A new algorithm applies Hubbard U corrections to electron-phonon g matrices via finite-displacement DFT+U, applied to 20% hole-doped LaNiO2 and strained RuO2, finding modest coupling increase insufficient for observed Tc in nickelates but stabilization and reduced coupling in ruthenates.
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Bayesian active learning with SSCHA predicts phase transitions in materials like CsPbI3 using only 50-256 first-principles calculations.
Raman spectra of NbTe4 reveal 25 low-temperature phonon modes and a warming-rate-dependent hysteretic transition between commensurate and incommensurate CDW phases at 45 K and 90 K.
First-principles calculations map the effect of individual infrared-active phonon modes on the magnetic exchange parameters of Y3Fe5O12 via changes in Fe-O-Fe geometry.
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Hubbard-$U$-corrected electron-phonon interactions in strongly correlated materials via the finite-displacement method
A new algorithm applies Hubbard U corrections to electron-phonon g matrices via finite-displacement DFT+U, applied to 20% hole-doped LaNiO2 and strained RuO2, finding modest coupling increase insufficient for observed Tc in nickelates but stabilization and reduced coupling in ruthenates.
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Predicting challenging phase transitions with Bayesian active learning
Bayesian active learning with SSCHA predicts phase transitions in materials like CsPbI3 using only 50-256 first-principles calculations.
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Raman scattering fingerprints of the charge density wave state in one-dimensional NbTe$_4$
Raman spectra of NbTe4 reveal 25 low-temperature phonon modes and a warming-rate-dependent hysteretic transition between commensurate and incommensurate CDW phases at 45 K and 90 K.
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Phonon-driven tuning of exchange interactions in Y3Fe5O12
First-principles calculations map the effect of individual infrared-active phonon modes on the magnetic exchange parameters of Y3Fe5O12 via changes in Fe-O-Fe geometry.