Abstract: Gielis transformations, with their origin in botany, are used to define square waves and trigonometric functions of higher order. They are rewritten in terms of Chebyshev polynomials. The origin of both, a uniform descriptor and the origin of orthogonal polynomials, can be traced back to a letter of Guido Grandi to Leibniz in 1713 on the mathematical description of the shape of flowers. In this way geometrical description and analytical tools are seamlessly combined.

Abstract: Non-charge-based logic devices are promising candidates for future logic circuits. Interest in studying and developing these devices has grown dramatically in the past decade as they possess key advantages over conventional CMOS technology. Due to their novel designs, a large number of micromagnetic simulations are required to fully characterize the behavior of these devices. The number and complexity of these simulations place large computational requirements on device development. We use state-of-the-art machine learning techniques to expedite identification of their behavior. Several intelligent sampling strategies are combined with machine learning multi-class classification models. These techniques are applied to a recently developed exchange-driven magnetic logic scheme that utilizes direct exchange coupling as the main driver.

Abstract: Environmental parameters such as temperature, relative humidity, visible light, UV radiation and pollution influence the deterioration rate of heritage items. To judge on the environmental appropriateness for heritage conservation, it is therefore important to monitor the environment. Often, an incomplete set of environmental parameters is measured, or sporadic or time-averaged measurements are performed. As a result, a wide range of undesirable situations and hazards remain unnoticed. This might lead to an underestimation of environmental dangers (i.e., inaccurate judgement) or to inappropriate mitigation measures (i.e., inaccurate decision making). We present an innovative and user-friendly monitoring device that simultaneously and continuously measures (1) environmental parameters and (2) material behavior. An extended combination of off-the-shelf sensors for temperature, relative humidity, air speed, CO2, NO2, O-3 and particulate matter are connected to a multipurpose datalogger. In-house developed sensors for the shrinkage and expansion behavior of wood, as well as sensors for metal corrosion rates are connected to the same datalogger. Such extended monitoring shows the identification of a wider range of undesirable situations, and it facilitates the search for correlations between such situations and the sources that cause them, i.e., the hazards.

Abstract: We model transport through two-dimensional topological insulator (TI) nanoribbons. To model the quantum transport, we employ the non-equilibrium Green's function approach. With the presented approach, we study the effect of lattice imperfections on the carrier transport. We observe that the topologically protected edge states of TIs are robust against a high percentage (2%) of vacancy defects. We also investigate tunneling of the edge states in two decoupled TI nanoribbons.

Abstract: Due to its strong bonds graphene can stretch up to 25% of its original size without breaking. Furthermore, mechanical deformations lead to the generation of pseudo-magnetic fields (PMF) that can exceed 300 T. The generated PMF has opposite direction for electrons originating from different valleys. We show that valley-polarized currents can be generated by local straining of multi-terminal graphene devices. The pseudo-magnetic field created by a Gaussian-like deformation allows electrons from only one valley to transmit and a current of electrons from a single valley is generated at the opposite side of the locally strained region. Furthermore, applying a pressure difference between the two sides of a graphene membrane causes it to bend/bulge resulting in a resistance change. We find that the resistance changes linearly with pressure for bubbles of small radius while the response becomes non-linear for bubbles that stretch almost to the edges of the sample. This is explained as due to the strong interference of propagating electronic modes inside the bubble. Our calculations show that high gauge factors can be obtained in this way which makes graphene a good candidate for pressure sensing.

Abstract: For the first time, we demonstrate, using an atomistic description of a 30nm diameter spin-transfer-torque magnetic random access memories (STT-MRAM), that the difference in mechanical properties of its sub-nanometer layers induces a high compressive strain in the magnetic tunnel junction (MTJ) and leads to a detrimental magnetostrictive effect. Our model explains the issues met in engineering the electrical and magnetic performances in scaled STT-MRAM devices. The resulting high compressive strain built in the stack, particularly in the MgO tunnel barrier (t-MgO), and its associated non-uniform atomic displacements, impacts on the quality of the MTJ interface and leads to strain relieve mechanisms such as surface roughness and adhesion issues. We illustrate that the strain gradient induced by the different materials and their thicknesses in the stacks has a negative impact on the tunnel magneto-resistance (TMR), on the magnetic nucleation process and on the STT-MRAM performance.

Abstract: The scalability potential of low resistivity ternary metallic alloys (MAX) as an interconnect medium has been benchmarked against copper through first-principle simulations. We report that some carbon and nitrogen MAX phases have the potential to display a reduced sensitivity of their intrinsic resistivity to scaling, while showing improved electromigration properties.