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      Original review of quantum chemistry and 3D modeling of artificial intelligence

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      Publication date (Print):
      Journal: Journal of Quantum Physics and Materials Chemistry
      Publisher: Jiangxi Province ChengZhu Environmental Engineering Company Ltd

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          Abstract

          This article has reviewed the quantum chemistry theories and case studies in the past, attempting to further improve both theories and methods on the basis of 3D modeling technology.

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          Most cited references11

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          Van der Waals force and Dark Matter

          Huan Liu (2022)
          Article 6. Van der Waals force and Dark Matter/范德华力与暗物质 Author: Liu Huan (1983-), Master of Science (First Class Honours), The University of Auckland.
          Article 0 comments Cited 14 times – based on 0 reviews     Review now
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            Quantum Mechanics

            Huan Liu (2022)
            Article 1. Quantum Mechanics/量子力学 Author: Liu Huan (1983- ), Master of Science (First Class Honours), The University of Auckland.
            Article 0 comments Cited 7 times – based on 0 reviews     Review now
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              The anti-matter of symmetric three-dimensional spaces along the fourth dimension axis

              Huan Liu (2022)
              Article 2. The anti-matter of symmetric three-dimensional spaces along the fourth dimension axis/第四维度轴上的对称三维空间与反物质原理 Author: Liu Huan (1983-), Master of Science (First Class Honours), The University of Auckland.
              Article 0 comments Cited 6 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Journal
                Title: Journal of Quantum Physics and Materials Chemistry
                Abbreviated Title: JQPMC
                Publisher: Jiangxi Province ChengZhu Environmental Engineering Company Ltd
                ISSN (Print): 29584027
                Publication date Created: November 21 2023
                Publication date (Print): November 21 2023
                Article
                DOI: 10.58473/JQPMC0013
                SO-VID: 694ff305-db78-4bfa-a22b-8e8e6a3dbdfb
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