A5049171548- Magnetic properties of thin films
- Advanced Memory and Neural Computing
- Neural Networks and Reservoir Computing
- Neural Networks and Applications
- Theoretical and Computational Physics
- Ferroelectric and Negative Capacitance Devices
- Quantum and electron transport phenomena
- Physics of Superconductivity and Magnetism
- Molecular Junctions and Nanostructures
- Magnetic and transport properties of perovskites and related materials
- Magnetic Properties and Applications
- Semiconductor materials and interfaces
- Atomic and Subatomic Physics Research
- Advanced Chemical Sensor Technologies
- Neural dynamics and brain function
- Smart Grid Security and Resilience
- Quantum optics and atomic interactions
- Spectroscopy and Quantum Chemical Studies
- nanoparticles nucleation surface interactions
- Advanced Electron Microscopy Techniques and Applications
- Optical Network Technologies
- Cellular Automata and Applications
- Advanced NMR Techniques and Applications
- Microgrid Control and Optimization
- Magneto-Optical Properties and Applications
University of Sheffield
2021-2024
Trinity College Dublin
2017-2019
University of York
2012-2017
Advanced Materials and BioEngineering Research
2017
University of Tulsa
2012
Low cost pollution sensors have been widely publicized, in principle offering increased information on the distribution of air and a democratization quality measurements to amateur users. We report laboratory study commonly-used electrochemical quantify number cross-interferences with other atmospheric chemicals, some which become significant at typical suburban concentrations. highlight that artefact signals from co-sampled pollutants such as CO2 can be greater than sensor signal generated...
Neural networks have revolutionized the area of artificial intelligence and introduced transformative applications to almost every scientific field industry. However, this success comes at a great price; energy requirements for training advanced models are unsustainable. One promising way address pressing issue is by developing low-energy neuromorphic hardware that directly supports algorithm's requirements. The intrinsic non-volatility, non-linearity, memory spintronic devices make them...
Abstract Magnetic recording using circularly polarised femto-second laser pulses is an emerging technology that would allow write speeds much faster than existing field driven methods. However, the mechanism drives magnetisation switching in ferromagnets unclear. Recent theories suggest interaction of light with magnetised media induces opto-magnetic within media, known as inverse Faraday effect. Here we show alternative mechanism, by thermal excitation over anisotropy energy barrier and a...
Abstract Emergent behaviors occur when simple interactions between a system's constituent elements produce properties that the individual do not exhibit in isolation. This article reports tunable emergent observed domain wall (DW) populations of arrays interconnected magnetic ring‐shaped nanowires under an applied rotating field. DWs interact stochastically at ring junctions to create mechanisms DW population loss and gain. These combine give dynamic, field‐dependent equilibrium is robust...
Machine learning techniques are commonly used to model complex relationships but implementations on digital hardware relatively inefficient due poor matching between conventional computer architectures and the structures of algorithms they required simulate. Neuromorphic devices, in particular reservoir computing architectures, utilize inherent properties physical systems implement machine so have potential be much more efficient. In this work, we demonstrate that dynamics individual domain...
The Landau-Lifshitz (LL) equation, originally proposed at the macrospin level, is increasingly used in Atomistic Spin Dynamic (ASD) models. models are based on a spin Hamiltonian featuring atomic spins of fixed length, with exchange introduced using Heisenberg formalism. ASD proving powerful approach to fundamental understanding ultrafast magnetisation dynamics, including prediction thermally induced switching phenomenon which reversed an laser pulse absence externally applied field. paper...
A unified model of molecular and atomistic spin dynamics is presented enabling simulations both in microcanonical canonical ensembles without the necessity additional phenomenological damping. Transfer energy angular momentum between lattice systems achieved by a coupling term representing spin-orbit interaction. The characteristic spectra phonon are analyzed for different strength temperatures. spectral density shows magnon modes together with uncorrelated noise induced to lattice....
The linear reversal mechanism in FePt grains ranging from 2.316 nm to 5.404 has been simulated using atomistic spin dynamics, parametrized ab-initio calculations. Curie temperature and the critical (T*), at which occurs, are observed decrease with system size whilst window T* < T TC increases. paths close have calculated, showing that for decreasing path becomes more elliptic lower temperatures, consistent arising finite effects. Calculations of minimum pulse duration show faster switching...
Abstract Devices based on arrays of interconnected magnetic nano-rings with emergent magnetization dynamics have recently been proposed for use in reservoir computing applications, but them to be computationally useful it must possible optimise their dynamical responses. Here, we a phenomenological model demonstrate that such reservoirs can optimised classification tasks by tuning hyperparameters control the scaling and input-rate data into system using rotating fields. We task-independent...
We propose thermally driven, voltage-controlled superparamagnetic ensembles as low-energy platforms for hardware-based reservoir computing. In the proposed devices, thermal noise is used to drive ensembles' magnetization dynamics, while control of their net states provided by strain-mediated voltage inputs. Using an ensemble CoFeB nanodots example, we use analytical models and micromagnetic simulations demonstrate how such a device can function perform two benchmark machine learning tasks...
In this paper, the ultrafast dynamic behavior of rare-earth doped permalloy is investigated using an atomistic spin model with Langevin dynamics. line experimental work, effective Gilbert damping calculated from transverse relaxation simulations, which shows that doping causes increase in damping. Analytic theory suggests would lead to a decrease demagnetization time. However, longitudinal calculations show concentration instead. The simulations are good agreement previous work Radu et al....
There exists a significant challenge in developing efficient magnetic tunnel junctions with low write currents for non-volatile memory devices. With the aim of analysing potential materials current-operated we have developed multi-scale methodology combining ab initio calculations spin-transfer torque large-scale time-dependent simulations using atomistic spin dynamics. In this work introduce our approach including discussion on number possible mapping schemes torques into We demonstrate...
Using the Landau-Lifshitz-Bloch (LLB) equation for ferromagnetic materials, we derive analytic expressions temperature-dependent absorption spectra as probed by resonance. By analyzing resulting expressions, can predict variation of resonance frequency and damping with temperature coupling to thermal bath. We base our calculations on technologically relevant ${\mathrm{L}1}_{0}\phantom{\rule{0.16em}{0ex}}\mathrm{FePt}$, parametrized from atomistic spin dynamics simulations, Hamiltonian mapped...
Echo state networks (ESNs) are a powerful form of reservoir computing that only require training linear output weights whilst the internal is formed fixed randomly connected neurons. With correctly scaled connectivity matrix, neurons' activity exhibits echo-state property and responds to input dynamics with certain timescales. Tuning timescales network can be necessary for treating tasks, some environments multiple an efficient representation. Here we explore in hierarchical ESNs, where...
Abstract The impressive performance of artificial neural networks has come at the cost high energy usage and CO 2 emissions. Unconventional computing architectures, with magnetic systems as a candidate, have potential alternative energy-efficient hardware, but, still face challenges, such stochastic behaviour, in implementation. Here, we present methodology for exploiting traditionally detrimental effects domain-wall motion nanowires. We demonstrate functional binary synapses alongside...
The common elements and major components of the "Smart Grid," integrated communication platforms that allow for these to become an infrastructure are discussed. basis definition a Grid" will parallel US government's as defined in Energy Independence & Security Act '07 (EISA 2007). Title XIII EISA 2007 is practical solutions current issues regarding: bulk generation, transmission systems, power distribution, customer domain system. Through integrating new modern microprocessor-based devices...
Exchange coupling between magnetic grains is essential for maintaining the stability of stored information in recording media. Using an atomistic spin model, we have investigated neighbouring where impurity atoms migrated into non-magnetic grain boundary. We find that when density low, a biquadratic term addition to bilinear found better describe inter-granular exchange coupling. The temperature dependence both terms follow power law behaviour with constant decaying faster than bilinear. For...
Gilbert damping plays a significant role in magnetic reversal processes, and it determines the timescale of switching. Here we investigate properties exchange-coupled composite media dependence switching time on constant soft layer using atomistic spin dynamics. For bilayer Fe/FePt medium, find an anomalous increase with increasing constant. The occurs via high-temperature exchange spring, show that is related to corresponding establish spring. This phenomenon delicately balanced only fields...
$\mathrm{L}{1}_{0}$ FePt is a technologically important material for range of novel data storage applications. In the ordered structure normally nonmagnetic Pt ion acquires magnetic moment, which depends on local field originating from neighboring Fe atoms. this work model constructed in induced moment simulated by using combined longitudinal and rotational spin dynamics. The parameterized to include linear variation with exchange field, so that at site ordering. Curie temperature calculated...
We present an ab initio study of the spin-transfer torque in Fe/MgO/FePt/Fe magnetic tunnel junctions. consider FePt film with a thickness up to six unit cells, either direct contact MgO spacer or intercalated ultrathin Fe seed layer. find that layer is not attenuated as strongly case pure Fe. Moreover, alternates sign at and Pt atomic planes throughout stack for all thicknesses considered. Finally, when between $L{1}_{0}$ FePt, sharply attenuated, it transferred only less than two thick....
Ultrafast switching of magnetic materials has been shown to be predominantly thermally driven, but excess heating limits the energy efficiency this process. By employing atomistic spin-lattice dynamics simulations, we show that efficient coherent magnetization an insulating magnet can triggered by a THz excitation phonons. We find is driven near <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"><a:mi>P</a:mi></a:math> point phonon spectrum in conditions where spins typically cannot...
<title>Abstract</title> Physical computing has the potential to enable widespread embodied intelligence by leveraging intrinsic dynamics of complex systems for efficient sensing, processing, and interaction. While individual devices provide basic data processing capabilities, networks interconnected can perform more varied tasks. However, designing dynamic tasks is challenging without physical models accurate quantification device noise. We propose a novel, noise-aware methodology training...
Advanced magnetic recording paradigms typically use large temperature changes to drive switching which is detrimental device longevity, hence finding non-thermal routes crucial for future applications. By employing atomistic spin-lattice dynamics simulations, we show efficient coherent magnetisation triggered by THz phonon excitation in insulating single species materials. The key ingredient near the $P$-point of spectrum conditions where spins cannot be excited and when manifold $k$ modes...