for Inverse Design (theory by A. Freeman, A. Zunger)
How it works e.g. for organic solar cells:
Egap = ELUMO − EHOMO − Eexciton
eVOC ≈ E acceptorLUMO − Edonor
HOMO − 0.3 eV
12 / 24
Case study: Calculation of material propertiesSolar cells: where is the bottleneck in power conversion efficiency?
6324
6
231714
976
341910
87
6
1 nm
590.3
1.20.9
1.50.006
0.010.8
m (cm /V/s)2
1 nm
HOMO
LUMO
Light absorption
Crystal structure Exciton transportHole transport
Electronic structure
Exciton diffusion length ∼ 100 nm, hole mobility ∼ 1 cm2/V·sSingle-crystal properties of the given molecule are perfect for photovoltaicsA.Z., O Postupna, R C Bakus II, G C Welch, G C Bazan, S Tretiak, J Phys Chem C 117, 4920 (2013) 13 / 24
Case study: Simulation of processesExplain pump-probe experiment: JACS 134, 19828 (2012); Nat Mater 11, 44 (2012)
t»0.3R /D2
20-nm crystalliteCrystal structure
Microscopic model Exciton dissociation kinetics
TEM of active layer
In absence of traps exciton dissociation proceeds in picoseconds 14 / 24
Case study: Materials design for OLEDsOlena Postupna, 2012, 2013 internships at LANL, advisor A.Z. and Sergei Tretiak
Practical goal:solution-processable OLEDwith tunable colorTheory: explain and predict
Donor-acceptor π-conjugated moleculeOCH3
H3CO
RR'
SolvatochromismR=NO2, R’=H
(nonmonotonic dependence on solvent)
HalochromismR=NH+
3 , R’=NMe+3
High sensitivity to chemicalmodifications and environment• solvatochromism – ACS Appl Mater Int 5, 4685 (2013)
• halochromism – Chem Sci 6, 789 (2015)
• functionalization – Chem Phys (2016)
15 / 24
Case study: Tuning performance by isovalent substitutionsThomas van der Poll, 2013 internship at LANL, advisor A.Z. and Sergei Tretiak
Good molecule for solar cells(good single-crystal properties)