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There are increasing efforts aiming to utilise endophytes as biological control agents (BCAs) to improve crop production. However, reliability remains a major practical constraint for the development of novel BCAs. Many organisms are adapted to their specific habitat; it is optimistic to expect that a new organism added can find a niche or even out-compete those adapted and already present. Our approach for isolating novel BCAs for specific plant diseases is therefore to look in healthy plants in a habitat where disease is a problem, since we predict that it is more likely to find competitive strains among those present and adapted. In vitro inhibitory activities often do not correlate with in planta efficacy, especially since endophytes rely on intimate plant contact. They can, however, be useful to indicate modes of action. We therefore screen for in planta biological activity as early as possible in the process in order to minimise the risk of discarding valuable strains. Finally, some fungi are endophytic in one situation and pathogenic in another (the mutualism–parasitism continuum). This depends on their biology, environmental conditions, the formulation of inoculum, the health, developmental stage and cultivar of the host plant, and the structure of the plant microbiome.
While the self-learning kinetic Monte Carlo (SLKMC) method enables the calculation of transition rates from a realistic potential, implementations of it were usually limited to one specific surface orientation. An example is the fcc (111) surface in Latz et al. 2012, J. Phys.: Condens. Matter 24, 485005. This work provides an extension by means of detecting the local orientation, and thus allows for the accurate simulation of arbitrarily shaped surfaces. We applied the model to the diffusion of Ag monolayer islands and voids on a Ag(111) and Ag(001) surface, as well as the relaxation of a three-dimensional spherical particle.
Understanding electromigration effects in monocrystalline metal becomes of increasing interest with decreasing width and thickness of interconnects. Using a three-dimensional, atomistic model based on the Kinetic Monte Carlo method, we investigate voids in monocrystalline silver. Subject to electromigration, voids begin to drift. We show that the drift velocity not only depends on the void size, but also on the electromigration force direction, with respect to the crystallographic orientation.
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