We have investigated the threshold current density required for depinning a domain wall from constrictions in NiFe nanowires, which give rise to pinning potentials of fixed amplitude but variable profile. We observed it to vary linearly with the angle of the triangular constriction. These results are reproduced using micromagnetic simulations including the adiabatic and nonadiabatic spin-torque terms. By curve-fitting the calculated variations to the experimental results, we obtain the nonadiabaticity parameter $\beta =0.04(\pm 0.005)$ and current spin polarization $P=0.51(\pm 0.02)$.

We have studied field- and current-driven domain-wall (DW) creep motion in a perpendicularly magnetized Co/Pt multilayer wire by real-time Kerr microscopy. The application of a dc current of density of $\lesssim${}107\,\,A/cm2 assisted only the DW creeping under field in the same direction as the electron flow, a signature of spin-transfer torque effects. We develop a model dealing with both bidirectional spin-transfer effects and Joule heating, with the same dynamical exponent $\mu${}=1/4 for both field- and current-driven creep, and use it to quantify the spin-transfer efficiency as 3.6\ifmmode\pm\else\textpm\fi{}0.6\,\,Oe\,cm2/MA in our wires, confirming the significant nonadiabatic contribution to the spin torque.

One of the most powerful laws in physics is the second law of thermodynamics, which states that the entropy of any system remains constant or increases over time. In fact, the second law is applicable to the evolution of the entire universe and Clausius stated, “The entropy of the universe tends to a maximum.” Here, we examine the time evolution of information systems, defined as physical systems containing information states within Shannon’s information theory framework. Our observations allow the introduction of the second law of information dynamics (infodynamics). Using two different information systems, digital data storage and a biological RNA genome, we demonstrate that the second law of infodynamics requires the information entropy to remain constant or to decrease over time. This is exactly the opposite to the evolution of the physical entropy, as dictated by the second law of thermodynamics. The surprising result obtained here has massive implications for future developments in genomic research, evolutionary biology, computing, big data, physics, and cosmology.

We present measurements of domain wall resistivity, pinned by nanoconstrictions in single layer ferromagnetic wires of ${\mathrm{Ni}}_{80}{\mathrm{Fe}}_{20}$ and Ni. Unpinning domain walls from the constriction by current-induced switching allows for an unambiguous measurement of their resistivity changes, namely, 1.7% in ${\mathrm{Ni}}_{80}{\mathrm{Fe}}_{20}$ and 1.82% in Ni and both positive, which supports the theory of spin-dependent impurity scattering. By deriving an empirical relation for the various constriction widths, the large percentage changes of resistivity in ballistic nanocontacts are reproduced, showing a correlation between domain wall magnetoresistance and ballistic magnetoresistance.

Ferroelectricity and piezoelectricity in CsBiNb ₂ O ₇ are demonstrated for the first time.

This work discusses the design and testing of a new computational spintronics research software. Boris is a comprehensive multi-physics open-source software, combining micromagnetics modeling capabilities with drift-diffusion spin transport modeling and a heat flow solver in multi-material structures. A multi-mesh paradigm is employed, allowing modeling of complex multi-layered structures with independent discretization and arbitrary relative positioning between different computational meshes. Implemented micromagnetics models include not only ferromagnetic materials modeling, but also two-sublattice models, allowing simulations of antiferromagnetic and ferrimagnetic materials, fully integrated into the multi-mesh and multi-material design approach. High computational performance is an important design consideration in Boris, and all computational routines can be executed on graphical processing units (GPUs), in addition to central processing units. In particular, a modified 3D convolution algorithm is used to compute the demagnetizing field on the GPU, termed pipelined convolution, and benchmark comparisons with existing GPU-accelerated software Mumax3 have shown performance improvements up to twice faster.