Modelado Molecular de Nanomateriales para
Fotovoltaica Molecular
Dr. Daniel Glossman-MitnikTemixco, Morelos – 10 de Marzo de 2011
CIMAV
PRINATEC
UAM
BUAP
CIATEC
CIMAV
CIQAUANL
UNISON
UNAM
IMP
IPN
CINVESTAV-DF
CINVESTAV-QRO
IPICYT
UASLP
Main research centers in México with activities in Nanoscience
and/or Nanotechnology
• Computational Simulation of the
Molecular Structure and Properties of
Nanomaterials
• Computational Nanotechnology
• Synthesis of Nanostructured Materials
• Chemical and Physical
Characterization of Nanomaterials
• Industrial Applications of
Nanotechnology
Tools of the Nanosciences
• Tools to make nanostructures
• Tools for measuring nanostructures
• Tools for modeling nanostructures
Computational Nanotechnology
• Modelling and Design of Nanomaterials using Computers
• Computational Characterization of the Molecular Structure of Nanomaterials
• Prediction of the IR, Raman, UV-Vis and NMR Spectra of the Nanostructures
• Determination of the Electric and Magnetic Properties of the Nanomaterials
• Computational Simulation of the Thermochemical Properties of the Nanomaterials in Gas Phase, Solid Phase and in Solution
• Analysis of the Chemical Reactivity of the Nanomaterials
• Simulation of Chemical and Physical Processes of the Nanostructures
Computational ChemistryIs that part of Chemistry where the solution to chemical
problems is obtained through calculations performed with
a computer.
Computational chemistry and molecular modeling have
reached a high level of predictability that makes them
useful tools for the design of new materials
Using Computational Chemistry it is posible to model a
molecular system once and once again without the need of
chemicals, thus avoiding the generation of waste. This
translates into resources, energy and money savings.
It is based on the
laws of classical
mechanics
It is based on the laws of quantum
mechanics
Computational
Chemistry
Molecular Mechanics
Electronic Structure Theory
Electronic Structure
Methods
Semiempirical
methods
Ab initio methods
DFT methods
“For the development of Density
Functional Theory - DFT"
Walter Kohn
Born in Vienna, Austria
University of California Santa Barbara, CA, USA
Nobel Prize in Chemistry 1998
“For the development of
computational methods in quantum
chemistry"
John A. Pople
Born in Burnham, Inglaterra
Northwestern University Evanston, IL, USA
Nobel Prize in Chemistry 1998
OBJECTIVES
Computational Modeling of the Molecular Structure and Properties, Spectroscopy, Thermochemistry and Chemical Reactivity of Molecules and (Bio)Nanomaterials, and of the Synthesis and Characterization Processes that Could be of Academic Interest and for the Solution of Industrial Problems
Nanomaterials for
Solar Energy Storage
and Conversion
In the NANOCOSMOS Group, we are engaged in
theoretical and computational approaches for solving
problems of interest in nanoscience and nanotechnology.
Computational Chemistry
of the Molecular
Structure and Properties of NANOMELFOS
********
Organic Light-Emitting
and Photovoltaic
Nanomaterials
Computational
simulation of the
molecular structure
and properties of
nanomaterials
potentially useful
for the fabrication
of solar cells and
photovoltaic devices
Nanomaterials for
Solar Energy Storage
and Conversion
Organic Photovoltaics
PEM Fuel Cells
OrganicElectroluminiscence
OLEDS
Lithium-Ion PolymerBatteries
N
C12H25O
C12H25O
Me
C60-3PV
ITO Al
Photocurrent
h
e-
e-
e-
e-
The electron transfer is one of the fundamentalprocesses that play an important role in physical,chemical, and biological systems.
Photochemical Solar Cells based on Molecular Assemblies
(Mimicking photosynthesis using porphyrins and chlorophyll)
Molecular clusters formed in mixed solvents exhibit broader absorption bands
HN
NNH
N
H H
H2P300 400 500 600 700 800
1.0
0.5
1.5
2.0
0
Wavelength, nm
Absorb
ance
0.75 mM (H2P)n in MeCN : toluene = 9 : 1
18M H2P in MeCN
Example 3.
Organic Semiconductors for
Nanolectronics and NANOMELFOS
Voc ≈ HOMO donor – LUMO acceptor
Isc ≈ LUMO donor – LUMO acceptor
ββ-carotene
Carotenoids
norbixin
crocetin
retinoic acid
Computational strategy
Validation the theoreticalmodel chemistry
Computationalcharacterization of five
carotenoids (sensitizers)
Dye-ZnO interactionanalysis
Validation of the theoretical model
chemistry for ββ-carotene• Four different density functionals and two
basis set were used in the calibration
• PBE01, B3LYP2 ,TPSSh3, M05-2X4
• 3-21G(d), 6-31G(d) • Molecular structure and infrared (IR) spectrum
• Excited states – UV-Vis and fluorescence spectra
• Dipole moment – Isotropic polarizability
• Free energies of solvation ΔG(solv)
• Chemical reactivity (Fukui indices)
*(Hideki Hashimoto, et al., Journal of Molecular
Structure 604 (2002) 125-146
Molecular structure of ββ-carotene
MODELO QUIMICO
PBE1PBE/
3-21G*
(Å)
B3LYP/6-
31G*
(Å)
B3LYP/ 3-21G*
(Å)
TPSSH/ 3-21G*
(Å)
MO52X/ 3-21G*
(Å)
REFERENCIA*
TEOR - DRX
Parámetro
R(1,2) 1.537 1.554 1.549 1.544 1.534 1.51 1.51
R(2,13) 1.472 1.475 1.478 1.474 1.479 1.46 1.48
R(2,45) 1.351 1.363 1.353 1.357 1.342 1.34 1.31
R(13,14) 1.349 1.358 1.351 1.358 1.341 1.34 1.34
A1(2,1,5) 110.860 110.906 110.931 111.001 110.728 112 116
A16 (3,4,5) 108.91 109.729 109.179 108.683 108.754 113 126
D36(45,2,13,15) 50.624 45.565 51.256 47.841 55.512 48.5º 48º
D164(63,62,42,41) 50.429 45.025 50.975 46.536 57.245 N.D N.D
δ=C-H . I.S. Krasnokutskaya, E.I. Finkelshtein, J. Mol. Struct. 349 (1995)
SDBS 3436,2952,2926,2863,1448,1369,955cm-1
Electronic transitions for ββ-carotene,
wavelength (nm) - energy (eV) – oscilator strength (f)
Abs Λ (nm) E (eV) f (S)
1 471.4 2.75 4.4086 S H-0->L+0(+78%) H-1->L+1(6%)
2 336.9 3.68 0.0009 S H-1->L+0(+74%)
3 313.4 3.96 0.0004 S H-0->L+1(+79%) H-1->L+0(+9%) H-1->L+2(+7%)
4 282.9 4.38 0.0889 S H-2->L+0(+73%) H-1->L+1(+8%)
5 268.3 4.62 0.3263 S H-0->L+2(+50%) H-1->L+1(+26%)
6 247.5 0.0028 0.0028 S H-3->L+0(+63%) H-2->L+1(+14%)
Calculated with M05-2X/6-31+G(d)
Solubility of the ββ-carotene molecule
Solvent
Water Ethanol Methanol Acetone CH3Cl THF C6H12
(ΔG)
Kcal/mol0.27 -11.21 -11.47 -2.46 2.92 1.97 -4.79
fk
= over C(8), C(15), C(16) y C(21),
fk
= over C(58), C(87) y C(74).
Electronic properties
M05 2X/6-31+G(d,p)
Molecule E (u.a) μ (Debye) α(Bohr3)
ββ-carotene 1598.202 1.2844 579.85
I
(eV)
A (eV)
Χ (eV)
η
(eV)
Ѕ
(eV)
ω (eV)
5.5479 1.2213 3.3846 2.1632 1.0816 2.6477
Bixina
500100015002000250030003500
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
330
541
606950
1063
1217
1382
14731562
1664
1765
3063
3263
1217
1382
1664
3063
1606
Tra
nsm
itancia
u.a
número de onda (cm-1)
IR-bixin-3-21G(d)
N.M Gómez-Ortíz, et al., Sol. Energy Mater. Sol. Cells (2009)
http://riodb01.ibase.aist.go.jp/sdbs/cgi-bin/cre_index.cgi?lang=eng
Bixin
Norbixin
05001000150020002500300035004000
0.0
0.2
0.4
0.6
0.8
1.0
500
613
787
879
1099
1255
1428
1671
3255
3561
% T
ran
smis
ion
u.a
número de onda(cm-1)
IR-Norbixin-M052X-3-21G(d)-gas
Transbixin
01000200030004000
0.0
0.2
0.4
0.6
0.8
1.0
57
9.4
10
95
.6
13
96
.2
175230
08
.6
1304.61617.5
% T
ran
sm
isio
n u
.a
numero de onda (cm-1)
IR-Transbixina-3-21G(d)-gas
Retinoic acid
1000200030004000
0.00
0.25
0.50
0.75
1.00
31
1
84
4
10
46
13
52
14
74
15
65
31
15
32
1234
94
226881114615073372
% T
ran
smit
an
cia u
.a
número de onda (cm-1)
IR-ácido retinóico-M052X-321G(d)-gas
L.F.C. de Oliveira, S.O. Dantas, E.S. Velozo, P.S. Santos, M.C.C. Ribeiro, Journal of
Molecular Structure 435, (1997), 101-107
0500100015002000250030003500
0.0
0.2
0.4
0.6
0.8
1.0
579.4
1095.6
1396.2
17523008.6
1304.61617.5
% T
ran
sm
ita
ncia
u.a
número de onda (cm-1)
IR-crocetina-3-21G(d)-gas
Crocetin
HOMO, LUMO and Fukui functions
)04.3(9Cf
k
)72.2(11
Cfk
First excited states for the carotenoids
Molécula Λ (nm)
(eV)
(f) (S) H=HOMO, L= LUMO
bixina 460.8 2.69 3.9273
S H-0->L+0(+81%)
H-1->L+1(5%)
norbixina 472.1
* 471.5 2.62 3.8699
S H-0->L+0(+82%)
H-1->L+1(6%)
transbixina 472.2 2.63 3.9274
S H-0->L+0(+82%)
H-1->L+1(6%)
crocetina 438.0 2.823 3.2313 S H-0->L+0(+82%)
ácido
retinoico 359.1 3.45 1.7841
S H-0->L+0(+83%)
Calculated properties of carotenoids using the M052X/6-31+G(d,p) model chemistry
PROPIEDAD FASE
MOLECULA CAROTENOIDE
bixina norbixina transbixina crocetinaAcido
retinoico
BRECHA DE
ENERGÍA GAP
gas 4.359 5.009 4.233 4.514 6.3541
acuosa 2.46 2.4603 2.468 2.6243 3.7096
MOMENTO
DIPOLAR
gas 3.8788 3.6095 1.126 3.1805 2.1745
acuosa 4.7075 4.60 0.1937 5.005 2.5051
HOMO
gas -6.413 -7.784 -6.388 -6.989 -7.986
acuosa -6.368 -6.727 -6.2314 -6.589 -6.7484
LUMO
gas -2.110 -2.178 -2.098 -2.090 -1.445
acuosa -2.009 -1.718 -2.144 -2.075 -1.4694
ENERGIA TOTAL
(Hartrees)
gas -1271.70 -1232.1504 -1271.4609 -1077.364 -929.3464
acuosa -1271.50 -1232.20 -1271.50 -1077.40 -929.370
pKa acuosa 4.784 4.768 4.778 H28= 3.77 H42= 6.65
α (Bohr3) acuosa 464.64 465.2 462.59 328.12 174.83
Conceptual DFT descriptors
* Utilizando las energías HOMO y LUMO con el teorema de Koopmans
DESCRIPTOR DE
REACTIVIDADFASE
MOLECULA CAROTENOIDE
bixina norbixina transbixina crocetina
Acido
retinoico
Potencial de Ionización
(I)
gas 6.68 7.09 6.68 6.99 7.22
acuosa 5.30 5.29 5.30 5.46 5.72
Afinidad electrónica
(A)
gas 1.77 1.31 1.82 1.72 0.94
acuosa 2.84 2.83 2.83 2.84 2.53
Electronegatividad
Χ
gas 4.23 4.20 4.254.32
* 4.33
4.08
*4.72
acuosa 4.23 4.22 4.26 4.36 4.12
Dureza
ηgas 2.45 2.89 2.43
2.62
*2.26
3.14
*3.27
acuosa 2.16 2.51 2.18 1.31 1.59
Blandura
Ѕ
gas 6.28 6.34 6.36 6.37 1.598
acuosa 0.616 0.615 0.617 0.67 0.79
Índice de
electrofilicidad
ω
gas 3.64 3.05 3.723.55
4.16*
3.30
*3.34
acuosa 4.19 3.56 4.29 4.18 5.32
Zinc oxide (ZnO) has a large
application potential owing to the
diverse physical properties and
the fine-tuning in the preparation
process. The wide band gap of
3.2 eV has also made it suitable
for short-wavelength
optoelectronic devices,
including UV detectors,
photocatalysts, laser diodes
and light-emitting diodes (LEDs).
(ZnO)16
Zincite (101) optimized with the M05-2X/LANL2DZ model chemistry
Calculated and experimental IR spectra of ZnO
2003004005006007008009001000
0.0
0.2
0.4
0.6
0.8
1.0
274.4
456.1
644.5
740.8
306.7599.6768.4
% T
ran
smit
an
ce
número de onda (cm-1)
X.Q.Wei,, et al. Optics and Laser Technology 41 (2009) 530-534
Calculated and experimental UV-Vis spectra of (Zn16O16)
200 400 600 800
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
476.1
9
377.3
6
425.53
Ab
sorb
an
cia
nanómetros (nm)
UV-ZnO-M052X-LANL2DZ-optimizado
Abs λ(nm)
E
(eV)
(f) S
1 476 2.6 0.164 S H-0->L+0(+74%) O
H-1->L+1(5%)
2 395 3.14 0.0657 S H-0->L+1(+74%) Zn
H-1->L+0(13%)
3 372 3.33 0.1497 S H-1->L+0(+49%) BV
H-0->L+1(+14%)
Shalaka C. Navale, I.S. Mulla, 2009 Materials Science and
Engineering C 29 (2009) 1317–1320
Wei,X.Q., Z, Zhang et al
2009
Calculated properties of (ZnO)16 using the M052X/LANL2DZ model chemistry
DESCRIPTOR DE REACTIVIDAD
(ZnO)16
Potencial de
Ionización (I) 6.94
Afinidad
electrónica (A) 1.759
Electronegatividad 4.35
*4.31
Dureza 2.59
*1.97
Blandura 1.29
Índice de
electrofilicidad
3.65
*4.71
PROPIEDAD (ZnO)16
Energía GAP 3.9 eV
Momento
dipolar 10.97 Debyes
HOMO -6.28eV
LUMO -2.34eV
Energía Total -2249.91Hartrees
*Koopmans’s theorem
Voc ≈ HOMO donor – LUMO acceptor
(interfacial bandgap)
η ≈ HOMO donor – LUMO acceptor
(interfacial hardness)
Voc ≈ η
Conclusion: The larger the interfacial
hardness η, the larger Voc, and then, the
larger the efficiency of the solar cell
Following the previous idea, and
considering Conceptual DFT, we can
define:
Χ ≈ HOMO donor + LUMO acceptor
(interfacial electronegativity)
and
ω (interfacial electrophilicity) as the
relation between the square of the
interfacial electronegativity divides by
twice the interfacial hardness
Conceptual DFT Interfacial Reactivity Descriptors for Carotenoids and ZnO
Electronegativity (Χ)
retinoic acid (4.582) crocetin(4.313) transbixin(4.254)
bixin(4.226) norbixin (4.201)
Hardness (η)
retinoic acid (3.140) norbixin(2.891) crocetin(2.619)
bixin (2.453) transbixin (2.430)
Electrofilicity (ω)transbixin(3.724) bixin(3.640) crocetin(3.551)
norbixin(3.303) retinoic acid (3.052)
General Conclusions• Three new concepts have been defined: the interfacial
electronegativity, the interfacial hardness and the interfacial
electrofilicity, all in terms of the HOMO of the donor and the
LUMO of the acceptor.
• The calculated results and their comparison with the
experimental values seem to suggest that, for a series of
sensitizer dyes of similar structure, the larger the interfacial
electronegativity and the interfacial hardness, and the
smaller the interfacial electrofilicity, for the interaction
between the dye and the nanostructured metallic oxide, will
result in a larger efficiency of the photovoltaic solar cell.
• Luz María Rodríguez-Valdez
• Norma Flores-Holguín
• Francisco Espinosa-Magaña
• Marco Gallo-Estrada
• Amelia Valdez-Aguirre
• Erika López-Martínez
• Erasmo Orrantia-Borunda
• Alejandra Favila-Pérez
• Mónica Alvarado-Beltrán
• Isis Rodríguez-Sánchez
• Ana María Mendoza-Wilson
• Diana Barraza Jiménez
• Manuel Alberto Flores-Hidalgo
• Melina Loya Mancilla
• Nora Sánchez-Bojorge
• Hazel Morales-Rodríguez
• Teresita Ruiz-Anchondo
• Cecilia Aguilar-Elguézabal
• Francisco Cervantes-Navarro
• Alfredo Aguilar-Elguézabal
Nanomateriales
Moleculares
Funcionales
Nanoagregados
Metálicos y
Moleculares
Nanomateriales para
Almacenamiento y
Conversión de Energía
Catálisis
Nanomolecular
Nanoelectrónica
Molecular y
Nanobiosensores
Fármacos,
Agroquímicos
y Alimentos
Inhibidores de
la corrosión
DFT Teórica
y Conceptual
Química Modelo
CHIH-DFT
Azatiofenos
Fullerenos
Nanotubos
NANO-OPORTUNIDADES EN QUÍMICA COMPUTACIONAL
Daniel Glossman-Mitnik
Grupo NANOCOSMOS y PRINATEC – CIMAV, SC
Miguel de Cervantes 120 – Comp. Ind. Chihuahua – Chihuahua, Chih. 31109 – México
E-mail: [email protected]
MONESOL Virtual Net•Organic Nanomaterials for Energy Applications•Photocatalysis•Photostability and Toxicity of Drugs and UV-Photoprotection•Solar Energy•Artificial Light Harvesting Systems•Photomedicine•Photo Nanosystems•Nano Tools for Solar Energy and Photochemistry•Solar Chemistry•Photochromism•Organic Light-Emitting Diodes•PV Systems•Nanostructured Solar Cells•Hybrid and Organic Photovoltaics (Dye Solar Cells and Organic Solar Cells)•Advanced Semiconductors for Nanostructured Inorganic Photovoltaics•Nanostructured Batteries and Capacitors•Nanomaterial-Based Sensors•Biomimetic and Microbial Approaches to Solar Fuel Generation•Basic Theory and New Phenomena at the Nanoscale•Artificial Photosynthesis
Thanks for your
attention!!!
Dr. Daniel Glossman-MitnikBox 37 C
Tel: +52 614 4391151
E-mail: [email protected]
WWW: http://www.cimav.edu.mx/cv/daniel.glossman
http://blogs.cimav.edu.mx/daniel.glossman
Secretary: Rocío Landeros - Tel +52 614 4391130
Grupo NANOCOSMOS
Departamento de Simulación Computacional
y Modelado Molecular
Boxes 10 C, 11 C and 12 C
Tel: +52 614 4391190 and 4394805