Combining graph deep learning and London dispersion interatomic potentials: A case study on pnictogen chalcohalides.

Machine-learning interatomic potential models based on graph neural network architectures have the potential to make atomistic materials modeling widely accessible due to their computational efficiency, scalability, and broad applicability. The training datasets for many such models are derived from density-functional theory calculations, typically using a semilocal exchange-correlation functional. As a result, long-range interactions such as London dispersion are often missing in these models.

Did changing work and family demands during COVID-19 (de)motivate academic parents to craft sustainable careers?

Background: Covid-19 has introduced many contextual changes into individuals' work and family lives, affecting their career sustainability. Although previous studies have provided evidence for these changes, little is known about how changing contextual demands (de)motivated them to take proactive initiatives for crafting sustainable careers.

Objective: This study aims to explore how changing work and family demands of academic parents during Covid-19 affected their career sustainability indicators and career initiatives regarding health, happiness, and productivity.

Enhancement of the magnetic anisotropy in single semiconductor nanowires via surface doping and adatom deposition.

The magnetic anisotropy of single semiconductor (ZnO and GaN) nanowires incorporating both a transition metal (Co and Mn, respectively) as a substitutional surface dopant and a heavy metal (Au, Bi, or Pt) adatom is studied by performing density-functional supercell calculations with the Hubbardcorrection. It is found that a substantial enhancement in the magnetic anisotropy energy is obtained through the deposition of Bi; the deposition of Au and Pt leads to significant variation in other magnetic properties, but not in the magnetic anisotropy energy. An analysis within a band description shows that the coexistence of Bi adatom and a surface dopant with large spin moment activates a mechanism involving reorientation and readjustment of the spin moments of electrons in occupied bands in response to the change of magnetization direction, which promotes giant magnetic anisotropy.

Segregation tendencies of transition-metal dopants in wide band gap semiconductor nanowires.

The segregation tendencies, defect energetics and electrical behavior of transition-metal (Mn and Co) dopants in wide band gap semiconductor (GaN and ZnO) nanowires are investigated by performing density-functional supercell calculations with the Hubbard U correction. Defect calculations and ab initio molecular dynamics simulations are carried out for a comparative exploration of various doping configurations where the dopant resides on interior, subsurface or surface sites. Mn and Co dopants in GaN and ZnO nanowires, respectively, are found to have different segregation tendencies: whereas a uniform distribution of Co dopants throughout ZnO nanowires takes place, indicating no segregation behavior, GaN nanowires can accommodate the majority of Mn dopants in the interior or surface sites, depending on the position of the Fermi level, which indicates not only segregation, but also that the direction of segregation can be reversed by shifting the Fermi level.

Combined hybrid functional and DFT+U calculations for metal chalcogenides.

In the density-functional studies of materials with localized electronic states, the local/semilocal exchange-correlation functionals are often either combined with a Hubbard parameter U as in the LDA+U method or mixed with a fraction of exactly computed (Fock) exchange energy yielding a hybrid functional. Although some inaccuracies of the semilocal density approximations are thus fixed to a certain extent, the improvements are not sufficient to make the predictions agree with the experimental data. Here, we put forward the perspective that the hybrid functional scheme and the LDA+U method should be treated as complementary, and propose to combine the range-separated Heyd-Scuseria-Ernzerhof (HSE) hybrid functional with the Hubbard U.

Origins of coexistence of conductivity and transparency in SnO(2).

SnO2 is a prototype "transparent conductor," exhibiting the contradictory properties of high metallic conductivity due to massive structural nonstoichiometry with nearly complete, insulator-like transparency in the visible range. We found, via first-principles calculations, that the tin interstitial and oxygen vacancy have surprisingly low formation energies and strong mutual attraction, explaining the natural nonstoichiometry of this system. The stability of these intrinsic defects is traced back to the multivalence of tin.