Magnetic domain walls : Types, processes and applications

Domain walls (DWs) in magnetic nanowires are promising candidates for a variety of applications including Boolean/unconventional logic, memories, in-memory computing as well as magnetic sensors and biomagnetic implementations. They show rich physical behaviour and are controllable using a number of methods including magnetic fields, charge and spin currents and spin-orbit torques. In this review, we detail types of domain walls in ferromagnetic nanowires and describe processes of manipulating their state. We look at the state of the art of DW applications and give our take on the their current status, technological feasibility and challenges.Comment: 32 pages, 25 figures, review pape

BOOLEAN AND BRAIN-INSPIRED COMPUTING USING SPIN-TRANSFER TORQUE DEVICES

Several completely new approaches (such as spintronic, carbon nanotube, graphene, TFETs, etc.) to information processing and data storage technologies are emerging to address the time frame beyond current Complementary Metal-Oxide-Semiconductor (CMOS) roadmap. The high speed magnetization switching of a nano-magnet due to current induced spin-transfer torque (STT) have been demonstrated in recent experiments. Such STT devices can be explored in compact, low power memory and logic design. In order to truly leverage STT devices based computing, researchers require a re-think of circuit, architecture, and computing model, since the STT devices are unlikely to be drop-in replacements for CMOS. The potential of STT devices based computing will be best realized by considering new computing models that are inherently suited to the characteristics of STT devices, and new applications that are enabled by their unique capabilities, thereby attaining performance that CMOS cannot achieve. The goal of this research is to conduct synergistic exploration in architecture, circuit and device levels for Boolean and brain-inspired computing using nanoscale STT devices. Specifically, we first show that the non-volatile STT devices can be used in designing configurable Boolean logic blocks. We propose a spin-memristor threshold logic (SMTL) gate design, where memristive cross-bar array is used to perform current mode summation of binary inputs and the low power current mode spintronic threshold device carries out the energy efficient threshold operation. Next, for brain-inspired computing, we have exploited different spin-transfer torque device structures that can implement the hard-limiting and soft-limiting artificial neuron transfer functions respectively. We apply such STT based neuron (or ‘spin-neuron’) in various neural network architectures, such as hierarchical temporal memory and feed-forward neural network, for performing “human-like” cognitive computing, which show more than two orders of lower energy consumption compared to state of the art CMOS implementation. Finally, we show the dynamics of injection locked Spin Hall Effect Spin-Torque Oscillator (SHE-STO) cluster can be exploited as a robust multi-dimensional distance metric for associative computing, image/ video analysis, etc. Our simulation results show that the proposed system architecture with injection locked SHE-STOs and the associated CMOS interface circuits can be suitable for robust and energy efficient associative computing and pattern matching

Energy Efficient Spintronic Device for Neuromorphic Computation

Future computing will require significant development in new computing device paradigms. This is motivated by CMOS devices reaching their technological limits, the need for non-Von Neumann architectures as well as the energy constraints of wearable technologies and embedded processors. The first device proposal, an energy-efficient voltage-controlled domain wall device for implementing an artificial neuron and synapse is analyzed using micromagnetic modeling. By controlling the domain wall motion utilizing spin transfer or spin orbit torques in association with voltage generated strain control of perpendicular magnetic anisotropy in the presence of Dzyaloshinskii-Moriya interaction (DMI), different positions of the domain wall are realized in the free layer of a magnetic tunnel junction to program different synaptic weights. Additionally, an artificial neuron can be realized by combining this DW device with a CMOS buffer. The second neuromorphic device proposal is inspired by the brain. Membrane potential of many neurons oscillate in a subthreshold damped fashion and fire when excited by an input frequency that nearly equals their Eigen frequency. We investigate theoretical implementation of such “resonate-and-fire” neurons by utilizing the magnetization dynamics of a fixed magnetic skyrmion based free layer of a magnetic tunnel junction (MTJ). Voltage control of magnetic anisotropy or voltage generated strain results in expansion and shrinking of a skyrmion core that mimics the subthreshold oscillation. Finally, we show that such resonate and fire neurons have potential application in coupled nanomagnetic oscillator based associative memory arrays

Magnetic domain walls : types, processes and applications

Domain walls (DWs) in magnetic nanowires are promising candidates for a variety of applications including Boolean/unconventional logic, memories, in-memory computing as well as magnetic sensors and biomagnetic implementations. They show rich physical behaviour and are controllable using a number of methods including magnetic fields, charge and spin currents and spin-orbit torques. In this review, we detail types of DWs in ferromagnetic nanowires and describe processes of manipulating their state. We look at the state of the art of DW applications and give our take on the their current status, technological feasibility and challenges

Engineering biocomputers in mammalian cells

Endowing cells with enhanced decision-making capacities is essential for creating smarter therapeutics and for dissecting phenotypes. Implementation of synthetic gene circuits affords a means for enhanced cellular control and genetic processing; however, genetic circuits for mammalian cells often require extensive fine-tuning to perform as intended. Here, a robust, general, and scalable system, called 'Boolean logic and arithmetic through DNA excision' (BLADE) is presented that is used to engineer genetic circuits with multiple inputs and outputs in mammalian cells with minimal optimization. The reliability of BLADE arises from its reliance on site-specific recombinases that regulate genes under the control of a single promoter that integrates circuit signals on a single transcriptional layer. Using BLADE, >100 circuits were tested in human embryonic kidney and Jurkat T cells and a quantitative metric was used to evaluate their performance. The circuits include a 3-input, two-output full adder; a 6-input, one-output Boolean logic look-up table; and circuits that incorporate CRISPR–Cas9 to regulate endogenous genes. Moreover, a large library of over 15 small-molecule, light and temperature-inducible recombinases has been established for fine-tuned control. BLADE enables execution of sophisticated cellular computation in mammalian cells, with applications in cell and tissue engineering

Modelling temperature dependence in the Arabidopsis thaliana circadian clock

The circadian clock is the mechanism responsible for generating and controlling the biological rhythms that occur with 24 h periodicity in most living organisms. This clock allows organisms to anticipate the environmental variation caused by the rotation of the Earth such as the daily light and temperature cycles, providing them adaptive advantages. The circadian clock is a complex network of genes interacting with each other in regulatory processes which have been represented by mathematical models. In the plant Arabidopsis thaliana, the mechanisms by which light regulates the circadian clock have been widely modelled mathematically and implemented computationally permitting to explain experimental observations and to generate hypotheses, which have led experimental investigation. However, the role of temperature and the mechanisms of adaptation to temperature variation are poorly understood, and especially in the scenario of global climate change, modelling a temperature responsive plant clock is of increasing importance. Here we present a framework of temperature dependence for the Arabidopsis circadian clock by applying Arrhenius equations to the most predominant models for the plant system and we additionally propose three minimal models via random parameterisations to explore design principles underlying temperature compensation. By numerical investigation, we conclude that temperature compensation is especially sensitive to degradation processes, and that the combined effect of light and temperature favors the robustness of the clock. We also propose to analyse the plant clock as a whole system and under that perspective we suggest that context graph-theoretic approaches could be a powerful tool to uncover the design principles for temperature mechanisms