3,738 research outputs found

    Neutron scattering studies of heterogeneous catalysis

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    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

    Analog Photonics Computing for Information Processing, Inference and Optimisation

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    This review presents an overview of the current state-of-the-art in photonics computing, which leverages photons, photons coupled with matter, and optics-related technologies for effective and efficient computational purposes. It covers the history and development of photonics computing and modern analogue computing platforms and architectures, focusing on optimization tasks and neural network implementations. The authors examine special-purpose optimizers, mathematical descriptions of photonics optimizers, and their various interconnections. Disparate applications are discussed, including direct encoding, logistics, finance, phase retrieval, machine learning, neural networks, probabilistic graphical models, and image processing, among many others. The main directions of technological advancement and associated challenges in photonics computing are explored, along with an assessment of its efficiency. Finally, the paper discusses prospects and the field of optical quantum computing, providing insights into the potential applications of this technology.Comment: Invited submission by Journal of Advanced Quantum Technologies; accepted version 5/06/202

    Физика космоса : труды 50-й Международной студенческой научной конференции (Екатеринбург, 30 января — 3 февраля. 2023 г.)

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    В сборнике представлены доклады и сообщения студенческой научной конференции, которая ежегодно проводится в Астрономической обсерватории Уральского федерального университета. Цель конференции — обобщить достижения в области астрономии и астрофизики и способствовать формированию навыков и способностей молодых исследователей. Сборник предназначен для профессиональных астрономов и физиков, студентов и аспирантов соответствующих специальностей.Отдел по делам молодежи администрации Октябрьского района г. Екатеринбурга; Уральский федеральный университет имени первого Президента России Б.Н. Ельцин

    Production and characterisation of dipolar Bose–Einstein condensates

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    Remarkable progress in the field of ultracold atoms has enabled the study of a great variety of topics in many-body quantum mechanics. The precise control of key parameters, such as interactions, temperature, density, internal and external degrees of freedom, dimensionality and the trapping geometry makes them a powerful and flexible experimental platform. The ability to create degenerate samples of atoms which feature long-range and anisotropic dipole–dipole interactions besides the more conventional short-range and isotropic contact interactions drew considerable attention, enabling the creation of quantum droplets and a supersolid phase. This thesis reports on experimental and theoretical progress in investigating dipolar many-body quantum systems. We present an overview of our experimental apparatus and the techniques used for obtaining a Bose–Einstein condensate (BEC) of erbium. We then discuss our experimental sequence for producing a quantum degenerate gas, creating a quasi-pure BEC with 2.2 x 10^5 atoms. To optimise the production of erbium BECs, we explore density- and temperature-dependent losses in 166Er and identify six previously unreported resonant loss features. Finally, to enable studies of density-dependent phenomena, we present a theoretical investigation of dipolar condensates in box-like traps, where we explore stability and how one can use it to replicate properties of an infinite, homogeneous system to study dipolar physics. We found that traps with hard walls trigger roton-like density oscillations even if the bulk of the system is far from the roton regime, so smoother potentials are better suited to recreate homogeneous conditions. This sets the ground for future experiments, where the atoms will be loaded into a box trap to enable studies of systems which are tightly trapped in one direction but homogeneous in the other two

    The OpenMolcas Web: A Community-Driven Approach to Advancing Computational Chemistry

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    The developments of the open-source OpenMolcas chemistry software environment since spring 2020 are described, with a focus on novel functionalities accessible in the stable branch of the package or via interfaces with other packages. These developments span a wide range of topics in computational chemistry and are presented in thematic sections: electronic structure theory, electronic spectroscopy simulations, analytic gradients and molecular structure optimizations, ab initio molecular dynamics, and other new features. This report offers an overview of the chemical phenomena and processes OpenMolcas can address, while showing that OpenMolcas is an attractive platform for state-of-the-art atomistic computer simulations

    TURBOMOLE: Today and Tomorrow

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    TURBOMOLE is a highly optimized software suite for large-scale quantum-chemical and materials science simulations of molecules, clusters, extended systems, and periodic solids. TURBOMOLE uses Gaussian basis sets and has been designed with robust and fast quantum-chemical applications in mind, ranging from homogeneous and heterogeneous catalysis to inorganic and organic chemistry and various types of spectroscopy, light–matter interactions, and biochemistry. This Perspective briefly surveys TURBOMOLE’s functionality and highlights recent developments that have taken place between 2020 and 2023, comprising new electronic structure methods for molecules and solids, previously unavailable molecular properties, embedding, and molecular dynamics approaches. Select features under development are reviewed to illustrate the continuous growth of the program suite, including nuclear electronic orbital methods, Hartree–Fock-based adiabatic connection models, simplified time-dependent density functional theory, relativistic effects and magnetic properties, and multiscale modeling of optical properties

    Multiscale modelling of mesoscopic behaviour in soft matter systems

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    Soft matter modelling has a wide range of applications, such as polymer additive manufacturing, organics electronics, and biomolecular engineering. Many physical properties and phenomena of soft matter are determined by interactions and processes at a wide range of length and time scales. Therefore, it is challenging for theoretical models to simulate processes involving features from multiple scales. To reach the mesoscopic scales for soft matter behaviour, coarse-grained models have been developed to accelerate the atomistic models by projecting out the relevant degrees of freedom, allowing coverage of a wider range of scales. However, due to the lack of a formalism to capture the dynamics and anisotropy of the system, conventional coarse-grained model shows significant errors in dynamical properties and inconsistent soft matter behaviour. In this thesis, a generalised systematic formalism for coarse-graining is presented. The Mori-Zwanzig formalism provides a dynamically-guided projection to construct a mesoscopic system directly from the underlying microscopic system. Moreover, the Gay-Berne functional is introduced to describe the anisotropic effect of the pairwise interactions at mesoscopic level. The performance of the model is demonstrated by comparing it to other coarse-grained models using benzene as an example, which shows significant improvement in both static and dynamical properties. For application, crystallization of pentacene is studied by treating pentacene molecule as ellipsoidal particle. Furthermore, a modified atomistic model and a modified continuum model are employed to simulate mesosopic behaviour of polymers in electrospinning and electro-optical poling, demonstrating mesoscopic modelling from the atomistic and continuum limits

    Application of multi-scale computational techniques to complex materials systems

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    The applications of computational materials science are ever-increasing, connecting fields far beyond traditional subfields in materials science. This dissertation demonstrates the broad scope of multi-scale computational techniques by investigating multiple unrelated complex material systems, namely scandate thermionic cathodes and the metallic foam component of micrometeoroid and orbital debris (MMOD) shielding. Sc-containing scandate cathodes have been widely reported to exhibit superior properties compared to previous thermionic cathodes; however, knowledge of their precise operating mechanism remains elusive. Here, quantum mechanical calculations were utilized to map the phase space of stable, highly-faceted and chemically-complex W nanoparticles, accounting for both finite temperature and chemical environment. The precise processing conditions required to form the characteristic W nanoparticle observed experimentally were then distilled. Metallic foams, a central component of MMOD shielding, also represent a highly-complex materials system, albeit at a far higher length scale than W nanoparticles. The non-periodic, randomly-oriented constituent ligaments of metallic foams and similar materials create a significant variability in properties that is generally difficult to model. Rather than homogenizing the material such that its unique characteristic structural features are neglected, here, a stochastic modeling approach is applied that integrates complex geometric structure and utilizes continuum calculations to predict the resulting probabilistic distributions of elastic properties. Though different in many aspects, scandate cathodes and metallic foams are united by complexity that is impractical, even dangerous, to ignore and well-suited to exploration with multi-scale computational methods
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