Quantum well states in two-dimensional gold clusters on MgO thin films

The electronic structure of ultra-small Au clusters on thin MgO/Ag(001) films has been analyzed by scanning tunneling spectroscopy and density functional theory. The clusters exhibit two-dimensional (2D) quantum well states, whose shapes resemble the eigen-states of a 2D electron gas confined in a parabolic potential. From the symmetries of the HOMO and LUMO of a particular cluster, its electron filling and charge state is determined. In accordance to a DFT Bader-charge analysis, aggregates containing up to twenty atoms accumulate one to four extra electrons due to a charge transfer from the MgO/Ag interface. The HOMO - LUMO gap is found to close for clusters containing between 70 and 100 atoms.Comment: 12 pages, 4 figure

Measuring dairy cow welfare with real-time sensor-based data and farm records: a concept study

Welfare assessment of dairy cows by in-person farm visits provides only a snapshot of welfare and is time-consuming and costly. Possible solutions to reduce the need for in-person assessments would be to exploit sensor data and other routinely collected on-farm records. The aim of this study was to develop an algorithm to classify dairy cow welfare based on sensors (accelerometer and/or milk meter) and farm records (e.g. days in milk, lactation number). In total, 318 cows from six commercial farms located in Finland, Italy and Spain (two farms each) were enrolled for a pilot study lasting 135 days. During this time, cows were routinely scored using 14 animal-based measures of good feeding, health and housing based on the Welfare Quality® (WQ®) protocol. WQ® measures were evaluated daily or approximately every 45 days, using disease treatments from farm records and on-farm visits, respectively. WQ® measures were supplemented with daily temperature-humidity index to account for heat stress. The severity and duration of each welfare measure were evaluated, and the final welfare index was obtained by summing up the values for each cow on each pilot study day, and stratifying the result into three classes: good, moderate and poor welfare. For model building, a machine-learning (ML) algorithm based on gradient-boosted trees (XGBoost) was applied. Two model versions were tested: (1) a global model tested on unseen herd, and (2) a herd-specific model tested on unseen part of the data from the same herd. The version (1) served as an example on the model performance on a herd not previsited by the evaluator, while version (2) resembled a custom-made solution requiring in-person welfare evaluation for model training. Our results indicated that the global model had a low performance with average sensitivity and specificity of 0.44 and 0.68, respectively. For the herd-specific version, the model performance was higher reaching an average of 0.64 sensitivity and 0.80 specificity. The highest classification performance was obtained for cows in poor welfare, followed by cows in good and moderate welfare (balanced accuracy of 0.77, 0.71 and 0.68, respectively). Since the global model had low classification accuracy, the use of the developed model as a stand-alone system based solely on sensor data is infeasible, and a combination of in-person and sensor-based welfare evaluation would be preferable for a reliable welfare assessment. ML-based solutions, even with fair discriminative abilities, have the potential to enhance dairy welfare monitoring

Density functional theory based screening of ternary alkali-transition metal borohydrides: A computational material design project

The dissociation of molecules, even the most simple hydrogen molecule, cannot be described accurately within density functional theory because none of the currently available functionals accounts for strong on-site correlation. This problem led to a discussion of properties that the local Kohn-Sham potential has to satisfy in order to correctly describe strongly correlated systems. We derive an analytic expression for the nontrivial form of the Kohn-Sham potential in between the two fragments for the dissociation of a single bond. We show that the numerical calculations for a one-dimensional two-electron model system indeed approach and reach this limit. It is shown that the functional form of the potential is universal, i.e., independent of the details of the two fragments.We acknowledge funding by the Spanish MEC (Grant No. FIS2007-65702-C02-01), “Grupos Consolidados UPV/EHU del Gobierno Vasco” (Grant No. IT-319-07), and the European Community through e-I3 ETSF project (Grant Agreement No. 211956).Peer reviewe

Charging of atoms, clusters, and molecules on metal-supported oxides: A general and long-ranged phenomenon

The density-functional theory is used to investigate the adsorption of Au atoms, Au clusters, and NO2 molecules on transition-metal-supported oxides. As compared to unsupported oxides, the adsorbates on supported oxide films are charged and experience a higher adsorption energy. The origin of the effect is explored by considering two different oxides (MgO and Al2O3) and a range of supporting metals. Moreover, the limits of the enhancement are probed by explicit calculations for thick MgO films and low coverage. The long-range character of the phenomenon is attributed to electrostatic polarization. The absolute strength depends on several contributions and their relative importance changes with system composition

Bayesian analysis of critical fatigue failure sources

Abstract A novel approach for inferring the underlying non-metallic inclusion distribution from fatigue test fractography is presented. It is shown that the non-metallic inclusion size distribution obtained from fatigue testing differs from the extreme value distributions, which do not take fatigue into account. Fatigue, as a process, acts as a filter for the observed inclusions, and by taking advantage of this allows us to extract more refined information from the fractography using statistical inference. The emphasis in this paper is on analysis of axial fatigue testing of smooth specimens. The concepts presented here apply to all fatigue testing where the data from fracture surfaces is collected

Finite element method modeling of crankshaft axial impact measurements

Abstract It has been recently discovered that there is a periodical axial impact phenomenon in a running engine crankshaft. Bending of the shaft causes significant extension of the crankshaft and impact to the engine block through the axial thrust bearing. The aim of this work is to study impact-induced energy fluctuations in a complex-shaped Wärtsilä sixteen vee 32 engine crankshaft by using an explicit finite element method (FEM) during the first 25 ms after impact. Using the FEM allows us to study real components used in industry, and analyze their dynamics in the transient phase. In conclusion, we found interesting results that can be used as guidelines for a full-scale crankshaft measurement instrumentation plan. The full-scale measurements will be performed later in the Wärtsilä Oy facility at Vaasa, Finland. The main finding is that a substantive amount of energy is trapped in the head region and the first two crank pins of the crankshaft, which can affect crankshaft durability regarding high-cycle fatigue