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Sigma-Aldrich

Aluminum oxide

nanopowder, 13 nm primary particle size (TEM), 99.8% trace metals basis

Synonym(s):

Aluminia, Alumina

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About This Item

Linear Formula:
Al2O3
CAS Number:
1344-28-1
Molecular Weight:
101.96
EC Number:
215-691-6
MDL number:
MFCD00003424
UNSPSC Code:
12352303
eCl@ss:
38120402
PubChem Substance ID:
329763581
NACRES:
NA.23

Quality Level

100

assay

99.8% trace metals basis

form

nanopowder

surface area

85-115 m2/g , BET

primary particle size

13 nm (TEM)

mp

2040 °C (lit.)

SMILES string

O=[Al]O[Al]=O

InChI

1S/2Al.3O

InChI key

TWNQGVIAIRXVLR-UHFFFAOYSA-N

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General description

Aluminum oxide nanoparticles (AlNPs) are porous nanomaterials with corundum-like structures. They possess high surface area, mechanical strength, and good optical properties. In addition, they have excellent chemical stability in harsh conditions such as abrasive environments and high temperatures. The ease of surface modification and bioinertess make them suitable for biomedical applications. These nanomaterials can be prepared by a cost-effective and simple protocol.

Application

Aluminum nanoparticles can be used to prepare:
  • Water-based nanofluids, which are used in engine cooling, heat exchangers, and nuclear cooling system. In graphene oxide/alumina nanofluid, the addition of aluminum nanoparticles improves the physical structure of graphene oxide and reduces the viscosity of the composite.
  • Polysiloxane-aluminum oxide composites, applicable as an elastomeric thermal pad for light-emitting diodes.
It can also be used as an additive to improve the mechanical properties of polyvinyl chloride. The Al2O3 nanoparticles act as a solid inert phase in the polymer matrix and restrict the mobility of chains. As a result glass transition temperature increases and elastic modulus decreases.

Features and Benefits

  • Stable in a harsh non-biological environment.
  • They can be easily prepared through established synthesis methods.
  • A vast surface area allows conjugation with chemical and biological molecules.
  • Their surface modification protocols are straightforward.
  • They can easily interact with biological interfaces.

wgk_germany

nwg

flash_point_f

Not applicable

flash_point_c

Not applicable

Certificates of Analysis (COA)

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Laura M Corredor et al.
Nanomaterials (Basel, Switzerland), 9(1) (2019-01-16)
Recent studies revealed higher polymer flooding performance upon adding metal oxide nanoparticles (NPs) to acrylamide-based polymers during heavy oil recovery. The current study considers the effect of TiO₂, Al₂O₃, in-situ prepared Fe(OH)₃ and surface-modified SiO₂ NPs on the performance of
Shuo Yang et al.
Sensors (Basel, Switzerland), 19(14) (2019-07-25)
Readily available temperature sensing in boilers is necessary to improve efficiencies, minimize downtime, and reduce toxic emissions for a power plant. The current techniques are typically deployed as a single-point measurement and are primarily used for detection and prevention of
Joohoon Kang et al.
ACS nano, 9(4), 3596-3604 (2015-03-19)
Solution dispersions of two-dimensional (2D) black phosphorus (BP)--often referred to as phosphorene--are achieved by solvent exfoliation. These pristine, electronic-grade BP dispersions are produced with anhydrous organic solvents in a sealed-tip ultrasonication system, which circumvents BP degradation that would otherwise occur
Chien-Chih Lin et al.
Nanoscale, 5(17), 8090-8097 (2013-07-25)
We demonstrated a promising route for enhancing temperature sensitivity, improving saturation voltage, and reducing power consumption of the MOS(p) tunneling temperature sensors by introducing ultrathin Al2O3 into the dielectric stacks. Detailed illustrations of the working mechanism and device concept are
Jaakko Akola et al.
Proceedings of the National Academy of Sciences of the United States of America, 110(25), 10129-10134 (2013-06-01)
Glass formation in the CaO-Al2O3 system represents an important phenomenon because it does not contain typical network-forming cations. We have produced structural models of CaO-Al2O3 glasses using combined density functional theory-reverse Monte Carlo simulations and obtained structures that reproduce experiments
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