Recent experiments demonstrating large spin-transfer torques in topological-insulator (TI)-ferromagnetic-metal (FM) bilayers have generated a great deal of excitement due to their potential applications in spintronics. The source of the observed spin-transfer torque, however, remains unclear. This is because the large charge transfer from the FM to the TI layer would prevent the Dirac cone at the interface from being anywhere near the Fermi level to contribute to the observed spin-transfer torque.

Eukaryotic cells sense molecular gradients by measuring spatial concentration variation through the difference in the number of occupied receptors to which molecules can bind. They also secrete enzymes that degrade these molecules, and it is presently not well understood how this affects the local gradient perceived by cells. Numerical and analytical results show that these enzymes can substantially increase the signal-to-noise ratio of the receptor difference and allow cells to respond to a much broader range of molecular concentrations and gradients than they would without these enzymes.

Models of cell function that assign a variable to each gene frequently lead to systems of equations with many parameters whose behavior is obscure. Geometric models reduce dynamics to intuitive pictorial elements that provide compact representations for sparse in vivo data and transparent descriptions of developmental transitions. To illustrate, a geometric model fit to vulval development in Caenorhabditis elegans, implies a phase diagram where cell-fate choices are displayed in a plane defined by EGF and Notch signaling levels.

After decades of progress and effort, obtaining a phase diagram for a strongly correlated topological system still remains a challenge. Although in principle one could turn to Wilson loops and long-range entanglement, evaluating these nonlocal observables at many points in phase space can be prohibitively costly. With growing excitement over topological quantum computation comes the need for an efficient approach for obtaining topological phase diagrams. Here we turn to machine learning using quantum loop topography (QLT), a notion we have recently introduced.

We investigated the influence of metal coating on the optical characteristics of Si nanopillar (NP) arrays with and without thin metal layers coated on the sample surface. The reflection dips of the metal-coated arrays were much broader and more pronounced than those of the bare arrays. The coated metal layers consisted of two parts—the metal disks on the Si NP top and the holey metal backreflectors on the Si substrate.

Finite element simulations are carried out to follow the evolution of residual stresses in Ti-7Al (α-hcp) alloy, as developed under an applied stress gradient. A model built upon phenomenological mesoscopic field dislocation mechanics is employed to simulate the deformation behavior. Model predictions are validated with results generated from high energy X-ray diffraction experiments using synchrotron radiation. These experiments provide for important simulation input, viz. grain positions and orientations, and strain rate sensitivities of the prismatic and basal slip systems of Ti-7Al.

We present an indentation-scope that interfaces with confocal microscopy, enabling direct observation of the three-dimensional (3D) microstructural response of coatings on substrates. Using this method, we compared microns-Thick polymer coatings on glass with and without silica nanoparticle filler. Bulk force data confirmed the >30% modulus difference, while microstructural data further revealed slip at the glass-coating interface. Filled coatings slipped more and about two times faster, as reflected in 3D displacement and von Mises strain fields.

Prominent systems like the high-Tc cuprates and heavy fermions display intriguing features going beyond the quasiparticle description. The Sachdev-Ye-Kitaev (SYK) model describes a (0+1)D quantum cluster with random all-to-all four-fermion interactions among N fermion modes which becomes exactly solvable as N→∞, exhibiting a zero-dimensional non-Fermi-liquid with emergent conformal symmetry and complete absence of quasiparticles. Here we study a lattice of complex-fermion SYK dots with random intersite quadratic hopping.

We propose a strategy to achieve an unconventional superconductor in a heterostructure: use a quantum paramagnet (QPM) as a substrate for heterostructure growth of metallic films to design exotic superconductors. The proposed setup allows us to "customize" electron-electron interaction imprinted on the metallic layer. The QPM material of our choice is quantum spin ice. Assuming the metallic layer forms a single isotropic Fermi pocket, we predict its coupling to spin fluctuations in quantum spin ice will drive topological odd-parity pairing.