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Chemical Structure| 629-41-4 Chemical Structure| 629-41-4
Chemical Structure| 629-41-4

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CAS No.: 629-41-4

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Mahadas, Nagarjuna A ; Suhail, Amir ; Sobczak, Martin Taylor ; Li, Xiaomeng ; Chen, Kezhi ; Song, Kenan , et al.

Abstract: Synthesis of high molecular weight long-chain aliphatic polyesters with mechanical properties similar to polyethylene is challenging. This study presents high molecular weight biobased polyesters synthesized via a three-step process involving transesterification, polycondensation, and postcondensation, using biobased 1,18-dimethyl octadecanedioate (C18-diester) and natural diols ranging from C3 to C12. All polyesters achieved weight-average molecular weights over 110 000 g/mol. The crystalline structures and thermomechanical properties of polyesters were largely influenced by the chain length of diols, with an odd?even effect observed. These polyesters exhibit tensile properties mimicking HDPE and LDPE, which allowed successful processing into filaments and 3D-printed objects. Although these polyesters exhibit semicrystalline structures similar to polyethylene, their melting temperatures are significantly lower, especially compared to HDPE. Chemical recycling of a representative polyester demonstrated its ability to undergo depolymerization and repolymerization, with the recovered polyesters displaying comparable mechanical properties to the virgin one. Coarse-grained molecular dynamic simulations of these polyesters demonstrated crystallization of the materials upon cooling from melts and reproduced the decrease in crystallization temperature with an increase in the ester-to-methylene ratio observed in the experiments. The proposed modeling approach allowed us to track the growth of crystalline domains upon cooling from the melt by characterizing the local nematic order parameter to quantify the effect of ester groups on the crystallization process. This study addresses common challenges that complicate synthesis and polymer processing, providing useful guidance for achieving reproducible polyester preparation.

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M. Królikowski ; M. Wi?ckowski ; K. ?ó?tańska ; M. Królikowska ;

Abstract: This work concentrates on the development of eutectic PCMs (ePCMs) that can effectively store and release thermal energy, showcasing high melting enthalpies, stability under thermal cycling, and lower flammability than pure diols. The first part presents the synthesis and characterization of dicationic ionic liquids (ILs), followed by the (solid + liquid) phase equilibrium, SLE studies of {[(i-Quin)2C6][2Br], or [(i-Quin)2C10][2Br] (1) + 1,6-hexanediol, 1,8-octanediol, 1,10-decanediol, or 1,12-dodecanediol (2)} systems. Eight ePCMs with enthalpies of melting varying from (190.1 to 204.5) J g–1 were determined. In the proposed systems, the bromide anion of the IL is the donor, and the hydroxyl group in the diol is the acceptor of the electron pair. The thermophysical characterization of pure ILs and the eutectic mixtures, including melting point, latent heat, as well as temperature and enthalpy of (solid + solid) phase transition, were determined by DSC analysis. Additionally, the composite systems of [(i-Quin)2C6][2Br] and [(i-Quin)2C10][2Br] with 1,8-octanediol and additions of single-walled carbon nanotubes (SWCNTs) and expanded graphite (EG) were prepared and characterized in terms of stability and performance. The research offers insights into the potential of these ePCMs in thermal energy storage applications, emphasizing their high latent heat and efficient thermal conductivity, especially when combined with carbon materials such as EG.

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Wieckowski, Mikolaj ; Krolikowski, Marek ; Zywolko, Magdalena ; Scheller, Lukasz ; Dzida, Marzena ;

Abstract: This paper presents solid-liquid phase equilibrium studies of binary systems composed of pyridinium chloride monohydrates: hexadecylpyridinium chloride monohydrate, [PyC16][Cl] or dodecylpyridinium chloride monohydrate, [PyC12][Cl] with diols: 1,2-hexanediol, 1,6-hexanediol, 1,8-octanediol, 1,10-decanediol and 1,12-dodecanediol. These systems were selected to obtain eutectic mixtures with a high melting enthalpy and lower volatility (thus flammability) than pure diols. Ten eutectic Phase Change Materials (ePCMs) with m.ps. ranging from 265 K to 333 K (-8°C to 60°C) and enthalpies of melting from 125.9 to 212.8 J.g-1 were obtained. Exptl. data were then correlated with the Non-Random Two-Liquid (NRTL) equation, and mixtures of eutectic composition were subjected to physicochem. characterization. Using DSC, the latent heats of pure components and eutectic mixtures were determined, as well as the viscosity and the thermal conductivity of ePCMs was measured as a function of temperature The final objective of the study was to increase the thermal conductivity of ePCMs by adding carbon nanotubes or expanded graphite, and to characterize the performance of such composite systems. The stability of nanofluids containing no less than 1 wt% SWCNTs and from about 10 wt% EG was confirmed under both isothermal and energy storage operating conditions, i.e. during a series of at least 1000 phase transformations. The addition of an inexpensive EG at 10 wt% increases the thermal conductivity by up to 200% and reduces the probability of ePCM leakage as the material retains its shape even after melting.

Keywords: Eutectic Phase Change Material (ePCM) ; Diols ; Ionic Liquids (ILs) ; Single Wall Carbon Nanotubes (SWCNTs) ; Thermal Energy Storage (TES) ; Solid ; Liquid Equilibrium (SLE)

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Alternative Products

Product Details of [ 629-41-4 ]

CAS No. :629-41-4
Formula : C8H18O2
M.W : 146.23
SMILES Code : C(CCCCO)CCCO
MDL No. :MFCD00002989
InChI Key :OEIJHBUUFURJLI-UHFFFAOYSA-N
Pubchem ID :69420

Safety of [ 629-41-4 ]

GHS Pictogram:
Signal Word:Warning
Hazard Statements:H319
Precautionary Statements:P280-P305+P351+P338-P337+P313

Calculated chemistry of [ 629-41-4 ] Show Less

Physicochemical Properties

Num. heavy atoms 10
Num. arom. heavy atoms 0
Fraction Csp3 1.0
Num. rotatable bonds 7
Num. H-bond acceptors 2.0
Num. H-bond donors 2.0
Molar Refractivity 42.89
TPSA ?

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

40.46 ?2

Lipophilicity

Log Po/w (iLOGP)?

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

2.11
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

1.37
Log Po/w (WLOGP)?

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

1.31
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.

1.29
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

1.62
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

1.54

Water Solubility

Log S (ESOL):?

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

-1.15
Solubility 10.4 mg/ml ; 0.0712 mol/l
Class?

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

Very soluble
Log S (Ali)?

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

-1.82
Solubility 2.2 mg/ml ; 0.015 mol/l
Class?

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

Very 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

-1.95
Solubility 1.66 mg/ml ; 0.0113 mol/l
Class?

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

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

 No
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.

-6.22 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

 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

 1.0
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

0.0 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<1.0
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)

 1.48
 

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