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Reverse Monte Carlo (RMC) simulations were performed to investigate the effectiveness of any combination of five experimentally motivated constraints on the reproduction of a test case, a ternary ab initio model. It was found that low energy structures fitting a variety of constraints commonly used in the RMC methodology could still provide an incorrect description of the chemical structural unit...
This paper presents a formal model for science clouds, capable of predicting and controlling resources scalably, as well as its implementation as an open source solution, called Chiminey. The feasibility of Chiminey is shown using case studies on biophysics and structural chemistry computations. Big data is acquired from scientific instruments such as synchrotrons and atomic force microscopes. The...
The enabling of scientific experiments that are embarrassingly parallel, long running and data-intensive into a cloud-based execution environment is a desirable, though complex undertaking for many researchers. The management of such virtual environments is cumbersome and not necessarily within the core skill set for scientists and engineers. We present here Chiminey, a software platform that enables...
The disordered microstructure of an industrial carbonaceous char has been characterised using X-ray, neutron and electron diffraction techniques to obtain pair correlation functions. Whilst consistency has been observed between all three techniques, electron diffraction has been found to have advantages by allowing data to be collected over a large range of scattering angles as well as without interference...
We present microstructural analysis of a disordered carbonaceous solid using simulations that employ a modified reverse Monte Carlo (RMC) algorithm. This algorithm incorporates an accurate environment dependent interaction potential (EDIP) in addition to commonly used constraints derived from experimental data, such as the sp 2 /sp 3 bonding ratio. Our approach improves the microstructural...
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