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Most quantum algorithms designed to generate or probe properties of the ground state of a quantum many-body system require as input an initial state with a large overlap with the desired ground state. One approach for preparing such a ground state is Imaginary Time Evolution (ITE). Recent work by [Motta, M., Sun, C., Tan, A.T.K. et al. (2020)] introduced an algorithm -- which we will refer to as Quantum Imaginary Time Evolution (QITE) -- that shows how ITE can be approximated by a sequence of unitary operators, making QITE potentially implementable on early fault-tolerant quantum computers. In this work, we provide a heuristic study of the capabilities of the QITE algorithm in approximating the ITE of lattice and molecular electronic structure Hamiltonians. We numerically study the performance of the QITE algorithm when provided with a good classical initial state for a large class of systems, some of which are of interest to industrial applications, and check if QITE is able to qualitatively replicate the ITE behavior and improve over a classical mean-field solution. The systems we consider in this work range from one- and two-dimensional lattice systems of various lattice geometries displaying short- and long-range interactions, to active spaces of molecular electronic structure Hamiltonians. In addition to the comparison of QITE and ITE, we explicitly show how imaginary time evolved fermionic Gaussian states can serve as initial states which can be efficiently computed on classical computers and efficiently implemented on quantum computers for generic spin Hamiltonians in arbitrary lattice geometries and dimensions, which can be of independent interest.

The Variational Quantum Eigensolver (VQE) is one of the most promising and widely used algorithms for exploiting the capabilities of current Noisy Intermediate-Scale Quantum (NISQ) devices. However, VQE algorithms suffer from a plethora of issues, such as barren plateaus, local minima, quantum hardware noise, and limited qubit connectivity, thus posing challenges for their successful deployment on hardware and simulators. In this work, we propose a VQE optimization strategy that builds upon recent advances in the literature, and exhibits very shallow circuit depths when applied to the specific system of interest, namely a model Hamiltonian representing a cuprate superconductor. These features make our approach a favorable candidate for generating good ground state approximations on current NISQ devices. Our findings illustrate the potential of VQE algorithmic development for leveraging the full capabilities of NISQ devices.

Quantum computers (QC) could harbor the potential to significantly advance materials simulations, particularly at the atomistic scale involving strongly correlated fermionic systems where an accurate description of quantum many-body effects scales unfavorably with size. While a full-scale treatment of condensed matter systems with currently available noisy quantum computers remains elusive, quantum embedding schemes like dynamical mean-field theory (DMFT) allow the mapping of an effective, reduced subspace Hamiltonian to available devices to improve the accuracy of ab initio calculations such as density functional theory (DFT). Here, we report on the development of a hybrid quantum-classical DFT+DMFT simulation framework which relies on a quantum impurity solver based on the Lehmann representation of the impurity Green's function. Hardware experiments with up to 14 qubits on the IBM Quantum system are conducted, using advanced error mitigation methods and a novel calibration scheme for an improved zero-noise extrapolation to effectively reduce adverse effects from inherent noise on current quantum devices. We showcase the utility of our quantum DFT+DMFT workflow by assessing the correlation effects on the electronic structure of a real material, Ca2CuO2Cl2, and by carefully benchmarking our quantum results with respect to exact reference solutions and experimental spectroscopy measurements., Comment: 25 pages, 6 figures, supplementary information

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions., Comment: 60 pages, 14 figures; comments welcome

X-ray diffraction (XRD) is an essential technique to determine a material's crystal structure in high-throughput experimentation, and has recently been incorporated in artificially intelligent agents in autonomous scientific discovery processes. However, rapid, automated and reliable analysis method of XRD data matching the incoming data rate remains a major challenge. To address these issues, we present CrystalShift, an efficient algorithm for probabilistic XRD phase labeling that employs symmetry-constrained pseudo-refinement optimization, best-first tree search, and Bayesian model comparison to estimate probabilities for phase combinations without requiring phase space information or training. We demonstrate that CrystalShift provides robust probability estimates, outperforming existing methods on synthetic and experimental datasets, and can be readily integrated into high-throughput experimental workflows. In addition to efficient phase-mapping, CrystalShift offers quantitative insights into materials' structural parameters, which facilitate both expert evaluation and AI-based modeling of the phase space, ultimately accelerating materials identification and discovery., Comment: 13 pages, 6 figures

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, representatives of classes of industry-relevant systems. As molecular test cases, we calculate the energy curve of H4 and relative energies of ozone and singlet molecular oxygen with respect to triplet molecular oxygen, which are industrially relevant in organic oxidation reactions. We find that trial wave functions beyond single Slater determinants improve the performance of AFQMC and allow to generate energies close to chemical accuracy compared to full configuration interaction (FCI) or experimental results. As a representative for material science we study a quasi-1D Fermi-Hubbard model derived from CuBr2, a compound displaying electronic structure properties analogous to cuprates. We find that trial wave functions with both, significantly larger fidelities and lower energies over a Hartree-Fock solution, do not necessarily lead to better AFQMC results.

We present a variational quantum thermalizer (VQT), called quantum-VQT (qVQT), which extends the variational quantum eigensolver (VQE) to finite temperatures. The qVQT makes use of an intermediate measurement between two variational circuits to encode a density matrix on a quantum device. A classical optimization provides the thermal state and, simultaneously, all associated excited states of a quantum mechanical system. We demonstrate the capabilities of the qVQT for two different spin systems. First, we analyze the performance of qVQT as a function of the circuit depth and the temperature for a 1-dimensional Heisenberg chain. Second, we use the excited states to map the complete, temperature dependent phase diagram of a 2-dimensional J1-J2 Heisenberg model. The numerical experiments demonstrate the efficiency of our approach, which can be readily applied to study various quantum many-body systems at finite temperatures on currently available NISQ devices., Comment: 10 pages, 7 figures

SiC polytypes have been studied for decades, both experimentally and with atomistic simulations, yet no consensus has been reached on the factors that determine their stability and growth. Proposed governing factors are temperature-dependent differences in the bulk energy, biaxial strain induced through point defects, and surface properties. In this work, we investigate the thermodynamic stability of the 3C, 2H, 4H, and 6H polytypes with density functional theory (DFT) calculations. The small differences of the bulk energies between the polytypes can lead to intricate changes in their energetic ordering depending on the computational method. Therefore, we employ and compare various DFT-codes: VASP, CP2K, and FHI-aims; exchange-correlation functionals: LDA, PBE, PBEsol, PW91, HSE06, SCAN, and RTPSS; and nine different van der Waals (vdW) corrections. At $T=0$~K, 4H-SiC is marginally more stable than 3C-SiC, and the stability further increases with temperature by including entropic effects from lattice vibrations. Neither the most advanced vdW corrections nor strain on the lattice have a significant effect on the relative polytype stability. We further investigate the energies of the (0001) polytype surfaces that are commonly exposed during epitaxial growth. For Si-terminated surfaces, we find 3C-SiC to be significantly more stable than 4H-SiC. We conclude that the difference in surface energy is likely the driving force for 3C-nucleation, whereas the difference in the bulk thermodynamic stability slightly favors the 4H and 6H polytypes. In order to describe the polytype stability during crystal growth correctly, it is thus crucial to take into account both of these effects., Comment: 14 pages, 12 figures

We study the thermal transport properties of three CaF$_{2}$ polymorphs up to a pressure of 30 GPa using first-principle calculations and an interatomic potential based on machine learning. The lattice thermal conductivity $\kappa$ is computed by iteratively solving the linearized Boltzmann transport equation (BTE) and by taking into account three-phonon scattering. Overall, $\kappa$ increases nearly linearly with pressure, and we show that the recently discovered $\delta$-phase with $P\bar{6}2m$ symmetry and the previously known $\gamma$-CaF$_{2}$ high-pressure phase have significantly lower lattice thermal conductivities than the ambient-thermodynamic cubic fluorite ($Fm\bar{3}m$) structure. We argue that the lower $\kappa$ of these two high-pressure phases stems mainly due to a lower contribution of acoustic modes to $\kappa$ as a result of their small group velocities. We further show that the phonon mean free paths are very short for the $P\bar{6}2m$ and $Pnma$ structures at high temperatures, and resort to the Cahill-Pohl model to assess the lower limit of thermal conductivity in these domains., Comment: 7 pages, 6 figures

Autonomous experimentation enabled by artificial intelligence (AI) offers a new paradigm for accelerating scientific discovery. Non-equilibrium materials synthesis is emblematic of complex, resource-intensive experimentation whose acceleration would be a watershed for materials discovery and development. The mapping of non-equilibrium synthesis phase diagrams has recently been accelerated via high throughput experimentation but still limits materials research because the parameter space is too vast to be exhaustively explored. We demonstrate accelerated synthesis and exploration of metastable materials through hierarchical autonomous experimentation governed by the Scientific Autonomous Reasoning Agent (SARA). SARA integrates robotic materials synthesis and characterization along with a hierarchy of AI methods that efficiently reveal the structure of processing phase diagrams. SARA designs lateral gradient laser spike annealing (lg-LSA) experiments for parallel materials synthesis and employs optical spectroscopy to rapidly identify phase transitions. Efficient exploration of the multi-dimensional parameter space is achieved with nested active learning (AL) cycles built upon advanced machine learning models that incorporate the underlying physics of the experiments as well as end-to-end uncertainty quantification. With this, and the coordination of AL at multiple scales, SARA embodies AI harnessing of complex scientific tasks. We demonstrate its performance by autonomously mapping synthesis phase boundaries for the Bi$_2$O$_3$ system, leading to orders-of-magnitude acceleration in establishment of a synthesis phase diagram that includes conditions for kinetically stabilizing $\delta$-Bi$_2$O$_3$ at room temperature, a critical development for electrochemical technologies such as solid oxide fuel cells.

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 micron-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 Ga$_2$O$_3$ 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 $\mu$m-resolution XRD experiments.

In this work we probe the possibility of high-temperature conventional superconductivity in the boron-carbon system, using ab-initio screening. A database of 320 metastable structures with fixed composition (50$\%$/50$\%$) is generated with the Minima-Hopping method, and characterized with electronic and vibrational descriptors. Full electron-phonon calculations on sixteen representative structures allow to identify general trends in $T_{\textrm{c}}$ across and within the four families in the energy landscape, and to construct an approximate $T_{\textrm{c}}$ predictor, based on transparently interpretable and easily computable electronic and vibrational descriptors. Based on these, we estimate that around 10$\%$ of all metallic structures should exhibit $T_{\textrm{c}}$'s above 30 $K$. This work is a first step towards ab-initio design of new high-$T_{\textrm{c}}$ superconductors., Comment: 16 pages, 21 figures, 1 table

FLAME is a software package to perform a wide range of atomistic simulations for exploring the potential energy surfaces (PES) of complex condensed matter systems. The range of methods include molecular dynamics simulations to sample free energy landscapes, saddle point searches to identify transition states, and gradient relaxations to find dynamically stable geometries. In addition to such common tasks, FLAME implements a structure prediction algorithm based on the minima hopping method (MHM) to identify the ground state structure of any system given solely the chemical composition, and a framework to train a neural network potential to reproduce the PES from $\textit{ab initio}$ calculations. The combination of neural network potentials with the MHM in FLAME allows a highly efficient and reliable identification of the ground state as well as metastable structures of molecules and crystals, as well as of nano structures, including surfaces, interfaces, and two-dimensional materials. In this manuscript, we provide detailed descriptions of the methods implemented in the FLAME code and its capabilities, together with several illustrative examples.

We employ an ab-initio structure search algorithm to explore the configurational space of Bi in quasi two dimensions. A confinement potential restricts the movement of atoms within a pre-defined thickness during structure search calculations within the minima hopping method to find the stable and metastable forms of bilayer Bi. In addition to recovering the two known low-energy structures (puckered monoclinic and buckled hexagonal), our calculations predict three new structures of bilayer Bi. We call these structures the $\alpha$, $\beta$, and $\gamma$ phases of bilayer Bi, which are, respectively, 63, 72, and 83 meV/atom higher in energy than that of the monoclinic ground state, and thus potentially synthesizable using appropriate substrates. We also compare the structural, electronic, and vibrational properties of the different phases. The puckered monoclinic, buckled hexagonal, and $\beta$ phases exhibit a semiconducting energy gap, whereas $\alpha$ and $\gamma$ phases are metallic. We notice an unusual Mexican-hat type band dispersion leading to a van Hove singularity in the buckled hexagonal bilayer Bi. Notably, we find symmetry-protected topological Dirac points in the electronic spectrum of the $\gamma$ phase. The new structures suggest that bilayer Bi provides a novel playground to study distortion-mediated metal-insulator phase transitions.

The compression of SH$_2$ and its subsequent decomposition to SH$_3$, presumably in a cubic Im$\overline{3}$m structure, has lead to the discovery of conventional superconductivity with the highest measured and confirmed $T_c$ to date, 203 K at 160 GPa. Recent theoretical studies suggest that a mixture of S with other elements of the chalcogen group could improve the superconducting temperature. Here, we present a detailed analysis of the thermodynamic properties of S and Se mixtures in the bcc lattice with Im$\overline{3}$m symmetry using a cluster expansion technique to explore the phase diagram of S$_x$Se$_{1-x}$H$_{3}$. In contrast to earlier reports, we find that S$_{0.5}$Se$_{0.5}$H$_3$ is not stable in the pressure range between 150-200 GPa. However, phases at compositions S$_{0.2}$Se$_{0.8}$H$_3$, S$_{0.\overline{3}}$Se$_{0.\overline{6}}$H$_3$, and S$_{0.6}$Se$_{0.4}$H$_3$ are stable at 200 GPa, while additional phases at S$_{0.25}$Se$_{0.75}$H$_3$ and S$_{0.75}$Se$_{0.25}$H$_3$ are accessible at lower pressures. Electron-phonon calculations show that the values of $T_c$ are consistently lower for all ternary phases, indicating that mixtures of S and Se with H might not be a viable route towards compounds with improved superconducting properties.

We report the computational investigation of a series of ternary X$_4$Y$_2$Z and X$_5$Y$_2$Z$_2$ compounds with X={Mg, Ca, Sr, Ba}, Y={P, As, Sb, Bi}, and Z={S, Se, Te}. The compositions for these materials were predicted through a search guided by machine learning, while the structures were resolved using the minima hopping crystal structure prediction method. Based on $\textit{ab initio}$ calculations, we predict that many of these compounds are thermodynamically stable. In particular, 21 of the X$_4$Y$_2$Z compounds crystallize in a tetragonal structure with $\textit{I-42d}$ symmetry, and exhibit band gaps in the range of 0.3 and 1.8 eV, well suited for various energy applications. We show that several candidate compounds (in particular X$_4$Y$_2$Te and X$_4$Sb$_2$Se) exhibit good photo absorption in the visible range, while others (e.g., Ba$_4$Sb$_2$Se) show excellent thermoelectric performance due to a high power factor and extremely low lattice thermal conductivities.

We perform a thorough structural search with the minima hopping method (MHM) to explore low-energy structures of methylammonium lead iodide. By combining the MHM with a forcefield, we efficiently screen vast portions of the configurational space with large simulation cells containing up to 96 atoms. Our search reveals two structures of methylammonium iodide perovskite (MAPI) that are substantially lower in energy than the well-studied experimentally observed low-temperature $Pnma$ orthorhombic phase according to density functional calculations. Both structures have not yet been reported in the literature for MAPI, but our results show that they could emerge as thermodynamically stable phases via compression at low temperatures. In terms of the electronic properties, the two phases exhibit larger band gaps than the standard perovskite-type structures. Hence, pressure induced phase selection at technologically achievable pressures (i.e., via thin-film strain) is a route towards the synthesis of several MAPI polymorph with variable band gaps.

A thorough in situ characterization of materials at extreme conditions is challenging, and computational tools such as crystal structural search methods in combination with ab initio calculations are widely used to guide experiments by predicting the composition, structure, and properties of high-pressure compounds. However, such techniques are usually computationally expensive and not suitable for large-scale combinatorial exploration. On the other hand, data-driven computational approaches using large materials databases are useful for the analysis of energetics and stability of hundreds of thousands of compounds, but their utility for materials discovery is largely limited to idealized conditions of zero temperature and pressure. Here, we present a novel framework combining the two computational approaches, using a simple linear approximation to the enthalpy of a compound in conjunction with ambient-conditions data currently available in high-throughput databases of calculated materials properties. We demonstrate its utility by explaining the occurrence of phases in nature that are not ground states at ambient conditions and estimating the pressures at which such ambient-metastable phases become thermodynamically accessible, as well as guiding the exploration of ambient-immiscible binary systems via sophisticated structural search methods to discover new stable high-pressure phases., Comment: 14 pages, 6 figures

Intermetallic compounds with sizable band gaps are attractive for their unusual properties but rare. Here, we present a new family of stable semiconducting quaternary Heusler compounds, designed and discovered by means of high-throughput \textit{ab initio} calculations based on the 18-electron rule. The 99 new semiconductors reported here adopt the ordered quaternary Heusler structure with the prototype of LiMgSnPd (F$\bar{\mathbf{4}}$3m, No.\,216) and contain 18 valence electrons per formula unit. They are realized by filling the void in the half Heusler structure with a small and electropositive atom, i.e., lithium. These new stable quaternary Heusler semiconductors possess a range of band gaps from 0.3 to 2.5\,eV, and exhibit some unusual properties different from conventional semiconductors, such as strong optical absorption, giant dielectric screening, and high Seebeck coefficient, which suggest these semiconductors have potential applications as photovoltaic and thermoelectric materials. While this study opens up avenues for further exploration of this novel class of semiconducting quaternary Heuslers, the design strategy used herein is broadly applicable across a potentially wide array of chemistries to discover new stable materials., Comment: 8 pages, 6 figures

Density Functional Theory (DFT) has become the quasi-standard for ab-initio simulations for a wide range of applications. While the intrinsic cubic scaling of DFT was for a long time limiting the accessible system size to some hundred atoms, the recent progress with respect to linear scaling DFT methods has allowed to tackle problems that are larger by many orders of magnitudes. However, as these linear scaling methods were developed for insulators, they cannot, in general, be straightforwardly applied to metals, as a finite temperature is needed to ensure locality of the density matrix. In this paper we show that, once finite electronic temperature is employed, the linear scaling version of the BigDFT code is able to exploit this locality to provide a computational treatment that scales linearly with respect to the number of atoms of a metallic system. We provide prototype examples based on bulk Tungsten, which plays a key role in finding safe and long-lasting materials for Fusion Reactors. We believe that such an approach might help in opening the path towards novel approaches for investigating the electronic structure of such materials, in particular when large supercells are required.

Although copper and bismuth do not form any compounds at ambient conditions, two intermetallics, CuBi and Cu$_{11}$Bi$_7$, were recently synthesized at high pressures. Here we report on the discovery of additional copper-bismuth phases at elevated pressures with high-densities from ab initio calculations. In particular, a Cu$_2$Bi compound is found to be thermodynamically stable at pressures above 59 GPa, crystallizing in the cubic Laves structure. In strong contrast to Cu$_{11}$Bi$_7$ and CuBi, cubic Cu$_2$Bi does not exhibit any voids or channels. Since the bismuth lone pairs in cubic Cu$_2$Bi are stereochemically inactive, the constituent elements can be closely packed and a high density of 10.52 g/cm$^{3}$ at 0 GPa is achieved. The moderate electron-phonon coupling of $\lambda=0.68$ leads to a superconducting temperature of 2 K, which exceeds the values observed both in Cu$_{11}$Bi$_7$and CuBi, as well as in elemental Cu and Bi ., Comment: 6 pages, 5 figures

We report on the ab initio discovery of a novel putative ground state for quasi two-dimensional TiO$_2$ through a structural search using the minima hopping method with an artificial neural network potential. The structure is based on a honeycomb lattice and is energetically lower than the experimentally reported lepidocrocite sheet by 7~meV/atom, and merely 13~meV/atom higher in energy than the ground state rutile bulk structure. According to our calculations, the hexagonal sheet is stable against mechanical stress, it is chemically inert and can be deposited on various substrates without disrupting the structure. Its properties differ significantly from all known TiO$_2$ bulk phases with a large gap of 5.05~eV that can be tuned through strain engineering., Comment: 8 pages, 5 figures

We report on the discovery of a 2-dimensional copper-bismuth nano sheet from \textit{ab initio} calculations, which we call cubine. According to our predictions, single layers of cubine can be isolated from the recently reported high-pressure CuBi bulk material (metastable at ambient conditions) at an energetic cost of merely $\approx 20$~meV/\AA$^2$, comparable to separating single layers of graphene from graphite. Our calculations suggest that cubine has remarkable electronic and electrochemical properties: It is a superconductor with a moderate electron-phonon coupling $\lambda=0.5$, leading to a $T_c$ of $\approx1$~K, and can be readily intercalated with lithium with a high diffusibility, rendering it a promising candidate material as an anode in lithium-ion batteries., Comment: 7 pages, 6 figures

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 $\approx36$ GPa, FeBi$_2$ and FeBi$_3$. According to our predictions, FeBi$_2$ is a metal at the border of magnetism with a conventional electron-phonon mediated superconducting transition temperature of $T_{\rm c}=1.3$ K at 40 GPa. In analogy to other iron-based materials, FeBi$_2$ is possibly a non-conventional superconductor with a real $T_{\rm c}$ significantly exceeding the values obtained within Bardeen-Cooper-Schrieffer (BCS) theory., Comment: 9 pages, 9 figures

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 ($X_2YZ$, $X$=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 $\kappa_{\text{L}}$ 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., Comment: 6 pages, 5 figures

Hydrogen-rich compounds have been extensively studied both theoretically and experimentally in the quest for novel high-temperature superconductors. Reports on sulfur-hydride attaining metallicity under pressure and exhibiting superconductivity at temperatures as high as 200 K have spurred an intense search for room-temperature superconductors in hydride materials. Recently, compressed phosphine was reported to metallize at pressures above 45 GPa, reaching a superconducting transition temperature (T$_{c}$) of 100 K at 200 GPa. However, neither the exact composition nor the crystal structure of the superconducting phase have been conclusively determined. In this work the phase diagram of PH$_n$ ($n=1,2,3,4,5,6$) was extensively explored by means of {\it ab initio} crystal structure predictions using the Minima Hopping Method (MHM). The results do not support the existence of thermodynamically stable PH$_n$ compounds, which exhibit a tendency for elemental decomposition at high pressure even when vibrational contributions to the free energies are taken into account. Although the lowest energy phases of PH$_{1,2,3}$ display T$_{c}$'s comparable to experiments, it remains uncertain if the measured values of T$_{c}$ can be fully attributed to a phase-pure compound of PH$_n$.

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 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 allow to 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 is an useful tool within various energy landscape exploration schemes, such as minima hopping, random search, swarm intelligence algorithms and high-throughput screenings.

Silicon materials play a key role in many technologically relevant fields, ranging from the electronic to the photovoltaic industry. A systematic search for silicon allotropes was performed by employing a modified ab initio minima hopping crystal structure prediction method. The algorithm was optimized to specifically investigate the hitherto barely explored low-density regime of the silicon phase diagram by imitating the guest-host concept of clathrate compounds. In total 44 metastable phases are presented, of which 11 exhibit direct or quasi-direct band-gaps in the range of $\approx$1.0-1.8 eV, close to the optimal Shockley-Queisser limit of $\approx$1.4 eV, with a stronger overlap of the absorption spectra with the solar spectrum compared to conventional diamond silicon. Due to the structural resemblance to known clathrate compounds it is expected that the predicted phases can be synthesized.

We use ab initio global structural prediction, and specifically the minima hopping method, to explore the periodic table in search of novel oxide phases. In total, we study 183 different compositions of the form MXO2, where M=(Cu, Ag, Au) and X is an element of the periodic table. This set includes the well-known Cu delafossite compounds that are, up to now, the best p-type transparent conductive oxides known to mankind. Our calculations discover 81 stable compositions, out of which only 36 are included in available databases. Some of these new phases are potentially good candidates for transparent electrodes. These results demonstrate, on one hand, how incomplete is still our knowledge of the phase-space of stable ternary materials. On the other hand, we show that structural prediction combined with high-throughput approaches is a powerful tool to extend that knowledge, paving the way for the experimental discovery of new materials on a large scale.

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 reactions 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., Comment: 15 pages, 8 figures

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 \alpha-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, mono-layer 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 \eta=1/5 and is therefore a potential candidate as a precursor for boron nano-structures.

According to previous interpretations of experimental data, sodium-scandium double-cation borohydride NaSc(BH$_4$)$_4$ 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 \textit{ab initio} calculations indicates that the structure is dynamically unstable and gives rise to an energetically and dynamically more favorable phase with $C222_1$ 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(BH$_4$)$_4$., Comment: Version published

We present novel structural motifs for boron-carbon nano-cages of the stochiometries B12C48 and B12C50, based on first principle calculations. These configurations are distinct from those proposed so far by the fact that the boron atoms are not isolated and distributed over the entire surface of the cages, but rather aggregate at one location to form a patch. Our putative ground state of B12C48 is 1.8 eV lower in energy than the previously proposed ground state and violates all the suggested empirical rules for constructing low energy fullerenes. The B12C50 configuration is energetically even more favorable than B12C48, showing that structures derived from the C60 Buckminsterfullerene are not necessarily magic sizes for heterofullerenes.

We study the thermodynamic stability at low temperatures of a series of alkali metal/zinc double-cation borohydrides, including LiZn(BH$_4$)$_3$, LiZn$_2$(BH$_4$)$_5$, NaZn(BH$_4$)$_3$, NaZn$_2$(BH$_4$)$_5$, KZn(BH$_4$)$_3$, and KZn$_2$(BH$_4$)$_5$. While LiZn$_2$(BH$_4$)$_5$, NaZn(BH$_4$)$_3$, NaZn$_2$(BH$_4$)$_5$ and KZn(BH$_4$)$_3$ were recently synthesized, LiZn(BH$_4$)$_3$ and KZn$_2$(BH$_4$)$_5$ are hypothetical compounds. Using the minima-hopping method, we discover two new lowest-energy structures for NaZn(BH$_4$)$_3$ and KZn$_2$(BH$_4$)$_5$ which belong to the $C2/c$ and $P2$ space groups, respectively. These structures are predicted to be both thermodynamically stable and dynamically stable, implying that their existence may be possible. On the other hand, the lowest-energy $P1$ structure of LiZn(BH$_4$)$_3$ is predicted to be unstable, suggesting a possible reason elucidating why this compound has not been experimentally identified. In exploring the low-energy structures of these compounds, we find that their energetic ordering is sensitive to the inclusion of the van der Waals interactions. We also find that a proper treatment of these interactions, e.g., as given by a non-local density functional such as vdW-DF2, is necessary to address the stability of the low-energy structures of these compounds., Comment: Final version

Low-energy structures of alanates are currently known to be described by patterns of isolated, nearly ideal tetrahedral [AlH$_4$] anions and metal cations. We discover that the novel polymeric motif recently proposed for LiAlH$_4$ plays a dominant role in a series of alanates, including LiAlH$_4$, NaAlH$_4$, KAlH$_4$, Mg(AlH$_4$)$_2$, Ca(AlH$_4$)$_2$ and Sr(AlH$_4$)$_2$. In particular, most of the low-energy structures discovered for the whole series are characterized by networks of corner-sharing [AlH$_6$] octahedra, forming wires and/or planes throughout the materials. Finally, for Mg(AlH$_4$)$_2$ and Sr(AlH$_4$)$_2$, we identify two polymeric phases to be lowest in energy at low temperatures., Comment: 9 pages, 8 figures, 2 tables, including supplemental material

We present a systematic study of the low-energy structures of zinc borohydride, a crystalline material proposed for the hydrogen storage purpose. In addition to the previously proposed structures, many new low-energy structures of zinc borohydride are found by utilizing the minima-hopping method. We identify a new dynamically stable structure which belongs to the $I4_122$ space group as the most stable phase of zinc borohydride at low temperatures. A low transition barrier between $I4_122$ and $P1$, the two lowest-lying phases of zinc borohydride is predicted, implying that a coexistence of low-lying phases of zinc borohydride is possible at ambient conditions. An analysis based on the simulated X-ray diffraction pattern reveals that the $I4_122$ structure exhibits the same major features as the experimentally synthesized zinc borohydride samples., Comment: Version accepted by Phys. Rev. B. Manuscript has 8 pages, 5 figures, 2 tables (with 6 pages, 5 figures, 2 tables in supplemental material)

We present state-of-the-art first-principle calculations of the electronic and optical properties of silicon allotropes with interesting characteristics for applications in thin-film solar cells. These new phases consist of distorted sp$^3$ silicon networks and have a lower formation energy than other experimentally produced silicon phases. Some of these structures turned out to have quasi-direct and dipole-allowed band gaps in the range 0.8--1.5\,eV, and to display absorption coefficients comparable with those of chalcopyrites used in thin-film record solar cells., Comment: submitted

A novel allotrope of carbon with $P2/m$ symmetry was identified during an \emph{ab-initio} minima-hopping structural search which we call $M10$-carbon. This structure is predicted to be more stable than graphite at pressures above 14.4 GPa and consists purely of $sp^3$ bonds. It has a high bulk modulus and is almost as hard as diamond. A comparison of the simulated X-ray diffraction pattern shows a good agreement with experimental results from cold compressed graphite., Comment: 3 pages, 3 figures

A systematic ab initio search for low enthalpy phases of disilane (Si_2H_6) at high pressures was performed based on the minima hopping method. We found a novel metallic phase of disilane with Cmcm symmetry, which is enthalpically more favorable than the recently proposed structures of disilane up to 280 GPa, but revealing compositional instability below 190 GPa. The Cmcm phase has a moderate electron-phonon coupling yielding a superconducting transition temperature T_c of around 20 K at 100 GPa, decreasing to 13 K at 220 GPa. These values are an order of magnitude smaller than previously predicted T_c for disilane, and cast strong doubts on the possibility of high-T_c superconductivity in these systems as well as in other hydrogen-rich compounds under moderate pressure.

Through a systematic structural search we found an allotrope of carbon with Cmmm symmetry which we predict to be more stable than graphite for pressures above 10 GPa. This material, which we refer to as Z-carbon, is formed by pure sp3 bonds and is the only carbon allotrope which provides an excellent match to unexplained features in experimental X-ray diffraction and Raman spectra of graphite under pressure. The transition from graphite to Z-carbon can occur through simple sliding and buckling of graphene sheets. Our calculations predict that Z-carbon is a transparent wide band gap semiconductor with a hardness comparable to diamond., Comment: 4 pages, 5 figures

Using the minima hopping global geometry optimization method on the density functional potential energy surface we study medium size and large boron clusters. Even though for isolated medium size clusters the ground state is a cage like structure they are unstable against external perturbations such as contact with other clusters. The energy landscape of larger boron clusters is glass like and has a large number of structures which are lower in energy than the cages. This is in contrast to carbon and boron nitride systems which can be clearly identified as structure seekers in our minima hopping runs. The differences in the potential energy landscape explain why carbon and boron nitride systems are found in nature whereas pure boron fullerenes have not been found., Comment: 5 pages 5 figures

A structure prediction method is presented based on the Minima Hopping method. Optimized moves on the configurational enthalpy surface are performed to escape local minima using variable cell shape molecular dynamics by aligning the initial atomic and cell velocities to low curvature directions of the current minimum. The method is applied to both silicon crystals and binary Lennard-Jones mixtures and the results are compared to previous investigations. It is shown that a high success rate is achieved and a reliable prediction of unknown ground state structures is possible., Comment: 9 pages, 6 figures, novel approach in structure prediction, submitted to the Journal of Chemical Physics

The accuracy of the energy landscape of silicon systems obtained from various density functional methods, a tight binding scheme and force fields is studied. Quantum Monte Carlo results serve as quasi exact reference values. In addition to the well known accuracy of DFT methods for geometric ground states and metastable configurations we find that DFT methods give a similar accuracy for transition states and thus a good overall description of the energy landscape. On the other hand, force fields give a very poor description of the landscape that are in most cases too rugged and contain many fake local minima and saddle points or ones that have the wrong height.