X-ray Absorption Near Edge Structure of FePt nanoclusters

X-ray Absorption Near Edge Structure [XANES] of FePt nanoclusters has been studied using a full multiple scattering, self-consistent field [SCF], real-space Green`s function approach realized via the powerful ab initio FEFF8 code. One purpose of our study is to determine the sensitivity of Pt L3 edge with respect to the size and shape of the FePt nanoclusters. We also give the results of the calculations with respect to the Fe L3 edge. Calculations are made with and without core-hole for two main reasons, to check and cross-check the FEFF code and also since in some cases it is known such as Pt clusters that better results are obtained without the core-hole. This is mainly because the screening electron will occupy empty d or f states and correspondingly reduce the white line intensity.Comment: TeX version 3.14159, LaTex2e, 6 pages with 6 figure

Stick and slip states in the probe-sample force interaction and informative nanomechanical measurements using AFM

The work was supported by FTP № 14.604.21.0200 (RFMEFI60417X0200)

Inelastic Scattering from Core-electrons: a Multiple Scattering Approach

The real-space multiple-scattering (RSMS) approach is applied to model non-resonant inelastic scattering from deep core electron levels over a broad energy spectrum. This approach is applicable to aperiodic or periodic systems alike and incorporates ab initio, self-consistent electronic structure and final state effects. The approach generalizes to finite momentum transfer a method used extensively to model x-ray absorption spectra (XAS), and includes both near edge spectra and extended fine structure. The calculations can be used to analyze experimental results of inelastic scattering from core-electrons using either x-ray photons (NRIXS) or electrons (EELS). In the low momentum transfer region (the dipole limit), these inelastic loss spectra are proportional to those from XAS. Thus their analysis can provide similar information about the electronic and structural properties of a system. Results for finite momentum transfer yield additional information concerning monopole, quadrupole, and higher couplings. Our results are compared both with experiment and with other theoretical calculations.Comment: 11 pages, 8 figures. Submitted to Phys. Rev.

Kinetics of rapid growth and melting of Al 50 Ni 50 alloying crystals: phase field theory versus atomistic simulations revisited *

A revised study of the growth and melting of crystals in congruently melting Al 50 Ni 50 alloy is carried out by molecular dynamics (MDs) and phase field (PF) methods. An embedded atom method (EAM) potential of Purja Pun and Mishin (2009 Phil. Mag. 89 3245) is used to estimate the material’s properties (density, enthalpy, and self-diffusion) of the B2 crystalline and liquid phases of the alloy. Using the same EAM potential, the melting temperature, density, and diffusion coefficient become well comparable with experimental data in contrast with previous works where other potentials were used. In the new revision of MD data, the kinetics of melting and solidification are quantitatively evaluated by the ‘crystal-liquid interface velocity–undercooling’ relationship exhibiting the well-known bell-shaped kinetic curve. The traveling wave solution of the kinetic PF model as well as the hodograph equation of the solid-liquid interface quantitatively describe the ‘velocity–undercooling’ relationship obtained in the MD simulation in the whole range of investigated temperatures for melting and growth of Al 50 Ni 50 crystals

Can we accurately calculate viscosity in multicomponent metallic melts?

Calculating viscosity in multicompoinent metallic melts is a challenging task for both classical and \textit{ab~initio} molecular dynamics simulations methods. The former may not to provide enough accuracy and the latter is too resources demanding. Machine learning potentials provide optimal balance between accuracy and computational efficiency and so seem very promising to solve this problem. Here we address simulating kinematic viscosity in ternary Al-Cu-Ni melts with using deep neural network potentials (DP) as implemented in the DeePMD-kit. We calculate both concentration and temperature dependencies of kinematic viscosity in Al-Cu-Ni and conclude that the developed potential allows one to simulate viscosity with high accuracy; the deviation from experimental data does not exceed 9\% and is close to the uncertainty interval of experimental data. More importantly, our simulations reproduce minimum on concentration dependency of the viscosity at the eutectic point. Thus, we conclude that DP-based MD simulations is highly promising way to calculate viscosity in multicomponent metallic melts.Comment: 11 pages, 7 figure

Application of atomic force microscopy for investigation of Na⁺,K⁺-ATPase signal-transducing function

The Young’s modulus of 10–12-day-old chick embryos’ sensory neurons cultivated in dissociated cell culture was measured using a PeakForce Quantitative Nanomechanical Mapping atomic force microscopy. The native cells were tested in control experiments and after application of ouabain. At low “endogenous” concentration of 10−10 M, ouabain tended to increase the rigidity of sensory neurons. We hypothesize that this trend resulted from activation of Na+,K+-ATPase signal-transducing function