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Li$_6$PS$_5$Cl is a promising candidate for the solid electrolyte in all-solid-state Li-ion batteries. In applications, this material is in a polycrystalline state with grain boundaries (GBs) that can affect ionic conductivity. While atomistic modeling provides valuable information on the impact of GBs on Li diffusion, such studies face either high computational cost (\textit{ab initio} methods) or accuracy limitations (classical potentials) as challenges. Here, we develop a quality-level-based active learning scheme for efficient and systematic development of \textit{ab initio}-based machine-learning interatomic potentials, specifically moment tensor potentials (MTPs), for large-scale, long-time, and high-accuracy simulations of complex atomic structures and diffusion mechanisms as encountered in solid electrolytes. Based on this scheme, we obtain MTPs for Li$_6$PS$_5$Cl and investigate two tilt GBs, $\Sigma3(1\bar{1}2)[110]$, $\Sigma3(\bar{1}11)[110]$, and one twist GB, $\Sigma5(001)[001]$. All three GBs exhibit low formation energies of less than \SI{20}{meV/\angstrom\textsuperscript{2}}, indicating their high stability in polycrystalline Li$_6$PS$_5$Cl. Using the MTPs, diffusion coefficients of the anion-ordered and anion-disordered bulk, as well as the three GBs, are obtained from molecular dynamics simulations of atomistic models. At \SI{300}{\kelvin}, the GB diffusion coefficients fall between the ones of the anion-ordered bulk structure (\SI{0.012e-7}{cm^2/s}, corresponding ionic conductivity about \SI{0.2}{mS/cm}) and the anion-disordered bulk structure (\SI{50}{\percent} Cl/S-anion disorder; \SI{2.203e-7}{cm^2/s}, about \SI{29.8}{mS/cm}) of Li$_6$PS$_5$Cl. Experimental data fall between the Arrhenius-extrapolated diffusion coefficients of the investigated atomic structures., Comment: 26 pages, 14 figures, 5 tables

The yield stress anomaly of L12 intermetallics such as Ni3Al or Ni3Ga is controlled by the so-called Kear-Wilsdorf lock (KWL), of which the formation and unlocking are governed by dislocation cross-slip. Despite the importance of L12 intermetallics for strengthening Ni-based superalloys, microscopic understanding of the KWL is limited. Here, molecular dynamics simulations are conducted by employing a dedicated machine-learning interatomic potential derived via physically-informed active-learning. The potential facilitates modelling of the dislocation behavior in Ni3Al with near ab initio accuracy. KWL formation and unlocking are observed and analyzed. The unlocking stress demonstrates a pronounced temperature dependence, contradicting the assumptions of existing analytical models. A phenomenological model is proposed to effectively describe the atomistic unlocking stresses and extrapolate them to the macroscopic scale. The model is general and applicable to other L12 intermetallics. The acquired knowledge of KWLs provides a deeper understanding on the origin of the yield stress anomaly.

Safe and high-density storage of hydrogen, for a clean-fuel economy, can be realized by hydride-forming materials, but these materials should be able to store hydrogen at room temperature. Some high-entropy alloys (HEAs) have recently been shown to reversibly store hydrogen at room temperature, but the design of HEAs with appropriate thermodynamics is still challenging. To explore HEAs with appropriate hydride formation enthalpy, this study employs machine learning (ML), in particular, Gaussian process regression (GPR) using four different kernels by training with 420 datum points collected from literature and curated here. The developed ML models are used to predict the formation enthalpy of hydrides for the TixZr2-xCrMnFeNi (x = 0.5, 1.0 and 1.5) system, which is not in the training set. The predicted values by ML are consistent with data from experiments and density functional theory (DFT). The present study thus introduces ML as a rapid and reliable approach for the design of HEAs with hydride formation enthalpies of -25 to -39 kJ/mol for hydrogen storage at room temperature.

We propose an efficient ab initio framework to compute the Gibbs energy of the transition state in vacancy-mediated diffusion including the relevant thermal excitations at density-functional-theory level. With the aid of a bespoke machine-learning interatomic potential, the temperature-dependent vacancy formation and migration Gibbs energies of the prototype system bcc tungsten are shown to be strongly affected by anharmonicity. This explains the physical origin of the experimentally observed non-Arrhenius behavior of W self-diffusion as a case study. The good agreement of the self-diffusivity with experiment demonstrates that accurate ab initio diffusion databases are in reach.

Despite high interest in compact and safe storage of hydrogen in the solid-state hydride form, the design of alloys that can reversibly and quickly store hydrogen at room temperature under pressures close to atmospheric pressure is a long-lasting challenge. In this study, first-principles calculations are combined with experiments to develop high-entropy alloys (HEAs) for room-temperature hydrogen storage. TixZr2-xCrMnFeNi (x = 0.4-1.6) alloys with the Laves phase structure and low hydrogen binding energies of -0.1 to -0.15 eV are designed and synthesized. The HEAs reversibly store hydrogen in the form of Laves phase hydrides at room temperature, while (de)hydrogenation pressure systematically reduces with increasing the zirconium fraction in good agreement with the binding energy calculations. The kinetics of hydrogenation are fast, the hydrogenation occurs without any activation or catalytic treatment, the hydrogen storage performance remains stable for at least 1000 cycles, and the storage capacity is higher than that for commercial LaNi5. The current findings demonstrate that a combination of theoretical calculations and experiments is a promising pathway to design new high-entropy hydrides with high performance for hydrogen storage.

Accurate prediction of thermodynamic properties requires an extremely accurate representation of the free energy surface. Requirements are twofold -- first, the inclusion of the relevant finite-temperature mechanisms, and second, a dense volume-temperature grid on which the calculations are performed. A systematic workflow for such calculations requires computational efficiency and reliability, and has not been available within an ab initio framework so far. Here, we elucidate such a framework involving direct upsampling, thermodynamic integration and machine-learning potentials, allowing us to incorporate, in particular, the full effect of anharmonic vibrations. The improved methodology has a five-times speed-up compared to state-of-the-art methods. We calculate equilibrium thermodynamic properties up to the melting point for bcc Nb, magnetic fcc Ni, fcc Al and hcp Mg, and find remarkable agreement with experimental data. Strong impact of anharmonicity is observed specifically for Nb. The introduced procedure paves the way for the development of ab initio thermodynamic databases., Comment: 6 figures, supplementary information, typos corrected

Solid state batteries can be built based on thiophosphate electrolytes such as beta-Li3PS4. For the preparation of these electrolytes, various solvent-based routes have been reported. For recycling of end-of-life solid state batteries based on such thiophosphates, we consider the development of dissolution and recrystallization strategies for the recovery of the model compound beta-Li3PS4. We show that recrystallization can only be performed in polar, slightly protic solvents such as N-methylformamide (NMF). The recrystallization is comprehensively studied, showing that it proceeds via an intermediate phase with composition Li3PS4*2NMF, which is structurally characterized. This phase has a high resistivity for the transport of lithium ions and must be removed in order to obtain a recrystallized product with a conductivity similar to the pristine material. Moreover, the recrystallization from solution results in an increase of the amorphous phase fraction next to crystalline beta-Li3PS4, which results in a decrease of the activation energy to 0.2 eV compared to 0.38 eV for the pristine phase.

The impact of ordered vacancies on the dynamic stability of perovskites is investigated under the $\textit{ab initio}$ framework with a focus on cubic BaFeO$_{3}$ ($Pm\bar{3}m$) and vacancy-ordered monoclinic BaFeO$_{2.67}$ ($P2_{1}/m$). The harmonic approximation shows that both structures are dynamically unstable at 0 K. For the monoclinic structure, the instability is related to rotational distortions of the Fe coordination tetrahedra near the ordered vacancies. $\textit{Ab initio}$ molecular dynamics simulations in combination with the introduced structural descriptor demonstrate that both structures are stabilized above 130 K. Our results suggest that the ordered vacancies do not significantly alter the critical temperature at which Ba$-$Fe$-$O perovskites are dynamically stabilized. Further, strong anharmonicity for the vacancy-ordered structure above its critical temperature is revealed by a significant asymmetry of the trajectories of O anions near the ordered vacancies., Comment: 13 pages, 7 figures

The influence of pre-strain and temperature on the superior properties exhibited by an Nb nanowire embedded in a NiTi shape memory alloy (SMA) are investigated via molecular dynamics simulations. To this end, a new Nb-Ni-Ti ternary interatomic potential based on the second nearest-neighbor modified embedded-atom method (2NN MEAM) is developed and employed. The origin of the unique phenomena of quasi-linear elasticity, slim hysteresis, and reduction in Young's modulus observed for pre-strained nanowire-SMA composites is uncovered. The results demonstrate the importance of plastic deformation in the embedded Nb nanowires and reveal how the deformation facilitates the just-mentioned, unprecedented phenomena. A simple and straightforwardly obtainable descriptor to correlate and monitor Young's modulus evolution during pre-straining is proposed. Furthermore, our simulations suggest that the desired Young's modulus can be obtained for a wide range of application temperatures through appropriate pre-straining., Comment: 59 pages, 25 figures, 10 tables

During many of its applications (especially as a catalyst support material), MoO3 acts as a medium for hydrogen storage via hydrogen spillover (H atom donation from proton and electron sources to a support), for which the energetics of H atoms on MoO3 are of importance. Despite the seeming simplicity of hydrogen spillover, previously reported ab initio results for the H adsorption on MoO3 contradict both experimental work and other ab initio results. In the present study, we resolve these discrepancies and provide a comprehensive ab initio understanding of H adsorption for MoO3 in the bulk and on the surface. To this end, we systematically investigate various exchange-correlation functionals and various H concentrations, and we carefully track the various relevant H positions. For a dilute H concentration, the asymmetric oxygen site (Oa) is found to be energetically the most favorable. With increasing H content, the difference of the H adsorption energies between the terminal (Ot) and the Oa sites becomes smaller. Previous contradictions are ascribed mostly to the disregard of the H position along the Oa-Oa zig-zag chains in the intrabilayer region. Using the modern non-empirical strongly-constrained and appropriately-normed (SCAN) meta-generalized gradient approximation (GGA), the dilute-limit H adsorption energies are obtained as -2.89 eV/(H atom) and -2.97 eV/(H atom) in the bulk and on the surface, respectively, and the activation energy of H diffusion between the Oa sites as 0.11-0.15 eV/(H atom), consistent with previous experiments.

Molecular dynamics simulations are performed to investigate the role of a coherent {\Sigma}3 (111) twin boundary on the plastic deformation behavior of Cu nanopillars. Our work reveals that the mechanical response of pillars with and without the twin boundary is decisively driven by the characteristics of initial dislocation sources. In the condition of comparably large pillar size and abundant initial mobile dislocations, overall yield and flow stresses are controlled by the longest, available mobile dislocation. An inverse correlation of the yield and flow stresses with the length of the longest dislocation is established, and its extrapolation agrees well with experimental yield stress data. The experimentally reported subtle differences in yield and flow stresses between pillars with and without the twin boundary are thus likely related to the maximum lengths of the mobile dislocations. In the condition of comparably small pillar size, for which a reduction of mobile dislocations during heat treatment and mechanical loading occurs, the mechanical response of pillars with and without the twin boundary can be clearly distinguished. Dislocation starvation during deformation is more clearly present in pillars without the twin boundary than in pillars with the twin boundary because the twin boundary acts as a pinning surface for the dislocation network., Comment: - Main document: 29 pages, 12 figures, 3 tables - Supplementary Material: 13 pages, 11 figures, 2tables

Molecular dynamics simulations are performed to provide a detailed understanding of the functional degradation of shape memory alloys at small scale. The origin of the experimentally reported accumulation of plastic deformation and the anomalous sudden increase of the residual strain under cyclic mechanical loading are explained by detailed insights into the relevant atomic scale processes. Our work reveals that the mechanical response of shape-memory-alloy pillars under cyclic compression is significantly influenced by the presence of an amorphous-like surface region as experimentally induced by focused ion beam milling. The main factor responsible for the observed degradation of superelasticity under cyclic loading is the accumulated plastic deformation and the resultant retained martensite originating from a synergetic contribution of the amorphous and crystalline shape-memory-alloy regions. We show that the reported sudden diminishment of the stress plateaus and hysteresis under cyclic loading is caused by the increased stability of the martensite phase due to the presence of the amorphous phase. Based on the identified mechanism responsible for the degradation, we validate reported methods of recovering the superelasticity and propose a new method to prohibit the synergetic contribution of the amorphous and crystalline regions, such as to achieve a sustainable operation of shape memory alloys at small scale., Comment: 32 pages, 15 figures, 1 table

We present the magnetic Moment Tensor Potentials (mMTPs), a class of machine-learning interatomic potentials, accurately reproducing both vibrational and magnetic degrees of freedom as provided, e.g., from first-principles calculations. The accuracy is achieved by a two-step minimization scheme that coarse-grains the atomic and the spin space. The performance of the mMTPs is demonstrated for the prototype magnetic system bcc iron, with applications to phonon calculations for different magnetic states, and molecular dynamics simulations with fluctuating magnetic moments.

We propose an approach to calculate the anharmonic part of the volumetric-strain and temperature dependent free energy of a crystal. The method strikes an effective balance between accuracy and computational efficiency, showing a $\times10$ speed-up on comparable free energy approaches at the level of density functional theory, with average errors less than 1 meV/atom. As a demonstration we make new predictions on the thermodynamics of substoichiometric ZrC$_x$, including vacancy concentration and heat capacity.

A density-functional-theory based approach to efficiently compute numerically exact vibrational free energies - including anharmonicity - for chemically complex multicomponent alloys is developed. It is based on a combination of thermodynamic integration and a machine-learning potential. We demonstrate the performance of the approach by computing the anharmonic free energy of the prototypical five-component VNbMoTaW refractory high entropy alloy.

Two different mechanisms have been reported in previous ab initio studies to describe basal slip in complex intermetallic Laves phases: synchroshear and undulating slip. To date, no clear answer has been given on which is the energetically favourable mechanism and whether either of them could effectively propagate as a dislocation. Using classical atomistic simulations supported by ab initio calculations, the present work removes the ambiguity and shows that the two mechanisms are, in fact, identical. Furthermore, we establish synchroshear as the mechanism for propagating dislocations within the basal plane in Laves phases.

We study the mutual coupling of spin fluctuations and lattice vibrations in paramagnetic CrN by combining atomistic spin dynamics and ab initio molecular dynamics. The two degrees of freedom are dynamically coupled leading to non-adiabatic effects. Those effects suppress the phonon life times at low temperature compared to an adiabatic approach. The here identified dynamic coupling provides an explanation for the experimentally observed unexpected temperature dependence of the thermal conductivity of magnetic semiconductors above the magnetic ordering temperature., Comment: 6 pages, 4 figures

Field ion microscopy (FIM) allows to image individual surface atoms by exploiting the effect of an intense electric field. Widespread use of atomic resolution imaging by FIM has been hampered by a lack of efficient image processing/data extraction tools. Recent advances in imaging and data mining techniques have renewed the interest in using FIM in conjunction with automated detection of atoms and lattice defects for materials characterization. After a brief overview of existing routines, we review the use of machine learning (ML) approaches for data extraction with the aim to catalyze new data-driven insights into high electrical field physics. Apart from exploring various supervised and unsupervised ML algorithms in this context, we also employ advanced image processing routines for data extraction from large sets of FIM images. The outcomes and limitations of such routines are discussed, and we conclude with the possible application of energy minimization schemes to the extracted point clouds as a way of improving the spatial resolution of FIM., Comment: 34 pages, 14 figures

Multi-principle element alloys have enormous potential, but their exploration suffers from the tremendously large range of configurations. In the last decade such alloys have been designed with a focus on random solid solutions. Here we apply an experimentally verified, combined thermodynamic and first-principles design strategy to reverse the traditional approach and to generate a new type of hcp Al-Hf-Sc-Ti-Zr high entropy alloy with a hitherto unique structure. A phase diagram analysis narrows down the large compositional space to a well-defined set of candidates. First-principles calculations demonstrate the energetic preference of an ordered superstructure over the competing disordered solid solutions. The chief ingredient is the Al concentration, which can be tuned to achieve a D019 ordering of the hexagonal lattice. The computationally designed D019 superstructure is experimentally confirmed by transmission electron microscopy and X-ray studies. Our scheme enables the exploration of a new class of high entropy alloys.

We explore the competition and coupling of vibrational and electronic contributions to the heat capacity of Al and Al$_3$Sc at temperatures below 50 K combining experimental calorimetry with highly converged finite temperature density functional theory calculations. We find that semilocal exchange correlation functionals accurately describe the rich feature set observed for these temperatures, including electron-phonon coupling. Using different representations of the heat capacity, we are therefore able to identify and explain deviations from the Debye behaviour in the low-temperature limit and in the temperature regime 30 - 50 K as well as the reduction of these features due to the addition of Sc., Comment: 10 pages, 6 figures in total, paper submitted to Physical Review B

The dynamical and thermodynamic phase stabilities of the stoichiometric compound CrN including different structural and magnetic configurations are comprehensively investigated using a first-principles density-functional-theory (DFT) plus U approach in conjunction with experimental measurements of the thermal expansion. Comparing DFT and DFT+U results with experimental data reveals that the treatment of electron correlations using methods beyond standard DFT is crucial. The non-magnetic face-centered cubic B1-CrN phase is both, elastically and dynamically unstable, even under high pressure, while CrN phases with non-zero local magnetic moments are predicted to be dynamically stable within the framework of the DFT+U scheme. Furthermore, the impact of different treatments for the exchange-correlation (xc)-functional is investigated by carrying out all computations employing the local density approximation and generalized gradient approximation. To address finite-temperature properties, both, magnetic and vibrational contributions to the free energy have been computed employing our recently developed spin-space averaging method. The calculated phase transition temperature between low-temperature antiferromagnetic and high-temperature paramagnetic (PM) CrN variants is in excellent agreement with experimental values and reveals the strong impact of the choice of the xc-functional. The temperature-dependent linear thermal expansion coefficient of CrN is experimentally determined by the wafer curvature method from a reactive magnetron sputter deposited single-phase B1-CrN thin film with dense film morphology. A good agreement is found between experimental and ab initio calculated linear thermal expansion coefficients of PM B1-CrN. Other thermodynamic properties, such as the specific heat capacity, have been computed as well and compared to previous experimental data., Comment: 10 figures