7,657 research outputs found
Neutron scattering studies of heterogeneous catalysis
Understanding the structural dynamics/evolution of catalysts and the related surface chemistry is essential for establishing structure–catalysis relationships, where spectroscopic and scattering tools play a crucial role. Among many such tools, neutron scattering, though less-known, has a unique power for investigating catalytic phenomena. Since neutrons interact with the nuclei of matter, the neutron–nucleon interaction provides unique information on light elements (mainly hydrogen), neighboring elements, and isotopes, which are complementary to X-ray and photon-based techniques. Neutron vibrational spectroscopy has been the most utilized neutron scattering approach for heterogeneous catalysis research by providing chemical information on surface/bulk species (mostly H-containing) and reaction chemistry. Neutron diffraction and quasielastic neutron scattering can also supply important information on catalyst structures and dynamics of surface species. Other neutron approaches, such as small angle neutron scattering and neutron imaging, have been much less used but still give distinctive catalytic information. This review provides a comprehensive overview of recent advances in neutron scattering investigations of heterogeneous catalysis, focusing on surface adsorbates, reaction mechanisms, and catalyst structural changes revealed by neutron spectroscopy, diffraction, quasielastic neutron scattering, and other neutron techniques. Perspectives are also provided on the challenges and future opportunities in neutron scattering studies of heterogeneous catalysis
Unveiling the anatomy of mode-coupling theory
The mode-coupling theory of the glass transition (MCT) has been at the
forefront of fundamental glass research for decades, yet the theory's
underlying approximations remain obscure. Here we quantify and critically
assess the effect of each MCT approximation separately. Using Brownian dynamics
simulations, we compute the memory kernel predicted by MCT after each
approximation in its derivation, and compare it with the exact one. We find
that some often-criticized approximations are in fact very accurate, while the
opposite is true for others, providing new guiding cues for further theory
development
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Pipeline quantum processor architecture for silicon spin qubits
Noisy intermediate-scale quantum (NISQ) devices seek to achieve quantum
advantage over classical systems without the use of full quantum error
correction. We propose a NISQ processor architecture using a qubit `pipeline'
in which all run-time control is applied globally, reducing the required number
and complexity of control and interconnect resources. This is achieved by
progressing qubit states through a layered physical array of structures which
realise single and two-qubit gates. Such an approach lends itself to NISQ
applications such as variational quantum eigensolvers which require numerous
repetitions of the same calculation, or small variations thereof. In exchange
for simplifying run-time control, a larger number of physical structures is
required for shuttling the qubits as the circuit depth now corresponds to an
array of physical structures. However, qubit states can be `pipelined' densely
through the arrays for repeated runs to make more efficient use of physical
resources. We describe how the qubit pipeline can be implemented in a silicon
spin-qubit platform, to which it is well suited to due to the high qubit
density and scalability. In this implementation, we describe the physical
realisation of single and two qubit gates which represent a universal gate set
that can achieve fidelities of , even under typical
qubit frequency variations.Comment: 21 pages (13 for main + 8 for supplement), 9 figures (4 for main + 5
for supplement
Collective variables between large-scale states in turbulent convection
The dynamics in a confined turbulent convection flow is dominated by multiple
long-lived macroscopic circulation states, which are visited subsequently by
the system in a Markov-type hopping process. In the present work, we analyze
the short transition paths between these subsequent macroscopic system states
by a data-driven learning algorithm that extracts the low-dimensional
transition manifold and the related new coordinates, which we term collective
variables, in the state space of the complex turbulent flow. We therefore
transfer and extend concepts for conformation transitions in stochastic
microscopic systems, such as in the dynamics of macromolecules, to a
deterministic macroscopic flow. Our analysis is based on long-term direct
numerical simulation trajectories of turbulent convection in a closed cubic
cell at a Prandtl number and Rayleigh numbers and
for a time lag of convective free-fall time units. The simulations
resolve vortices and plumes of all physically relevant scales resulting in a
state space spanned by more than 3.5 million degrees of freedom. The transition
dynamics between the large-scale circulation states can be captured by the
transition manifold analysis with only two collective variables which implies a
reduction of the data dimension by a factor of more than a million. Our method
demonstrates that cessations and subsequent reversals of the large-scale flow
are unlikely in the present setup and thus paves the way to the development of
efficient reduced-order models of the macroscopic complex nonlinear dynamical
system.Comment: 24 pages, 12 Figures, 1 tabl
Greater Trochanteric Pain Syndrome: a comparison of exercise programmes and identification of subgroups
Greater trochanteric pain syndrome (GTPS) is a musculoskeletal condition for which exercise programmes are considered an essential part of management. Isometric exercise has been directly compared to isotonic exercise for other tendinopathies but the effectiveness of isometric exercise programmes for GTPS is currently unknown. A number of individuals with GTPS fail to experience clinical improvements following exercise programmes, which could be related to the presence of certain clinical characteristics, including health co-morbidities, co-existing physical symptoms and psychological factors. The prevalence of these clinical characteristics in GTPS populations is largely unknown. Subgroups based on such characteristics have yet to be defined. It is plausible that subgroups exist within GTPS populations who do not respond to current loading programmes.
Three studies were undertaken for this thesis. Firstly, a randomised controlled pilot study investigated whether there was any difference in clinical outcomes when 12 weeks of isometric exercise and isotonic exercise were compared. No difference was observed between both groups at 4 and 12-week follow-up. Secondly, a systematic review of 10 randomised controlled trials evaluated whether isometric exercise was superior to isotonic exercise or any other treatment in the management of tendinopathy. Isometric exercise did not appear to be superior in terms of immediate or short-term pain relief for any tendinopathy. Finally, an on line survey of 261 individuals with GTPS was completed. Subgroups were defined for younger individuals ( 40 years) and sedentary and active individuals. The clinical characteristics identified in younger and older individuals were similar. Subgrouping based on physical activity level revealed that sedentary individuals had a greater number of health co-morbidities, co-existing physical symptoms and higher prevalence of psychological factors.
This thesis reports a number of important findings in relation to the effectiveness of isometric exercise in the management of GTPS and tendinopathy. For the first time subgroups of individuals with GTPS have been defined based on clinical characteristics which may guide future research
Topological Signatures and Quenches in One Dimensional Fermionic Systems
L'abstract è presente nell'allegato / the abstract is in the attachmen
Ultrafast Optical Control of Order Parameters in Quantum Materials
Developing protocols to realize quantum phases that are not accessible thermally and to manipulate material properties on demand is one of the central problems of modern condensed matter physics. Impulsive electromagnetic stimulus provides an extensive playground not only to exert desired control over the material macroscopic properties but also to optically detect the underlying microscopic mechanisms. Two indispensable components form the cornerstone to realize these goals: a meticulous comprehension of light-induced phenomena and a suitable and versatile platform.
Abundant photoinduced phenomena emerge upon light irradiation. A collective oscillation of order parameter can be launched and probed in the weak perturbation regime; further increasing light intensity can transiently modulate the free-energy landscape, inducing a suppression, enhancement, reversal, and switch of order parameters; in the strong non-perturbative excitation regime, the system can be driven nonlinearly with microscopic coupling parameters modified. Understanding these light driven emergent phenomena lays the foundation of optical control and novel functionalities.
Quantum materials, embodying a large portfolio of topological and strongly correlated compounds, afford an exceptional venue to realize optical control. Owing to the complex interplay between the charge, spin, orbital, and lattice degrees of freedom, a rich phase diagram can be generated with various phases that are selectively and independently accessible via optical perturbations. They hence offer a wealth of opportunities to not only improve our comprehension of the underlying physics but also develop the next generation of ultrafast technologies.
In Chapter I of this thesis, I will first cover a multitude of light-induced emergent phenomena in quantum materials under the framework of time-dependent Landau theory, Keldysh theory, and Floquet theory, and then introduce several canonical microscopic models to quantitatively rationalize the intra- and interactions between different degrees of freedom in quantum materials. As the necessary theoretical background is established, three main experimental techniques that have been extensively utilized in my research: time-resolved reflectivity and Kerr effect, time-resolved second harmonic generation rotational anisotropy, and coherent phonon spectroscopy will be introduced in Chapter II. In Chapter III, I will demonstrate that a light-induced topological phase transition can be engendered concomitant with an inverse-Peierls structural phase transition in elemental Te. In Chapter IV, I will describe signatures of ultrafast reversal of excitonic order in excitonic insulator candidate Ta2NiSe5 and substantiate a manipulation of the reversal as well as the Higgs mode with tailored light pulses. In Chapter V, a light-induced switch of spin-orbit-coupled quadrupolar order in multiband Mott insulator Ca2RuO4 will be introduced. In Chapter VI, a Keldysh tuning of nonlinear carrier excitation and Floquet bandwidth renormalization in strongly driven Ca2RuO4 will be covered.</p
Modeling and Simulation in Engineering
The Special Issue Modeling and Simulation in Engineering, belonging to the section Engineering Mathematics of the Journal Mathematics, publishes original research papers dealing with advanced simulation and modeling techniques. The present book, “Modeling and Simulation in Engineering I, 2022”, contains 14 papers accepted after peer review by recognized specialists in the field. The papers address different topics occurring in engineering, such as ferrofluid transport in magnetic fields, non-fractal signal analysis, fractional derivatives, applications of swarm algorithms and evolutionary algorithms (genetic algorithms), inverse methods for inverse problems, numerical analysis of heat and mass transfer, numerical solutions for fractional differential equations, Kriging modelling, theory of the modelling methodology, and artificial neural networks for fault diagnosis in electric circuits. It is hoped that the papers selected for this issue will attract a significant audience in the scientific community and will further stimulate research involving modelling and simulation in mathematical physics and in engineering
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