Efficient and accurate determination of lattice-vacancy diffusion coefficients via non equilibrium ab initio molecular dynamics

We revisit the color-diffusion algorithm [P. C. Aeberhard et al., Phys. Rev. Lett. 108, 095901 (2012)] in nonequilibrium ab initio molecular dynamics (NE-AIMD), and propose a simple efficient approach for the estimation of monovacancy jump rates in crystalline solids at temperatures well below melting. Color-diffusion applied to monovacancy migration entails that one lattice atom (colored-atom) is accelerated toward the neighboring defect-site by an external constant force F. Considering bcc molybdenum between 1000 and 2800 K as a model system, NE-AIMD results show that the colored-atom jump rate k_{NE} increases exponentially with the force intensity F, up to F values far beyond the linear-fitting regime employed previously. Using a simple model, we derive an analytical expression which reproduces the observed k_{NE}(F) dependence on F. Equilibrium rates extrapolated by NE-AIMD results are in excellent agreement with those of unconstrained dynamics. The gain in computational efficiency achieved with our approach increases rapidly with decreasing temperatures, and reaches a factor of four orders of magnitude at the lowest temperature considered in the present study

Optimizing Marketing Activities for Different Levels of Customer Relationships

The discipline of marketing is evolving from a product centric paradigm where all value is invested in the product by the supplier and it is exchanged for a market determined price by means of an arm’s length transaction, to a service centric paradigm where value is co-created by customer and supplier through complex relationships in which the rewards are determined through negotiation. This study recognizes that in practice a supplier will and ought to continue to have some customer relationships that are transactional and others that involve higher levels of value co-creation. A five point continuum of relationships from transactional to strategic alliance is defined. Dyadic data in which customer and supplier are asked to evaluate the same relationship from their respective points of view are analyzed resulting in a portfolio of a supplier’s relationships that include each of the five levels. Three structured equation models are validated: first, the customer’s assessment of the level of relationship as a function of new, behaviorally anchored measures; second, the supplier’s assessment as a function of new, behaviorally anchored measures of investment; third, the differences between customer and supplier assessments as a function of differences in ratings of new, behaviorally anchored measures. Additionally, segmentation of the customer base is identified based on the level of assessment of the current and desired future level of relationship. Servicing processes are defined to enable the supplier to match the right offerings to each level of customer thereby optimizing their investment in their customer portfolio

Dissociation of O2 at Al(111): The Role of Spin Selection Rules

A most basic and puzzling enigma in surface science is the description of the dissociative adsorption of O2 at the (111) surface of Al. Already for the sticking curve alone, the disagreement between experiment and results of state-of-the-art first-principles calculations can hardly be more dramatic. In this paper we show that this is caused by hitherto unaccounted spin selection rules, which give rise to a highly non-adiabatic behavior in the O2/Al(111) interaction. We also discuss problems caused by the insufficient accuracy of present-day exchange-correlation functionals.Comment: 4 pages including 3 figures; related publications can be found at http://www.fhi-berlin.mpg.de/th/th.htm

Applying causality principles to the axiomatization of probabilistic cellular automata

Cellular automata (CA) consist of an array of identical cells, each of which may take one of a finite number of possible states. The entire array evolves in discrete time steps by iterating a global evolution G. Further, this global evolution G is required to be shift-invariant (it acts the same everywhere) and causal (information cannot be transmitted faster than some fixed number of cells per time step). At least in the classical, reversible and quantum cases, these two top-down axiomatic conditions are sufficient to entail more bottom-up, operational descriptions of G. We investigate whether the same is true in the probabilistic case. Keywords: Characterization, noise, Markov process, stochastic Einstein locality, screening-off, common cause principle, non-signalling, Multi-party non-local box.Comment: 13 pages, 6 figures, LaTeX, v2: refs adde

Non-adiabatic Effects in the Dissociation of Oxygen Molecules at the Al(111) Surface

The measured low initial sticking probability of oxygen molecules at the Al(111) surface that had puzzled the field for many years was recently explained in a non-adiabatic picture invoking spin-selection rules [J. Behler et al., Phys. Rev. Lett. 94, 036104 (2005)]. These selection rules tend to conserve the initial spin-triplet character of the free O2 molecule during the molecule's approach to the surface. A new locally-constrained density-functional theory approach gave access to the corresponding potential-energy surface (PES) seen by such an impinging spin-triplet molecule and indicated barriers to dissociation which reduce the sticking probability. Here, we further substantiate this non-adiabatic picture by providing a detailed account of the employed approach. Building on the previous work, we focus in particular on inaccuracies in present-day exchange-correlation functionals. Our analysis shows that small quantitative differences in the spin-triplet constrained PES obtained with different gradient-corrected functionals have a noticeable effect on the lowest kinetic energy part of the resulting sticking curve.Comment: 17 pages including 11 figures; related publications can be found at http://www.fhi-berlin.mpg.de/th/th.htm

Non-Adiabatic Potential-Energy Surfaces by Constrained Density-Functional Theory

Non-adiabatic effects play an important role in many chemical processes. In order to study the underlying non-adiabatic potential-energy surfaces (PESs), we present a locally-constrained density-functional theory approach, which enables us to confine electrons to sub-spaces of the Hilbert space, e.g. to selected atoms or groups of atoms. This allows to calculate non-adiabatic PESs for defined charge and spin states of the chosen subsystems. The capability of the method is demonstrated by calculating non-adiabatic PESs for the scattering of a sodium and a chlorine atom, for the interaction of a chlorine molecule with a small metal cluster, and for the dissociation of an oxygen molecule at the Al(111) surface.Comment: 11 pages including 7 figures; related publications can be found at http://www.fhi-berlin.mpg.de/th/th.htm

ForestHash: Semantic Hashing With Shallow Random Forests and Tiny Convolutional Networks

Hash codes are efficient data representations for coping with the ever growing amounts of data. In this paper, we introduce a random forest semantic hashing scheme that embeds tiny convolutional neural networks (CNN) into shallow random forests, with near-optimal information-theoretic code aggregation among trees. We start with a simple hashing scheme, where random trees in a forest act as hashing functions by setting `1' for the visited tree leaf, and `0' for the rest. We show that traditional random forests fail to generate hashes that preserve the underlying similarity between the trees, rendering the random forests approach to hashing challenging. To address this, we propose to first randomly group arriving classes at each tree split node into two groups, obtaining a significantly simplified two-class classification problem, which can be handled using a light-weight CNN weak learner. Such random class grouping scheme enables code uniqueness by enforcing each class to share its code with different classes in different trees. A non-conventional low-rank loss is further adopted for the CNN weak learners to encourage code consistency by minimizing intra-class variations and maximizing inter-class distance for the two random class groups. Finally, we introduce an information-theoretic approach for aggregating codes of individual trees into a single hash code, producing a near-optimal unique hash for each class. The proposed approach significantly outperforms state-of-the-art hashing methods for image retrieval tasks on large-scale public datasets, while performing at the level of other state-of-the-art image classification techniques while utilizing a more compact and efficient scalable representation. This work proposes a principled and robust procedure to train and deploy in parallel an ensemble of light-weight CNNs, instead of simply going deeper.Comment: Accepted to ECCV 201

Phonon self-energy and origin of anomalous neutron scattering spectra in SnTe and PbTe thermoelectrics

The anharmonic lattice dynamics of rock-salt thermoelectric compounds SnTe and PbTe are investigated with inelastic neutron scattering (INS) and first-principles calculations. The experiments show that, surprisingly, although SnTe is closer to the ferroelectric instability, phonon spectra in PbTe exhibit a more anharmonic character. This behavior is reproduced in first-principles calculations of the temperature-dependent phonon self-energy. Our simulations reveal how the nesting of phonon dispersions induces prominent features in the self-energy, which account for the measured INS spectra and their temperature dependence. We establish that the phase-space for three-phonon scattering processes, rather than just the proximity to the lattice instability, is the mechanism determining the complex spectrum of the transverse-optical ferroelectric mode

Selectivity of the First Two Glycerol Dehydrogenation Steps Determined Using Scaling Relationships

Glycerol is a byproduct of biodiesel production and an abundant feedstock that can be used for the synthesis of high-value chemicals. There are many approaches for glycerol valorization, but, due to the complicated reaction mechanism, controlling which products are produced is challenging. Here, we describe glycerol\u27s chemical selectivity for different metallic catalysts using descriptors for carbon (mainly *C, *CH2OH) and oxygen (mainly *O, CH3O*). The quality of these descriptors and the weighted combinations thereof are validated based on their fit, via linear regression, to the binding energies of all reaction intermediates generated in the first two glycerol dehydrogenation steps on a number of close-packed Ru, Co, Rh, Ir, Ni, Pd, Pt, Cu, Ag, and Au surfaces. We show that *CH2OH is a better descriptor than *C for the studied carbon-bound intermediates, which is attributed to the observation that the adjacent *OH group interacts with the surface. This leads to a negative oxygen dependence, which can be generalized to similar alcohol-derived adsorbates. Furthermore, we show that CH3O* is a better oxygen descriptor than *0 for the studied intermediates. This is mainly attributed to the difference between the single and double bonds, as we show that *OH is closer to the accuracy of CH3O*. Multilinear regression with different combinations of *C, *O, and *OH is comparable in accuracy to that of *CH2OH and CH3O*. Scaling relationships are used to determine the selectivity map for glycerol dehydrogenation. The results show that the first dehydrogenation is selective toward two different intermediates (one bonded via the secondary carbon and the other via the secondary oxygen) depending on the relative bond strength of the carbon and oxygen descriptors. The second dehydrogenation step results in five intermediates, again depending primarily on the relative bond strength of carbon and oxygen to the surface. The selectivity maps can be used together with kinetic considerations and experimental data to find catalyst candidates for glycerol dehydrogenation

Macroscopic Strings and "Quirks" at Colliders

We consider extensions of the standard model containing additional heavy particles ("quirks") charged under a new unbroken non-abelian gauge group as well as the standard model. We assume that the quirk mass m is in the phenomenologically interesting range 100 GeV--TeV, and that the new gauge group gets strong at a scale Lambda < m. In this case breaking of strings is exponentially suppressed, and quirk production results in strings that are long compared to 1/Lambda. The existence of these long stable strings leads to highly exotic events at colliders. For 100 eV < Lambda < keV the strings are macroscopic, giving rise to events with two separated quirk tracks with measurable curvature toward each other due to the string interaction. For keV < Lambda < MeV the typical strings are mesoscopic: too small to resolve in the detector, but large compared to atomic scales. In this case, the bound state appears as a single particle, but its mass is the invariant mass of a quirk pair, which has an event-by-event distribution. For MeV < Lambda < m the strings are microscopic, and the quirks annihilate promptly within the detector. For colored quirks, this can lead to hadronic fireball events with 10^3 hadrons with energy of order GeV emitted in conjunction with hard decay products from the final annihilation.Comment: Added discussion of photon-jet decay, fixed minor typo