Transparent Conductors (TCs) exhibit optical transparency and electron conductivity, and are essential for many opto-electronic and photo-voltaic devices. The most common TCs are electron-doped oxides, which are limited in the choice of possible dopants, as transitions metals most often are not suitable, in view of their tendency to form strong bond with oxygen. Non-oxides TCs have the potential of extending the class of materials to the magnetic realm, bypass technological bottlenecks, and bring TCs to the field of spintronics. Here we propose new functional materials that combine transparency and conductivity with magnetic spin polarization that can be used for spintronic applications, such as spin filters. By using high-throughput first- principles techniques, we identified a large number of potential TCs, including non-oxides materials. Our results indicate that proper doping with transition metals introduces a finite magnetization that can provide spin filtering up to 90% in the electrical conductivity, still maintaining a transparency greater than 90%.

A new sphalerite derivative compound, Cu 7 VSnS 8 , for thermoelectric applications was discovered using the pseudo-binary approach within the “Cu 3 SnS 4 ”–“Cu 4 VS 4 ” system.

In the past decades many density-functional theory methods and codes adopting periodic boundary conditions have been developed and are now extensively used in condensed matter physics and materials science research. Only in 2016, however, their precision (i.e., to which extent properties computed with different codes agree among each other) was systematically assessed on elemental crystals: a first crucial step to evaluate the reliability of such computations. We discuss here general recommendations for verification studies aiming at further testing precision and transferability of density-functional-theory computational approaches and codes. We illustrate such recommendations using a greatly expanded protocol covering the whole periodic table from Z=1 to 96 and characterizing 10 prototypical cubic compounds for each element: 4 unaries and 6 oxides, spanning a wide range of coordination numbers and oxidation states. The primary outcome is a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve nine pseudopotential-based approaches. Such effort is facilitated by deploying AiiDA common workflows that perform automatic input parameter selection, provide identical input/output interfaces across codes, and ensure full reproducibility. Finally, we discuss the extent to which the current results for total energies can be reused for different goals (e.g., obtaining formation energies).

Copper-rich sulfides are very promising for energy conversion applications due to their environmental compatibility, cost effectiveness, and earth abundance. Based on a comparative analysis of the structural and transport properties of Cu3BiS3 with those of tetrahedrite (Cu12Sb4S13) and other Cu-rich sulfides, we highlight the role of the cationic coordination types and networks on the electrical and thermal properties. By precession-assisted 3D electron diffraction analysis, we find very high anisotropic thermal vibration of copper attributed to its 3-fold coordination, with an anisotropic atomic displacement parameter up to 0.09 Å2. Density functional theory calculations reveal that these Cu atoms are weakly bonded and give rise to low-energy Einstein-like vibrational modes that strongly scatter heat-carrying acoustic phonons, leading to ultralow thermal conductivity. Importantly, we demonstrate that the 3-fold coordination of copper in Cu3BiS3 and in other copper-rich sulfides constituted of interconnected CuS3 networks causes a hole blockade. This phenomenon hinders the possibility of optimizing the carrier concentration and electronic properties through mixed valency Cu+/Cu2+, differently from tetrahedrite and most other copper-rich chalcogenides, where the main interconnected Cu-S network is built of CuS4 tetrahedra. The comparison with various copper-rich sulfides demonstrates that seeking for frameworks characterized by the coexistence of tetrahedral and 3-fold coordinated copper is very attractive for the discovery of efficient thermoelectric copper-rich sulfides. Considering that lattice vibrations and carrier concentration are key factors for engineering transport phenomena (electronic, phonon, ionic, etc.) in copper-rich chalcogenides for various types of applications, our findings improve the guidelines for the design of materials enabling sustainable energy solutions with wide-ranging applications.

We aim at exploring the potential of quantum computation to solve practical problems that are currently targeted by "traditional" high performance computing (HPC). Along the way, we will develop theoretical frameworks and algorithmic strategies. We propose computational research activities that will advance the application of quantum computers to selected materials/molecular properties: (1) Band structure of solids; (2) Molecular electronic/vibronic properties; (3) Free energies and phase transitions.

Copper-based sulfide semiconductors with the structure based on a sphalerite-like network can provide environmentally sound solutions to thermoelectric and photovoltaic energy conversion at a low cost. In this study, we report the synthesis and characterization of a copper-based sulfide, Cu(3)0Ti(6)Sb(2)S(32), discovered within the pseudobinary Cu3SbS4-Cu4TiS4 system. This new compound crystallizes in a colusite-like cubic structure, which is characterized by "interstitial" Ti atoms forming tetrahedral-octahedral [TiS4]Cu-6 complexes linearly arranged within the Cu-S corner-sharing matrix. The [TiS4]Cu-6 unit arrangement distinguishes the crystal structures of Cu26Ti2Sb6S32 (isolated units, 0D linkage), Cu30Ti6Sb2S32 (chain of linked units, 1D), and Cu4TiS4 (plane of linked units, 2D). We emphasize the semiconducting nature and the low thermal conductivity. The electronic structure and vibrational properties are investigated by the combination of experiments and first-principles calculations. We demonstrate that a design approach based on the pseudobinary composition, here, with the generic formula (Cu3SbS4)(1-x) (Cu4TiS4)( x ), is a fruitful direction for the discovery of new copper-based sulfides with tunable transport properties.

The realization of novel technological opportunities given by computational and autonomous materials design requires efficient and effective frameworks. For more than two decades, aflow++ (Automatic-Flow Framework for Materials Discovery) has provided an interconnected collection of algorithms and workflows to address this challenge. This article contains an overview of the software and some of its most heavily-used functionalities, including algorithmic details, standards, and examples. Key thrusts are highlighted: the calculation of structural, electronic, thermodynamic, and thermomechanical properties in addition to the modeling of complex materials, such as high-entropy ceramics and bulk metallic glasses. The aflow++ software prioritizes interoperability, minimizing the number of independent parameters and tolerances. It ensures consistency of results across property sets - facilitating machine learning studies. The software also features various validation schemes, offering real-time quality assurance for data generated in a high-throughput fashion. Altogether, these considerations contribute to the development of large and reliable materials databases that can ultimately deliver future materials systems

Understanding the relationship between the crystal structure, chemical bonding, and lattice dynamics is crucial for the design of materials with low thermal conductivities, which are essential in fields as diverse as thermoelectrics, thermal barrier coatings, and optoelectronics. The bismuthinite-aikinite series, Cu1–x□xPb1–xBi1+xS3 (0 ≤ x ≤ 1, where □ represents a vacancy), has recently emerged as a family of n-type semiconductors with exceptionally low lattice thermal conductivities. We present a detailed investigation of the structure, electronic properties, and the vibrational spectrum of aikinite, CuPbBiS3 (x = 0), in order to elucidate the origin of its ultralow thermal conductivity (0.48 W m–1 K–1 at 573 K), which is close to the calculated minimum for amorphous and disordered materials, despite its polycrystalline nature. Inelastic neutron scattering data reveal an anharmonic optical phonon mode at ca. 30 cm–1, attributed mainly to the motion of Pb2+ cations. Analysis of neutron diffraction data, together with ab-initio molecular dynamics simulations, shows that the Pb2+ lone pairs are rotating and that, with increasing temperature, Cu+ and Pb2+ cations, which are separated at distances of ca. 3.3 Å, exhibit significantly larger displacements from their equilibrium positions than Bi3+ cations. In addition to bond heterogeneity, a temperature-dependent interaction between Cu+ and the rotating Pb2+ lone pair is a key contributor to the scattering effects that lower the thermal conductivity in aikinite. This work demonstrates that coupling of rotating lone pairs and the vibrational motion is an effective mechanism to achieve ultralow thermal conductivity in crystalline materials.

Electronic transport coefficients such as the electrical conductivity, the termo-power, and the charge carrier concentration are routinely measured in a variety of application areas such as electronics or thermoelectric power-generation and cooling. Using fitting procedures, those measurements are used to infer microscopic features of the samples. The code m*2T facilitates the estimation of electronic structure parameters such as the effective masses and band energies improving the current approach by increasing the complexity of the band structure representation. The software is designed with a server-client architecture to enhance performance and scalability. The server is implemented in the Julia programming language. We illustrate the design and the efficiency of the code with selected applications, which are relevant to the optimization of thermoelectric materials. Program summary Program Title: m*2T CPC Library link to program files: https://doi .org /10 .17632 /494nj6ftbv.1 Developer's repository link: https://github .com /marcofornari /etransport .git Licensing provisions: GPLv3 Programming language: Julia, Python. Nature of problem: Electronic transport measurements are routinely used to link the functional properties exploited in electronics and energy sciences applications with the underlying electronic structure of the material under investigation. Experimentalists collect data of derived and integrated physical quantities, from which they estimate properties and parameters, e.g., nature of the conduction mechanisms and effective mass. The interpretation is based on simplistic models that rarely represent the complexity of the band structure. The code m*2T improves the current state of the art and facilitates the estimation of effective masses and energies from experimental measurements of electrical conductivity, Seebeck coefficients, and carrier concentration using a multi-valley anisotropic parabolic band structure as a model for the unknown real band structure. Experimental data can be imported and visualized to facilitate the comparison with theoretical analysis. Solution method: The Boltzmann equation within the relaxation-time approximation is used to compute the electronic transport tensors from the electronic density of states characterized in terms of a set of effective masses tensors m*i and critical energies Ei. Numerical and analytical techniques are adopted to integrate the Boltzmann equation efficiently. By tuning the features of the density of states, temperature, Fermi level, and the functional expression for the relaxation time, the software streamlines the reconstruction of the underlying electronic properties from experimental data. Additional comments including restrictions and unusual features: The software is designed with a serverclient architecture to enhance performance and scalability. The server is implemented in the Julia programming language as a stand-alone library. It performs all the numerical operations to compute the transport tensors from a set of multi-valley parabolic band structures. The client is implemented either

Understanding the mechanism that connects heat transport with crystal structures and order/disorder phenomena is crucial to develop materials with ultralow thermal conductivity (κ), for thermoelectric and thermal barrier applications, and requires the study of highly pure materials. We synthesized the n-type sulfide CuPbBi5S9 with an ultralow κ value of 0.6-0.4 W m-1 K-1 in the temperature range 300-700 K. In contrast to prior studies, we show that this synthetic sulfide does not exhibit the ordered gladite mineral structure but instead forms a copper-deficient disordered aikinite structure with partial Pb replacement by Bi, according to the chemical formula Cu1/3□2/3Pb1/3Bi5/3S3. By combining experiments and lattice dynamics calculations, we elucidated that the ultralow κ value of this compound is due to very low energy optical modes associated with Pb and Bi ions and, to a smaller extent, Cu. This vibrational complexity at low energy hints at substantial anharmonic effects that contribute to enhance phonon scattering. Importantly, we show that this aikinite-type sulfide, despite being a poor semiconductor, is a potential matrix for designing novel, efficient n-type thermoelectric compounds with ultralow κ values. A drastic improvement in the carrier concentration and thermoelectric figure of merit have been obtained upon Cl for S and Bi for Pb substitution. The Cu1-x□xPb1-xBi1+xS3 series provides a new, interesting structural prototype for engineering n-type thermoelectric sulfides by controlling disorder and optimizing doping.

In this paper, we perform two-layer high-throughput calculations. In the first layer, which involves changing the crystal structure and/or chemical composition, we analyze selected III–V semiconductors, filled and unfilled skutterudites, as well as rock salt and layered chalcogenides. The second layer searches the full Brillouin zone (BZ) for critical points within 1.5 eV (1 eV = 1.602176 × 10−19 J) of the Fermi level and characterizes those points by computing the effective masses. We introduce several methods to compute the effective masses from first principles and compare them to each other. Our approach also includes the calculation of the density-of-states effective masses for warped critical points, where traditional approaches fail to give consistent results due to an underlying non-analytic behavior of the critical point. We demonstrate the need to consider the band structure in its full complexity and the value of complementary approaches to compute the effective masses. We also provide computational evidence that warping occurs only in the presence of degeneracies.

Spintronic application prospects and tuning of the electrical and magnetic properties obtained in substituted clay mineral lizardites.

We highlight with first-principles molecular dynamics the persistence of intrinsic off-centerings for BaTiO 3 in its cubic paraelectric phase. Intriguingly, these are inconsistent with the Pm¯3m space group often used to atomistically model this phase using density functional theory or similar methods. Therefore we deploy a systematic symmetry analysis to construct representative structural models in the form of supercells that satisfy a desired point symmetry but are built from the combination of lower-symmetry primitive cells. We define as structural prototypes the smallest of these that are both energetically and dynamically stable. Remarkably, two 40-atom prototypes can be identified for paraelectric BaTiO 3 ; these are also common to many other ABO 3 perovskites. These prototypes can offer structural models of paraelectric phases that can be used for the computational engineering of functional materials. Last, we show that the emergence of B-cation off-centerings and the primitive-cell phonon instabilities is controlled by the equilibrium volume, in turn dictated by the filler A cation.

Regardless of its success, the constant relaxation time approximation has limited validity. Temperature and energy dependent effects are important to match experimental trends even in simple situations. We present the implementation of relaxation time approximation models in the calculation of Boltzmann transport in PAOFLOW 2.0 and apply those to model band-structures. In addition, using a self-consistent fitting of the model parameters to experimental conductivity data, we provide a flexible tool to extract scattering rates with high accuracy. We illustrate the approximations using simple models and then apply the method to GaAs, Si, Mg3Sb2, and CoSb3.

Recent research in materials science opens exciting perspectives to design novel quantum materials and devices, but it calls for quantitative predictions of properties which are not accessible in standard first principles packages. PAOFLOW is a software tool that constructs tight-binding Hamiltonians from self-consistent electronic wavefunctions by projecting onto a set of atomic orbitals. The electronic structure provides numerous materials properties that otherwise would have to be calculated via phenomenological models. In this paper, we describe recent re-design of the code as well as the new features and improvements in performance. In particular, we have implemented symmetry operations for unfolding equivalent k-points, which drastically reduces the runtime requirements of first principles calculations, and we have provided internal routines of projections onto atomic orbitals enabling generation of real space atomic orbitals. Moreover, we have included models for non-constant relaxation time in electronic transport calculations, doubling the real space dimensions of the Hamiltonian as well as the construction of Hamiltonians directly from analytical models. Importantly, PAOFLOW has been now converted into a Python package, and is streamlined for use directly within other Python codes. The new object oriented design treats PAOFLOW’s computational routines as class methods, providing an API for explicit control of each calculation.

Hyperbolic metamaterials (HMMs) are highly anisotropic optical materials that behave as metals or as dielectrics depending on the direction of propagation of light. They are becoming essential for a plethora of applications, ranging from aerospace to automotive, from wireless to medical and IoT. These applications often work in harsh environments or may sustain remarkable external stresses. This calls for materials that show enhanced optical properties as well as tailorable mechanical properties. Depending on their specific use, both hard and ultrasoft materials could be required, although the combination with optical hyperbolic response is rarely addressed. Here, we demonstrate the possibility to combine optical hyperbolicity and tunable mechanical properties in the same (meta)material, focusing on the case of extreme mechanical hardness. Using high-throughput calculations from first principles and effective medium theory, we explored a large class of layered materials with hyperbolic optical activity in the near-IR and visible range, and we identified a reduced number of ultrasoft and hard HMMs among more than 1800 combinations of transition metal rocksalt crystals. Once validated by the experiments, this new class of metamaterials may foster previously unexplored optical/mechanical applications.

The discovery of the monoclinic Cu5Sn2S7phase adds a high mobility member to the Cu–Sn–S diagram and demonstrates how the crystal structure can be advantageously manipulated to design novel compositions for energy-oriented applications.

Modeling and analysis of the materials universe is an emerging area of research with many important applications in materials science. The main goal is to create a map of materials which allows not only to visualize and navigate the materials space, but also reveal complex relationships and "connections" among materials and potentially find clusters of materials with similar properties. In this paper, we consider the problem of mapping and exploring the materials universe using network science tools and concepts. The networks are based on the open-source materials data repository AFLOW.org where each material is represented as a node, and each pair of nodes is connected by a link if the respective materials exhibit a high level of similarity between their Density of States (DOS) functions. We discuss the importance of similarity measure selection, investigate basic structural properties of the resulting networks, and demonstrate advantages and limitations of the proposed approaches. Materials networks, similarity measures, DOS function, materials informatics, network analysis, clique.