Abstract An innovation method has been invented for the feasibility of combined Artificial Intelligence (AI) and nanoscale techniques for improving the quality of turquoise. The type of gemstone characterized by gemological properties, digital image analysis and Artificial intelligence (AI). The method relies on digital image acquisition,optical properties of gemstones analysis and image processing by Artificial intelligence (AI). 1600 series of digital images were taken from 18 samples from different areas of Neyshabour mine turquoise and then transmitted to a database. The accuracy of gemstone identification using the method was %94 for turquoise. Neyshabur turquoise is highly valued due to its unique mineralogical composition and very high quality of its turquoise. However, microstructural heterogeneity, the presence of secondary phases and variable amounts of impurities affect the quality and classification of this gemstone. In this study, A systematic mineralogical, geochemical and spectroscopic studies of high and low-quality turquoises from the Neyshabur turquoise mine were examined using conventional gemological methods combined with advanced techniques such as XRD, X-ray fluorescence (XRF), SEM, Raman spectroscopy and X ray maping (XRM). Comparison of RAMAN, XRF, XRD, and SEM analyses of Neyshabur turquoise with turquoise from other regions of the world showed that Neyshabur turquoise has its own unique XRD pattern that is significantly different from that of turquoise from other regions of the world. This study demonstrated that high-quality turquoise from the Neyshabur mine should be introduced as the standard reference for turquoise in the world. Keywords: Neyshabur turquoise, advanced techniques, Artificial intelligence (AI), XRM

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