Strain and correlation of self-organized<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mtext>Ge</mml:mtext></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:mi>x</mml:mi></mml:mrow></mml:msub><mml:msub><mml:mrow><mml:mtext>Mn</mml:mtext></mml:mrow><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math>nanocolumns embedded in Ge (001)

Tardif, Samuel; Favre‐Nicolin, V.; Lançon, Frédéric; Arras, Emmanuel; Jamet, M.; Barski, A.; Porret, Clément; Bayle–Guillemaud, Pascale; Pochet, Pascal; Devillers, Thibaut; Rovezzi, Mauro

doi:10.1103/physrevb.82.104101

Cited by 17 publications

(17 citation statements)

References 49 publications

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“…However a 15 min annealing at 650 °C activates the volume diffusion of Mn atoms, and the nanocolumns collapse into Mn 5 Ge 3 nanoparticles. Detailed structural and magnetic properties have been reported in References [35,36,37,38]. …”

Section: Mn-doped Gementioning

confidence: 99%

Mn-doped Ge and Si: A Review of the Experimental Status

Zhou

Schmidt

2010

Materials

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Diluted ferromagnetic semiconductors (FMS) are in the focus of intense research due to their potential applications in spintronics and their striking new physical properties. So far Mn-doped III-V compound semiconductors such as GaMnAs are the most important and best understood ones, but they are ferromagnetic only at well below room temperature. An interesting alternative could be magnetic semiconductors based on elemental semiconductors, also owing to their compatibility with Si microelectronics. In the last decades, considerable amount of work has been devoted to fabricate Mn-doped Ge and Si FMS. In this article, the structural, magnetic and magneto-transport properties of Mn-doped Ge and Si will be reviewed.

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Section: Mn-doped Gementioning

confidence: 99%

Mn-doped Ge and Si: A Review of the Experimental Status

Zhou

Schmidt

2010

Materials

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“…According to our data, it was possible to determine that AA exposure through potato chips C brand did not exceed the value of Tolerable Daily Intake (TDI) of AA associated with neurotoxicity effects (40 μg/kg bw/day) and cancer (2.6 μg/kg bw/day) (Tardif et al, 2010). However, the level of AA exposure through D brand potato chips exceeded 1.7-fold the TDI associated with cancer.…”

Section: Discussionmentioning

confidence: 93%

Evaluation of acrylamide-removing properties of two Lactobacillus strains under simulated gastrointestinal conditions using a dynamic system

Rivas-Jimenez

Ramírez-Ortiz

González‐Córdova

et al. 2016

Microbiological Research

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The aim of this study was to evaluate the capability of Lactobacillus reuteri NRRL 14171 and Lactobacillus casei Shirota to remove dietary acrylamide (AA) under simulated gastrointestinal conditions using a dynamic system. The effects of different AA levels or bacteria concentration on toxin removal by Lactobacillus strains were assessed. Thereafter, AA-removing capability of bacteria strains under either fasting or postprandial simulated gastrointestinal conditions was evaluated. Commercial potato chips were analyzed for their AA content, and then used as a food model. Average AA content (34,162μg/kg) in potato chips exceeded by ca. 34-fold the indicative values recommended by the EU. Toxin removal ability was dependent on AA content and bacterial cell concentration. A reduction on bacterial viability was observed in the food model and at the end of both digestive processes evaluated. However, bacteria survived in enough concentrations to remove part of the toxin (32-73%). Both bacterial strains were able to remove AA under different simulated gastrointestinal conditions, being L. casei Shirota the most effective (ca. 70% removal). These findings confirmed the risk of potato chips as dietary AA exposure for consumers, and that strains of the genus Lactobacillus could be employed to reduce the bioavailability of dietary AA.

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“…We have found that errors due to single precision floating point calculations were not significant in practice: indeed, most of the time structural models for which this type of computation is used are not ideal (see examples of simulated calculations using our code in Tardif et al (2010) and Favre-Nicolin et al (2010)) and therefore do not present a very large dynamic range (larger than 8 orders of magnitude).…”

Section: Figurementioning

confidence: 99%

Fast computation of scattering maps of nanostructures using graphical processing units

et al. 2011

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Scattering maps from strained or disordered nano-structures around a Bragg reflection can either be computed quickly using approximations and a (Fast) Fourier transform, or using individual atomic positions. In this article we show that it is possible to compute up to 4.10 10 re f lections · atoms · s −1 using a single graphics card, and we evaluate how this speed depends on number of atoms and points in reciprocal space. An open-source software library (PyNX) allowing easy scattering computations (including grazing incidence conditions) in the Python language is described, with examples of scattering from non-ideal nanostructures.

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Strain and correlation of self-organizedGe1−xMnxnanocolumns embedded in Ge (001)

Cited by 17 publications

References 49 publications

Mn-doped Ge and Si: A Review of the Experimental Status

Mn-doped Ge and Si: A Review of the Experimental Status

Evaluation of acrylamide-removing properties of two Lactobacillus strains under simulated gastrointestinal conditions using a dynamic system

Fast computation of scattering maps of nanostructures using graphical processing units

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