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Oxygen vacancies (VO's) are of paramount importance in influencing the properties and applications of ceria (CeO2). Yet, comprehending the distribution and nature of the VO's poses a significant challenge due to the vast number of electronic configurations and intricate many-body interactions among VO's and polarons (Ce3+'s). In this study, we employed a combination of LASSO regression in machine learning, in conjunction with a cluster expansion model and first-principles calculations to decouple the interactions among the Ce3+'s and VO's, thereby circumventing the limitations associated with sampling electronic configurations. By separating these interactions, we identified specific electronic configurations characterized by the most favorable VO-Ce3+ attractions and the least Ce3+-Ce3+/VO-VO repulsions, which are crucial in determining the stability of vacancy structures. Through more than 10^8 Metropolis Monte Carlo samplings of Vo's and Ce3+ in the near-surface of CeO2(111), we explored potential configurations within an 8x8 supercell. Our findings revealed that oxygen vacancies tend to aggregate and are most abundant in the third oxygen layer, primarily due to extensive geometric relaxation-an aspect previously overlooked. This behavior is notably dependent on the concentration of Vo. This work introduces a novel theoretical framework for unraveling the complex vacancy structures in metal oxides, with potential applications in redox and catalytic chemistry., Comment: 22 pages, 1 scheme, 5 figures

Big data has ushered in a new wave of predictive power using machine learning models. In this work, we assess what {\it big} means in the context of typical materials-science machine-learning problems. This concerns not only data volume, but also data quality and veracity as much as infrastructure issues. With selected examples, we ask (i) how models generalize to similar datasets, (ii) how high-quality datasets can be gathered from heterogenous sources, (iii) how the feature set and complexity of a model can affect expressivity, and (iv) what infrastructure requirements are needed to create larger datasets and train models on them. In sum, we find that big data present unique challenges along very different aspects that should serve to motivate further work.

Antiperovskite nitrides are potential candidates for applications harvesting solar light. With a comprehensive state-of-the-art approach combining hybrid density-functional theory, many-body perturbation theory, the Wannier-Mott model, density-functional perturbation theory, and the Feynman polaron model, we explore excitonic and polaronic effects in X$_3$NA (X: Mg, Ca, Sr, Ba, A = Sb, As). For all of them, we uncover a significant influence of the ionic dielectric screening on the static dielectric constant. Small exciton binding energies, weak electron-phonon coupling, and high charge-carrier mobilities facilitate enhanced charge transport in Mg$_3$NSb, Sr$_3$NSb, and Ba$_3$NSb. Our results highlight the potential of these nitrides as optimal candidates for efficient photovoltaic absorbers.

Computational materials science produces large quantities of data, both in terms of high-throughput calculations and individual studies. Extracting knowledge from this large and heterogeneous pool of data is challenging due to the wide variety of computational methods and approximations, resulting in significant veracity in the sheer amount of available data. Here, we present MADAS, a Python framework for computing similarity relations between material properties. It can be used to automate the download of data from various sources, compute descriptors and similarities between materials, analyze the relationship between materials through their properties, and can incorporate a variety of existing machine learning methods. We explain the design of the package and demonstrate its power with representative examples.

Currently, many ab initio codes are being prepared for exascale computing. A first and important step is to significantly improve the efficiency of existing implementations by devising better algorithms that can accomplish the same tasks with enhanced scalability. This manuscript addresses this challenge for real-time time-dependent density functional theory in the full-potential all-electron code exciting, with a focus on systems with reduced dimensionality. Following the strategy described here, calculations can run orders of magnitude faster than before. We demonstrate this with the molecules H$_2$ and CO, achieving speedups between 98 to over 50,000. We also present an example where conventional calculations would be particularly costly, namely the inorganic/organic heterostructure of pyridine physisorbed on monolayer MoS$_2$.

The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the upcoming v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development.

The Tamura model is a particular type of 1$^{\text{st}}$ Born approximation of the phonon-isotope scattering problem. The expression for the mode-resolved phonon-isotope scattering rates in this model, derived in 1983, is still widely used in ab initio transport calculations. While the original work emphasized its applicability to low-energy acoustic phonons only, it has, nevertheless, been also applied to optical phonons in the field of phonon transport. The model has the salient feature of being a perturbation theory on top of a virtual crystal background. As such, this approach does not correspond to the proper methodology for solving the phonon-substitution defect problem in the respective limit. Here, we explore three avenues to go beyond the Tamura model and carry out calculations on a set of common materials to compare the different approaches. This work allows a systematic improvement of the treatment of phonon-isotope scattering in ab initio phonon transport, while unifying it with the general phonon-substitution scattering problem.

We present the Python package CELL, which provides a modular approach to the cluster expansion (CE) method. CELL can treat a wide variety of substitutional systems, including one-, two-, and three-dimensional alloys, in a general multi-component and multi-sublattice framework. It is capable of dealing with complex materials comprising several atoms in their parent lattice. CELL uses state-of-the-art techniques for the construction of training data sets, model selection, and finite-temperature simulations. The user interface consists of well-documented Python classes and modules (http://sol.physik.hu-berlin.de/cell/). CELL also provides visualization utilities and can be interfaced with virtually any ab initio package, total-energy codes based on interatomic potentials, and more. The usage and capabilities of CELL are illustrated by a number of examples, comprising a Cu-Pt surface alloy with oxygen adsorption, featuring two coupled binary sublattices, and the thermodynamic analysis of its order-disorder transition; the demixing transition and lattice-constant bowing of the Si-Ge alloy; and an iterative CE approach for a complex clathrate compound with a parent lattice consisting of 54 atoms.

Two-dimensional (2D) materials combine many fascinating properties that make them more interesting than their three-dimensional counterparts for a variety of applications. For example, 2D materials exhibit stronger electron-phonon and electron-hole interactions, and their energy gaps and effective carrier masses can be easily tuned. Surprisingly, published band gaps of several 2D materials obtained with the $GW$ approach, the state-of-the-art in electronic-structure calculations, are quite scattered. The details of these calculations, such as the underlying geometry, the starting point, the inclusion of spin-orbit coupling, and the treatment of the Coulomb potential can critically determine how accurate the results are. Taking monolayer MoS$_2$ as a representative material, we employ the linearized augmented planewave + local orbital method to systematically investigate how all these aspects affect the quality of $G_0W_0$ calculations, and also provide a summary of literature data. We conclude that the best overall agreement with experiments and coupled-cluster calculations is found for $G_0W_0$ results with HSE06 as a starting point including spin-orbit coupling, a truncated Coulomb potential, and an analytical treatment of the singularity at $q=0$., Comment: This version of the article has been accepted for publication, after peer review but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1038/s41524-024-01253-2

Graph-based neural networks and, specifically, message-passing neural networks (MPNNs) have shown great potential in predicting physical properties of solids. In this work, we train an MPNN to first classify materials through density functional theory data from the AFLOW database as being metallic or semiconducting/insulating. We then perform a neural-architecture search to explore the model architecture and hyperparameter space of MPNNs to predict the band gaps of the materials identified as non-metals. The parameters in the search include the number of message-passing steps, latent size, and activation-function, among others. The top-performing models from the search are pooled into an ensemble that significantly outperforms existing models from the literature. Uncertainty quantification is evaluated with Monte-Carlo Dropout and ensembling, with the ensemble method proving superior. The domain of applicability of the ensemble model is analyzed with respect to the crystal systems, the inclusion of a Hubbard parameter in the density functional calculations, and the atomic species building up the materials.

Organic/inorganic hybrid systems offer great potential for novel solar cell design combining the tunability of organic chromophore absorption properties with high charge carrier mobilities of inorganic semiconductors. However, often such material combinations do not show the expected performance: while ZnO, for example, basically exhibits all necessary properties for a successful application in light-harvesting, it was clearly outpaced by TiO$_2$ in terms of charge separation efficiency. The origin of this deficiency has long been debated. This study employs femtosecond time-resolved photoelectron spectroscopy and many-body ab initio calculations to identify and quantify all elementary steps leading to the suppression of charge separation at an exemplary organic/ZnO interface. We demonstrate that charge separation indeed occurs efficiently on ultrafast (350 fs) timescales, but that electrons are recaptured at the interface on a 100 ps timescale and subsequently trapped in a strongly bound (0.7 eV) hybrid exciton state with a lifetime exceeding 5 $\mu$s. Thus, initially successful charge separation is followed by delayed electron capture at the interface, leading to apparently low charge separation efficiencies. This finding provides a sufficiently large timeframe for counter-measures in device design to successfully implement specifically ZnO and, moreover, invites material scientists to revisit charge separation in various kinds of previously discarded hybrid systems.

A new method is presented that allows for efficient evaluation of spin-orbit coupling (SOC) in density-functional theory calculations. In the so-called second-variational scheme, where Kohn-Sham functions obtained in a scalar-relativistic calculation are employed as a new basis for the spin-orbit-coupled problem, we introduce a rich set of local orbitals as additional basis functions. Also relativistic local orbitals can be used. The method is implemented in the all-electron full-potential code \exciting. We show that, for materials with strong SOC effects, this approach can reduce the overall basis-set size and thus computational costs tremendously.

We present an x-ray absorption spectroscopy study from the carbon $K$, sulfur $K$, and sulfur $L_{2,3}$ edges of crystalline oligothiophenes of varying length, i.e., bithiophene (2T), quaterthiophene (4T), and sexithiophene (6T), performed from first principles by means of all-electron density-functional theory and many-body perturbation theory. A comprehensive assignment of all relevant spectral features is performed based on the electronic structure and the character of the target conduction states. The inclusion of electron-hole effects leads to significant redistribution of oscillator strengths and to strongly bound excitons with binding energies ranging from 1.5 to 4.5 eV. When going from 2T to 6T, exciton binding energies decrease by up to 1 eV, which we attribute to the reduction of the average Coulomb attraction with increasing oligomer length. These high values are significantly larger than their counterparts in the optical excitations of these systems and indicative of their localization on the respective molecules. For the same reason, local-field effects which typically dominate the optical absorption of organic crystals, turn out to play only a negligible role at all edges. We identify two sets of carbon atoms, i.e., with or without sulfur bonding, which exhibit distinct features at the C $K$-edge. The sulfur atoms, on the other hand, yield similar contributions in the S, $K$, and $L_{2,3}$ edge spectra. Our results show excellent agreement with available experimental data.

X-ray absorption spectroscopy (XAS) is an element-specific materials characterization technique that is sensitive to structural and electronic properties. First-principles simulated XAS has been widely used as a powerful tool to interpret experimental spectra and draw physical insights. Recently, there has also been growing interest in building computational XAS databases to enable data analytics and machine learning applications. However, there are non-trivial differences among commonly used XAS simulation codes, both in underlying theoretical formalism and in technical implementation. Reliable and reproducible computational XAS databases require systematic benchmark studies. In this work, we benchmarked Ti K-edge XAS simulations of ten representative Ti-O binary compounds, which we refer to as the Ti-O-10 dataset, using three state-of-the-art codes: xspectra, ocean and exciting. We systematically studied the convergence behavior with respect to the input parameters and developed a workflow to automate and standardize the calculations to ensure converged spectra. Our benchmark comparison shows: (1) the two Bethe-Salpeter equation (BSE) codes (ocean and exciting) have excellent agreement in the energy range studied (up to 35 eV above the onset) with an average Spearman's rank correlation score of 0.998; (2) good agreement is obtained between the core-hole potential code (xspectra) and BSE codes (ocean and exciting) with an average Spearman's rank correlation score of 0.990. Our benchmark study provides important standards for first-principles XAS simulations with broad impact in data-driven XAS analysis., Comment: 32 pages, 11 figures and 7 tables

The numerical precision of density-functional-theory (DFT) calculations depends on a variety of computational parameters, one of the most critical being the basis-set size. The ultimate precision is reached with an infinitely large basis set, i.e., in the limit of a complete basis set (CBS). Our aim in this work is to find a machine-learning model that extrapolates finite basis-size calculations to the CBS limit. We start with a data set of 63 binary solids investigated with two all-electron DFT codes, exciting and FHI-aims, which employ very different types of basis sets. A quantile-random-forest model is used to estimate the total-energy correction with respect to a fully converged calculation as a function of the basis-set size. The random-forest model achieves a symmetric mean absolute percentage error of lower than 25% for both codes and outperforms previous approaches in the literature. Our approach also provides prediction intervals, which quantify the uncertainty of the models' predictions.

We present a first-principles method for relaxing a material's geometry in an optically excited state. This method, based on the Bethe-Salpeter equation, consists of solving coupled equations for exciton wavefunctions and atomic displacements. Our approach allows for structural relaxation of excited states to be achieved through a single iteration. As results, one obtains not only energy and wavefunction of the thus modified, i.e. self-trapped, exciton, but also the mechanism of relaxation in terms of atomic displacements in the respective phonon eigenmodes. We demonstrate and evaluate our formalism with the example of the three molecules CO, H$_{2}$O, and NH$_{3}$., Comment: 5 pages, 1 figure

First-principles computational spectroscopy is a critical tool for interpreting experiment, performing structure refinement, and developing new physical understanding. Systematically setting up input files for different simulation codes and a diverse class of materials is a challenging task with a very high barrier-to-entry, given the complexities and nuances of each individual simulation package. This task is non-trivial even for experts in the electronic structure field and nearly formidable for non-expert researchers. Lightshow solves this problem by providing a uniform abstraction for writing computational x-ray spectroscopy input files for multiple popular codes, including FEFF, VASP, OCEAN, EXCITING and XSPECTRA. Its extendable framework will also allow the community to easily add new functions and to incorporate new simulation codes., Comment: 3 pages, 1 figure, software can be found open source under the BSD-3-clause license at https://github.com/AI-multimodal/Lightshow

The widely used linear-response (LR) theory of thermal conduction in the quantum regime rests on the yet unproven assumption, that the thermal conductivity is invariant with respect to the gauge of the energy density of the system. This assumption manifests itself clearly in, e.g., Hardy's formulation of the heat-flux operator [Phys. Rev. 132, 168 (1963)]. In this work, we rigorously prove this assumption. Our proof, being valid for the nuclear and electronic subsystems, not only puts the state-of-the-art theory on solid grounds, but also enables going beyond the scope of the widely-used Boltzmann transport equation (BTE) within the LR framework for many-body systems., Comment: 5 pages

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing., Comment: Submitted as a roadmap article to Modelling and Simulation in Materials Science and Engineering; Address any correspondence to Vikram Gavini (vikramg@umich.edu) and Danny Perez (danny_perez@lanl.gov)

A main goal of data-driven materials research is to find optimal low-dimensional descriptors, allowing us to predict a physical property, and to interpret them in a human-understandable way. In this work, we advance methods to identify descriptors out of a large pool of candidate features by means of compressed sensing. To this extent, we develop schemes for engineering appropriate candidate features that are based on simple basic properties of building blocks that constitute the materials and that are able to represent a multi-component system by scalar numbers. Cross-validation based feature-selection methods are developed for identifying the most relevant features, thereby focusing on high generalizability. We apply our approaches to an \textit{ab initio} dataset of ternary group-IV compounds to obtain a set of descriptors for predicting lattice constants and energies of mixing. In particular, we introduce simple complexity measures in terms of involved algebraic operations as well as the amount of utilized basic properties.

The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data principles (Findable, Accessible, Interoperable, and Reusable) must not be too narrow. Besides, the wider materials-science community ought to agree on the strategies to tackle the challenges that are specific to its data, both from computations and experiments. In this paper, we present the result of the discussions held at the workshop on "Shared Metadata and Data Formats for Big-Data Driven Materials Science". We start from an operative definition of metadata, and what features a FAIR-compliant metadata schema should have. We will mainly focus on computational materials-science data and propose a constructive approach for the FAIRification of the (meta)data related to ground-state and excited-states calculations, potential-energy sampling, and generalized workflows. Finally, challenges with the FAIRification of experimental (meta)data and materials-science ontologies are presented together with an outlook of how to meet them.

We present a formalism for the resonant inelastic x-ray scattering (RIXS) cross section. The resulting compact expression in terms of polarizability matrix elements, particularly lends itself to the implementation in an all-electron many-body perturbation theory (MBPT) framework, which is realized in the full-potential package exciting. With the carbon K edge RIXS of diamond and the oxygen K edge RIXS of $\beta-\mathrm{Ga_2 O_3}$, respectively, we demonstrate the importance of electron-hole correlation and atomic coherence in the RIXS spectra.

The prosperity and lifestyle of our society are very much governed by achievements in condensed matter physics, chemistry and materials science, because new products for sectors such as energy, the environment, health, mobility and information technology (IT) rely largely on improved or even new materials. Examples include solid-state lighting, touchscreens, batteries, implants, drug delivery and many more. The enormous amount of research data produced every day in these fields represents a gold mine of the twenty-first century. This gold mine is, however, of little value if these data are not comprehensively characterized and made available. How can we refine this feedstock; that is, turn data into knowledge and value? For this, a FAIR (findable, accessible, interoperable and reusable) data infrastructure is a must. Only then can data be readily shared and explored using data analytics and artificial intelligence (AI) methods. Making data 'findable and AI ready' (a forward-looking interpretation of the acronym) will change the way in which science is carried out today. In this Perspective, we discuss how we can prepare to make this happen for the field of materials science.

Identifying similar materials, i.e., those sharing a certain property or feature, requires interoperable data of high quality. It also requires means to measure similarity. We demonstrate how a spectral fingerprint as a descriptor, combined with a similarity metric, can be used for establishing quantitative relationships between materials data, thereby serving multiple purposes. This concerns, for instance, the identification of materials exhibiting electronic properties similar to a chosen one. The same approach can be used for assessing uncertainty in data that potentially come from different sources. Selected examples show how to quantify differences between measured optical spectra or the impact of methodology and computational parameters on calculated properties, like the the density of states or excitonic spectra. Moreover, combining the same fingerprint with a clustering approach allows us to explore materials spaces in view of finding (un)expected trends or patterns. In all cases, we provide physical reasoning behind the findings of the automatized assessment of data.

The influence of spin-orbit interaction on chemical bonds in elemental solids and homonuclear dimers is analyzed by means of density-functional-theory calculations. Employing highly precise all-electron full-potential methodology, our results represent benchmark quality. Comparison of the scalar- and fully-relativistic approaches for elemental solids shows that the spin-orbit interaction may contract or expand the volume of the considered material. The largest variation of the volume is obtained for Au, Tl, I, Bi, Po and Hg, exhibiting changes between 1.0--7.6\%. Using the tight-binding model, we show for diatomic molecules that the nature of this effect lies in the angular rearrangement of bonding and antibonding orbitals introduced by spin-orbit coupling. Such an angular rearrangement appears in partially filled $p$- or $d$-orbitals in heavy elements. Finally, we discuss the impact of the relativistic effects on the chemical bonding in single-layer iodides and transition metal dichalcogenides

The emerging interest in two-dimensional electron gases (2DEGs), formed at interfaces between two insulating oxide perovskites poses crucial fundamental question in view of future electronic devices. In the framework of density-functional theory, we investigate the possibility to control the characteristics of the 2DEG formed at the LaInO$_3$/BaSnO$_3$ interface by including a ferroelectric BaTiO$_3$ layer. To do so, we examine how the orientation of the ferroelectric polarization impacts density and confinement of the 2DEG. We find that aligning the ferroelectric polarization toward (outward) the LaInO$_3$/BaSnO$_3$ interface leads to an accumulation (depletion) of the interfacial 2DEG. Varying its magnitude, we find a linear effect on the 2DEG charge density that is confined within the BaSnO$_3$ side. Analysis of the optimized geometries revels that inclusion of the BaTiO$_3$ block makes structural distortions at the LaInO$_3$/BaSnO$_3$ less pronounced, which, in turn, enhances the 2DEG density. Thicker ferroelectric layers allow for reaching higher polarization magnitudes. We discuss the mechanisms behind all these findings and rationalize how the characteristics of both 2DEG and 2D hole gases can be controlled in the considered heterostructures. Overall, our results can be generalized to other combinations of ferroelectric, polar, and nonpolar materials.

Ehrenfest Dynamics combined with real-time time-dependent density functional theory has proven to be a reliable tool to study non-adiabatic molecular dynamics with a reasonable computational cost. Among other possibilities, it allows for assessing in real time electronic excitations generated by ultra-fast laser pulses, as e.g., in pump-probe spectroscopy, and their coupling to the nuclear vibrations even beyond the linear regime. In this work, we present its implementation in the all-electron full-potential package exciting. Three cases are presented as examples: diamond and cubic BN relaxed after an initial lattice distortion, and cubic BN exposed to a laser pulse. Comparison with the Octopus code exhibits good agreement.

Two-dimensional halide perovskites are among intensely studied materials platforms profiting from solution based growth and chemical flexibility. They feature exceptionally strong interactions among electronic, optical as well as vibrational excitations and hold a great potential for future optoelectronic applications. A key feature for these materials is the occurrence of structural phase transitions that can impact their functional properties, including the electronic band gap and optical response dominated by excitons. However, to what extent the phase-transitions in two-dimensional perovskites alter the fundamental exciton properties remains barely explored so far. Here, we study the influence of the phase transition on both exciton binding energy and exciton diffusion, demonstrating their robust nature across the phase transition. These findings are unexpected in view of the associated substantial changes of the free carrier masses, strongly contrast broadly considered effective mass and drift-diffusion transport mechanisms, highlighting the unusual nature of excitons in two-dimensional perovskites.

With the example of LaInO$_{3}$/BaSnO$_3$, we demonstrate how both density and distribution of a two-dimensional electron gas (2DEG) formed at the interface between these perovskite oxides, can be efficiently controlled by a ferroelectric functional material. A polarization induced in a BaTiO$_3$ layer pointing toward the interface enhances the polar discontinuity which, in turn, significantly increases the 2DEG density and confinement, while, the opposite polarization depletes the 2DEG. Our predictions and analysis, based on first-principles calculations, can serve as a guide for designing such material combinations to be used in electronic devices., Comment: 5 pages, 3 figures

We develop a materials descriptor based on the electronic density of states and investigate the similarity of materials based on it. As an application example, we study the Computational 2D Materials Database that hosts thousands of two-dimensional materials with their properties calculated by density-functional theory. Combining our descriptor with a clustering algorithm, we identify groups of materials with similar electronic structure. We characterize these clusters in terms of their crystal structure, their atomic composition, and the respective electronic configurations to rationalize the found (dis)similarities.

We present a first-principles investigation of the electronic and optical properties of hybrid organic-inorganic interfaces consisting of MoS$_2$ monolayer and the $\pi$-conjugate molecules pyrene and pyridine. For both hybrid systems, the quasi-particle band structure obtained from the $G_0W_0$ approximation shows -- in contrast to density-functional theory -- level alignment of type II, owing to the mutual dynamical screening of the interface constituents. $\textit{Ab initio}$ calculations of the absorption spectrum based on the Bethe-Salpeter equation reveal besides intra-layer excitons on the MoS$_2$ side, hybrid as well as charge-transfer excitons at the interface. These findings indicate that hybrid systems consisting of semiconducting transition-metal dichalcogenides and organic $\pi$-conjugate molecules can host a rich variety of optical excitations and thus provide a promising venue to explore many-body interactions and exciton physics in low dimensionality., Comment: 10 pages, 8 figures

By enabling control of valley degrees of freedom in transition-metal dichalcogenides, valley-selective circular dichroism has become a key concept in valleytronics. In this manuscript, we show that valley excitons -- bound electron-hole pairs formed at either the K or K' valleys upon absorption of circularly-polarized light -- are chiral quasiparticles characterized by a finite orbital angular momentum (OAM). We further formulate an ab-initio many-body theory of valley-selective circular dichroism and valley excitons based on the Bethe-Salpeter equation. Beside governing the interaction with circularly polarized light, the OAM confers excitons a finite magnetization which manifests itself through an excitonic Zeeman splitting upon interaction with external magnetic fields. The good agreement between our ab-initio calculations and recent experimental measurements of the exciton Zeeman shifts corroborate this picture.

Elastic and structural properties of $\beta$-Ga$_2$O$_3$ and $\alpha$-Ga$_2$O$_3$ are investigated from first principles. The full elastic tensors and elastic moduli of both phases at $0$ K are computed in the framework of semi-local density-functional theory. We determine mechanical instabilities of $\beta$-Ga$_2$O$_3$ by evaluating the full stiffness tensor under load for a range of hydrostatic pressure values. While a phase transition from the $\beta$ to $\alpha$ phase is found to be energetically favored at $2.6$ GPa, we show that the $\beta$ phase is only mechanically unstable for much higher pressures ($>30$ GPa), which agrees well with experimental results. Our employed approach is based on the Born stability criterion, is independent of crystal symmetry, and thus can be readily applied to different materials., Comment: 8 pages, 3 figures, 5 tables

Bulk hybride halide perovskites are governed by significant Rashba and Dresselhaus splitting. This indicates that such effects will not only affect their optoelectronic properties but also those of their two dimensional layered relatives. This work aims at understanding how different ways of symmetry breaking influence these effects in those materials. For this purpose, model structures are adopted where the organic compounds are replaced by Cs atoms. Disregarding possible distortions in the inorganic layers, results in structures with composition Cs$_{n+1}$Pb$_n$I$_{3n+1}$. Using the all-electron full-potential density-functional-theory code \texttt{exciting}, the impact of atomic displacement on the band structure is systematically studied for $n=1$, 2, 3 and $\infty$. The displacement patterns that yield Rashba or Dresselhaus splitting are identified, and the amount of the splitting is determined as a function of displacement. Furthermore, the spin textures in the electronic states around the band gap are analyzed to differentiate between Rashba and Dresselhaus effects. This study reveals in-plane Pb displacements as the origin of the strongest effects., Comment: 10 pages, 8 figures, 1 table

Organic-inorganic metal halide perovskites (HaPs) are intensively studied for their light-harvesting properties. Owing to the interplay between strong electron-electron interaction and spin-orbit coupling (SOC), their quantitative theoretical description is still a challenge as evidenced by the wide variety of results available in literature. Here, various methodologies for computing their electronic structure are evaluated, also accounting for SOC. More specific, the GW approach as well as variants of the hybrid functionals PBE0 and HSE are at the center of our investigations. For both functionals, we explore methods to determine the mixing parameter $\alpha$, and for HSE, we investigate the impact of the screening-parameter $\omega$. An extensive investigation of PbI2, a precursor of many HaPs, leads to the conclusion that hybrid functionals with $\alpha$ tuned by the density-based mixing method are most suitable for obtaining band gaps comparable to $G_0W_0$ results. Moreover, this methodology is transferable to CsPbI3, and the same behaviour is expected for the entire family of lead-iodine perovskites.

We derive a formula for the electrical conductivity of solids that includes relaxation, dissipation, and quantum coherence. The derivation is based on the Kubo formula, with a Mori memory function approach to include dissipation effects at all orders in the relaxation interaction. It offers a practical method to evaluate the conductivity with electronic-structure codes and avoids the complications and limitations of the Kubo formula in the thermodynamic limit. The derivation of our formula provides a method applicable to other transport coefficients and correlation functions.

By employing ab initio Migdal-Eliashberg calculations, we predict a 4-fold enhancement of the superconducting critical temperature of MgB$_{2}$ when proximity-coupled to the topological crystal Bi$_{2}$Se$_{3}$. We support this result with calculations using the general Leavens scaling method. We show that this effect is a result of dynamic resonant anti-shielding of Cooper pairs by plasmon polarons of Dirac electrons in the topological crystal. Our calculations show that such superconductivity enhancement varies strongly with Coulomb coupling between plasmon polarons and Cooper pairs, with a pronounced maximum of $\textit{T}_{c}$ at a critical value of the coupling parameter. This feature is universal, and so can occur in other superconductor-topological crystal combinations, including with non-phonon mediated superconductors. We discuss methods to experimentally optimize the key coupling parameter.

Among the transparent conducting oxides, the perovskite barium stannate is most promising for various electronic applications due to its outstanding carrier mobility achieved at room temperature. However, most of its important characteristics, such as band gaps, effective masses, and absorption edge, remain controversial. Here, we provide a fully consistent picture by combining state-of-the-art {\it ab initio} methodology with forefront electron energy-loss spectroscopy and optical absorption measurements. Valence electron energy-loss spectra, featuring signals originating from band gap transitions, are acquired on defect-free sample regions of a BaSnO$_{3}$ single crystal. These high-energy-resolution measurements are able to capture also very weak excitations below the optical gap, attributed to indirect transitions. By temperature-dependent optical absorption measurements, we assess band-gap renormalization effects induced by electron-phonon coupling. Overall, we find for the effective electronic mass, the direct and the indirect gap, the optical gap, as well as the absorption onsets and spectra, excellent agreement between both experimental techniques and the theoretical many-body results, supporting also the picture of a phonon-mediated mechanism where indirect transitions are activated by phonon-induced symmetry lowering. This work demonstrates a fruitful connection between different high-level theoretical and experimental methods for exploring the characteristics of advanced materials.

We report experimental and theoretical evidence of strong electron-plasmon interaction in n-doped single-layer MoS2. Angle-resolved photoemission spectroscopy (ARPES) measurements reveal the emergence of distinctive signatures of polaronic coupling in the electron spectral function. Calculations based on many-body perturbation theory illustrate that electronic coupling to two-dimensional (2D) carrier plasmons provides an exhaustive explanation of the experimental spectral features and their energies. These results constitute compelling evidence of the formation of plasmon-induced polaronic quasiparticles, suggesting that highly-doped transition-metal dichalcogenides may provide a new platform to explore strong-coupling phenomena between electrons and plasmons in 2D.

Two-dimensional election gases (2DEG), arising due to quantum confinement at interfaces between transparent conducting oxides, have received tremendous attention in view of electronic applications. The challenge is to find a material system that exhibits both a high charge-carrier density and mobility, at and even above room temperature. Here, we explore the potential of interfaces formed by two lattice-matched wide-gap oxides of emerging interest, $\textit{i.e.}$, the polar, orthorhombic perovskite LaInO$_{3}$ and the non-polar, cubic perovskite BaSnO$_{3}$, employing density-functional theory and many-body theory. We demonstrate that this material combination exhibits all the key features for reaching the goal. For periodic heterostructures, we find that the polar discontinuity at the interface is mainly compensated by electronic relaxation through charge transfer from the LaInO$_{3}$ to the BaSnO$_{3}$ side. This leads to the formation of a 2DEG hosted by the highly-dispersive Sn-$s$-derived conduction band and a 2D hole gas of O-$p$ character, strongly localized inside LaInO$_{3}$. Remarkably, structural distortions through octahedra tilts induce a depolarization field counteracting the polar discontinuity, and thus increasing the $critical$ (minimal) LaInO$_{3}$ thickness, $t_c$, required for the formation of a 2DEG. These polar distortions decrease with increasing LaInO$_{3}$ thickness, enhancing the polar discontinuity and leading to a 2DEG density of 0.5 electron per unit-cell surface. Interestingly, in non-periodic heterostructures, these distortions lead to a decrease of $t_c$, thereby enhancing and delocalizing the 2DEG. We rationalize how polar distortions, termination, and thickness can be exploited in view of tailoring the 2DEG characteristics, and why this material is superior to the most studied prototype LaAlO$_{3}$/SrTiO$_{3}$.

The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification., Comment: 11 pages, 1 table

Linearized augmented planewaves combined with local-orbitals (LAPW+lo) are arguably the most precise basis set to represent Kohn-Sham states. When employed within real-time time-dependent density functional theory (RT-TDDFT), they promise ultimate precision achievable for exploring the evolution of electronic excitations. In this work, we present an implementation of RT-TDDFT in the full-potential LAPW+lo code exciting. We benchmark our results against those obtained by linear-response TDDFT with exciting and by RT-TDDFT calculations with the Octopus code, finding a satisfactory level of agreement. To illustrate possible applications of our implementation, we have chosen three examples: the dynamic behavior of excitations in MoS$_2$ induced by a laser pulse, the third harmonic generation in silicon, and a pump-probe experiment in diamond.

We provide a combined theoretical and experimental study of the electronic structure and the optical absorption edge of the orthorhombic perovskite LaInO$_{3}$. Employing density-functional theory and many-body perturbation theory, we predict a direct electronic quasiparticle band gap of about 5 eV and an effective electron (hole) mass of 0.31 (0.48) m$_{0}$. We find the lowest-energy excitation at 0.2 eV below the fundamental gap, reflecting a sizeable electron-hole attraction. Since the transition from the valence band maximum (VBM, $\Gamma$ point) is, however, dipole forbidden the onset is characterized by weak excitations from transitions around it. The first intense excitation appears about 0.32 eV above. Interestingly, this value coincides with an experimental value obtained by ellipsometry (4.80 eV) which is higher than the onset from optical absorption spectroscopy (4.35 eV). The latter discrepancy is attributed to the fact that the weak transitions that define the optical gap are not resolved by the ellipsometry measurement. The absorption edge shows a strong dependency on the light polarization, reflecting the character of the involved valence states. Temperature-dependent measurements show a redshift of the optical gap by about 120 meV by increasing the temperature from 5 to 300 K. Renormalization due to zero-point vibrations is extrapolated from the latter measurement to amount to 150 meV. By adding the excitonic binding energy of 0.2 eV obtained theoretically to the experimental optical absorption onset, we determine the fundamental band gap at room temperature to be 4.55 eV.

Here we report the optical and x-ray absorption (XAS) spectra of the wide-band-gap oxide MgO using density functional theory (DFT) and many-body perturbation theory (MBPT). Our comprehensive study of the electronic structure shows that while the band gap is underestimated with the exchange-correlation functional PBEsol (4.58 eV) and the hybrid functional HSE06 (6.58 eV) compared to the experimental value (7.7 eV), it is significantly improved (7.52 eV) and even overcompensated (8.53 eV) when quasiparticle corrections are considered. Inclusion of excitonic effects by solving the Bethe-Salpeter equation (BSE) yields the optical spectrum in excellent agreement with experiment. Excellent agreement is observed also for the O and Mg K-edge absorption spectra, demonstrating the importance of the electron-hole interaction within MBPT. Projection of the electron-hole coupling coefficients from the BSE eigenvectors on the band structure allows us to determine the origin of prominent peaks and identify the orbital character of the relevant contributions. The real space projection of the lowest energy exciton wavefunction of the optical spectrum indicates a Wannier-Mott type, whereas the first exciton in the O K-edge is more localized.

On the quest for efficient thermoelectrics, semiconducting behavior is a targeted property. Yet, this is often difficult to achieve due to the complex interplay between electronic structure, temperature, and disorder. We find this to be the case for the thermoelectric clathrate Ba$_8$Al$_{16}$Si$_{30}$: Although this material exhibits a band gap in its groundstate, a temperature-driven partial order-disorder transition leads to its effective closing. This finding is enabled by a novel approach to calculate the temperature-dependent effective band structure of alloys. Our method fully accounts for the effects of short-range order and can be applied to complex alloys with many atoms in the primitive cell, without relying on effective medium approximations., Comment: 5 pages, 3 figures