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Institution

Agilent Technologies

CompanySanta Clara, California, United States
About: Agilent Technologies is a company organization based out in Santa Clara, California, United States. It is known for research contribution in the topics: Signal & Mass spectrometry. The organization has 7398 authors who have published 11518 publications receiving 262410 citations. The organization is also known as: Agilent Technologies, Inc..


Papers
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Journal ArticleDOI
TL;DR: In this paper, surface-adhered magnetic nanoparticles (NPs) are synthesized by a facile thermal-decomposition method and two different sized graphenes (Gra-10 and Gra-40) are used.
Abstract: Magnetic graphene nanocomposites (MGNCs) with surface-adhered magnetic nanoparticles (NPs) are synthesized by a facile thermal-decomposition method. Two different sized graphenes (Gra-10 and Gra-40) are used. The stacking of a few layers of NPs is revealed by the AFM observation in the nanocomposites, especially with a higher particle loading. The TEM observations show that the average particle size increases from 12.1 to 17.4 nm with increasing particle loading from 2 to 10% on Gra-10 substrate. The NPs exhibit a core@shell structure with an iron core and iron oxide shell, confirmed by high resolution TEM, selected area electron diffraction and X-ray diffraction analysis. The graphene size and particle loading dependent behavior such as dielectric permittivity, electrical conductivity, magnetization and giant magnetoresistance (GMR) are observed. The electrical conductivity has been significantly changed in the different sized graphenes after coating with NPs (conductivity: Gra-10 > NPs/Gra-10; Gra-40 < NPs/Gra-40). The MR is observed to vary from 38 to 64% at 130 K, and even higher MR of about 46–72% is observed at 290 K. More interestingly, the dielectric permittivity can be tuned from negative to positive at high frequency with increasing particle loading. All the results indicate that graphene with smaller size obtains superior properties than the one with larger size.

90 citations

Journal ArticleDOI
TL;DR: In this paper, an analytical method for the simultaneous determination of aflatoxins B 1, B 2, G 1, G 2, ochratoxin A, fumonisins B 2 and B 2, zearalenone, deoxynivalenol, T 2 toxin, and HT-2 toxin using rapid liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed.

90 citations

Journal ArticleDOI
TL;DR: This work studied the signaling network for the peroxisome proliferator-associated receptor alpha (PPARα) in primary human hepatocytes using the selective PPARα ligand, GW7647 and developed two novel bioinformatics methods to visualize the dose-dependent activation of both the transcription factor circuitry for PPAR α and the downstream metabolic network in relation to functional annotation categories.

90 citations

Journal ArticleDOI
TL;DR: A novel polymeric microfluidic device with an on-chip enzyme reactor has been developed for the characterization of recombinant glycoproteins and a single chip was shown to retain activity and perform equivalently for over 250 replicate glycan profiles from a recombinant antibody.
Abstract: A novel polymeric microfluidic device with an on-chip enzyme reactor has been developed for the characterization of recombinant glycoproteins. The enzyme reactor chip packed with PNGase F-modified solid support material was combined with a microfluidic glycan cleanup chip and a commercially available HPLC-chip to perform glycoprotein deglycosylation, protein removal, glycan capture, glycan LC separation, and nanoelectrospray into a time-of-flight mass spectrometry (TOF-MS) system. With this integrated chip, the combined sample preparation and sample analysis time was reduced from multiple hours to less than 10 min. A once tedious and time-consuming glycan analysis workflow is now integrated into an HPLC-chip device. Glycan profiling analysis has been achieved with as little as 100 ng of monoclonal antibody. Furthermore, a single chip was shown to retain activity and perform equivalently for over 250 replicate glycan profiles from a recombinant antibody.

90 citations

Journal ArticleDOI
TL;DR: In this paper, the self-sensing capabilities of fly ash-based geopolymeric composites containing in situ reduced graphene oxide (rGO) were evaluated and the results indicated that the rGO sheets can easily be reduced due to the effect of the alkaline solution on the functional groups of GO.
Abstract: The reduction of graphene oxide during the processing of fly ash-based geopolymers offers a completely new way of developing low-cost multifunctional materials with significantly improved mechanical and electrical properties for civil engineering applications such as bridges, buildings and roads. In this paper, we present for the first time the self-sensing capabilities of fly ash-based geopolymeric composites containing in situ reduced graphene oxide (rGO). Geopolymeric composites with rGO concentrations of 0.0, 0.1 and 0.35% by weight were prepared and their morphology and conductivity were determined. The piezoresistive effect of the rGO-geopolymeric composites was also determined under tension and compression. The Fourier transform infrared spectroscopy (FTIR) results indicate that the rGO sheets can easily be reduced during synthesis of geopolymers due to the effect of the alkaline solution on the functional groups of GO. The scanning electron microscope (SEM) images showed that the majority of pores and voids within the geopolymers were significantly reduced due to the addition of rGO. The rGO increased the electrical conductivity of the fly ash-based rGO-geopolymeric composites from 0.77 S m−1 at 0.0 wt% to 2.38 S m−1 at 0.35 wt%. The rGO also increased the gauge factor by as much as 112% and 103% for samples subjected to tension and compression, respectively.

90 citations


Authors

Showing all 7402 results

NameH-indexPapersCitations
Hongjie Dai197570182579
Zhuang Liu14953587662
Jie Liu131153168891
Thomas Quertermous10340552437
John E. Bowers102176749290
Roy G. Gordon8944931058
Masaru Tomita7667740415
Stuart Lindsay7434722224
Ron Shamir7431923670
W. Richard McCombie7114464155
Tomoyoshi Soga7139221209
Michael R. Krames6532118448
Shabaz Mohammed6418817254
Geert Leus6260919492
Giuseppe Gigli6154115159
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
20228
2021142
2020157
2019168
2018164