It may be essential for the further development of optoelectronic devices based on hybrid halide perovskites.We study the effect of a perpendicular magnetic field B on a multinode Weyl semimetal (mWSM) of arbitrary integer monopole charge n, with the two Weyl multinodes separated in k-space. Besides type-I mWSMs, there exist type-II mWSMs which are characterized by the tilted minimal dispersion for low-energy excitations; the Weyl points in type-II mWSMs are still protected crossings but appear at the contact of the electron and hole pockets, after the Lifshitz transition. We find that the presence of a perpendicular magnetic field quantizes the occupation pockets due to the presence of Fermi tubes. In this theory, the Hilbert space is spanned by a set of n chiral degenerate ground states, and a countably infinite number of particle-hole symmetric Landau levels. We calculate the Hall conductivity for the tilt-symmetric case of type-I mWSM using the Kubo formula, in the zero-frequency (DC) limit, and recover the well-known vacuum contribution. We compute the Fermi surface corrections and show that the expression generalizes from the formula for elementary (n = 1) type-I WSMs. We derive an expression for the type-II mWSM Hall conductivity, which is bounded by a Landau level cutoff introduced on physical grounds. Selleck EIDD-2801 Interestingly, we find that the anomalous vacuum Hall conductivity is vanishing in the type-II phase at all temperatures. The corresponding thermal Hall and Nernst conductivities are evaluated and characterized for both phases. The qualitative and quantitative observations presented here may serve in the characterization of generic mWSMs of both types.For many years, in electrochemical processes, carbon nanostructures with metal-supported have been employed as electrodes due to their high surface area, chemical stability, and excellent performance as catalyst support by allowing a better electronic transfer. Nevertheless, on the surface, metallic nanoparticles are susceptible to corrosion. Instead, by encapsulating individual nanoparticles, they are protected. Among the carbon nanostructures, the most common are graphene, carbon nanotubes (CNTs), and carbon nanospheres (CNSs). Unlike CNTs and CNSs, graphene is difficult to obtain in mass production limiting their applications. Regarding CNTs and CNSs, the second one present better catalytic activity. Nonetheless, the process of synthesis of CNSs with metal inside is commonly made by time-consuming autoclave processes, some involve more than 43 hours, and hence are expensive. Here, we suggest an advantageous synthesis of carbon nanospheres with iron-nickel alloy encapsulated inside, by using a one-step CVD process in less than 3 hours. This material has potential applications for environmental and energy processes. According to the authors, the uses of iron-nickel alloys as an electrocatalyst for the ammonia oxidation reaction has not been proved. Thus, we evaluate the composite as an electrocatalyst for the ammonia oxidation reaction, an electrochemical process that offers environmental remediation and hydrogen as a fuel. The electrochemical characterization shows that the use of a bimetallic electrode improves the catalytic activity. In this case, nickel is the active specie and iron is the metal added which reduces the reaction potential. Besides, the composite presents high specific capacitance, better than other materials proposed such as graphene decorated with FeNi alloys. This behavior can be related to the variation of the catalyst morphology (supported vs. encapsulated) by improving the catalyst dispersion and particle size stabilization.We handshake statistical mechanics with continuum mechanics to develop a methodology for consistent evaluation of the continuum scale properties of two-dimensional materials. The methodology is tested on pristine graphene. Our scope is kept limited to elastic modulus, E, which has been reported to vary between 0.912 TPa and 7 TPa, Poisson's ratio, ν, which has been reported to vary from being negative to a value as large as 0.46, and effective thickness, q, whose value varies between 0.75 Å and 3.41 Å. Such a large scatter arises due to inconsistent evaluation of these properties and making assumptions that may not be valid at atomistic scales. Our methodology combines three separate methods uniaxial tension, equibiaxial tension, and flexural out-of-plane free vibrations of simply supported sheets, which, when used in tandem in molecular dynamics, can provide consistent values of E, ν and q. The only assumption made in the present study is the validity of the continuum scale thin plate vibration equation to represent the free vibrations of a graphene sheet. Our results suggest that-(i) graphene is auxetic in nature, (ii) E decreases with increasing size and temperature, and (iii) the effective thickness q increases with increasing size and temperature. Further, a robustness study of the computed mechanical properties shows consistent results, with differences varying between 1.4% and 6%. To develop a method that can reduce and estimate uncertainty in quantitative MR parameter maps without the need for hand-tuning of any hyperparameters. We present an estimation method where uncertainties are reduced by incorporating information on spatial correlations between neighbouring voxels. The method is based on a Bayesian hierarchical non-linear regression model, where the parameters of interest are sampled, using Markov chain Monte Carlo (MCMC), from a high-dimensional posterior distribution with a spatial prior. The degree to which the prior affects the model is determined by an automatic hyperparameter search using an information criterion and is, therefore, free from manual user-dependent tuning. The samples obtained further provide a convenient means to obtain uncertainties in both voxels and regions. The developed method was evaluated on T estimations based on the variable flip angle method. The proposed method delivers noise-reduced T parameter maps with associated error estimates by combining MCMC sampling, the widely applicable information criterion, and total variation-based denoising. The proposed method results in an overall decrease in estimation error when compared to conventional voxel-wise maximum likelihood estimation. However, this comes with an increased bias in some regions, predominately at tissue interfaces, as well as an increase in computational time. This study provides a method that generates more precise estimates compared to the conventional method, without incorporating user subjectivity, and with the added benefit of uncertainty estimation.This study provides a method that generates more precise estimates compared to the conventional method, without incorporating user subjectivity, and with the added benefit of uncertainty estimation.