Search

The discovery of materials is increasingly guided by quantum‐mechanical crystal‐structure prediction, but the structural complexity in bulk and nanoscale materials remains a bottleneck. Here we demonstrate how data‐driven approaches can vastly accelerate the search for complex structures, combining a machine‐learning (ML) model for the potential‐energy surface with efficient, fragment‐based searching. We use the characteristic building units observed in Hittorf's and fibrous phosphorus to seed stochastic ("random") structure searches over hundreds of thousands of runs. Our study identifies a family of hierarchically structured allotropes based on a P8 cage as principal building unit, including one‐dimensional (1D) single and double helix structures, nanowires, and two‐dimensional (2D) phosphorene allotropes with square‐lattice and kagome topologies. These findings yield new insight into the intriguingly diverse structural chemistry of phosphorus, and they provide an example for how ML methods may, in the long run, be expected to accelerate the discovery of hierarchical nanostructures. [ABSTRACT FROM AUTHOR]

The discovery of materials is increasingly guided by quantum‐mechanical crystal‐structure prediction, but the structural complexity in bulk and nanoscale materials remains a bottleneck. Here we demonstrate how data‐driven approaches can vastly accelerate the search for complex structures, combining a machine‐learning (ML) model for the potential‐energy surface with efficient, fragment‐based searching. We use the characteristic building units observed in Hittorf's and fibrous phosphorus to seed stochastic ("random") structure searches over hundreds of thousands of runs. Our study identifies a family of hierarchically structured allotropes based on a P8 cage as principal building unit, including one‐dimensional (1D) single and double helix structures, nanowires, and two‐dimensional (2D) phosphorene allotropes with square‐lattice and kagome topologies. These findings yield new insight into the intriguingly diverse structural chemistry of phosphorus, and they provide an example for how ML methods may, in the long run, be expected to accelerate the discovery of hierarchical nanostructures. [ABSTRACT FROM AUTHOR]

The computer program LOBSTER (Local Orbital Basis Suite Towards Electronic-Structure Reconstruction) enables chemical-bonding analysis based on periodic plane-wave (PAW) density-functional theory (DFT) output and is applicable to a wide range of first-principles simulations in solid-state and materials chemistry. LOBSTER incorporates analytic projection routines described previously in this very journal [J. Comput. Chem. 2013, 34, 2557] and offers improved functionality. It calculates, among others, atom-projected densities of states (pDOS), projected crystal orbital Hamilton population (pCOHP) curves, and the recently introduced bond-weighted distribution function (BWDF). The software is offered free-of-charge for non-commercial research. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Synthesis and utilization of nanocrystals are highly active fields of current research, but they require a thorough understanding of the underlying crystal surfaces. In this Minireview, we span the arc from surfaces to free nanocrystals, and onward to their chemical synthesis, using as examples lead selenide (PbSe), tin telluride (SnTe), and their direct chemical relatives. Besides experimental insights, we highlight the increasingly influential role played by quantum-chemical simulations of surfaces and nanocrystals. What can theory do today, or possibly tomorrow; where are its limits? Answering these questions, and skillfully linking them to experiments, could open up new atomistically (that is, chemically) guided perspectives for nanosynthesis. [ABSTRACT FROM AUTHOR]

Die Synthese und die Nutzbarmachung von Nanokristallen sind hochaktuelle Forschungsfelder, doch setzen sie ein gründliches Verständnis der beteiligten Kristallflächen voraus. In diesem Kurzaufsatz schlagen wir ebendiesen Bogen von Oberflächen zu freien und weiter zu naβchemisch synthetisierten Nanokristallen, und zwar exemplarisch für Bleiselenid (PbSe), Zinntellurid (SnTe) und ihre direkten chemischen Verwandten. Wir diskutieren experimentelle Einblicke und darüber hinaus die - zunehmend einfluβreiche - quantenchemische Simulation von Oberflächen und Nanokristallen. Was kann die Theorie heute leisten, was möglicherweise morgen, was kann sie eben nicht? Die Beantwortung dieser Fragen und ihre geschickte Verknüpfung mit Experimenten könnten neue, atomistisch (und damit chemisch) geleitete Perspektiven in der Nanosynthese eröffnen. [ABSTRACT FROM AUTHOR]

Phase-change materials (PCMs) are widely used for data storage and in other functional devices. Despite their seemingly simple compositions, these materials exhibit intriguing microscopic complexity and a portfolio of interesting properties. In this Feature Article, it is shown that structural and electronic peculiarities on the atomic scale are key determinants for the technological success of PCMs. Particular emphasis is put on the interplay of different experimental and theoretical methods, on the bonding nature of crystalline and amorphous PCMs, and on the role of surfaces and nanostructures. Then, unconventional transport properties of the crystalline phases are highlighted, both with regard to electrical and heat conduction. Finally, perspectives and future directions are drawn: for finding new PCMs based on microscopic understanding, and also for new applications of these materials in emerging fields. [ABSTRACT FROM AUTHOR]

Amorphous red phosphorus (a‐P) is one of the remaining puzzling cases in the structural chemistry of the elements. Here, we elucidate the structure, stability, and chemical bonding in a‐P from first principles, combining machine‐learning and density‐functional theory (DFT) methods. We show that a‐P structures exist with a range of energies slightly higher than those of phosphorus nanorods, to which they are closely related, and that the stability of a‐P is linked to the degree of structural relaxation and medium‐range order. We thus complete the stability range of phosphorus allotropes [Angew. Chem. Int. Ed. 2014, 53, 11629] by now including the previously poorly understood amorphous phase, and we quantify the covalent and van der Waals interactions in all main phases of phosphorus. We also study the electronic densities of states, including those of hydrogenated a‐P. Beyond the present study, our structural models are expected to enable wider‐ranging first‐principles investigations—for example, of a‐P‐based battery materials. [ABSTRACT FROM AUTHOR]

Amorpher roter Phosphor (a‐P) stellt eine der verbleibenden Herausforderungen in der Strukturchemie der Elemente dar. In diesem Beitrag klären wir Struktur, Stabilität und chemische Bindung im a‐P auf Grundlage voraussetzungsfreier Rechnungen auf, indem wir maschinelles Lernen und dichtefunktionaltheoretische (DFT‐) Methoden kombinieren. Wir zeigen, dass die Energien von a‐P‐Strukturen leicht höher liegen als jene von Phosphor‐Nanostäben, mit denen sie eng verwandt sind, und dass die Stabilität von a‐P mit dem Grad an struktureller Relaxation und mittelreichweitiger Ordnung verknüpft ist. Wir vervollständigen damit die Stabilitätsreihe der Phosphorallotrope [Angew. Chem. Int. Ed. 2014, 53, 11629], indem wir die bislang unvollständig verstandene amorphe Phase hinzufügen, und wir quantifizieren die kovalenten und van‐der‐Waals‐Wechselwirkungen in allen wichtigen Phasen des Phosphors. Wir untersuchen darüberhinaus die elektronische Zustandsdichte, einschließlich jener des wasserstoffhaltigen a‐P. Über die vorliegende Arbeit hinaus erwarten wir, dass unsere Strukturmodelle weiterführende voraussetzungsfreie Untersuchungen ermöglichen werden – beispielsweise zu a‐P‐basierten Batteriematerialien. [ABSTRACT FROM AUTHOR]

Despite its simple chemical constitution and unparalleled technological importance, the phase-change material germanium telluride (GeTe) still poses fundamental questions. In particular, the bonding mechanisms in amorphous GeTe have remained elusive to date, owing to the lack of suitable bond-analysis tools. Herein, we introduce a bonding indicator for amorphous structures, dubbed 'bond-weighted distribution function' (BWDF), and we apply this method to amorphous GeTe. The results underline a peculiar role of homopolar GeGe bonds, which locally stabilize tetrahedral fragments but not the global network. This atom-resolved (i.e., chemical) perspective has implications for the stability of amorphous 'zero bits' and thus for the technologically relevant resistance-drift phenomenon. [ABSTRACT FROM AUTHOR]

Ungeachtet seiner einfachen Zusammensetzung und enormen technischen Wichtigkeit wirft das Phasenwechselmaterial Germaniumtellurid (GeTe) auch heute noch grundlegende Fragen auf. Insbesondere die Bindungsmechanismen in amorphem GeTe haben sich bislang einer schlüssigen Erklärung entzogen, da geeignete bindungsanalytische Hilfsmittel fehlten. Hier führen wir einen neuen Bindungsindikator für amorphe Strukturen ein, den wir als “bindungsgewichtete Verteilungsfunktion” (BWDF) bezeichnen, und wenden diese Methode auf amorphes GeTe an. Die Ergebnisse belegen, daß homopolare Ge ‐ Ge ‐ Bindungen darin eine besondere Rolle spielen: sie stabilisieren einzelne tetraedrische Fragmente, nicht aber das globale Netzwerk. Diese atomaufgelöste (d. h. chemische) Perspektive hat Bedeutung für die Langzeitstabilität amorpher “Null ‐ Bits” und damit für das technisch wichtige Phänomen der Widerstandsdrift. Amorph – kein Problem! Wie man eine Kristallstruktur in lokale Fragmente und kovalente Bindungen zerlegt, haben Chemiker lange perfektioniert. Mit neuen Hilfsmitteln läßt sich diese chemische Sprache auf amorphe Festkörpermaterialien erweitern – hier auf das Phasenwechsel ‐ Speichermaterial Germaniumtellurid. [ABSTRACT FROM AUTHOR]

Quantum-chemical computations of solids benefit enormously from numerically efficient plane-wave (PW) basis sets, and together with the projector augmented-wave (PAW) method, the latter have risen to one of the predominant standards in computational solid-state sciences. Despite their advantages, plane waves lack local information, which makes the interpre-tation of local densities-of-states (DOS) difficult and precludes the direct use of atom-resolved chemical bonding indicators such as the crystal orbital overlap population (COOP) and the crystal orbital Hamilton population (COHP) techniques. Recently, a number of methods have been proposed to over-come this fundamental issue, built around the concept of basis-set projection onto a local auxiliary basis. In this work, we propose a novel computational technique toward this goal by transferring the PW/PAW wavefunctions to a properly cho- sen local basis using analytically derived expressions. In partic-ular, we describe a general approach to project both PW and PAW eigenstates onto given custom orbitals, which we then exemplify at the hand of contracted multiple-Ç Slater-type orbitals. The validity of the method presented here is illus-trated by applications to chemical textbook examples--dia-mond, gallium arsenide, the transition-metal titanium--as well as nanoscale allotropes of carbon: a nanotube and the C6o full-erene. Remarkably, the analytical approach not only recovers the total and projected electronic DOS with a high degree of confidence, but it also yields a realistic chemical-bonding pic-ture in the framework of the projected COHP method. [ABSTRACT FROM AUTHOR]

Germanium dioxide (Ge02) takes two forms at ambient pressure: a thermodynamically stable rutile-type structure and a high-temperature quartz-type polymorph. Here, we investigate the phase stability at finite temperatures by ab initio phonon and thermochemical computations. We use gradient-corrected den-sity-functional theory (PBE-GGA) and pay particular attention to the modeling of the "semicore" germanium 3d Orbitals (ascrib-ing them either to the core or to the valence region). The phase transition is predicted correctly in both cases, and computed heat capacities and entropies are in excellent agreement with thermochemical database values. Nonetheless, the computed formation energies of α-quartz-type GeO2 (and, consequently, the predicted transition temperatures) differ significantly depending on theoretical method. Remarkably, the simpler and cheaper computational approach produces seemingly better results, not worse. In our opinion, GeO2 is a nice test case that illustrates both possibilities and limitations of modern ab initio thermochemistry. [ABSTRACT FROM AUTHOR]

The structure of amorphous silicon (a‐Si) is widely thought of as a fourfold‐connected random network, and yet it is defective atoms, with fewer or more than four bonds, that make it particularly interesting. Despite many attempts to explain such "dangling‐bond" and "floating‐bond" defects, respectively, a unified understanding is still missing. Here, we use advanced computational chemistry methods to reveal the complex structural and energetic landscape of defects in a‐Si. We study an ultra‐large‐scale, quantum‐accurate structural model containing a million atoms, and thousands of individual defects, allowing reliable defect‐related statistics to be obtained. We combine structural descriptors and machine‐learned atomic energies to develop a classification of the different types of defects in a‐Si. The results suggest a revision of the established floating‐bond model by showing that fivefold‐bonded atoms in a‐Si exhibit a wide range of local environments–analogous to fivefold centers in coordination chemistry. Furthermore, it is shown that fivefold (but not threefold) coordination defects tend to cluster together. Our study provides new insights into one of the most widely studied amorphous solids, and has general implications for understanding defects in disordered materials beyond silicon alone. [ABSTRACT FROM AUTHOR]

The structure of amorphous silicon (a‐Si) is widely thought of as a fourfold‐connected random network, and yet it is defective atoms, with fewer or more than four bonds, that make it particularly interesting. Despite many attempts to explain such "dangling‐bond" and "floating‐bond" defects, respectively, a unified understanding is still missing. Here, we use advanced computational chemistry methods to reveal the complex structural and energetic landscape of defects in a‐Si. We study an ultra‐large‐scale, quantum‐accurate structural model containing a million atoms, and thousands of individual defects, allowing reliable defect‐related statistics to be obtained. We combine structural descriptors and machine‐learned atomic energies to develop a classification of the different types of defects in a‐Si. The results suggest a revision of the established floating‐bond model by showing that fivefold‐bonded atoms in a‐Si exhibit a wide range of local environments–analogous to fivefold centers in coordination chemistry. Furthermore, it is shown that fivefold (but not threefold) coordination defects tend to cluster together. Our study provides new insights into one of the most widely studied amorphous solids, and has general implications for understanding defects in disordered materials beyond silicon alone. [ABSTRACT FROM AUTHOR]

Studies of supercooled liquid phase‐change materials are important for the development of phase‐change memory and neuromorphic computing devices. Herein, a machine‐learning (ML)‐based interatomic potential for Ge2Sb2Te5 (GST) to conduct large‐scale molecular dynamics simulations of liquid and supercooled liquid GST is used. A pronounced effect of the thermostat parameters on the simulation results is demonstrated, and it is shown how using a Langevin thermostat with optimized damping values can lead to excellent agreement with reference ab initio molecular dynamics (AIMD) simulations. Structural and dynamical analyses are presented, including the studies of radial and angular distributions, homopolar bonds, and the temperature‐dependent diffusivity. Herein, the usefulness of ML‐driven molecular dynamics for further studies of supercooled liquid GST, with length and timescales far exceeding those that are accessible to AIMD is demonstrated. [ABSTRACT FROM AUTHOR]

The layered crystal structure of Cr2Ge2Te6 shows ferromagnetic ordering at the two‐dimensional limit, which holds promise for spintronic applications. However, external voltage pulses can trigger amorphization of the material in nanoscale electronic devices, and it is unclear whether the loss of structural ordering leads to a change in magnetic properties. Here, it is demonstrated that Cr2Ge2Te6 preserves the spin‐polarized nature in the amorphous phase, but undergoes a magnetic transition to a spin glass state below 20 K. Quantum‐mechanical computations reveal the microscopic origin of this transition in spin configuration: it is due to strong distortions of the CrTeCr bonds, connecting chromium‐centered octahedra, and to the overall increase in disorder upon amorphization. The tunable magnetic properties of Cr2Ge2Te6 can be exploited for multifunctional, magnetic phase‐change devices that switch between crystalline and amorphous states. [ABSTRACT FROM AUTHOR]

Review: [focus on PbSe and SnSe; 59 refs. [ABSTRACT FROM AUTHOR]

A glimpse into amorphous materials. In their Communication on page 10817 ff. R. Mazzarello, R. Dronskowski et al. investigate the bonding nature of amorphous GeTe, a prototypical phase‐change data‐storage material. Starting from a molecular‐dynamics snapshot, the role of different structural motifs is elucidated by the use of new tools; this way, the chemical “language” of bonding and coordination polyhedra may be transferred to the amorphous state. [ABSTRACT FROM AUTHOR]

Einen Ausflug ins Amorphe unternehmen R. Mazzarello, R. Dronskowski et al.: In ihrer Zuschrift auf S. 10993 ff. berichten sie über die Bindungsverhältnisse in amorphem GeTe, einem prototypischen Phasenwechselmaterial zur Datenspeicherung. Ausgehend von einem Moleküldynamik ‐ Schnappschuss analysieren sie die Rolle verschiedener Strukturmotive mithilfe neuer Verfahren; so lässt sich die chemische “Sprache” von Bindungen und Koordinationspolyedern auf den amorphen Zustand übertragen. [ABSTRACT FROM AUTHOR]

Ti1.6Os1.4RuB2 and its isotypical ternary derivative Ti1.6Os2.4B2 are characterized by DFT calculations. [ABSTRACT FROM AUTHOR]

The title compound is prepared by solid state reaction of a stoichiometric mixture of the elements (1. [ABSTRACT FROM AUTHOR]

While metals can be readily processed and reshaped by cold rolling, most bulk inorganic semiconductors are brittle materials that tend to fracture when plastically deformed. Manufacturing thin sheets and foils of inorganic semiconductors is therefore a bottleneck problem, severely restricting their use in flexible electronic applications. It is recently reported that a few single‐crystalline 2D van der Waals (vdW) semiconductors, such as InSe, are deformable under compressive stress. Here it is demonstrated that intralayer fracture toughness can be tailored via compositional design to make inorganic semiconductors processable by cold rolling. Systematic ab initio calculations covering a range of van der Waals semiconductors homologous to InSe are reported, leading to material‐property maps that forecast trends in both the susceptibility to interlayer slip and the intralayer fracture toughness against cracking. GaSe is predicted, and experimentally confirmed, to be practically amenable to being rolled to large (three quarters) thickness reduction and length extension by a factor of three. The fracture toughness and cleavage energy are predicted to be 0.25 MPa m0.5 and 15 meV Å−2, respectively. The findings open a new realm of possibility for alloy selection and design toward processing‐friendly group‐III chalcogenides for practical applications. [ABSTRACT FROM AUTHOR]

We present an update on recently developed methodology and functionality in the computer program Local Orbital Basis Suite Toward Electronic‐Structure Reconstruction (LOBSTER) for chemical‐bonding analysis in periodic systems. LOBSTER is based on an analytic projection from projector‐augmented wave (PAW) density‐functional theory (DFT) computations (Maintz et al., J. Comput. Chem.2013, 34, 2557), reconstructing chemical information in terms of local, auxiliary atomic orbitals and thereby opening the output of PAW‐based DFT codes to chemical interpretation. We demonstrate how LOBSTER has been improved by taking into account time‐reversal symmetry, thereby speeding up the DFT and LOBSTER calculations by a factor of 2. Over the recent years, the functionalities have also been continually expanded, including accurate projected densities of states (DOSs), crystal orbital Hamilton population (COHP) analysis, atomic and orbital charges, gross populations, and the recently introduced k‐dependent COHP. The software is offered free‐of‐charge for non‐commercial research. [ABSTRACT FROM AUTHOR]

Solid electrolyte materials are crucial for the development of high‐energy‐density all‐solid‐state batteries (ASSB) using a nonflammable electrolyte. In order to retain a low lithium‐ion transfer resistance, fast lithium ion conducting solid electrolytes are required. We report on the novel superionic conductor Li9AlP4 which is easily synthesised from the elements via ball‐milling and subsequent annealing at moderate temperatures and which is characterized by single‐crystal and powder X‐ray diffraction. This representative of the novel compound class of lithium phosphidoaluminates has, as an undoped material, a remarkable fast ionic conductivity of 3 mS cm−1 and a low activation energy of 29 kJ mol−1 as determined by impedance spectroscopy. Temperature‐dependent 7Li NMR spectroscopy supports the fast lithium motion. In addition, Li9AlP4 combines a very high lithium content with a very low theoretical density of 1.703 g cm−3. The distribution of the Li atoms over the diverse crystallographic positions between the [AlP4]9− tetrahedra is analyzed by means of DFT calculations. [ABSTRACT FROM AUTHOR]

Solid electrolyte materials are crucial for the development of high‐energy‐density all‐solid‐state batteries (ASSB) using a nonflammable electrolyte. In order to retain a low lithium‐ion transfer resistance, fast lithium ion conducting solid electrolytes are required. We report on the novel superionic conductor Li9AlP4 which is easily synthesised from the elements via ball‐milling and subsequent annealing at moderate temperatures and which is characterized by single‐crystal and powder X‐ray diffraction. This representative of the novel compound class of lithium phosphidoaluminates has, as an undoped material, a remarkable fast ionic conductivity of 3 mS cm−1 and a low activation energy of 29 kJ mol−1 as determined by impedance spectroscopy. Temperature‐dependent 7Li NMR spectroscopy supports the fast lithium motion. In addition, Li9AlP4 combines a very high lithium content with a very low theoretical density of 1.703 g cm−3. The distribution of the Li atoms over the diverse crystallographic positions between the [AlP4]9− tetrahedra is analyzed by means of DFT calculations. [ABSTRACT FROM AUTHOR]

Phase‐change materials (PCMs) are an intriguing class of materials that enable non‐volatile data storage and other technological applications. To gain a thorough understanding of PCMs, a variety of advanced experimental techniques is routinely used, but theory and computer simulation have long been of central importance as well. In their Review @ RRL (article no. 1800579), Konze et al. describe the role that orbital‐based chemical‐bonding analyses have played in PCM research: they can be used to identify stabilizing ("bonding") and de‐stabilizing ("antibonding") interactions between atoms using local‐orbital basis sets or (nowadays) a projection from plane‐wave DFT output. Besides a concise overview of the methodology and a survey of applications to PCMs, Konze et al. also highlight recent applications in other materials classes, aiming to make new links to the PCM field—and so to enable new microscopic insight into the crystalline and amorphous structures of these important materials. [ABSTRACT FROM AUTHOR]

The atomic‐scale structures of chalcogenide phase‐change materials (PCMs) are directly relevant for macroscopic properties and practical applications. In PCMs and throughout materials science, quantum‐mechanically based atomistic simulations and chemical‐bonding analyses are increasingly helping to understand structures and properties of solids. Here, new insights into PCMs are highlighted that have recently been obtained from orbital‐based bonding indicators—in particular, from crystal orbital Hamilton population (COHP) analysis. Applications of these methods in other areas of solid‐state and materials chemistry are also discussed, from classical to emerging topics, which may have useful lessons for PCM research in store. It is hoped that this overview will inspire research in the field and enable new chemical insight into structures and properties of PCMs. The role of chemical‐bonding analyses for phase‐change materials research is highlighted in this Review. The focus is on energy‐resolved, orbital‐based bonding indicators: in particular, the crystal orbital Hamilton population (COHP) technique. This work surveys recent applications in the field and in neighboring areas, aiming to enable new chemical insight into the crystalline and amorphous structures of these important materials. [ABSTRACT FROM AUTHOR]

Amorphous materials are being described by increasingly powerful computer simulations, but new approaches are still needed to fully understand their intricate atomic structures. Here, we show how machine‐learning‐based techniques can give new, quantitative chemical insight into the atomic‐scale structure of amorphous silicon (a‐Si). We combine a quantitative description of the nearest‐ and next‐nearest‐neighbor structure with a quantitative description of local stability. The analysis is applied to an ensemble of a‐Si networks in which we tailor the degree of ordering by varying the quench rates down to 1010 K s−1. Our approach associates coordination defects in a‐Si with distinct stability regions and it has also been applied to liquid Si, where it traces a clear‐cut transition in local energies during vitrification. The method is straightforward and inexpensive to apply, and therefore expected to have more general significance for developing a quantitative understanding of liquid and amorphous states of matter. [ABSTRACT FROM AUTHOR]

Amorphous materials are being described by increasingly powerful computer simulations, but new approaches are still needed to fully understand their intricate atomic structures. Here, we show how machine‐learning‐based techniques can give new, quantitative chemical insight into the atomic‐scale structure of amorphous silicon (a‐Si). We combine a quantitative description of the nearest‐ and next‐nearest‐neighbor structure with a quantitative description of local stability. The analysis is applied to an ensemble of a‐Si networks in which we tailor the degree of ordering by varying the quench rates down to 1010 K s−1. Our approach associates coordination defects in a‐Si with distinct stability regions and it has also been applied to liquid Si, where it traces a clear‐cut transition in local energies during vitrification. The method is straightforward and inexpensive to apply, and therefore expected to have more general significance for developing a quantitative understanding of liquid and amorphous states of matter. [ABSTRACT FROM AUTHOR]

B Deformable Inorganic Semiconductors b In article number 2203776, Wei Zhang, En Ma, and co-workers achieve inorganic semiconductors that can be shaped via cold-rolling, advocating adequate fracture toughness in their design. The cracking-resistant van der Waals crystal, depicted here in the form of a highly deformed Mobius ribbon, is amenable to use in flexible thermoelectric, neuromorphic and optoelectronic devices. Designing Inorganic Semiconductors with Cold-Rolling Processability (Adv. Sci. 30/2022). [Extracted from the article]

Keywords: Feste Elektrolyte; Festkörperbatterien; Festkörperstrukturen; Impedanzspektroskopie; Lithium EN Feste Elektrolyte Festkörperbatterien Festkörperstrukturen Impedanzspektroskopie Lithium 1 1 1 03/23/20 20200327 NES 200327 B Festkörperelektrolyte b T. F. Fässler et al. beschreiben in ihrem Forschungsartikel auf S. 5714 die Synthese und Eigenschaften eines neuartigen niedrigdichten Materials mit hoher Lithiumionenleitfähigkeit. Feste Elektrolyte, Festkörperbatterien, Festkörperstrukturen, Impedanzspektroskopie, Lithium. [Extracted from the article]

Na2MgPb is obtained from a stoichiometric melt of the elements (BN crucible in stainless steel tube, 1. [ABSTRACT FROM AUTHOR]