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Malinowski, Daniel ; He, Guiying ; Salcido-Santacruz, Bernardo ; Majumder, Kanad ; Kwon, Junho ; Sfeir, Matthew Y , et al.

Abstract: Multiexciton (ME) mechanisms hold great promise for enhancing energy conversion efficiency in optoelectronic and photochemical systems. In singlet fission (SF), the generation of two triplet excitons from a single photon provides a route to circumvent thermal energy losses and organic systems offer opportunities to modulate ME dynamics. However, the practical implementation of SF-based materials is hindered by poor triplet exciton mobility, interfacial recombination losses, and complex dynamics at heterogeneous interfaces. While studies of interfacial SF dynamics have demonstrated the potential for efficient charge and exciton transfer, experimental conditions and design of interfaces vary widely. To address this, we explore polymer-based self-assembled architectures as a tunable platform for studying mesoscale SF interfacial dynamics of (multi)exciton transfer, as well as electron and hole transfer. Specifically, we design amphiphilic block copolymers (BCPs) incorporating pendent tetracene moieties that self-assemble into micellar nanoparticles, placing the tetracenes in the amorphous core. These micelles provide a controlled environment to systematically introduce “dopants” to investigate interfacial dynamics. Importantly, the use of solvents within the micelle core can be also applied to impart polymer chain mobility.

Purchased from AmBeed: ;

Zachary T. Armstrong ; Miriam Bohlmann Kunz ; Andrew C. Jones ; Martin T. Zanni ;

Abstract: Defects in molecular crystals, created by nonequilibrium crystal packing, can have significant influence over the energetics and dynamics of singlet fission. Though normally thought of as detrimental to the performance of organic semiconductors, in principle, defects could have crystal packings with better energetics and couplings for singlet fission than equilibrium crystal packing structures. Using two-dimensional electronic microscopy and X-ray diffraction, we monitor the population of nonequilibrium slip-stacked geometries in microcrystals of TIPS-pentacene before and after thermal annealing. We find that the presence of these slip-stacked structures enhances the singlet fission yield, as measured by triplet excited state absorption. The slip-stacked geometry matches no known polymorph of TIPS-pentacene, according to X-ray diffraction but indicates that slip-stacked molecules are present as tiny crystalline domains within the larger microcrystal. The data presented here provide evidence that slip-stacked geometries, present as defects in larger TIPS-pentacene microcrystals, enhance singlet fission yields.

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Alternative Products

Product Details of [ 373596-08-8 ]

CAS No. :373596-08-8
Formula : C44H54Si2
M.W : 639.07
SMILES Code : CC(C)[Si](C#CC1=C2C=C3C=CC=CC3=CC2=C(C#C[Si](C(C)C)(C(C)C)C(C)C)C2=CC3=C(C=CC=C3)C=C12)(C(C)C)C(C)C
MDL No. :MFCD15143658
InChI Key :FMZQNTNMBORAJM-UHFFFAOYSA-N
Pubchem ID :15530606

Safety of [ 373596-08-8 ]

GHS Pictogram:
Signal Word:Warning
Hazard Statements:H315-H319-H335
Precautionary Statements:P261-P305+P351+P338

Computational Chemistry of [ 373596-08-8 ] Show Less

Physicochemical Properties

Num. heavy atoms 46
Num. arom. heavy atoms 22
Fraction Csp3 0.41
Num. rotatable bonds 6
Num. H-bond acceptors 0.0
Num. H-bond donors 0.0
Molar Refractivity 214.6
TPSA ?

Topological Polar Surface Area: Calculated from
Ertl P. et al. 2000 J. Med. Chem.

0.0 Ų

Lipophilicity

Log Po/w (iLOGP)?

iLOGP: in-house physics-based method implemented from
Daina A et al. 2014 J. Chem. Inf. Model.

6.82
Log Po/w (XLOGP3)?

XLOGP3: Atomistic and knowledge-based method calculated by
XLOGP program, version 3.2.2, courtesy of CCBG, Shanghai Institute of Organic Chemistry

16.08
Log Po/w (WLOGP)?

WLOGP: Atomistic method implemented from
Wildman SA and Crippen GM. 1999 J. Chem. Inf. Model.

13.6
Log Po/w (MLOGP)?

MLOGP: Topological method implemented from
Moriguchi I. et al. 1992 Chem. Pharm. Bull.
Moriguchi I. et al. 1994 Chem. Pharm. Bull.
Lipinski PA. et al. 2001 Adv. Drug. Deliv. Rev.

9.74
Log Po/w (SILICOS-IT)?

SILICOS-IT: Hybrid fragmental/topological method calculated by
FILTER-IT program, version 1.0.2, courtesy of SILICOS-IT, http://www.silicos-it.com

10.64
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

11.38

Water Solubility

Log S (ESOL):?

ESOL: Topological method implemented from
Delaney JS. 2004 J. Chem. Inf. Model.

-13.89
Solubility 0.0 mg/ml ; 0.0 mol/l
Class?

Solubility class: Log S scale
Insoluble < -10 < Poorly < -6 < Moderately < -4 < Soluble < -2 Very < 0 < Highly

Insoluble
Log S (Ali)?

Ali: Topological method implemented from
Ali J. et al. 2012 J. Chem. Inf. Model.

-16.24
Solubility 0.0 mg/ml ; 5.79e-17 mol/l
Class?

Solubility class: Log S scale
Insoluble < -10 < Poorly < -6 < Moderately < -4 < Soluble < -2 Very < 0 < Highly

Insoluble
Log S (SILICOS-IT)?

SILICOS-IT: Fragmental method calculated by
FILTER-IT program, version 1.0.2, courtesy of SILICOS-IT, http://www.silicos-it.com

-14.05
Solubility 0.0 mg/ml ; 0.0 mol/l
Class?

Solubility class: Log S scale
Insoluble < -10 < Poorly < -6 < Moderately < -4 < Soluble < -2 Very < 0 < Highly

Insoluble

Pharmacokinetics

GI absorption?

Gatrointestinal absorption: according to the white of the BOILED-Egg

Low
BBB permeant?

BBB permeation: according to the yolk of the BOILED-Egg

No
P-gp substrate?

P-glycoprotein substrate: SVM model built on 1033 molecules (training set)
and tested on 415 molecules (test set)
10-fold CV: ACC=0.72 / AUC=0.77
External: ACC=0.88 / AUC=0.94

Yes
CYP1A2 inhibitor?

Cytochrome P450 1A2 inhibitor: SVM model built on 9145 molecules (training set)
and tested on 3000 molecules (test set)
10-fold CV: ACC=0.83 / AUC=0.90
External: ACC=0.84 / AUC=0.91

No
CYP2C19 inhibitor?

Cytochrome P450 2C19 inhibitor: SVM model built on 9272 molecules (training set)
and tested on 3000 molecules (test set)
10-fold CV: ACC=0.80 / AUC=0.86
External: ACC=0.80 / AUC=0.87

No
CYP2C9 inhibitor?

Cytochrome P450 2C9 inhibitor: SVM model built on 5940 molecules (training set)
and tested on 2075 molecules (test set)
10-fold CV: ACC=0.78 / AUC=0.85
External: ACC=0.71 / AUC=0.81

No
CYP2D6 inhibitor?

Cytochrome P450 2D6 inhibitor: SVM model built on 3664 molecules (training set)
and tested on 1068 molecules (test set)
10-fold CV: ACC=0.79 / AUC=0.85
External: ACC=0.81 / AUC=0.87

No
CYP3A4 inhibitor?

Cytochrome P450 3A4 inhibitor: SVM model built on 7518 molecules (training set)
and tested on 2579 molecules (test set)
10-fold CV: ACC=0.77 / AUC=0.85
External: ACC=0.78 / AUC=0.86

No
Log Kp (skin permeation)?

Skin permeation: QSPR model implemented from
Potts RO and Guy RH. 1992 Pharm. Res.

1.22 cm/s

Druglikeness

Lipinski?

Lipinski (Pfizer) filter: implemented from
Lipinski CA. et al. 2001 Adv. Drug Deliv. Rev.
MW ≤ 500
MLOGP ≤ 4.15
N or O ≤ 10
NH or OH ≤ 5

2.0
Ghose?

Ghose filter: implemented from
Ghose AK. et al. 1999 J. Comb. Chem.
160 ≤ MW ≤ 480
-0.4 ≤ WLOGP ≤ 5.6
40 ≤ MR ≤ 130
20 ≤ atoms ≤ 70

None
Veber?

Veber (GSK) filter: implemented from
Veber DF. et al. 2002 J. Med. Chem.
Rotatable bonds ≤ 10
TPSA ≤ 140

0.0
Egan?

Egan (Pharmacia) filter: implemented from
Egan WJ. et al. 2000 J. Med. Chem.
WLOGP ≤ 5.88
TPSA ≤ 131.6

1.0
Muegge?

Muegge (Bayer) filter: implemented from
Muegge I. et al. 2001 J. Med. Chem.
200 ≤ MW ≤ 600
-2 ≤ XLOGP ≤ 5
TPSA ≤ 150
Num. rings ≤ 7
Num. carbon > 4
Num. heteroatoms > 1
Num. rotatable bonds ≤ 15
H-bond acc. ≤ 10
H-bond don. ≤ 5

3.0
Bioavailability Score?

Abbott Bioavailability Score: Probability of F > 10% in rat
implemented from
Martin YC. 2005 J. Med. Chem.

0.17

Medicinal Chemistry

PAINS?

Pan Assay Interference Structures: implemented from
Baell JB. & Holloway GA. 2010 J. Med. Chem.

0.0 alert
Brenk?

Structural Alert: implemented from
Brenk R. et al. 2008 ChemMedChem

3.0 alert: heavy_metal
Leadlikeness?

Leadlikeness: implemented from
Teague SJ. 1999 Angew. Chem. Int. Ed.
250 ≤ MW ≤ 350
XLOGP ≤ 3.5
Num. rotatable bonds ≤ 7

No; 1 violation:MW<2.0
Synthetic accessibility?

Synthetic accessibility score: from 1 (very easy) to 10 (very difficult)
based on 1024 fragmental contributions (FP2) modulated by size and complexity penaties,
trained on 12'782'590 molecules and tested on 40 external molecules (r2 = 0.94)

5.6
 

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