Gas-surface interactions in the thermal and sub-thermal regime: A molecular dynamics study

Molecular dynamics simulations are used to study the interaction of low-energy Ar atoms with the Ni(001) surface, Angular scattering distributions, in and out of the plane of incidence, are investigated as a function of incident energy, angles of incidence, crystallographic orientation of the incident beam and surface temperature. The results show a clear transition to the structure scattering regime at around 2 eV. However, at lower energies, two sub-regimes are revealed by the simulations, Far energies up to 250 meV, scattering is mainly diffuse, and significant trapping on the surface is observed, At energies above this level, lobular patterns start to form and trapping decreases with the increase in energy, Generally, there is a weak temperature dependence, but variations in the angle of incidence and/or changes in the crystallographic direction, generate significant changes in the scattering patterns.

Forecasting regional crop production using SOI phases: an example for the Australian peanut industry

Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing bodies. The industry could profitably use forecasts of likely production to adjust their operations strategically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.