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91852

Supelco

D-(+)-Cellobiose

analytical standard

Synonym(s):

β-D-Glc-(1→4)-D-Glc, 4-O-β-D-Glucopyranosyl-D-glucose

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About This Item

Empirical Formula (Hill Notation):
C12H22O11
CAS Number:
Molecular Weight:
342.30
Beilstein:
93795
EC Number:
MDL number:
UNSPSC Code:
41116107
NACRES:
NA.24

grade

analytical standard

Quality Level

Assay

≥98% (HPLC)

optical activity

[α]/D 34±1°, c = 10 in H2O

shelf life

limited shelf life, expiry date on the label

analyte chemical class(es)

oligosaccharides

mp

239 °C (dec.) (lit.)

application(s)

food and beverages

format

neat

SMILES string

OC[C@@H](O)[C@@H](O[C@@H]1O[C@H](CO)[C@@H](O)[C@H](O)[C@H]1O)[C@H](O)[C@@H](O)C=O

InChI

1S/C12H22O11/c13-1-4(16)7(18)11(5(17)2-14)23-12-10(21)9(20)8(19)6(3-15)22-12/h1,4-12,14-21H,2-3H2/t4-,5+,6+,7+,8+,9-,10+,11+,12-/m0/s1

InChI key

DKXNBNKWCZZMJT-WELRSGGNSA-N

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General description

Cellobiose is a disaccharide, commonly classified as a reducing sugar. It is mostly produced as an intermediate in the hydrolysis of the polysaccharide cellulose.

Application

D-(+)-Cellobiose may be used as an analytical standard in the following:
  • Training, testing, and external validation of the gradient retention model developed in ion chromatography using the artificial intelligence-quantitative structure retention relationship (QSRR) model approach.
  • Amperometric detection of the analyte in anion-exchange chromatography using copper/cupric oxide nanostructured electrode.

D-(+)-Cellobiose may be used as an analytical reference standard for the quantification of the analyte in caramel samples using gas–liquid chromatography coupled to mass spectrometry (GLC–MS).

Storage Class Code

11 - Combustible Solids

WGK

WGK 3

Flash Point(F)

Not applicable

Flash Point(C)

Not applicable


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Journal of Chromatography A, 844(1-2), 283-293 (1999)
Nanostructured cupric oxide electrode: An alternative to amperometric detection of carbohydrates in anion-exchange chromatography
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Development of Gradient Retention Model in Ion Chromatography. Part II: Artificial Intelligence QSRR Approach
Ukic S, et al.
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