Modelling the increase in anisotropic reaction rates in metal nanoparticle oxidation using carbon nanotubes as thermal conduits

Nanostructured energetic materials are attracting attention for their faster reaction rates compared to materials with micron-scale particles. We numerically solve the coupled energy balances for a carbon nanotube with an annular coating of reactive metal, such that coupling to thermal transport in the nanotube accelerates reaction in the annulus. For the case of Zr metal, the nanotube increases the velocity of the reaction front in the direction of the nanotube length from 530 to 5100?mm?s(-1). This offers a proof-of-concept for one-dimensional anisotropic energetic materials, which could find new applications in inorganic synthesis and novel propellants. Nanotube conductivity as well as the relative sizes of the Zr annulus and the nanotube limit enhancement of the reaction velocity to a maximum of a factor of ～10. Interestingly, the interfacial heat conductance is not the most significant factor affecting the coupling, due to the large temperature differences (more than 1000?K) between the nanotube and the annulus at the reaction front and directional heat conduction in the nanotube. Although the enhancement is insufficient to change a Zr/nanotube composite from a deflagrating to a detonating material, using faster-reacting materials may enable nanotubes to effect this transition.     

Effect of suspension characteristics on the performance of thermal barrier coatings deposited by suspension plasma spray

This paper investigates the influence of suspension characteristics on microstructure and performance of suspensions plasma sprayed (SPS) thermal barrier coatings (TBCs). Five suspensions were produced using various suspension characteristics, namely, type of solvent and solid load content, and the resultant suspensions were utilized to deposit five different TBCs under identical processing conditions. The produced TBCs were evaluated for their performance i.e. thermal conductivity, thermal cyclic fatigue (TCF) and thermal shock (TS) lifetime. This experimental study revealed that the differences in the microstructure of SPS TBCs produced using varied suspensions resulted in a wide-ranging overall TBC performance. All TBCs exhibited thermal conductivity lower than 1 W/(m. K) except water-ethanol mixed suspension produced TBC. The TS lifetime was also affected to a large extent where 10 wt % solid loaded ethanol and 25 wt % solid loaded water suspensions produced TBCs exhibited the highest and the lowest lifetime, respectively. On the contrary, TCF lifetime was not as significantly affected as thermal conductivity and TS lifetime, and all ethanol suspensions showed marginally better TCF lifetime than water and ethanol-water mixed suspensions deposited TBCs.     

Quantitative EEG and effect of hypothermia on brain recovery after cardiac arrest

In this paper, we provide a quantitative electroencephalogram (EEG) analysis to study the effect of hypothermia on the neurological recovery of brain after cardiac arrest. We hypothesize that the brain injury results in a reduction in information of the brain rhythm. To measure the information content of the EEG a new measure called information quantity (IQ), which is the Shannon entropy of decorrelated EEG signals, is developed. For decorrelating EEG signals, we use the discrete wavelet transform (DWT) which is known to have good decorrelating properties and to show a good match to the standard clinical bands in EEG. In measuring the amount of information, IQ shows better tracking capability for dynamic amplitude change and frequency component change than conventional entropy-based measures. Experiments are carried out in rodents (n = 30) to monitor the neurological recovery after cardiac arrest. In addition, EEG signal recovery under normothermic (37 degrees C) and hypothermic (33 degrees C) resuscitation following 5, 7, and 9 min of cardiac arrest is recorded and analyzed. Experimental results show that the IQ is greater for hypothermic than normothermic rats, with an IQ difference of more than 0.20 (0.20 +/- 0.11 is 95% condidence interval). The results quantitatively support the hypothesis that hypothermia accelerates the electrical recovery from brain injury after cardiac arrest.     

Aggregate input-output models of neuronal populations

An extraordinary amount of electrophysiological data has been collected from various brain nuclei to help us understand how neural activity in one region influences another region. In this paper, we exploit the point process modeling (PPM) framework and describe a method for constructing aggregate input-output (IO) stochastic models that predict spiking activity of a population of neurons in the "output" region as a function of the spiking activity of a population of neurons in the "input" region. We first build PPMs of each output neuron as a function of all input neurons, and then cluster the output neurons using the model parameters. Output neurons that lie within the same cluster have the same functional dependence on the input neurons. We first applied our method to simulated data, and successfully uncovered the predetermined relationship between the two regions. We then applied our method to experimental data to understand the input-output relationship between motor cortical neurons and 1) somatosensory and 2) premotor cortical neurons during a behavioral task. Our aggregate IO models highlighted interesting physiological dependences including relative effects of inhibition/excitation from input neurons and extrinsic factors on output neurons.     

Adaptive Filterng of Evoked Potentials

We present an adaptive filtering (AF) technique for rapid processing of evoked potentials (EP). The AF algorithm minimizes the mean-square error (MSE) between successive ensembles. We demonstrate theoretically that the filter output converges to the least square estimate of the underlying signal. Computer simulations with known signal and added noise show that AF produces lower MSE than ensemble averaging. We also compare results of AF to those obtained by ensemble averaging for some EP recorded from animals and humans. For very noisy EP recordings, we propose techniques that combine AF and ensemble averaging. The AF technique shows promise for requiring fewer ensembles than averaging to attain adequate signal quality.     

Defect mechanisms in BaTiO3‐BiMO3 ceramics

Often, addition of BiMO₃ to BaTiO₃ (BT) leads to improvement in resistivity with a simultaneous shift to n‐type conduction from p‐type for BT. In considering one specific BiMO₃ composition, that is, Bi(Zn_1/2Ti_1/2)O₃ (BZT), several prospective candidates for the origin of this n‐type behavior in BT‐BZT were studied—loss of volatile cations, oxygen vacancies, bismuth present in multiple valence states and precipitation of secondary phases. Combined x‐ray and neutron diffraction, prompt gamma neutron activation analysis and electron energy loss spectroscopy suggested much higher oxygen vacancy concentration in BT‐BZT ceramics (>4%) as compared to BT alone. X‐ray photoelectron spectroscopy and x‐ray absorption spectroscopy did not suggest the presence of bismuth in multiple valence states. At the same time, using transmission electron microscopy, some minor secondary phases were observed, whose compositions were such that they could result in effective donor doping in BT‐BZT ceramics. Using experimentally determined thermodynamic parameters for BT and slopes of Kröger‐Vink plots, it has been suggested that an ionic compensation mechanism is prevalent in these ceramics instead of electronic compensation. These ionic defects have an effect of shifting the conductivity minimum in the Kröger‐Vink plots to higher oxygen partial pressure values in BT‐BZT ceramics as compared to BT, resulting in a significantly higher resistivity values in air atmosphere and n‐type behavior. This provides an important tool to tailor transport properties and defects in BT‐BiMO₃ ceramics, to make them better suited for dielectric or other applications.     

In-Plane Magnetic Field-Driven Creation and Annihilation of Magnetic Skyrmion Strings in Nanostructures

In bulk chiral crystals, 3D structures of magnetic skyrmions form topologically protected skyrmion strings (SkS) that have shown potential as magnonic nano-waveguides for information transfer. Although SkS stability is expected to be enhanced in nanostructures of skyrmion-hosting materials, experimental observation and detection of SkS in nanostructures under an applied in-plane magnetic field is difficult. Here, temperature-dependent magnetic field-driven creation and annihilation of SkS in B20 FeGe nanostructures (nanowires and nanoplates) under in-plane magnetic field (H_||) are shown and the mechanisms behind these transformations are explained. Unusual asymmetric and hysteretic magnetoresistance (MR) features are observed but previously unexplained during magnetic phase transitions within the SkS stability regime when H_|| is along the nanostructure's long edge, which increase the sensitivity of MR detection. Lorentz transmission electron microscopy of the SkS and other magnetic textures under H_|| in corroboration with the analysis of the anisotropic MR responses elucidates the field-driven creation and annihilation processes of SkS responsible for such hysteretic MR features and reveals an unexplored stability regime in nanostructures.     

Electrical Detection and Magnetic Imaging of Stabilized Magnetic Skyrmions in Fe1−xCoxGe (x < 0.1) Microplates

Magnetic skyrmions are topologically protected spin textures that are being investigated for their potential use in next generation magnetic storage devices. Here, magnetic skyrmions and other magnetic phases in Fe_1?xCo_xGe (x < 0.1) microplates (MPLs) newly synthesized via chemical vapor deposition are studied using both magnetic imaging and transport measurements. Lorentz transmission electron microscopy reveals a stabilized magnetic skyrmion phase near room temperature (≈280 K) and a quenched metastable skyrmion lattice via field cooling. Magnetoresistance (MR) measurements in three different configurations reveal a unique anomalous MR signal at temperatures below 200 K and two distinct field dependent magnetic transitions. The topological Hall effect (THE), known as the electronic signature of magnetic skyrmion phase, is detected for the first time in a Fe_1?xCo_xGe nanostructure, with a large and positive peak THE resistivity of ≈32 nΩ cm at 260 K. This large magnitude is attributed to both nanostructuring and decreased carrier concentrations due to Co alloying of the Fe_1?xCo_xGe MPL. A consistent magnetic phase diagram summarized from both the magnetic imaging and transport measurements shows that the magnetic skyrmions are stabilized in Fe_1?xCo_xGe MPLs compared to bulk materials. This study lays the foundation for future skyrmion‐based nanodevices in information storage technologies.     

Electrical fatigue failure in (Na1/2Bi1/2)TiO3–BaTiO3 relaxor ceramics

Many devices containing ferroelectric ceramics are subjected to different loading conditions and cycles, and lack of adequate long-term reliability studies is a major concern. Here, we explore a (Na_1/2Bi_1/2)TiO₃–BaTiO₃ solid solution and study electrical fatigue as a function of amplitude, temperature, frequency, and static offset voltage (dc bias). This is expected to act as a guide for other similar material systems. Empirical relationships to quantify the dependence of fatigue on these parameters are presented. With electric field amplitude (E_max), the number of cycles to fatigue failure (N_fail) varies as: E_max × = C, where a and C are constants whose values are different when the field amplitude is below and above the coercive field. With changes in temperature, N_fail exhibits an activated behavior and follows an Arrhenius relationship with an activation energy of 0.7 eV at an amplitude above the coercive field. In the absence of self-heating, a power law relationship is observed between N_fail and frequency of fatigue cycles at an amplitude above the coercive field. On applying a dc bias, N_fail increases by an order of magnitude, an observation that is attributed to domain switching effects. A majority of the above-mentioned effects have been explained in terms of the motion of domain walls under a given fatigue condition and their interaction with point defects.     

The Kernel Recursive Least Squares CMAC with Vector Eligibility

The cerebellar model articulation controller (CMAC) neural network is an associative memory that is biologically inspired by the cerebellum, which is found in the brains of animals. In recent works, the kernel recursive least squares CMAC (KRLS–CMAC) was proposed as a superior alternative to the standard CMAC as it converges faster and does not require tuning of a learning rate parameter. One improvement to the standard CMAC that has been discussed in the literature is eligibility, and vector eligibility. With vector eligibility the CMAC is able to control online motion control problems that it could not previously, stabilize the system much faster, and converge to a more intelligent solution. This paper integrates vector eligibility with the KRLS–CMAC and shows how the combination is advantageous through two simulated control experiments.