Unusual superparamagnetic behavior of Co3O4 nanoparticles

We report detailed studies on magnetic properties of Co3O4 nanoparticles of average size 12.5 nm. Temperature and field dependence of magnetization, wait time dependence of magnetic relaxation (aging), memory effects and temperature dependence of specific heat have been investigated to understand the magnetic behavior of these particles. We find that the particles show some features characteristic of nanoparticle magnetism such as bifurcation of field cooled (FC) and zero field cooled (ZFC) susceptibilities and a slow relaxation of magnetization. However, strangely, the temperature at which ZFC magnetization peaks coincides with the bifurcation temperature and does not shift on application of magnetic fields up to 1 kOe, unlike most other nanoparticle systems. Aging effects in these particles are negligible in both FC and ZFC protocol and memory effects are present only in FC protocol. Our results show that Co3O4 nanoparticles constitute a unique system where superparamagnetic blocking starts above the N\'eel temperature, in the paramagnetic state.Comment: 5 pages, 4 figure

Memory, Aging and Spin Glass Nature: A Study of NiO Nanoparticles

We report studies on magnetization dynamics in NiO nanoparticles of average size 5 nm. Temperature and time dependence of dc magnetization, wait time dependence of magnetic relaxation (aging) and memory phenomena in the dc magnetization are studied with various temperature and field protocols. We observe that the system shows memory and aging in field cooled and zero field cooled magnetization measurements. These experiments show that the magnetic behavior of NiO nanoparticles is similar to spin glasses. We argue that the spin glass behavior originates from the freezing of spins at the surface of the individual particles.Comment: 5 pages, 4 figures typos adde

An Efficient Deep Learning Technique for the Navier-Stokes Equations: Application to Unsteady Wake Flow Dynamics

We present an efficient deep learning technique for the model reduction of the Navier-Stokes equations for unsteady flow problems. The proposed technique relies on the Convolutional Neural Network (CNN) and the stochastic gradient descent method. Of particular interest is to predict the unsteady fluid forces for different bluff body shapes at low Reynolds number. The discrete convolution process with a nonlinear rectification is employed to approximate the mapping between the bluff-body shape and the fluid forces. The deep neural network is fed by the Euclidean distance function as the input and the target data generated by the full-order Navier-Stokes computations for primitive bluff body shapes. The convolutional networks are iteratively trained using the stochastic gradient descent method with the momentum term to predict the fluid force coefficients of different geometries and the results are compared with the full-order computations. We attempt to provide a physical analogy of the stochastic gradient method with the momentum term with the simplified form of the incompressible Navier-Stokes momentum equation. We also construct a direct relationship between the CNN-based deep learning and the Mori-Zwanzig formalism for the model reduction of a fluid dynamical system. A systematic convergence and sensitivity study is performed to identify the effective dimensions of the deep-learned CNN process such as the convolution kernel size, the number of kernels and the convolution layers. Within the error threshold, the prediction based on our deep convolutional network has a speed-up nearly four orders of magnitude compared to the full-order results and consumes an insignificant fraction of computational resources. The proposed CNN-based approximation procedure has a profound impact on the parametric design of bluff bodies and the feedback control of separated flows.Comment: 49 pages, 12 figure

Paramagnetic to Superparamagnetic Transition in Ni(OH)_2 Nanoparticles

We report the temperature and field dependence of dc magnetization on sol-gel prepared nanoparticles of Ni(OH)_2. At higher temperature the system is found to behave as a paramagnet while we find evidence for superparamagnetic blocking at low temperature. The system shows a paramagnet-superparamagnet transition and we discuss the underlying mechanism.Comment: 4 pages, 7 figures, a floating reference remove

Magnetic Susceptibility of NiO Nanoparticles

Nickel oxide nanoparticles of different sizes are prepared and characterized by x-ray diffraction and transmission electron microscopy. A.C. susceptibility measurements as a function of temperature are carried out for various particle sizes and frequencies. We find that the behavior of the system is spin glass like.Comment: 16 pages, 5 figure

Further Evidences for Spin Glass like behavior in NiO nanoparticles

Nickel oxide nanoparticles are prepared by a sol gel method and characterized by x-ray diffraction and transmission electron microscope. Here we present measurements on temperature and field dependence of magnetization and time dependence of thermoremanent magnetization. Our conclusion based on these measurements is that the system shows spin glass like behavior.Comment: 5 pages, 3 figure

Evidence for topological surface states in metallic single crystals of Bi2Te3

Bi2Te3 is a member of a new class of materials known as topological insulators which are supposed to be insulating in the bulk and conducting on the surface. However experimental verification of the surface states has been difficult in electrical transport measurements due to a conducting bulk. We report low temperature magnetotransport measurements on single crystal samples of Bi2Te3. We observe metallic character in our samples and large and linear magnetoresistance from 1.5 K to 290 K with prominent Shubnikov-de Haas (SdH) oscillations whose traces persist upto 20 K. Even though our samples are metallic we are able to obtain a Berry phase close to the value of {\pi} expected for Dirac fermions of the topological surface states. This indicates that we might have obtained evidence for the topological surface states in metallic single crystals of Bi2Te3. Other physical quantities obtained from the analysis of the SdH oscillations are also in close agreement with those reported for the topological surface states. The linear magnetoresistance observed in our sample, which is considered as a signature of the Dirac fermions of the surface states, lends further credence to the existence of topological surface states

Anomalous magnetic behavior of CuO nanoparticles

We report studies on temperature, field and time dependence of magnetization on cupric oxide nanoparticles of sizes 9 nm, 13 nm and 16 nm. The nanoparticles show unusual features in comparison to other antiferromagnetic nanoparticle systems. The field cooled (FC) and zero field cooled (ZFC) magnetization curves bifurcate well above the N\'eel temperature and the usual peak in the ZFC magnetization curve is absent. The system does not show any memory effects which is in sharp contrast to the usual behavior shown by other antiferromagnetic nanoparticles. It turns out that the non-equilibrium behavior of CuO nanoparticles is very strange and is neither superparamagnetic nor spin glass-like.Comment: 8 pages, 5 figure

Spin glass behavior of gelatin coated NiO nanoparticles

We report magnetic studies on gelatin coated NiO nanoparticles of average size 7 nm. Temperature and time dependence of dc magnetization, wait time dependence of magnetic relaxation (aging), memory effects in the dc magnetization and frequency dependence of ac susceptibility have been investigated. We observe that the magnetic behavior of coated NiO nanoparticles differs substantially from that of bare nanoparticles. The magnetic moment of the particles is highly enhanced and the ZFC magnetization data displays a sharp peak (Tp1 = 15 K) at a low temperature in addition to a usual high temperature peak (Tp2 =170 K). We observe that this system exhibits various features characteristic of spin glass like behavior and Tp2 corresponds to the average freezing temperature. We argue that this behavior is due to surface spin freezing within a particle. The nature of the low temperature peak is, however, ambiguous as below Tp1 some features observed are characteristic of superparamagnetic blocking while some other features correspond to spin glass like behavior.Comment: 8 pages, 10 figure

Unusual non-equilibrium behavior of cupric oxide nanoparticles

We report studies on temperature, field and time dependence of magnetization on cupric oxide nanoparticles of sizes 9 nm, 13 nm and 16 nm. The nanoparticles show unusual features in comparison to other antiferromagnetic nanoparticle systems. The field cooled (FC) and zero field cooled (ZFC) magnetization curves bifurcate well above the Neel temperature and the usual peak in the ZFC magnetization curve is absent. The system does not show any memory effects which is in sharp contrast to the usual behavior shown by other antiferromagnetic nanoparticles. It turns out that the nature of CuO nanoparticles is very strange and is neither superparamagnetic nor spin glass-like .Comment: 5 pages,4 figure