Absence of a Crystal Direction Regime in which Sputtering Corresponds to Amorphous Material.

Erosion of material by energetic ions, i.e., sputtering, is widely used in industry and research. Using experiments and simulations that, independently of each other, obtain the sputter yield of thousands of individual grains, we demonstrate here that the sputter yield for heavy keV ions on metals changes as a continuous function of the crystal direction. Moreover, we show that polycrystalline metals with randomly oriented grains do not sputter with the same yield as the amorphous material. The key reason for this is attributed to linear collision sequences rather than channeling.

Thermodynamics of standing and lying behavior in lactating dairy cows in freestall and parlor holding pens during conditions of heat stress.

Heat load is a challenge for high-producing dairy cows, with adverse consequences on production, reproduction, and welfare. The objectives of this observational study in 2 commercial dairy herds were to determine the effects of environmental heat stress on standing and lying behavior, to monitor the changes in core body temperature (CBT) of cows during lying and standing bouts, and to compare changes in CBT during standing bouts in freestall pens versus standing in holding pens. High-producing cows were selected for data collection over a period of 6 d of increasing heat stress during a heat wave to which they were not acclimated. A total of 20 cows were fitted with leg accelerometers that recorded lying behavior and with vaginal temperature loggers that recorded CBT. These data were recorded at 30-s intervals. Time in the parlor holding pen was calculated from automated parlor software that recorded milking unit attachment and removal times. Mean daily temperature-humidity index in the pens increased from 68.5 to 79.0 during the 6-d trial, whereas mean daily lying time decreased from 9.5 to 6.2 h/d. The mean number of lying bouts per day remained similar at 11.1 to 12.2, but duration of lying bouts decreased from a high of 49.7 min on the coolest day to 32.8 min on the hottest day. During lying bouts, CBT increased at a mean rate of 0.50°C/h. In contrast, CBT changed at a mean rate of -0.25°C/h when standing in the freestall pens and only -0.09°C/h when standing in the milking-center holding pens. Explanatory models for the CBT at which cows ended either standing or lying bouts were derived from 6 selected lying bouts and 3 selected standing bouts for each cow on each day. The CBT at which a cow ended a lying bout was positively related to CBT and temperature-humidity index at the start of the bout, bout duration, and rate of CBT change during the bout. The CBT at which a cow ended a standing bout was negatively related to bout duration and positively related to start CBT, start temperature-humidity index, and rate of CBT change. Insights into the thermodynamics of standing and lying behavior in dairy cows during periods of heat stress provided by this study may contribute to the development of more effective strategies to mitigate heat load in dairy cattle.

Nanoscale density variations induced by high energy heavy ions in amorphous silicon nitride and silicon dioxide.

The cylindrical nanoscale density variations resulting from the interaction of 185 MeV and 2.2 GeV Au ions with 1.0 µm thick amorphous SiN x :H and SiO x :H layers are determined using small angle x-ray scattering measurements. The resulting density profiles resembles an under-dense core surrounded by an over-dense shell with a smooth transition between the two regions, consistent with molecular-dynamics simulations. For amorphous SiN x :H, the density variations show a radius of 4.2 nm with a relative density change three times larger than the value determined for amorphous SiO x :H, with a radius of 5.5 nm. Complementary infrared spectroscopy measurements exhibit a damage cross-section comparable to the core dimensions. The morphology of the density variations results from freezing in the local viscous flow arising from the non-uniform temperature profile in the radial direction of the ion path. The concomitant drop in viscosity mediated by the thermal conductivity appears to be the main driving force rather than the presence of a density anomaly.

Mechanism of Radiation Damage Reduction in Equiatomic Multicomponent Single Phase Alloys.

Recently a new class of metal alloys, of single-phase multicomponent composition at roughly equal atomic concentrations ("equiatomic"), have been shown to exhibit promising mechanical, magnetic, and corrosion resistance properties, in particular, at high temperatures. These features make them potential candidates for components of next-generation nuclear reactors and other high-radiation environments that will involve high temperatures combined with corrosive environments and extreme radiation exposure. In spite of a wide range of recent studies of many important properties of these alloys, their radiation tolerance at high doses remains unexplored. In this work, a combination of experimental and modeling efforts reveals a substantial reduction of damage accumulation under prolonged irradiation in single-phase NiFe and NiCoCr alloys compared to elemental Ni. This effect is explained by reduced dislocation mobility, which leads to slower growth of large dislocation structures. Moreover, there is no observable phase separation, ordering, or amorphization, pointing to a high phase stability of this class of alloys.

Exploring relationships between Dairy Herd Improvement monitors of performance and the Transition Cow Index in Wisconsin dairy herds.

Transition cow management has been tracked via the Transition Cow Index (TCI; AgSource Cooperative Services, Verona, WI) since 2006. Transition Cow Index was developed to measure the difference between actual and predicted milk yield at first test day to evaluate the relative success of the transition period program. This project aimed to assess TCI in relation to all commonly used Dairy Herd Improvement (DHI) metrics available through AgSource Cooperative Services. Regression analysis was used to isolate variables that were relevant to TCI, and then principal components analysis and network analysis were used to determine the relative strength and relatedness among variables. Finally, cluster analysis was used to segregate herds based on similarity of relevant variables. The DHI data were obtained from 2,131 Wisconsin dairy herds with test-day mean ≥30 cows, which were tested ≥10 times throughout the 2014 calendar year. The original list of 940 DHI variables was reduced through expert-driven selection and regression analysis to 23 variables. The K-means cluster analysis produced 5 distinct clusters. Descriptive statistics were calculated for the 23 variables per cluster grouping. Using principal components analysis, cluster analysis, and network analysis, 4 parameters were isolated as most relevant to TCI; these were energy-corrected milk, 3 measures of intramammary infection (dry cow cure rate, linear somatic cell count score in primiparous cows, and new infection rate), peak ratio, and days in milk at peak milk production. These variables together with cow and newborn calf survival measures form a group of metrics that can be used to assist in the evaluation of overall transition period performance.

Cluster analysis of Dairy Herd Improvement data to discover trends in performance characteristics in large Upper Midwest dairy herds.

Principal component analysis (PCA) is a variable reduction method used on over-parameterized data sets with a vast number of variables and a limited number of observations, such as Dairy Herd Improvement (DHI) data, to select subsets of variables that describe the largest amount of variance. Cluster analysis (CA) segregates objects, in this case dairy herds, into groups based upon similarity in multiple characteristics simultaneously. This project aimed to apply PCA to discover the subset of most meaningful DHI variables and to discover groupings of dairy herds with similar performance characteristics. Year 2011 DHI data was obtained for 557 Upper Midwest herds with test-day mean ≥200 cows (assumed mostly freestall housed), that remained on test for the entire year. The PCA reduced an initial list of 22 variables to 16. The average distance method of CA grouped farms based on best goodness of fit determined by the minimum cophenetic distance. Six groupings provided the optimal fitting number of clusters. Descriptive statistics for the 16 variables were computed per group. On observations of means, groups 1, 2, and 6 demonstrated the best performances in most variables, including energy-corrected milk, linear somatic cell score (log of somatic cell count), dry period intramammary infection cure rate, new intramammary infection risk, risk of subclinical intramammary infection at first test, age at first calving, days in milk, and Transition Cow Index. Groups 3, 4, and 5 demonstrated the worst mean performances in most the PCA-selected variables, including DIM, age at first calving, risk of subclinical intramammary infection at first test, and dry period intramammary infection cure rate. Groups 4 and 5 also had the worst mean herd performances in energy-corrected milk, Transition Cow Index, linear somatic cell score, and new intramammary infection risk. Further investigation will be conducted to reveal patterns of management associated with herd categorization. The PCA and CA should be used when describing the multivariate performance of dairy herds and whenever working with over-parameterized data sets, such as DHI databases.

Survey of facility and management characteristics of large, Upper Midwest dairy herds clustered by Dairy Herd Improvement records.

A survey of management practices was conducted to investigate potential associations with groupings of herds formed by cluster analysis (CA) of Dairy Herd Improvement (DHI) data of 557 Upper Midwest herds of 200 cows or greater. Differences in herd management practices were identified between the groups, despite underlying similarities; for example, freestall housing and milking in a parlor. Group 6 comprised larger herds with a high proportion of primiparous cows and most frequently utilized practices promoting increased production [e.g., 84.4% used recombinant bovine somatotropin (rbST)], decreased lameness (e.g., 96.9% used routine hoof trimming for cows), and improved efficiency in reproduction [e.g., 93.8% synchronized the first breeding in cows (SYNCH)] and labor (e.g., mean ± SD, 67 ± 19 cows per 50-h per week full-time equivalent worker). Group 1 had the best mean DHI performances and followed most closely group 6 for the rate of adoption of intensive management practices while tending to outperform group 6 despite a generally smaller mean herd size (e.g., 42.3 ± 3.6 kg vs. 39.9 ± 3.6 kg of energy-corrected milk production; 608 ± 352 cows vs. 1,716 ± 1,405 cows). Group 2 were smaller herds with relatively high levels of performance that used less intensive management (e.g., 100% milked twice daily) and less technology (33.3 vs. 73.0% of group 1 used rbST). Group 4 were smaller but poorer-performing herds with low turnover and least frequently used intensive management practices (e.g., 39.1% SYNCH; 30.4% allowed mature, high-producing cows access to pasture). Group 5 used modern technologies and practices associated with improved production, yet had the least desirable mean DHI performance of all 6 groups. This group had the lowest proportion of deep loose-bedded stalls (only 52.2% used sand bedding) and the highest proportion (34.8%) of herds not using routine hoof trimming. The survey of group 3 herds did not reveal strong trends in management. The differences identified between herd groupings confirm significant variation in management practices linked to variation in overall herd performance measured by DHI variables. This approach provides an opportunity for consultants and outreach educators to better tailor efforts toward a certain type of dairy management philosophy, rather than taking a blanket approach to applying recommendations to farms simply because of their larger herd size.

Risk factors for postpartum problems in dairy cows: explanatory and predictive modeling.

The postpartum period is associated with a high incidence of most dairy cattle diseases and a high risk of removal from the herd. Postpartum diseases often share risk factors, and these factors may trigger a cascade of other diseases. The objective of this cohort study was to derive explanatory and predictive models for treatment or removal from the herd within the first 30 d in milk (TXR30). The TXR30 outcome was specifically defined as ≥1 treatment for ≥1 occurrence of milk fever, retained placenta, metritis, ketosis, displaced abomasum, lameness, or pneumonia; removal from the herd (sold or died); or both treatment and later herd removal. The study population consisted of 765 multiparous and 544 primiparous cows (predominantly Holstein) from 4 large commercial freestall-housed dairy herds. Treatment or removal from the herd was recorded as a binary outcome for each cow. Potential explanatory and predictive variables were limited to routine cow data that could be collected either before or within 24 h of calving. Models for multiparous and primiparous cows were developed separately because previous lactation variables are available only for multiparous cows. Adjusted odds ratios for TXR30 in the explanatory model for the multiparous cohort were 2.1 for lactation 3 compared with lactation 2, and 2.3 for lactation 4 or greater compared with lactation 2; 2.3 for locomotion score 3 or 4 compared with score 1; 3.3 for an abnormality at calving compared with no calving abnormality; 1.8 for each 1-standard deviation increase in previous lactation length; and 0.4 for each 5,000-kg increment in previous lactation milk yield in cows with longer previous lactation length. The final predictive model for TXR30 in multiparous cows included predictors similar but not identical to those included in the explanatory model. The area under the curve for the receiver operating characteristic curve from the final predictive model for the multiparous cohort was 0.70, with 60% sensitivity. For the primiparous cohort, calving abnormality increased the odds of TXR30 and was the only variable included in both the explanatory and predictive models. The area under the curve for the receiver operating characteristic curve from the final predictive model for the primiparous cohort was 0.66, with 35% sensitivity. This study identified key risk factors for TXR30 and developed equations for the prediction of TXR30. This information can help dairy producers better understand causes of postpartum problems.

Latent ion tracks were finally observed in diamond.

Injecting high-energy heavy ions in the electronic stopping regime into solids can create cylindrical damage zones called latent ion tracks. Although these tracks form in many materials, none have ever been observed in diamond, even when irradiated with high-energy GeV uranium ions. Here we report the first observation of ion track formation in diamond irradiated with 2-9 MeV C60 fullerene ions. Depending on the ion energy, the mean track length (diameter) changed from 17 (3.2) nm to 52 (7.1) nm. High resolution scanning transmission electron microscopy (HR-STEM) indicated the amorphization in the tracks, in which π-bonding signal from graphite was detected by the electron energy loss spectroscopy (EELS). Since the melting transition is not induced in diamond at atmospheric pressure, conventional inelastic thermal spike calculations cannot be applied. Two-temperature molecular dynamics simulations succeeded in the reproduction of both the track formation under MeV C60 irradiations and the no-track formation under GeV monoatomic ion irradiations.

Enhanced sputtering yields from single-ion impacts on gold nanorods.

Sputtering yields, enhanced by more than an order of magnitude, have been observed for 80 keV Xe ion irradiation of monocrystalline Au nanorods. Yields are in the range 100-1900 atoms/ion compared with values for a flat surface of ≈50. This enhancement results in part from the proximity of collision cascades and ensuing thermal spikes to the nanorod surfaces. Molecular dynamic modeling reveals that the range of incident angles occurring for irradiation of nanorods and the larger number of atoms in "explosively ejected" atomic clusters make a significant contribution to the enhanced yield.

Tracks and voids in amorphous Ge induced by swift heavy-ion irradiation.

Ion tracks formed in amorphous Ge by swift heavy-ion irradiation have been identified with experiment and modeling to yield unambiguous evidence of tracks in an amorphous semiconductor. Their underdense core and overdense shell result from quenched-in radially outward material flow. Following a solid-to-liquid phase transformation, the volume contraction necessary to accommodate the high-density molten phase produces voids, potentially the precursors to porosity, along the ion direction. Their bow-tie shape, reproduced by simulation, results from radially inward resolidification.

Molecular dynamics simulation of radiation damage in CaCd6 quasicrystal cubic approximant up to 10 keV.

Due to the peculiar nature of the atomic order in quasicrystals, examining phase transitions in this class of materials is of particular interest. Energetic particle irradiation can provide a way to modify the structure locally in a quasicrystal. To examine irradiation-induced phase transitions in quasicrystals on the atomic scale, we have carried out molecular dynamics simulations of collision cascades in CaCd6 quasicrystal cubic approximant with energies up to 10 keV at 0 and 300 K. The results show that the threshold energies depend surprisingly strongly on the local coordination environments. The energy dependence of stable defect formation exhibits a power-law dependence on cascade energy, and surviving defects are dominated by Cd interstitials and vacancies. Only a modest effect of temperature is observed on defect survival, while irradiation temperature increases lead to a slight increase in the average size of both vacancy clusters and interstitial clusters.

Molecular dynamics study of hydrogen isotopes at the Be/BeO interface.

Molecular dynamics simulations are used to investigate the behaviour of D atoms at two interfaces between beryllium (Be) and beryllium oxide (BeO). After relaxation of the simulation cell, there are (a) localised defects at the interface and (b) a hexagonal misfit dislocation network creating a succession of compressed and expanded area from each side of the interface. The simulations between 750 K and 1500 K for tens to hundreds of nanoseconds show that both interfaces act as trapping sites for D atoms. The simulations also show that D atoms tend to migrate in the material where the hydrogen isotope solubility is the highest as predicted by thermodynamics. However, the simulations also shows that there are additional kinetic barriers (D trapping sites, D2formation/dissociation in BeO) that slow down the path to equilibrium. These additional kinetic barriers may influence the fuel retention and permeation in Be materials.

Multiscale machine-learning interatomic potentials for ferromagnetic and liquid iron.

A large and increasing number of different types of interatomic potentials exist, either based on parametrised analytical functions or machine learning. The choice of potential to be used in a molecular dynamics simulation should be based on the affordable computational cost and required accuracy. We develop and compare four interatomic potentials of different complexity for iron: a simple machine-learned embedded atom method (EAM) potential, a potential with machine-learned two- and three-body-dependent terms, a potential with machine-learned EAM and three-body terms, and a Gaussian approximation potential with the smooth overlap of atomic positions descriptor. All potentials are trained to the same diverse database of body-centred cubic and liquid structures computed with density functional theory. The first three potentials are tabulated and evaluated efficiently using cubic spline interpolations, while the fourth one is implemented without additional optimisation. The four potentials span three orders of magnitude in computational cost. We compare and discuss the advantages of each potential in terms of transferability and the balance between accuracy and computational cost.

Measurement of two solvation regimes in water-ethanol mixtures using x-ray compton scattering.

Water-ethanol mixtures exhibit interesting anomalies in their macroscopic properties. Despite a lot of research, the origin of the anomalies and the microscopic structure itself is still far from completely known. We have utilized the synchrotron x-ray Compton scattering technique to elucidate the structure of aqueous ethanol from a new experimental perspective. The technique is uniquely sensitive to the local molecular geometries at the angstrom and subangstrom scales. The experiments reveal two distinct mixing regimes in terms of geometry: the dilute 5 mol % and the concentrated >15 mol % regimes. By comparing with pure liquids, the former regime is characterized by an intramolecular and the latter by an intermolecular change. The findings bring new light to evaluating the hypothesis of formation of clathratelike structures at the dilute concentrations.

Molecular dynamics simulation of beryllium oxide irradiated by deuterium ions: sputtering and reflection.

The sputtering and reflection properties of wurtzite beryllium oxide (BeO) subjected to deuterium (D) ions bombardment at 300 K with ion energy between 10 eV and 200 eV is studied by classical molecular dynamics. Cumulative irradiations of wurtzite BeO show a D concentration threshold above which an 'unphysical dramatic' sputtering is observed. From the cumulative irradiations, simulation cells with different D concentrations are used to run non-cumulative irradiations at different concentrations. Using a D concentration close to the experimentally determined saturation concentration (0.12 atomic fraction), the simulations are able to reproduce accurately the experimental sputtering yield of BeO materials. The processes driving the sputtering of beryllium (Be) and oxygen (O) atoms as molecules are subsequently determined. At low irradiation energy, between 10 eV and 80 eV, swift chemical sputtering (SCS) is dominant and produces mostly OD z molecules. At high energy, the sputtered molecules are mostly Be x O y  molecules (mainly BeO dimer). Four different processes are associated to the formation of such molecules: the physical sputtering of BeO dimer, the delayed SCS not involving D ions and the detachment-induced sputtering. The physical sputtering of BeO dimer can be delayed if the sputtering event implies two interactions with the incoming ion (first interaction in its way in the material, the other in its way out if it is backscattered). The detachment-induced sputtering is a characteristic feature of the 'dramatic' sputtering and is mainly observed when the concentration of D is close to the threshold leading to this sputtering regime.

Modeling of high-fluence irradiation of amorphous Si and crystalline Al by linearly focused Ar ions.

Long time ion irradiation of surfaces under tilted incidence causes formation of regular nanostructures known as surface ripples. The nature of mechanisms leading to ripples is still not clear, this is why computational methods can shed the light on such a complex phenomenon and help to understand which surface processes are mainly responsible for it. In this work, we analyse the surface response of two materials, a semiconductor (silicon) and a metal (aluminium) under irradiation with the 250 eV and 1000 eV Ar ions focused at 70° from the normal to the surface. We simulate consecutive ion impacts by the means of molecular dynamics to investigate the effect on ripple formation. We find that the redistribution mechanism seems to be the main creator of ripples in amorphous materials, while the erosion mechanism is the leading origin for the pattern formation in crystalline metals.

Radiation damage in tungsten from cascade overlap with voids and vacancy clusters.

We have performed a systematic molecular dynamics investigation of the effects of overlap of collision cascades in tungsten with pre-existing vacancy-type defects. In particular, we focus on the implications for fusion neutron irradiated tungsten in relation to comparisons with damage production under ion irradiation conditions. We find that overlap of a cascade with a vacancy-type defect decreases the number of new defects with roughly the same functional dependence as previously shown for interstitial clusters. We further find that different mechanisms govern the formation of dislocation loops, resulting in different Burgers vectors, depending on the degree of overlap between the cascade and the defect. Furthermore, we show that overlapping cascades consistently decrease the size of the pre-existing defect. We also observe void-induced cascade splitting at energies far below the subcascade splitting threshold in tungsten. The impact of these mechanisms on radiation damage accumulation and dose rate effects are discussed.

Analytical interatomic bond-order potential for simulations of oxygen defects in iron.

We present an analytical bond-order potential for the Fe-O system, capable of reproducing the basic properties of wüstite as well as the energetics of oxygen impurities in [Formula: see text]-iron. The potential predicts binding energies of various small oxygen-vacancy clusters in [Formula: see text]-iron in good agreement with density functional theory results, and is therefore suitable for simulations of oxygen-based defects in iron. We apply the potential in simulations of the stability and structure of Fe/FeO interfaces and FeO precipitates in iron, and observe that the shape of FeO precipitates can change due to formation of well-defined Fe/FeO interfaces. The interface with crystalline Fe also ensures that the precipitates never become fully amorphous, no matter how small they are.

Collision cascades overlapping with self-interstitial defect clusters in Fe and W.

Overlap of collision cascades with previously formed defect clusters become increasingly likely at radiation doses typical for materials in nuclear reactors. Using molecular dynamics, we systematically investigate the effects of different pre-existing self-interstitial clusters on the damage produced by an overlapping cascade in bcc iron and tungsten. We find that the number of new Frenkel pairs created in direct overlap with an interstitial cluster is reduced to essentially zero, when the size of the defect cluster is comparable to that of the disordered cascade volume. We develop an analytical model for this reduced defect production as a function of the spatial overlap between a cascade and a defect cluster of a given size. Furthermore, we discuss cascade-induced changes in the morphology of self-interstitial clusters, including transformations between [Formula: see text] and [Formula: see text] dislocation loops in iron and tungsten, and between C15 clusters and dislocation loops in iron. Our results provide crucial new cascade-overlap effects to be taken into account in multi-scale modelling of radiation damage in bcc metals.