The Defects Genome of Janus Transition Metal Dichalcogenides.

2D Janus Transition Metal Dichalcogenides (TMDs) have attracted much interest due to their exciting quantum properties arising from their unique two-faced structure, broken-mirror symmetry, and consequent colossal polarization field within the monolayer. While efforts are made to achieve high-quality Janus monolayers, the existing methods rely on highly energetic processes that introduce unwanted grain-boundary and point defects with still unexplored effects on the material's structural and excitonic properties Through high-resolution scanning transmission electron microscopy (HRSTEM), density functional theory (DFT), and optical spectroscopy measurements; this work introduces the most encountered and energetically stable point defects. It establishes their impact on the material's optical properties. HRSTEM studies show that the most energetically stable point defects are single (VS and VSe) and double chalcogen vacancy (VS -VSe), interstitial defects (Mi), and metal impurities (MW) and establish their structural characteristics. DFT further establishes their formation energies and related localized bands within the forbidden band. Cryogenic excitonic studies on h-BN-encapsulated Janus monolayers offer a clear correlation between these structural defects and observed emission features, which closely align with the results of the theory. The overall results introduce the defect genome of Janus TMDs as an essential guideline for assessing their structural quality and device properties.

A substitutional quantum defect in WS2 discovered by high-throughput computational screening and fabricated by site-selective STM manipulation.

Point defects in two-dimensional materials are of key interest for quantum information science. However, the parameter space of possible defects is immense, making the identification of high-performance quantum defects very challenging. Here, we perform high-throughput (HT) first-principles computational screening to search for promising quantum defects within WS2, which present localized levels in the band gap that can lead to bright optical transitions in the visible or telecom regime. Our computed database spans more than 700 charged defects formed through substitution on the tungsten or sulfur site. We found that sulfur substitutions enable the most promising quantum defects. We computationally identify the neutral cobalt substitution to sulfur (Co S 0 ) and fabricate it with scanning tunneling microscopy (STM). The Co S 0 electronic structure measured by STM agrees with first principles and showcases an attractive quantum defect. Our work shows how HT computational screening and nanoscale synthesis routes can be combined to design promising quantum defects.

Small-pore hydridic frameworks store densely packed hydrogen.

Nanoporous materials have attracted great attention for gas storage, but achieving high volumetric storage capacity remains a challenge. Here, by using neutron powder diffraction, volumetric gas adsorption, inelastic neutron scattering and first-principles calculations, we investigate a magnesium borohydride framework that has small pores and a partially negatively charged non-flat interior for hydrogen and nitrogen uptake. Hydrogen and nitrogen occupy distinctly different adsorption sites in the pores, with very different limiting capacities of 2.33 H2 and 0.66 N2 per Mg(BH4)2. Molecular hydrogen is packed extremely densely, with about twice the density of liquid hydrogen (144 g H2 per litre of pore volume). We found a penta-dihydrogen cluster where H2 molecules in one position have rotational freedom, whereas H2 molecules in another position have a well-defined orientation and a directional interaction with the framework. This study reveals that densely packed hydrogen can be stabilized in small-pore materials at ambient pressures.

Limits to Hole Mobility and Doping in Copper Iodide.

Over one hundred years have passed since the discovery of the p-type transparent conducting material copper iodide, predating the concept of the "electron-hole" itself. Supercentenarian status notwithstanding, little is understood about the charge transport mechanisms in CuI. Herein, a variety of modeling techniques are used to investigate the charge transport properties of CuI, and limitations to the hole mobility over experimentally achievable carrier concentrations are discussed. Poor dielectric response is responsible for extensive scattering from ionized impurities at degenerately doped carrier concentrations, while phonon scattering is found to dominate at lower carrier concentrations. A phonon-limited hole mobility of 162 cm2 V-1 s-1 is predicted at room temperature. The simulated charge transport properties for CuI are compared to existing experimental data, and the implications for future device performance are discussed. In addition to charge transport calculations, the defect chemistry of CuI is investigated with hybrid functionals, revealing that reasonably localized holes from the copper vacancy are the predominant source of charge carriers. The chalcogens S and Se are investigated as extrinsic dopants, where it is found that despite relatively low defect formation energies, they are unlikely to act as efficient electron acceptors due to the strong localization of holes and subsequent deep transition levels.

High-throughput identification of spin-photon interfaces in silicon.

Color centers in host semiconductors are prime candidates as spin-photon interfaces for quantum applications. Finding an optimal spin-photon interface in silicon would move quantum information technologies toward a mature semiconducting host. However, the space of possible charged defects is vast, making the identification of candidates from experiments alone extremely challenging. Here, we use high-throughput first-principles computational screening to identify spin-photon interfaces among more than 1000 charged defects in silicon. The use of a single-shot hybrid functional approach is critical in enabling the screening of many quantum defects with a reasonable accuracy. We identify three promising spin-photon interfaces as potential bright emitters in the telecom band: [Formula: see text], [Formula: see text], and [Formula: see text]. These candidates are excited through defect-bound excitons, stressing the importance of such defects in silicon for telecom band operations. Our work paves the way to further large-scale computational screening for quantum defects in semiconductors.

Strong electron-phonon coupling driven pseudogap modulation and density-wave fluctuations in a correlated polar metal.

There is tremendous interest in employing collective excitations of the lattice, spin, charge, and orbitals to tune strongly correlated electronic phenomena. We report such an effect in a ruthenate, Ca3Ru2O7, where two phonons with strong electron-phonon coupling modulate the electronic pseudogap as well as mediate charge and spin density wave fluctuations. Combining temperature-dependent Raman spectroscopy with density functional theory reveals two phonons, B2P and B2M, that are strongly coupled to electrons and whose scattering intensities respectively dominate in the pseudogap versus the metallic phases. The B2P squeezes the octahedra along the out of plane c-axis, while the B2M elongates it, thus modulating the Ru 4d orbital splitting and the bandwidth of the in-plane electron hopping; Thus, B2P opens the pseudogap, while B2M closes it. Moreover, the B2 phonons mediate incoherent charge and spin density wave fluctuations, as evidenced by changes in the background electronic Raman scattering that exhibit unique symmetry signatures. The polar order breaks inversion symmetry, enabling infrared activity of these phonons, paving the way for coherent light-driven control of electronic transport.

A map of single-phase high-entropy alloys.

High-entropy alloys have exhibited unusual materials properties. The stability of equimolar single-phase solid solution of five or more elements is supposedly rare and identifying the existence of such alloys has been challenging because of the vast chemical space of possible combinations. Herein, based on high-throughput density-functional theory calculations, we construct a chemical map of single-phase equimolar high-entropy alloys by investigating over 658,000 equimolar quinary alloys through a binary regular solid-solution model. We identify 30,201 potential single-phase equimolar alloys (5% of the possible combinations) forming mainly in body-centered cubic structures. We unveil the chemistries that are likely to form high-entropy alloys, and identify the complex interplay among mixing enthalpy, intermetallics formation, and melting point that drives the formation of these solid solutions. We demonstrate the power of our method by predicting the existence of two new high-entropy alloys, i.e. the body-centered cubic AlCoMnNiV and the face-centered cubic CoFeMnNiZn, which are successfully synthesized.

Structural insight into the magnesium borohydride - ethylenediamine solid-state Mg-ion electrolyte system.

A highly complex crystal structure of stoichiometric Mg5(en)6(BH4)10 was solved from single crystal synchrotron X-ray diffraction and confirmed by neutron powder diffraction (NPD) on isotopically substituted Mg(en)1.2(11BD4)2. We highlight the role of the amorphous Mg(BH4)2 in the reactivity of the Mg(BH4)2-en system and characterized a previously overlooked phase, Mg(en)2(BH4)2.

Unlocking the thermoelectric potential of the Ca14AlSb11 structure type.

Yb14MnSb11 and Yb14MgSb11 are among the best p-type high-temperature (>1200 K) thermoelectric materials, yet other compounds of this Ca14AlSb11 structure type have not matched their stability and efficiency. First-principles computations show that the features in the electronic structures that have been identified to lead to high thermoelectric performances are present in Yb14ZnSb11, which has been presumed to be a poor thermoelectric material. We show that the previously reported low power factor of Yb14ZnSb11 is not intrinsic and is due to the presence of a Yb9Zn4+xSb9 impurity uniquely present in the Zn system. Phase-pure Yb14ZnSb11 synthesized through a route avoiding the impurity formation reveals its exceptional high-temperature thermoelectric properties, reaching a peak zT of 1.2 at 1175 K. Beyond Yb14ZnSb11, the favorable band structure features for thermoelectric performance are universal among the Ca14AlSb11 structure type, opening the possibility for high-performance thermoelectric materials.

Automated Bonding Analysis with Crystal Orbital Hamilton Populations.

Invited for this month's cover are researchers from Bundesanstalt für Materialforschung und -prüfung (Federal Institute for Materials Research and Testing) in Germany, Friedrich Schiller University Jena, Université catholique de Louvain, University of Oregon, Science & Technology Facilities Council, RWTH Aachen University, Hoffmann Institute of Advanced Materials, and Dartmouth College. The cover picture shows a workflow for automatic bonding analysis with Python tools (green python). The bonding analysis itself is performed with the program LOBSTER (red lobster). The starting point is a crystal structure, and the results are automatic assessments of the bonding situation based on Crystal Orbital Hamilton Populations (COHP), including automatic plots and text outputs. Coordination environments and charges are also assessed. More information can be found in the Research Article by J. George, G. Hautier, and co-workers.

Extending the low-temperature operation of sodium metal batteries combining linear and cyclic ether-based electrolyte solutions.

Nonaqueous sodium-based batteries are ideal candidates for the next generation of electrochemical energy storage devices. However, despite the promising performance at ambient temperature, their low-temperature (e.g., < 0 °C) operation is detrimentally affected by the increase in the electrolyte resistance and solid electrolyte interphase (SEI) instability. Here, to circumvent these issues, we propose specific electrolyte formulations comprising linear and cyclic ether-based solvents and sodium trifluoromethanesulfonate salt that are thermally stable down to -150 °C and enable the formation of a stable SEI at low temperatures. When tested in the Na||Na coin cell configuration, the low-temperature electrolytes enable long-term cycling down to -80 °C. Via ex situ physicochemical (e.g., X-ray photoelectron spectroscopy, cryogenic transmission electron microscopy and atomic force microscopy) electrode measurements and density functional theory calculations, we investigate the mechanisms responsible for efficient low-temperature electrochemical performance. We also report the assembly and testing between -20 °C and -60 °C of full Na||Na3V2(PO4)3 coin cells. The cell tested at -40 °C shows an initial discharge capacity of 68 mAh g-1 with a capacity retention of approximately 94% after 100 cycles at 22 mA g-1.

Automated Bonding Analysis with Crystal Orbital Hamilton Populations.

Understanding crystalline structures based on their chemical bonding is growing in importance. In this context, chemical bonding can be studied with the Crystal Orbital Hamilton Population (COHP), allowing for quantifying interatomic bond strength. Here we present a new set of tools to automate the calculation of COHP and analyze the results. We use the program packages VASP and LOBSTER, and the Python packages atomate and pymatgen. The analysis produced by our tools includes plots, a textual description, and key data in a machine-readable format. To illustrate those capabilities, we have selected simple test compounds (NaCl, GaN), the oxynitrides BaTaO2 N, CaTaO2 N, and SrTaO2 N, and the thermoelectric material Yb14 Mn1 Sb11 . We show correlations between bond strengths and stabilities in the oxynitrides and the influence of the Mn-Sb bonds on the magnetism in Yb14 Mn1 Sb11 . Our contribution enables high-throughput bonding analysis and will facilitate the use of bonding information for machine learning studies.

OPTIMADE, an API for exchanging materials data.

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.

Ferroelectricity and multiferroicity in anti-Ruddlesden-Popper structures.

Combining ferroelectricity with other properties such as visible light absorption or long-range magnetic order requires the discovery of new families of ferroelectric materials. Here, through the analysis of a high-throughput database of phonon band structures, we identify a structural family of anti-Ruddlesden-Popper phases [Formula: see text]O (A=Ca, Sr, Ba, Eu, X=Sb, P, As, Bi) showing ferroelectric and antiferroelectric behaviors. The discovered ferroelectrics belong to the new class of hyperferroelectrics that polarize even under open-circuit boundary conditions. The polar distortion involves the movement of O anions against apical A cations and is driven by geometric effects resulting from internal chemical strains. Within this structural family, we show that [Formula: see text]O combines coupled ferromagnetic and ferroelectric order at the same atomic site, a very rare occurrence in materials physics.

Structure motif-centric learning framework for inorganic crystalline systems.

Incorporation of physical principles in a machine learning (ML) architecture is a fundamental step toward the continued development of artificial intelligence for inorganic materials. As inspired by the Pauling's rule, we propose that structure motifs in inorganic crystals can serve as a central input to a machine learning framework. We demonstrated that the presence of structure motifs and their connections in a large set of crystalline compounds can be converted into unique vector representations using an unsupervised learning algorithm. To demonstrate the use of structure motif information, a motif-centric learning framework is created by combining motif information with the atom-based graph neural networks to form an atom-motif dual graph network (AMDNet), which is more accurate in predicting the electronic structures of metal oxides such as bandgaps. The work illustrates the route toward fundamental design of graph neural network learning architecture for complex materials by incorporating beyond-atom physical principles.

Discovery of multivalley Fermi surface responsible for the high thermoelectric performance in Yb14MnSb11 and Yb14MgSb11.

The Zintl phases, Yb14 MSb11 (M = Mn, Mg, Al, Zn), are now some of the highest thermoelectric efficiency p-type materials with stability above 873 K. Yb14MnSb11 gained prominence as the first p-type thermoelectric material to double the efficiency of SiGe alloy, the heritage material in radioisotope thermoelectric generators used to power NASA's deep space exploration. This study investigates the solid solution of Yb14Mg1-x Al x Sb11 (0 ≤ x ≤ 1), which enables a full mapping of the metal-to-semiconductor transition. Using a combined theoretical and experimental approach, we show that a second, high valley degeneracy (N v = 8) band is responsible for the groundbreaking performance of Yb14 MSb11 This multiband understanding of the properties provides insight into other thermoelectric systems (La3-x Te4, SnTe, Ag9AlSe6, and Eu9CdSb9), and the model predicts that an increase in carrier concentration can lead to zT > 1.5 in Yb14 MSb11 systems.

Amorphization mechanism of SrIrO3 electrocatalyst: How oxygen redox initiates ionic diffusion and structural reorganization.

The use of renewable electricity to prepare materials and fuels from abundant molecules offers a tantalizing opportunity to address concerns over energy and materials sustainability. The oxygen evolution reaction (OER) is integral to nearly all material and fuel electrosyntheses. However, very little is known about the structural evolution of the OER electrocatalyst, especially the amorphous layer that forms from the crystalline structure. Here, we investigate the interfacial transformation of the SrIrO3 OER electrocatalyst. The SrIrO3 amorphization is initiated by the lattice oxygen redox, a step that allows Sr2+ to diffuse and O2- to reorganize the SrIrO3 structure. This activation turns SrIrO3 into a highly disordered Ir octahedral network with Ir square-planar motif. The final Sr y IrO x exhibits a greater degree of disorder than IrO x made from other processing methods. Our results demonstrate that the structural reorganization facilitated by coupled ionic diffusions is essential to the disordered structure of the SrIrO3 electrocatalyst.

Electron-Phonon beyond Fröhlich: Dynamical Quadrupoles in Polar and Covalent Solids.

We include the treatment of quadrupolar fields beyond the Fröhlich interaction in the first-principles electron-phonon vertex in semiconductors. Such quadrupolar fields induce long-range interactions that have to be taken into account for accurate physical results. We apply our formalism to Si (nonpolar), GaAs, and GaP (polar) and demonstrate that electron mobilities show large errors if dynamical quadrupoles are not properly treated.

Combining phonon accuracy with high transferability in Gaussian approximation potential models.

Machine learning driven interatomic potentials, including Gaussian approximation potential (GAP) models, are emerging tools for atomistic simulations. Here, we address the methodological question of how one can fit GAP models that accurately predict vibrational properties in specific regions of configuration space while retaining flexibility and transferability to others. We use an adaptive regularization of the GAP fit that scales with the absolute force magnitude on any given atom, thereby exploring the Bayesian interpretation of GAP regularization as an "expected error" and its impact on the prediction of physical properties for a material of interest. The approach enables excellent predictions of phonon modes (to within 0.1 THz-0.2 THz) for structurally diverse silicon allotropes, and it can be coupled with existing fitting databases for high transferability across different regions of configuration space, which we demonstrate for liquid and amorphous silicon. These findings and workflows are expected to be useful for GAP-driven materials modeling more generally.

ChemEnv: a fast and robust coordination environment identification tool.

Coordination or local environments have been used to describe, analyze and understand crystal structures for more than a century. Here, a new tool called ChemEnv, which can identify coordination environments in a fast and robust manner, is presented. In contrast to previous tools, the assessment of the coordination environments is not biased by small distortions of the crystal structure. Its robust and fast implementation enables the analysis of large databases of structures. The code is available open source within the pymatgen package and the software can also be used through a web app available on http://crystaltoolkit.org through the Materials Project.