Classical and quantum trial wave functions in auxiliary-field quantum Monte Carlo applied to oxygen allotropes and a CuBr2 model system.

In this work, we test a recently developed method to enhance classical auxiliary-field quantum Monte Carlo (AFQMC) calculations with quantum computers against examples from chemistry and material science, representative of classes of industry-relevant systems. As molecular test cases, we calculate the energy curve of H4 and the relative energies of ozone and singlet molecular oxygen with respect to triplet molecular oxygen, which is industrially relevant in organic oxidation reactions. We find that trial wave functions beyond single Slater determinants improve the performance of AFQMC and allow it to generate energies close to chemical accuracy compared to full configuration interaction or experimental results. In the field of material science, we study the electronic structure properties of cuprates through the quasi-1D Fermi-Hubbard model derived from CuBr2, where we find that trial wave functions with both significantly larger fidelities and lower energies over a mean-field solution do not necessarily lead to AFQMC results closer to the exact ground state energy.

Conformational Gap Control in CsTaS3.

Simple arguments based on orbital energies and crystal symmetry suggest the band gap of CsTaS3 to be suitable for solar cell photovoltaics. Here, we combine chemical theory with sophisticated calculations to describe an intricate relationship between the structure and optical properties of this material. Orbital interactions govern both the presence and nature of CsTaS3's gap. In the first place, through a second-order Jahn-Teller (JT) distortion, which slides the Ta ion along the axial direction of TaS3 chains. This displacement creates a gap that remains direct in the face of minor distortions. Using an advanced methodology, compressive sensing lattice dynamics, we compute the anharmonic interatomic force constants up to the fourth order and use them to renormalize the phonons at finite temperatures. This analysis predicts CsTaS3 to undergo the JT metal-to-semiconductor transition at temperatures below 1000 K. At around room temperature, we find a second distortion that moves the Ta ion along the equatorial direction of the TaS3 chains, giving rise to many possible supercell conformations. By relaxing all symmetry-inequivalent structures with Ta ion displacements, in supercells with up to 12 formula units, we obtain 204 symmetrically distinct conformations and sort them by energy and (direct) band gap magnitude. Since all structures with a gap lie within an energy range of 30 meV/Ta above the ground state, we expect CsTaS3's optical properties to be controlled by the full polymorphic ensemble of gapped conformations. Using the GW-Bethe-Salpeter approach, we predict a band gap of 1.3-1.4 eV as well as potent absorption in the visible range.

The 2021 room-temperature superconductivity roadmap.

Designing materials with advanced functionalities is the main focus of contemporary solid-state physics and chemistry. Research efforts worldwide are funneled into a few high-end goals, one of the oldest, and most fascinating of which is the search for an ambient temperature superconductor (A-SC). The reason is clear: superconductivity at ambient conditions implies being able to handle, measure and access a single, coherent, macroscopic quantum mechanical state without the limitations associated with cryogenics and pressurization. This would not only open exciting avenues for fundamental research, but also pave the road for a wide range of technological applications, affecting strategic areas such as energy conservation and climate change. In this roadmap we have collected contributions from many of the main actors working on superconductivity, and asked them to share their personal viewpoint on the field. The hope is that this article will serve not only as an instantaneous picture of the status of research, but also as a true roadmap defining the main long-term theoretical and experimental challenges that lie ahead. Interestingly, although the current research in superconductor design is dominated by conventional (phonon-mediated) superconductors, there seems to be a widespread consensus that achieving A-SC may require different pairing mechanisms.In memoriam, to Neil Ashcroft, who inspired us all.

Autonomous materials synthesis via hierarchical active learning of nonequilibrium phase diagrams.

Autonomous experimentation enabled by artificial intelligence offers a new paradigm for accelerating scientific discovery. Nonequilibrium materials synthesis is emblematic of complex, resource-intensive experimentation whose acceleration would be a watershed for materials discovery. We demonstrate accelerated exploration of metastable materials through hierarchical autonomous experimentation governed by the Scientific Autonomous Reasoning Agent (SARA). SARA integrates robotic materials synthesis using lateral gradient laser spike annealing and optical characterization along with a hierarchy of AI methods to map out processing phase diagrams. Efficient exploration of the multidimensional parameter space is achieved with nested active learning cycles built upon advanced machine learning models that incorporate the underlying physics of the experiments and end-to-end uncertainty quantification. We demonstrate SARA's performance by autonomously mapping synthesis phase boundaries for the Bi2O3 system, leading to orders-of-magnitude acceleration in the establishment of a synthesis phase diagram that includes conditions for stabilizing δ-Bi2O3 at room temperature, a critical development for electrochemical technologies.

Optical Identification of Materials Transformations in Oxide Thin Films.

Recent advances in high-throughput experimentation for combinatorial studies have accelerated the discovery and analysis of materials across a wide range of compositions and synthesis conditions. However, many of the more powerful characterization methods are limited by speed, cost, availability, and/or resolution. To make efficient use of these methods, there is value in developing approaches for identifying critical compositions and conditions to be used as a priori knowledge for follow-up characterization with high-precision techniques, such as micrometer-scale synchrotron-based X-ray diffraction (XRD). Here, we demonstrate the use of optical microscopy and reflectance spectroscopy to identify likely phase-change boundaries in thin film libraries. These methods are used to delineate possible metastable phase boundaries following lateral-gradient laser spike annealing (lg-LSA) of oxide materials. The set of boundaries are then compared with definitive determinations of structural transformations obtained using high-resolution XRD. We demonstrate that the optical methods detect more than 95% of the structural transformations in a composition-gradient La-Mn-O library and a Ga2O3 sample, both subject to an extensive set of lg-LSA anneals. Our results provide quantitative support for the value of optically detected transformations as a priori data to guide subsequent structural characterization, ultimately accelerating and enhancing the efficient implementation of micrometer-resolution XRD experiments.

Low-Energy Phases of Bi Monolayer Predicted by Structure Search in Two Dimensions.

We employ an ab-initio structure search algorithm to explore the configurational space of bismuth in quasi-two dimensions. A confinement potential is introduced to restrict the movement of atoms within a predefined thickness to find the stable and metastable forms of monolayer Bi. In addition to the two known low-energy structures (puckered monoclinic and buckled hexagonal), our calculations predict three new phases: α, ß, and γ. Each phase exhibits peculiar electronic properties, ranging from metallic (α and γ) to semiconducting (puckered monoclinic, buckled hexagonal, and ß) monolayers. Topologically nontrivial features are predicted for buckled hexagonal and γ phases. We also remark on the role of 5d electrons on the electronic properties of Bi monolayer. We conclude that Bi provides a rich playground to study distortion-mediated metal-insulator phase transitions in quasi-2D.

Optimized symmetry functions for machine-learning interatomic potentials of multicomponent systems.

Current machine-learning methods to reproduce ab initio potential energy landscapes suffer from an unfavorable computational scaling with respect to the number of chemical species. In this work, we propose a new approach by using optimized symmetry functions to explore similarities of structures in multicomponent systems in order to yield linear complexity. We combine these symmetry functions with the charge equilibration via neural network technique, a reliable artificial neural network potential for ionic materials, and apply this method to study alkali-halide materials MX with 6 chemical species (M = {Li, Na, K} and X = {F, Cl, Br}). Our results show that our approach provides good agreement both with experimental and DFT reference data of many physical and structural properties for any chemical combination.

First-Principles Study of Lithium Cobalt Spinel Oxides: Correlating Structure and Electrochemistry.

Embedding a lithiated cobalt oxide spinel (Li2Co2O4, or LiCoO2) component or a nickel-substituted LiCo1- xNi xO2 analogue in structurally integrated cathodes such as xLi2MnO3·(1- x)LiM'O2 (M' = Ni/Co/Mn) has been recently proposed as an approach to advance the performance of lithium-ion batteries. Here, we first revisit the phase stability and electrochemical performance of LiCoO2 synthesized at different temperatures using density functional theory calculations. Consistent with previous studies, we find that the occurrence of low- and high-temperature structures (i.e., cubic lithiated spinel LT-LiCoO2; or Li2Co2O4 ( Fd3̅ m) vs trigonal-layered HT-LiCoO2 ( R3̅ m), respectively) can be explained by a small difference in the free energy between these two compounds. Additionally, the observed voltage profile of a Li/LiCoO2 cell for both cubic and trigonal phases of LiCoO2, as well as the migration barrier for lithium diffusion from an octahedral (Oh) site to a tetrahedral site (Td) in Fd3̅ m LT-Li1- xCoO2, has been calculated to help understand the complex electrochemical charge/discharge processes. A search of LiCo xM1- xO2 lithiated spinel (M = Ni or Mn) structures and compositions is conducted to extend the exploration of the chemical space of Li-Co-Mn-Ni-O electrode materials. We predict a new lithiated spinel material, LiNi0.8125Co0.1875O2 ( Fd3̅ m), with a composition close to that of commercial, layered LiNi0.8Co0.15Al0.05O2, which may have the potential for exploitation in structurally integrated, layered spinel cathodes for next-generation lithium-ion batteries.

Prediction of superconducting iron-bismuth intermetallic compounds at high pressure.

The synthesis of materials in high-pressure experiments has recently attracted increasing attention, especially since the discovery of record breaking superconducting temperatures in the sulfur-hydrogen and other hydrogen-rich systems. Commonly, the initial precursor in a high pressure experiment contains constituent elements that are known to form compounds at ambient conditions, however the discovery of high-pressure phases in systems immiscible under ambient conditions poses an additional materials design challenge. We performed an extensive multi component ab initio structural search in the immiscible Fe-Bi system at high pressure and report on the surprising discovery of two stable compounds at pressures above ≈36 GPa, FeBi2 and FeBi3. According to our predictions, FeBi2 is a metal at the border of magnetism with a conventional electron-phonon mediated superconducting transition temperature of Tc = 1.3 K at 40 GPa.

Discovery of a Superconducting Cu-Bi Intermetallic Compound by High-Pressure Synthesis.

A new intermetallic compound, the first to be structurally identified in the Cu-Bi binary system, is reported. This compound is accessed by high-pressure reaction of the elements. Its detailed characterization, physical property measurements, and ab initio calculations are described. The commensurate crystal structure of Cu11 Bi7 is a unique variation of the NiAs structure type. Temperature-dependent electrical resistivity and heat capacity measurements reveal a bulk superconducting transition at Tc =1.36 K. Density functional theory calculations further demonstrate that Cu11 Bi7 can be stabilized (relative to decomposition into the elements) at high pressure and temperature. These results highlight the ability of high-pressure syntheses to allow for inroads into heretofore-undiscovered intermetallic systems for which no thermodynamically stable binaries are known.

Ultralow Thermal Conductivity in Full Heusler Semiconductors.

Semiconducting half and, to a lesser extent, full Heusler compounds are promising thermoelectric materials due to their compelling electronic properties with large power factors. However, intrinsically high thermal conductivity resulting in a limited thermoelectric efficiency has so far impeded their widespread use in practical applications. Here, we report the computational discovery of a class of hitherto unknown stable semiconducting full Heusler compounds with ten valence electrons (X_{2}YZ, X=Ca, Sr, and Ba; Y=Au and Hg; Z=Sn, Pb, As, Sb, and Bi) through high-throughput ab initio screening. These new compounds exhibit ultralow lattice thermal conductivity κ_{L} close to the theoretical minimum due to strong anharmonic rattling of the heavy noble metals, while preserving high power factors, thus resulting in excellent phonon-glass electron-crystal materials.

A fingerprint based metric for measuring similarities of crystalline structures.

Measuring similarities/dissimilarities between atomic structures is important for the exploration of potential energy landscapes. However, the cell vectors together with the coordinates of the atoms, which are generally used to describe periodic systems, are quantities not directly suitable as fingerprints to distinguish structures. Based on a characterization of the local environment of all atoms in a cell, we introduce crystal fingerprints that can be calculated easily and define configurational distances between crystalline structures that satisfy the mathematical properties of a metric. This distance between two configurations is a measure of their similarity/dissimilarity and it allows in particular to distinguish structures. The new method can be a useful tool within various energy landscape exploration schemes, such as minima hopping, random search, swarm intelligence algorithms, and high-throughput screenings.

Materials Design On-the-Fly.

The dream of any solid-state theorist is to be able to predict new materials with tailored properties from scratch, i.e., without any input from experiment. Over the past decades, we have steadily approached this goal. Recent developments in the field of high-throughput calculations focused on finding the best material for specific applications. However, a key input for these techniques still had to be obtained experimentally, namely, the crystal structure of the materials. Here, we give a step further and show that one can indeed optimize material properties using as a single starting point the knowledge of the periodic table and the fundamental laws of quantum mechanics. This is done by combining state-of-the-art methods of global structure prediction that allow us to obtain the ground-state crystal structure of arbitrary materials, with an evolutionary algorithm that optimizes the chemical composition for the desired property. As a first showcase demonstration of our method, we perform an unbiased search for superhard materials and for transparent conductors. We stress that our method is completely general and can be used to optimize any property (or combination of properties) that can be calculated in a computer.

Novel phases of lithium-aluminum binaries from first-principles structural search.

Intermetallic Li-Al compounds are on the one hand key materials for light-weight engineering, and on the other hand, they have been proposed for high-capacity electrodes for Li batteries. We determine from first-principles the phase diagram of Li-Al binary crystals using the minima hopping structural prediction method. Beside reproducing the experimentally reported phases (LiAl, Li3Al2, Li9Al4, LiAl3, and Li2Al), we unveil a structural variety larger than expected by discovering six unreported binary phases likely to be thermodynamically stable. Finally, we discuss the behavior of the elastic constants and of the electric potential profile of all Li-Al stable compounds as a function of their stoichiometry.

Minima hopping guided path search: an efficient method for finding complex chemical reaction pathways.

The Minima Hopping global optimization method uses physically realizable molecular dynamics moves in combination with an energy feedback that guarantees the escape from any potential energy funnel. For the purpose of finding reaction pathways, we argue that Minima Hopping is particularly suitable as a guide through the potential energy landscape and as a generator for pairs of minima that can be used as input structures for methods capable of finding transition states between two minima. For Lennard-Jones benchmark systems we compared this Minima Hopping guided path search method to a known approach for the exploration of potential energy landscapes that is based on deterministic mode-following. Although we used a stabilized mode-following technique that reliably allows to follow distinct directions when escaping from a local minimum, we observed that Minima Hopping guided path search is far superior in finding lowest-barrier reaction pathways. We, therefore, suggest that Minima Hopping guided path search can be used as a simple and efficient way to identify energetically low-lying chemical reaction pathways. Finally, we applied the Minima Hopping guided path search approach to 75-atom and 102-atom Lennard-Jones systems. For the 75-atom system we found pathways whose highest energies are significantly lower than the highest energy along the previously published lowest-barrier pathway. Furthermore, many of these pathways contain a smaller number of intermediate transition states than the previously publish lowest-barrier pathway. In case of the 102-atom system Minima Hopping guided path search found a previously unknown and energetically low-lying funnel.

Isomerism and structural fluxionality in the Au26 and Au26(-) nanoclusters.

Using the minima hopping global optimization method at the density functional level, we found low-energy nanostructures for neutral Au26 and its anion. The local-density and a generalized gradient approximation of the exchange­correlation functional predict different nanoscale motifs. We found a vast number of isomers within a small energy range above the respective putative global minima with each method. Photoelectron spectroscopy of Au26(-) under different experimental conditions revealed definitive evidence of the presence of multiple isomers, consistent with the theoretical predictions. Comparison between the experimental and simulated photoelectron spectra suggests that the photoelectron spectra of Au26(-) contain a mixture of three isomers, all of which are low-symmetry core­shell-type nanoclusters with a single internal Au atom. We present a disconnectivity graph for Au26(-) that has been computed completely at the density functional level. The transition states used to build this disconnectivity graph are complete enough to predict Au26(-) to have a possible fluxional shell, which facilitates the understanding of its catalytic activity.

Comment on "Towards direct-gap silicon phases by the inverse band structure design approach".

A Comment on the Letter by H. J. Xiang, B. Huang, E. Kan, S.-H. Wei, and X. G. Gong, [Phys. Rev. Lett. 110, 118702 (2013).

First-principles predicted low-energy structures of NaSc(BH4)4.

According to previous interpretations of experimental data, sodium-scandium double-cation borohydride NaSc(BH4)4 crystallizes in the crystallographic space group Cmcm where each sodium (scandium) atom is surrounded by six scandium (sodium) atoms. A careful investigation of this phase based on ab initio calculations indicates that the structure is dynamically unstable and gives rise to an energetically and dynamically more favorable phase with C2221 symmetry and nearly identical x-ray diffraction pattern. By additionally performing extensive structural searches with the minima-hopping method we discover a class of new low-energy structures exhibiting a novel structural motif in which each sodium (scandium) atom is surrounded by four scandium (sodium) atoms arranged at the corners of either a rectangle with nearly equal sides or a tetrahedron. These new phases are all predicted to be insulators with band gaps of 7.9-8.2 eV. Finally, we estimate the influence of these structures on the hydrogen-storage performance of NaSc(BH4)4.

Conducting boron sheets formed by the reconstruction of the α-boron (111) surface.

Systematic ab initio structure prediction was applied for the first time to predict low energy surface reconstructions by employing the minima hopping method on the α-boron (111) surface. Novel reconstruction geometries were identified and carefully characterized in terms of structural and electronic properties. Our calculations predict the formation of a planar, monolayer sheet at the surface, which is responsible for conductive surface states. Furthermore, the isolated boron sheet is shown to be the ground state 2D structure in vacuum at a hole density of η=1/5 and is therefore a potential candidate as a precursor for boron nanostructures.

Low-energy polymeric phases of alanates.

Low-energy structures of alanates are currently known to be described by patterns of isolated, nearly ideal tetrahedral [AlH4] anions and metal cations. We discover that the novel polymeric motif recently proposed for LiAlH4 plays a dominant role in a series of alanates, including LiAlH4, NaAlH4, KAlH4, Mg(AlH4)2, Ca(AlH4)2, and Sr(AlH4)2. In particular, most of the low-energy structures discovered for the whole series are characterized by networks of corner-sharing [AlH6] octahedra, forming wires and/or planes throughout the materials. Finally, for Mg(AlH4)2 and Sr(AlH4)2, we identify two polymeric phases to be lowest in energy at low temperatures.