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reliability of the reported properties, and deliver the data in a well-structured form to the final industrial users. Recent advances in AI (Artificial Intelligence), specifically in NLP (Natural
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the metals and polymers sectors. Innovations that improve the availability of reliable, custom, on-demand ceramic parts will benefit a range of structural, thermal management, medical, and electronic
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reliable results on larger molecular systems with suitable parameterization. We are studying ways to automate parameter generation to facilitate further studies. Applications of the tight binding methodology
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distorts the electronic wave functions and perturbs the associated energy levels. This effect is likely to be a serious material issue, which can affect the reliability and the performance of the finished
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correlations were traditionally developed on the basis of some reliable but often very limited data compilations. Currently, large comprehensive experimental data collections have not only become more readily
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stimulates the search for more effective approaches. Two groups of thermophysical property prediction methods are under rapid development presently – Quantitative Structure-Property Relationship (QSPR) methods