Transport properties of C and O in UN fuels

Schuler, Thomas M.; Lopes, Denise Adorno; Claisse, Antoine; Olsson, Pär

doi:10.1103/physrevb.95.094117

Cited by 11 publications

(12 citation statements)

References 43 publications

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“…36 In another, the parameters of an effective finite Anderson model are variationally optimized. 37 Here we show that the DED approach gives an excellent description of the Anderson model inside and outside the Kondo regime, except for very strong correlations. We find that already for a very small number of 1-2 bath sites, the spectra are in good qualitative agreement with exact spectra calculated by NRG.…”

Section: Introductionmentioning

confidence: 62%

Kondo physics of the Anderson impurity model by distributional exact diagonalization

2016

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The Distributional Exact Diagonalization (DED) scheme is applied to the description of Kondo physics in the Anderson impurity model. DED maps Anderson's problem of an interacting impurity level coupled to an infinite bath onto an ensemble of finite Anderson models, each of which can be solved by exact diagonalization. An approximation to the self-energy of the original infinite model is then obtained from the ensemble averaged self-energy. Using Friedel's sum rule, we show that the particle number constraint, a central ingredient of the DED scheme, ultimately imposes Fermi liquid behavior on the ensemble averaged self-energy, and thus is essential for the description of Kondo physics within DED. Using the Numerical Renormalization Group (NRG) method as a benchmark, we show that DED yields excellent spectra, both inside and outside the Kondo regime for a moderate number of bath sites. Only for very strong correlations (U/Γ 10) does the number of bath sites needed to achieve good quantitative agreement become too large to be computationally feasible.

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Section: Introductionmentioning

confidence: 62%

Kondo physics of the Anderson impurity model by distributional exact diagonalization

2016

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“…Before presenting the numerical results, it is interesting to compare the above NO-based Lanczos method with the variational exact diagonalization (VED) method in Ref. [33]. Both methods use the cluster-plus-bath scheme to represent the transformed/auxilliary Hamiltonian.…”

Section: )mentioning

confidence: 99%

“…The results obtained using N b = 301 are compared with the results from NRG, demonstrating the superior advantage of this method compared to traditional ED or Lanczos methods. Recently, the variational determination of the optimal electron orbital was demonstrated on the one-and five-orbital AIMs [33].…”

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confidence: 99%

Natural orbital-based Lanczos method for Anderson impurity models

Tong

2019

Computer Physics Communications

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We implement the Lanczos algorithm on natural orbital basis to solve the zero-temperature Green's function of Anderson impurity models, following the work of Y. Lu, M. Höppner, O.Gunnarsson, and M. W. Haverkort, Phys. Rev. B 90 (2014) 085102. We present the technical details, generalize the algorithm to the cases of particle-hole asymmetry, with local magnetic field, and of two impurities. The results are benchmarked with conventional Lanczos, quantum Monte Carlo, and numerical renormalization group methods, demonstrating its potential as a powerful impurity solver for the dynamical mean-field theory.Keywords: Lanczos, natural orbital, Anderson impurity model, quantum impurity solver IntroductionThe Anderson impurity model (AIM) [1] is one of the basic models in condensed matter physics. It describes the physics of a local electron orbital with on-site Coulomb repulsion embedded in a conduction electron band and is widely used to describe the dilute magnetic impurities in metals [2], Kondo effect [3], as well as impurity quantum phase transitions [4]. In the past two decades, stimulated by the development and application of the dynamical mean-field theory (DMFT) [5,6], the study of AIM receives revived attention because in DMFT, a lattice Hamiltonian for the correlated electrons is mapped into an AIM with self-consistently determined electron bath. The core calculation of DMFT is the iterative solution of the self-energy *

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“…Besides, the experimental characterization of atomic transport at low temperature is in general not feasible, and only some of the transport coefficients can be experimentally determined. Thanks to the progress of DFT applied to the calculation of migration barriers [16][17][18], atom jump-frequency databases are in construction for metallic alloys [6,[19][20][21][22], and to a smaller extent for ceramics [23,24] and semiconductors [25][26][27][28][29]. The use of these databases is mainly dedicated to the study of self-and solute diffusion [19,21].…”

Section: Introductionmentioning

confidence: 99%

KineCluE: A kinetic cluster expansion code to compute transport coefficients beyond the dilute limit

Schuler

Messina

Nastar

2020

Computational Materials Science

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This paper introduces the KineCluE code that implements the self-consistent mean-field theory for clusters of finite size. Transport coefficients are obtained as a sum over cluster contributions (in a cluster expansion formalism), each being individually computed with KineCluE. This method allows for the calculation of these coefficients beyond the infinitely dilute limit, and is an important step in bridging the gap between dilute and concentrated approaches. Inside a finite volume of space containing the components of a given cluster, all kinetic trajectories are accounted for in an exact manner. The code, written in Python, adapts to a wide variety of systems, with various crystallographic structures (possibly under strain), defects and solute amount and types, and various jump mechanisms, including collective ones. The code also features a set of useful tools, such as the sensitivity study routine that allows for the identification of the most important jump frequencies to get accurate transport coefficients with minimum computational cost. PROGRAM SUMMARYProgram Title: KineCluE (KINEtic CLUster Expansion) Licensing provisions: LGPL Programming language: Python 3.6 Nature of problem: Providing a general method for computing transport coefficients from atomic jump frequencies, taking into account kinetic correlations.Solution method: The program relies on the selfconsistent mean field (SCMF) theory. The system is described in terms of lattice sites, defects and jump mechanisms. The first part of the code translates the diffusion problem for such system into an analytical linear eigenvalue problem. The second part of the code assigns numerical values to each analytical variable and then solves the linear problem.

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Transport properties of C and O in UN fuels

Cited by 11 publications

References 43 publications

Kondo physics of the Anderson impurity model by distributional exact diagonalization

Kondo physics of the Anderson impurity model by distributional exact diagonalization

Natural orbital-based Lanczos method for Anderson impurity models

KineCluE: A kinetic cluster expansion code to compute transport coefficients beyond the dilute limit

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