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Chemical Structure| 178265-65-1 Chemical Structure| 178265-65-1

Structure of 178265-65-1

Chemical Structure| 178265-65-1

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Minog Kim ; Xin I. N. Dong ; Brian D. Spindler ; Philippe Bühlmann ; Andreas Stein ;

Abstract: With a view to potentiometric sensing with minimal calibration requirements and high long-term stability, colloid-imprinted mesoporous (CIM) carbon was functionalized by the covalent attachment of a redox and used as a new solid contact for ion-selective electrodes (ISEs). The CIM carbon surface was first modified by electroless grafting of a ligand (Tpy-ph) using diazonium chemistry, followed by stepwise binding of Co(II) and an additional Tpy ligand to the grafted ligand, forming a bis(terpyridine) Co(II) complex, CIM-ph-Tpy-Co(II)-Tpy. Half a molar equivalent of ferrocenium tetrakis(3-chlorophenyl)borate was then used to partially oxidize the Co(II) complex. Electrodes prepared with this surface-attached CIM-ph-Tpy-Co(III/II)-Tpy redox as a solid contact were tested as K+ sensors in combination with valinomycin as the ionophore and Dow 3140 silicone or plasticized poly(vinyl chloride) (PVC) as the matrixes for the ion-selective membrane (ISM). This solid contact is characterized by a redox capacitance of 3.26 F/g, ensuring a well-defined interfacial potential that underpins the transduction mechanism. By use of a redox couple as an internal reference element to control the phase boundary potential at the interface of the ISM and the CIM carbon solid contact, solid-contact ion-selective electrodes (SC-ISEs) with a standard deviation of E° as low as 0.3 mV for plasticized PVC ISMs and 3.5 mV for Dow 3140 silicone ISMs were obtained. Over 100 h, these SC-ISEs exhibit an emf drift of 20 μV/h for plasticized PVC ISMs and 62 μV/h for silicone ISMs. The differences in long-term stability and reproducibility between electrodes with ISMs comprising either a plasticized PVC or silicone matrix offer valuable insights into the effect of the polymeric matrix on sensor performance.

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Kim, Minog ;

Abstract: In this dissertation, synthetic methods for the preparation of materials containing multiple components with different properties were developed. Nanostructured multicomponent materials were synthesized with controlled architecture and composition to achieve desirable properties for applications in adsorption, charge storage, and ion sensing. In Chapter 2, our goal was to develop a dye adsorptive material with nanostructured properties for higher capacity and easy handling. To achieve our goal, a threedimensionally ordered macroporous (3DOM) structure was applied to an adsorptive material, ZIF-8, because the 3DOM structure can provide nanosized features along with bulk properties that allow for easy handling. An adsorptive ZIF-8 layer was grown on 3DOM ZnO-CeO2-Al2O3 via a vapor-phase pseudomorphic transformation. The developed 3DOM multicomponent adsorbent improved the adsorption capacity from 20 mg/g (unsupported ZIF-8 particles) to 47 mg/g and could be recycled after use. In Chapter 3, multicomponent charge storage materials were studied for application in lithium-ion batteries. The irreversible lithium loss during the first cycle reduces the battery capacity for the rest of its operating life. Li8ZrO6 was utilized as a pre-lithiation additive to compensate for the lithium loss in combination with the cathode material LiNi0.5Mn1.5O4 and assembled in coin cells with graphite as an anode. A loading of 5 wt % LZO in the multicomponent material released 5 Li+ per Li8ZrO6 and resulted in up to 18% improved reversible capacity and up to 30% improved capacity retention, compared to pristine LiNi0.5Mn1.5O4. iv Chapter 4 addresses the development of a nanostructured multicomponent material used for ion sensing. A method of functionalizing carbon surfaces with a Co(II/III) redox buffer as a solid contact was developed with the goal to ultimately prepare calibration-free solid-contact ion-selective electrode. The Co(II/III) redox buffer was covalently attached to the carbon substrate by grafting a terpyridine ligand (Tpy-ph), followed by attaching Co2+ ions and an additional Tpy ligand. The preliminary electrochemical characterization of this solid contact showed an improved E˚ reproducibility with 8.8 mV electrode-toelectrode potential variation (or 1.5 mV for the best three electrodes), compared to electrodes without any solid contact (21.4 mV) or electrodes without the Co(II/III) redox buffer (13.9 mV).

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Alternative Products

Product Details of [ 178265-65-1 ]

CAS No. :178265-65-1
Formula : C21H16N4
M.W : 324.38
SMILES Code : NC1=CC=C(C2=CC(C3=NC=CC=C3)=NC(C4=NC=CC=C4)=C2)C=C1
MDL No. :MFCD06796989
InChI Key :CYISWQZYBSHTNN-UHFFFAOYSA-N
Pubchem ID :10860314

Safety of [ 178265-65-1 ]

GHS Pictogram:
Signal Word:Warning
Hazard Statements:H302-H315-H320-H335
Precautionary Statements:P261-P280-P301+P312-P302+P352-P305+P351+P338

Computational Chemistry of [ 178265-65-1 ] Show Less

Physicochemical Properties

Num. heavy atoms 25
Num. arom. heavy atoms 24
Fraction Csp3 0.0
Num. rotatable bonds 3
Num. H-bond acceptors 3.0
Num. H-bond donors 1.0
Molar Refractivity 100.54
TPSA ?

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

64.69 Ų

Lipophilicity

Log Po/w (iLOGP)?

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

2.94
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

2.91
Log Po/w (WLOGP)?

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

4.46
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.

1.78
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

4.22
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

3.26

Water Solubility

Log S (ESOL):?

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

-4.2
Solubility 0.0206 mg/ml ; 0.0000636 mol/l
Class?

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

Moderately soluble
Log S (Ali)?

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

-3.93
Solubility 0.0382 mg/ml ; 0.000118 mol/l
Class?

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

Soluble
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

-8.45
Solubility 0.00000116 mg/ml ; 0.0000000036 mol/l
Class?

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

Poorly soluble

Pharmacokinetics

GI absorption?

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

High
BBB permeant?

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

Yes
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

Yes
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

Yes
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

Yes
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

Yes
Log Kp (skin permeation)?

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

-6.21 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

0.0
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

0.0
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

0.0
Bioavailability Score?

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

0.55

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

1.0 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<0.0
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)

2.55
 

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Technical Information

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