arXiv subjects

S. Hu

Publications and source records attributed to S. Hu.

40 records · Page 3Linked to original sources

arXiv2015

Strain-induced magnetic phase transition in SrCoO$_{3-δ}$ thin films

It has been well established that both in bulk at ambient pressure and for films under modest strains, cubic SrCoO$_{3-δ}$ ($δ< 0.2$) is a ferromagnetic metal. Recent theoretical work, however, indicates that a magnetic phase transition to an antiferromagnetic structure could occur under large strain accompanied by a metal-insulator transition. We have observed a strain-induced ferromagnetic to antiferromagnetic phase transition in SrCoO$_{3-δ}$ films grown on DyScO$_3$ substrates, which provide a large tensile epitaxial strain, as compared to ferromagnetic films under lower tensile strain on SrTiO$_3$ substrates. Magnetometry results demonstrate the existence of antiferromagnetic spin correlations and neutron diffraction experiments provide a direct evidence for a G-type antiferromagnetic structure with Neél temperatures between $T_N \sim 135\,\pm\,10\,K$ and $\sim 325\,\pm\,10\,K$ depending on the oxygen content of the samples. Therefore, our data experimentally confirm the predicted strain-induced magnetic phase transition to an antiferromagnetic state for SrCoO$_{3-δ}$ thin films under large epitaxial strain.

cond-mat.mtrl-sci↗

arXiv2014

Proton transport through one atom thick crystals

Graphene is impermeable to all gases and liquids, and even such a small atom as hydrogen is not expected to penetrate through graphene's dense electronic cloud within billions of years. Here we show that monolayers of graphene and hexagonal boron nitride (hBN) are unexpectedly permeable to thermal protons, hydrogen ions under ambient conditions. As a reference, no proton transport could be detected for a monolayer of molybdenum disulfide, bilayer graphene or multilayer hBN. At room temperature, monolayer hBN exhibits the highest proton conductivity with a low activation energy of about 0.3 eV but graphene becomes a better conductor at elevated temperatures such that its resistivity to proton flow is estimated to fall below 10^-3 Ohm per cm2 above 250 C. The proton barriers can be further reduced by decorating monolayers with catalytic nanoparticles. These atomically thin proton conductors could be of interest for many hydrogen-based technologies.

cond-mat.mtrl-sci↗

arXiv2011

Generalizations of a Nonlinear Fluid Model for Void Formation in Dusty Plasmas

New developments in the theory and numerical simulation of a recently proposed one-dimensional nonlinear time-dependent fluid model [K. Avinash, A. Bhattacharjee, and S. Hu, Phys. Rev. Lett. 90, 075001 (2003)] for void formation in dusty plasmas are presented. The model describes an initial instability caused by the ion drag, rapid nonlinear growth, and a nonlinear saturation mechanism that realizes a quasi-steady state containing a void. The earlier one-dimensional model has been extended to two and three dimensions (the latter, assuming spherical symmetry), using a more complete set of dynamical equations than was used in the earlier one-dimensional formulation. The present set of equations includes an ion continuity equation and a nonlinear ion drag operator. Qualitative features of void formation are shown to be robust with respect to different functional forms of the ion drag operator.

physics.comp-ph↗

arXiv2004

Stages of Relaxation of Patterns and the Role of Stochasticity on the Final Stage

The disorder function formalism [Gunaratne et.al., Phys. Rev. E, {\bf 57}, 5146 (1998)]^M is used to show that pattern relaxation in an experiment on a vibrated layer of brass beads^M occurs in three distinct stages. During stage I, all lengthscales associated with ^M moments of the disorder grow at a single universal rate, given by $L(t) \sim t^{0.5}$. In stage II, pattern evolution is non-universal and includes a range of growth indices. Relaxation in the final stage is characterized by a single, non-universal index. We use analysis of patterns from the Swift-Hohenberg equation to argue that mechanisms that underlie the observed pattern evolution are linear spatio-temporal dynamics (stage I), non-linear saturation (stage II), and stochasticity (stage III)

nlin.PS↗