Loss of classicality in the alternating spin-½/spin-1 chain, in the presence of next-neighbor couplings and Dzyaloshinskii-Moriya interactions

We have considered and alternating spin-½/spin-1 chain with nearest-neighbor (J1), next-nearest neighbor (J2) antiferromagnetic Heisenberg interactions along with z-component of the Dzyaloshinskii-Moriya(DM) (Dz) interaction. The Hamiltonian has been studied using (a) Linear Spin-Wave Theory(LSWT) and (b) Density Matrix Renormalization Group (DMRG). The system had been reported earlier as a classical ferrimagnet only when nearest neighbor exchange interactions are present. Both the antiferromagnetic next-nearest neighbor interactions and DM interactions introduce strong quantum fluctuations and due to which all the signatures of ferrimagnetism vanishes. We find that the nonzero J2 introduces strong quantum fluctuations in each of the spin sites due to which the z-components of both spin-1 and spin-1/2 sites average out to be zero. The ground state becomes a singlet. The presence of J1 along with Dzintroduces a short range order but develops long range order along the XY plane. J1 along with J2induces competing phases with structure factor showing sharp and wide peaks, at two different angles reflecting the spin spiral structure locally as well as in the underlying lattice. Interestingly, we find that the Dz term removes the local spin spiral structure in z-direction, while developing a spiral order in the XY plane.

Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography

Chemical short-range order (CSRO) refers to atoms of specific elements self-organising within a disordered crystalline matrix. These particular atomic neighbourhoods can modify the mechanical and functional performances of materials 1-6. CSRO is typically characterized indirectly, using volume-averaged (e.g. X-ray/neutron scattering) 2,7,8 or through projection (i.e. two-dimensional) microscopy techniques 5,6,9,10 that fail to capture the complex, three-dimensional atomistic architectures. Quantitative assessment of CSRO and concrete structure-property relationships remain unachievable. Here, we present a machine-learning enhanced approach to break the inherent resolution limits of atom probe tomography to reveal three-dimensional analytical imaging of the size and morphology of multiple CSRO. We showcase our approach by addressing a long-standing question encountered in a body-centred-cubic Fe-18Al (at.%) solid solution alloy that sees anomalous property changes upon heat treatment 2. After validating our method against artificial data for ground truth, we unearth non-statistical B2-CSRO (FeAl) instead of the generally-expected D03-CSRO (Fe3Al) 11,12. We propose quantitative correlations among annealing temperature, CSRO, and the nano-hardness and electrical resistivity, supported by atomistic simulations. The proposed strategy can be generally employed to investigate short/medium/long-range ordering phenomena in a vast array of materials and help design future high-performance materials.

Х-ray Study and Computer Simulation of the Structure of Amorphous-Crystalline Titanite

The structure of amorphous-crystalline titanite obtained by mechanical activation was studied by X-ray diffraction and simulation methods. The short-range order characteristics were calculated using Finbak-Warren's method. It was found that the coordination numbers of metal atoms decreased as the result of titanite grinding. The atomic configurations of short-range order of ground titanite were constructed by translation of titanite unit cell. The theoretical X-ray patterns were calculated using Debye's method and were compared with the experimental curves. The structure of ground titanite in the mill with centrifugal factor 40 g was described satisfactorily by the model of mechanical mixture of clusters containing 2016 atoms, disordered during the molecular dynamics with clusters containing 12096 atoms. The increase of grinding intensity led to the sharp decrease of sizes of small cluster.