2021
DOI: 10.1016/j.jpcs.2020.109912
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Testing whether flat bands in the calculated electronic density of states are good predictors of superconducting materials

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Cited by 8 publications
(6 citation statements)
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“…Thus, we make the graph of the superconducting gap (eigenvalues), for different values of temperature. These results are presented in the Figure 6, for different values of the mating orbital function as a function of temperature, results that coincide with the experimental results [33], [34], [35], [36], [37]. The inter-orbital potential is 𝑉 𝜒𝜒 = 0.…”
Section: Numerical Solution Of the Klein-gordon And Bogoliubov-degenn...supporting
confidence: 81%
“…Thus, we make the graph of the superconducting gap (eigenvalues), for different values of temperature. These results are presented in the Figure 6, for different values of the mating orbital function as a function of temperature, results that coincide with the experimental results [33], [34], [35], [36], [37]. The inter-orbital potential is 𝑉 𝜒𝜒 = 0.…”
Section: Numerical Solution Of the Klein-gordon And Bogoliubov-degenn...supporting
confidence: 81%
“…1 While there are a wide range of superconducting applications that would strongly benefit from new materials, state-of-the-art computational methods are struggling to predict the highly complex collective electronic state of superconductors. 2,3 Hence, for the search of new and improved superconducting materials, one has to rely on utilizing chemical and physical design principles, such as looking for new materials with structural features from known superconductors and electron counting. 4−9 One chemical approach to this has been the exploration of materials in which the electronic properties can be tuned precisely by the addition of dopants between layers or into void positions.…”
Section: ■ Introductionmentioning
confidence: 99%
“…The discovery of new superconductors and improved superconducting properties remains a long-standing challenge in solid-state and materials chemistry . While there are a wide range of superconducting applications that would strongly benefit from new materials, state-of-the-art computational methods are struggling to predict the highly complex collective electronic state of superconductors. , Hence, for the search of new and improved superconducting materials, one has to rely on utilizing chemical and physical design principles, such as looking for new materials with structural features from known superconductors and electron counting. One chemical approach to this has been the exploration of materials in which the electronic properties can be tuned precisely by the addition of dopants between layers or into void positions. For this purpose, electron-donor atoms, or cations, are most commonly incorporated into the structure, as, for example, in Cu x TiSe 2 , where superconductivity with a critical temperature of T c ≈ 4 K was discovered via the intercalation of copper between the TiSe 2 layers . Less commonly, electron-acceptor atoms, or anions, are doped into structural void positions to achieve superconductivity. , A recent example for the enhancement of superconductivity in such a material is Nb 5 Ir 3 O with a critical temperature of T c ≈ 10.5 K .…”
Section: Introductionmentioning
confidence: 99%
“…Such enhanced DOS has long been considered a promising way to boost T c . However, a very recent study using experimental T c and DFT-based DOS calculations failed to discover a strong and consistent correlation between superconductivity and peaks in the electronic DOS 97 . Yet, the strongest conclusion from the latter study was on "…the restrictions that the current availability and organization of materials data place on reliable machine-learning and data-based experimentation," underscoring the need for a more systematic approach to collecting and organizing quantum materials data.…”
Section: Ai For Computational Quantum Materialsmentioning
confidence: 99%