Publication date: 27th June 2014
A program to design the best semi-conductor materials meeting various performance standards relating to functionality in target contexts, could be designed. This program could use empirical and projected data, relating to conductivity, temperature and pressure-related properties in order to design semi-conductors as required. The program would be based on decision tree form algorithm. Thus with the required performance data loaded, the program could work in a combinatorial manner to find the best semi-conductor compound meeting questions asked in a decision tree manner, e.g., a soft metal halide or transition metal oxide, in terms of conductivity in terms of load and velocity, temperature and pressure-related properties and other properties such as how brittle or flexible, as well as longevity given the projected workload. The level of importance of each criterion could be ranked, e.g., temperature might the most important and thus compounds suitable with respect to this criterion selected and then ranking in terms of the other properties would follow. A final list could deliver compounds ranked with respect to these requirements. Thus, for example, the program might first considering temperature related features and considering compounds in a combinatorial fashion, find a range that meet that criteria, then for example flexibility could be considered and the compounds found to be suitable in terms of temperature could be ranked in terms of required flexibility of the material and so on in the order of priority in terms of required properties. Triangulation wcould allow the optimum semi-conducting material to be chosen, given the relative importance of the various criteria and the semi-conductor's properties as ranked with respect to various aspects under consideration. In this way, circuitry could be designed for all types of computational devices, from super-computers, laptops and tablets, to computational hardware relating to such devices as mobile telephones, portable mp3 players as well as home entertainment systems. After in silico design of a semi-conducting material, empirical studies could be used to confirm and indeed optimize the choice of material for the target device and context.
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