产品名称
碳, microleaf, 25x70mm, thinness 0.25μm, specific density 50μg/cm2, temporary glass support, 99.997%
InChI
1S/C
SMILES string
[C]
InChI key
OKTJSMMVPCPJKN-UHFFFAOYSA-N
vapor pressure
<0.1 mmHg ( 20 °C)
assay
99.997%
form
wire
autoignition temp.
842 °F
manufacturer/tradename
Goodfellow 826-380-29
resistivity
1375 μΩ-cm, 20°C (graphite)
size × thickness
25 × 70 mm × 0.25 μm
mp
3550 °C (lit.)
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General description
For updated SDS information please visit www.goodfellow.com.
Legal Information
Product of Goodfellow
存储类别
13 - Non Combustible Solids
wgk
nwg
flash_point_f
Not applicable
flash_point_c
Not applicable
法规信息
新产品
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Chi-Jung Su et al.
Journal of nanoscience and nanotechnology, 14(6), 4201-4206 (2014-04-18)
Carbon nanofibers (CNFs) have wide applications in energy storage devices, electrically conducting composites, selective adsorbents, and catalyst supports. Catalytic chemical vapor deposition was carried out in this work to synthesize CNFs at mild temperatures of 700 and 800 degrees C.
Cancer treatment: Sharp shooters.
Vivien Marx
Nature, 508(7494), 133-138 (2014-04-04)
Anna Iliadi et al.
American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics, 145(4), 425-433 (2014-04-08)
The aim of this study was to assess the effect of intraoral aging on the setting status of a resin composite and a glass ionomer adhesive, relative to control specimens stored in water. Metallic brackets were bonded with resin composite
Ivar Zekker et al.
Environmental technology, 35(9-12), 1565-1576 (2014-04-08)
Maintaining stability of low concentration (< 1 g L(-1)) floccular biomass in the nitritation-anaerobic ammonium oxidation (anammox) process in the sequencing batch reactor (SBR) system for the treatment of high COD (> 15,000 mg O2 L(-1)) to N (1680 mg
Marshall W Bowles et al.
Science (New York, N.Y.), 344(6186), 889-891 (2014-05-09)
Sulfate reduction is a globally important redox process in marine sediments, yet global rates are poorly quantified. We developed an artificial neural network trained with 199 sulfate profiles, constrained with geomorphological and geochemical maps to estimate global sulfate-reduction rate distributions.
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