Scientific software flexibility

Finally, critical cues, as visual guides, need to be provided to enable the modeler to appraise progress. For example, the adequacy of data to facilitate identification of a particular parameter or the flexibility of a model to mimic temporal patterns manifest in the data may be issues at the back of the investigators mind as the modeling episode advances. Modeling software must anticipate these and address them in terms that the user is comfortable with as opposed to terms which a scientific programmer might respond to. 

In Figure 7, each circle depicts the research database of a department in a chemical/ pharmaceutical company. The union of all circles represents the chemical-scientific database of the company. Intersecting circles indicate data sharing and communication between departments. Since each department views its data in special ways and may select particular software, it is difficult to design a chemical-scientific database system that treats all unions and intersections. A chemical-scientific database system that can be customised for the various data views is a flexible solution to this difficulty. 

Microsoft Excel and Visual Basic for Application (VBA) are also frequently used for scientific calculations. They are convenient to use and generally available but suffer from the fact that the calculations performed in Basic code or the Excel sheet are not easy to read and understand by users other than the developer. Several examples employ Excel and/or VBA and demonstrate applications where they offer great advantages due to their flexibility and the ability to easily interface to COM components of other software products. For the less-trained or infrequent... 

Lee, M. H., and J. J. Rowland, eds. 1995. Intelligent Assembly Systems. Singapore/Hackensack, NJ World Scientific. Written for robotics, mechanical, and systems engineers, this book covers topics like software tools and administration, diagnosis systems and error handling, and sensor-actuator integration methods—all essential for the development of flexible automation systems and robotics. 

However, to move these KMC modeling tools from the hands of experts to a more general audience, there needs to be a more concerted and focused effort in software development. Many of the scientific contributions mentioned in this review are based on individual efforts that rely on in-house codes. The impact of these efforts could be expanded if some flexible, benchmarked codes were readily available. Unfortunately, the variety of electrochemical systems encountered creates limits to simple transferability. Finally, as DFT-based parameter estimation becomes more robust and cost-effective, and as additional KMC simulations of electrochemical systems are demonstrated, we expect that KMC will play an important role in connecting atomistic-level information to experimentally observable phenomena, aiding in the design of many next-generation electrochemical devices. 

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