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 phase diagram of solid oxygen

Nomura, Toshihiro; Matsuda, Yuji; Kobayashi, T. C.

doi:10.1103/physrevb.96.054439

Cited by 50 publications

(68 citation statements)

References 24 publications

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“…X-ray techniques with ab initio molecular dynamics (MD) simulations. The close agreement achieved between theory and experiment surpasses previous reports [10] and provides a comprehensive understanding of the a-IGO structure, which in turn provides an unprecedented description of how Ga influences the structure-property relationships at play in a-IGO.…”

supporting

confidence: 77%

Probing the Unique Role of Gallium in Amorphous Oxide Semiconductors through Structure–Property Relationships

Moffitt

Zhu

et al. 2017

Adv Elect Materials

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This study explores the unique role of Ga in amorphous (a‐) InGaO oxide semiconductors through combined theory and experiment. It reveals substitutional effects that have not previously been attributed to Ga, and that are investigated by examining how Ga influences structure–property relationships in a series of pulsed laser deposited a‐InGaO thin films. Element‐specific structural studies (X‐ray absorption and anomalous scattering) show good agreement with the results of ab initio molecular dynamics simulations. This structural knowledge is used to understand the results of air‐annealing and Hall effect electrical measurements. The crystallization temperature of a‐IO is shown to increase by as much as 325 °C on substituting Ga for In. This increased thermal stability is understood on the basis of the large changes in local structure that Ga undergoes, as compared to In, during crystallization. Hall measurements reveal an initial sharp drop in both carrier concentration and mobility with increasing Ga incorporation, which moderates at >20 at% Ga content. This decline in both the carrier concentration and mobility with increasing Ga is attributed to dilution of the charge‐carrying InO matrix and to increased structural disorder. The latter effect saturates at high at% Ga.

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supporting

confidence: 77%

Probing the Unique Role of Gallium in Amorphous Oxide Semiconductors through Structure–Property Relationships

Moffitt

Zhu

et al. 2017

Adv Elect Materials

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“…with 77 atoms. The amorphization procedure was done by means of classical molecular dynamics (MD) simulations with the GULP code [38] following methodologically the pioneering work of Nomura et al [39] The MD simulations were started at 5000 K and subsequently cooled down in steps of 10 K per ps with time steps of 2 fs at constant temperature and constant volume. The resulting structures were subsequently relaxed with LDA (for further details see Refs.…”

mentioning

confidence: 99%

Generic origin of subgap states in transparent amorphous semiconductor oxides illustrated for the cases of In-Zn-O and In-Sn-O

Körner

Urban

Elsässer

2015

Phys. Status Solidi A

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We present a microscopic interpretation for the appearance and behaviour of subgap states in stoichiometric and oxygen-deficient, amorphous In-Zn-O (a-IZO) and In-Sn-O (a-ITO) derived from a density functional theory analysis using a self-interaction-correction scheme. Our findings concerning the defect structures and the resulting deep levels are qualitatively similar to earlier results on a-IGZO and a-ZTO and in agreement with recent experimental results. Based on our extensive set of DFT results for In-, Sn-, Zn- based oxides we develop a general concept of the subgap states which is applicable to these systems. Electronic defect levels in the lower half of the band gap are created by undercoordinated oxygen atoms while local oxygen deficiencies cause defect levels in the upper part of the band gap

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“…As is discussed in Ref. 25, by combining the RBM with other powerful wave functions, the same accuracy can be achieved by smaller number of variational parameters. It is an interesting future issue to implement such a combination to study excited states.…”

Section: Discussionmentioning

confidence: 88%

“…[7][8][9][10][11][12][13][14][15][16] The relationship between the RBM and tensor network methods has also been discussed. 4,[17][18][19] The applicability of machine learning solvers has been extended to, for example, frustrated spin systems, 14-16, 20, 21) itinerant boson systems, 11,12) topological states, 3,[17][18][19][22][23][24] fermion systems, 14,[25][26][27][28] excited states, 29,30) open quantum states, [31][32][33][34] and quantum states with nonabelian or anyonic symmetries. 30) In the present paper, we report two crucial extensions of machine learning solvers.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Quantum States — Extensions to Fermion–Boson Coupled Systems and Excited-State Calculations

Nomura

2020

J. Phys. Soc. Jpn.

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To analyze quantum many-body Hamiltonians, recently, machine learning techniques have been shown to be quite useful and powerful. However, the applicability of such machine learning solvers is still limited. Here, we propose schemes that make it possible to apply machine learning techniques to analyze fermion-boson coupled Hamiltonians and to calculate excited states. As for the extension to fermion-boson coupled systems, we study the Holstein model as a representative of the fermion-boson coupled Hamiltonians. We show that the machine-learning solver achieves highly accurate ground-state energy, improving the accuracy substantially compared to that obtained by the variational Monte Carlo method. As for the calculations of excited states, we propose a different approach than that proposed in K. Choo et al., Phys. Rev. Lett. 121 (2018) 167204. We discuss the difference in detail and compare the accuracy of two methods using the one-dimensional S = 1/2 Heisenberg chain. We also show the benchmark for the frustrated two-dimensional S = 1/2 J 1 -J 2 Heisenberg model and show an excellent agreement with the results obtained by the exact diagonalization. The extensions shown here open a way to analyze general quantum many-body problems using machine learning techniques.

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H−T phase diagram of solid oxygen

Cited by 50 publications

References 24 publications

Probing the Unique Role of Gallium in Amorphous Oxide Semiconductors through Structure–Property Relationships

Probing the Unique Role of Gallium in Amorphous Oxide Semiconductors through Structure–Property Relationships

Generic origin of subgap states in transparent amorphous semiconductor oxides illustrated for the cases of In-Zn-O and In-Sn-O

Machine Learning Quantum States — Extensions to Fermion–Boson Coupled Systems and Excited-State Calculations

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