Quantifying the distortion by spin–orbit and spin–spin coupling in molecular clusters using Molecular Quantum Similarity
Abstract The manuscript discusses the concepts of spin–orbit and spin–spin coupling in atomic physics and Molecular Quantum Similarity (MQS) in molecular clusters. spin–orbit and spin–spin coupling arises from the interaction between an electron's spin and its motion around the nucleus and elec...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Morales-Bayuelo, Alejandro [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
Molecular Quantum Similarity indices |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Journal of mathematical chemistry - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987, 62(2023), 3 vom: 13. Dez., Seite 591-605 |
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| Übergeordnetes Werk: |
volume:62 ; year:2023 ; number:3 ; day:13 ; month:12 ; pages:591-605 |
| Links: |
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| DOI / URN: |
10.1007/s10910-023-01552-x |
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SPR054738032 |
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| 520 | |a Abstract The manuscript discusses the concepts of spin–orbit and spin–spin coupling in atomic physics and Molecular Quantum Similarity (MQS) in molecular clusters. spin–orbit and spin–spin coupling arises from the interaction between an electron's spin and its motion around the nucleus and electron–electron interaction and plays a crucial role in determining energy levels and spectral lines in atoms with heavy nuclei. On the other hand, MQS is a computational approach to compare the electronic density distributions in different molecular systems. In this order of ideas, the study aims to answer questions about electronic and structural differences caused by the spin–orbit and spin–spin coupling from the initial geometry [Steradians (SR) geometry] using the MQS framework. The MQS is based on the Molecular Quantum Similarity Measure (MQSM) using different positive operators such as Dirac delta and Coulomb operators to quantify the similarity between molecular systems. The paper presents tables with MQSM indices and Euclidean distances for different molecular clusters using initial geometry vs. geometry involved spin–orbit and spin–spin coupling. The scalar, spin–orbit and spin–spin relativistic coupling were incorporated using Amsterdam Density Functional code. The results show significant coupling of spin–orbit and spin–spin coupling on the similarity measures between different molecules. The manuscript suggests that understanding the relationship between spin–orbit and spin–spin coupling and quantum similarity could lead to deeper insights into electronic interactions in complex molecular systems and has potential applications in quantum mechanics and molecular physics. | ||
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| 650 | 4 | |a Geometry distortion |7 (dpeaa)DE-He213 | |
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10.1007/s10910-023-01552-x doi (DE-627)SPR054738032 (SPR)s10910-023-01552-x-e DE-627 ger DE-627 rakwb eng Morales-Bayuelo, Alejandro verfasserin aut Quantifying the distortion by spin–orbit and spin–spin coupling in molecular clusters using Molecular Quantum Similarity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The manuscript discusses the concepts of spin–orbit and spin–spin coupling in atomic physics and Molecular Quantum Similarity (MQS) in molecular clusters. spin–orbit and spin–spin coupling arises from the interaction between an electron's spin and its motion around the nucleus and electron–electron interaction and plays a crucial role in determining energy levels and spectral lines in atoms with heavy nuclei. On the other hand, MQS is a computational approach to compare the electronic density distributions in different molecular systems. In this order of ideas, the study aims to answer questions about electronic and structural differences caused by the spin–orbit and spin–spin coupling from the initial geometry [Steradians (SR) geometry] using the MQS framework. The MQS is based on the Molecular Quantum Similarity Measure (MQSM) using different positive operators such as Dirac delta and Coulomb operators to quantify the similarity between molecular systems. The paper presents tables with MQSM indices and Euclidean distances for different molecular clusters using initial geometry vs. geometry involved spin–orbit and spin–spin coupling. The scalar, spin–orbit and spin–spin relativistic coupling were incorporated using Amsterdam Density Functional code. The results show significant coupling of spin–orbit and spin–spin coupling on the similarity measures between different molecules. The manuscript suggests that understanding the relationship between spin–orbit and spin–spin coupling and quantum similarity could lead to deeper insights into electronic interactions in complex molecular systems and has potential applications in quantum mechanics and molecular physics. Molecular Quantum Similarity indices (dpeaa)DE-He213 Spin–orbit and spin–spin coupling (dpeaa)DE-He213 Coulomb similarity (dpeaa)DE-He213 Overlap similarity (dpeaa)DE-He213 Euclidean distances (dpeaa)DE-He213 Geometry distortion (dpeaa)DE-He213 Enthalten in Journal of mathematical chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987 62(2023), 3 vom: 13. Dez., Seite 591-605 (DE-627)30246879X (DE-600)1491406-2 1572-8897 nnns volume:62 year:2023 number:3 day:13 month:12 pages:591-605 https://dx.doi.org/10.1007/s10910-023-01552-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 62 2023 3 13 12 591-605 |
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10.1007/s10910-023-01552-x doi (DE-627)SPR054738032 (SPR)s10910-023-01552-x-e DE-627 ger DE-627 rakwb eng Morales-Bayuelo, Alejandro verfasserin aut Quantifying the distortion by spin–orbit and spin–spin coupling in molecular clusters using Molecular Quantum Similarity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The manuscript discusses the concepts of spin–orbit and spin–spin coupling in atomic physics and Molecular Quantum Similarity (MQS) in molecular clusters. spin–orbit and spin–spin coupling arises from the interaction between an electron's spin and its motion around the nucleus and electron–electron interaction and plays a crucial role in determining energy levels and spectral lines in atoms with heavy nuclei. On the other hand, MQS is a computational approach to compare the electronic density distributions in different molecular systems. In this order of ideas, the study aims to answer questions about electronic and structural differences caused by the spin–orbit and spin–spin coupling from the initial geometry [Steradians (SR) geometry] using the MQS framework. The MQS is based on the Molecular Quantum Similarity Measure (MQSM) using different positive operators such as Dirac delta and Coulomb operators to quantify the similarity between molecular systems. The paper presents tables with MQSM indices and Euclidean distances for different molecular clusters using initial geometry vs. geometry involved spin–orbit and spin–spin coupling. The scalar, spin–orbit and spin–spin relativistic coupling were incorporated using Amsterdam Density Functional code. The results show significant coupling of spin–orbit and spin–spin coupling on the similarity measures between different molecules. The manuscript suggests that understanding the relationship between spin–orbit and spin–spin coupling and quantum similarity could lead to deeper insights into electronic interactions in complex molecular systems and has potential applications in quantum mechanics and molecular physics. Molecular Quantum Similarity indices (dpeaa)DE-He213 Spin–orbit and spin–spin coupling (dpeaa)DE-He213 Coulomb similarity (dpeaa)DE-He213 Overlap similarity (dpeaa)DE-He213 Euclidean distances (dpeaa)DE-He213 Geometry distortion (dpeaa)DE-He213 Enthalten in Journal of mathematical chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987 62(2023), 3 vom: 13. Dez., Seite 591-605 (DE-627)30246879X (DE-600)1491406-2 1572-8897 nnns volume:62 year:2023 number:3 day:13 month:12 pages:591-605 https://dx.doi.org/10.1007/s10910-023-01552-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 62 2023 3 13 12 591-605 |
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10.1007/s10910-023-01552-x doi (DE-627)SPR054738032 (SPR)s10910-023-01552-x-e DE-627 ger DE-627 rakwb eng Morales-Bayuelo, Alejandro verfasserin aut Quantifying the distortion by spin–orbit and spin–spin coupling in molecular clusters using Molecular Quantum Similarity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The manuscript discusses the concepts of spin–orbit and spin–spin coupling in atomic physics and Molecular Quantum Similarity (MQS) in molecular clusters. spin–orbit and spin–spin coupling arises from the interaction between an electron's spin and its motion around the nucleus and electron–electron interaction and plays a crucial role in determining energy levels and spectral lines in atoms with heavy nuclei. On the other hand, MQS is a computational approach to compare the electronic density distributions in different molecular systems. In this order of ideas, the study aims to answer questions about electronic and structural differences caused by the spin–orbit and spin–spin coupling from the initial geometry [Steradians (SR) geometry] using the MQS framework. The MQS is based on the Molecular Quantum Similarity Measure (MQSM) using different positive operators such as Dirac delta and Coulomb operators to quantify the similarity between molecular systems. The paper presents tables with MQSM indices and Euclidean distances for different molecular clusters using initial geometry vs. geometry involved spin–orbit and spin–spin coupling. The scalar, spin–orbit and spin–spin relativistic coupling were incorporated using Amsterdam Density Functional code. The results show significant coupling of spin–orbit and spin–spin coupling on the similarity measures between different molecules. The manuscript suggests that understanding the relationship between spin–orbit and spin–spin coupling and quantum similarity could lead to deeper insights into electronic interactions in complex molecular systems and has potential applications in quantum mechanics and molecular physics. Molecular Quantum Similarity indices (dpeaa)DE-He213 Spin–orbit and spin–spin coupling (dpeaa)DE-He213 Coulomb similarity (dpeaa)DE-He213 Overlap similarity (dpeaa)DE-He213 Euclidean distances (dpeaa)DE-He213 Geometry distortion (dpeaa)DE-He213 Enthalten in Journal of mathematical chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987 62(2023), 3 vom: 13. Dez., Seite 591-605 (DE-627)30246879X (DE-600)1491406-2 1572-8897 nnns volume:62 year:2023 number:3 day:13 month:12 pages:591-605 https://dx.doi.org/10.1007/s10910-023-01552-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 62 2023 3 13 12 591-605 |
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10.1007/s10910-023-01552-x doi (DE-627)SPR054738032 (SPR)s10910-023-01552-x-e DE-627 ger DE-627 rakwb eng Morales-Bayuelo, Alejandro verfasserin aut Quantifying the distortion by spin–orbit and spin–spin coupling in molecular clusters using Molecular Quantum Similarity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The manuscript discusses the concepts of spin–orbit and spin–spin coupling in atomic physics and Molecular Quantum Similarity (MQS) in molecular clusters. spin–orbit and spin–spin coupling arises from the interaction between an electron's spin and its motion around the nucleus and electron–electron interaction and plays a crucial role in determining energy levels and spectral lines in atoms with heavy nuclei. On the other hand, MQS is a computational approach to compare the electronic density distributions in different molecular systems. In this order of ideas, the study aims to answer questions about electronic and structural differences caused by the spin–orbit and spin–spin coupling from the initial geometry [Steradians (SR) geometry] using the MQS framework. The MQS is based on the Molecular Quantum Similarity Measure (MQSM) using different positive operators such as Dirac delta and Coulomb operators to quantify the similarity between molecular systems. The paper presents tables with MQSM indices and Euclidean distances for different molecular clusters using initial geometry vs. geometry involved spin–orbit and spin–spin coupling. The scalar, spin–orbit and spin–spin relativistic coupling were incorporated using Amsterdam Density Functional code. The results show significant coupling of spin–orbit and spin–spin coupling on the similarity measures between different molecules. The manuscript suggests that understanding the relationship between spin–orbit and spin–spin coupling and quantum similarity could lead to deeper insights into electronic interactions in complex molecular systems and has potential applications in quantum mechanics and molecular physics. Molecular Quantum Similarity indices (dpeaa)DE-He213 Spin–orbit and spin–spin coupling (dpeaa)DE-He213 Coulomb similarity (dpeaa)DE-He213 Overlap similarity (dpeaa)DE-He213 Euclidean distances (dpeaa)DE-He213 Geometry distortion (dpeaa)DE-He213 Enthalten in Journal of mathematical chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987 62(2023), 3 vom: 13. Dez., Seite 591-605 (DE-627)30246879X (DE-600)1491406-2 1572-8897 nnns volume:62 year:2023 number:3 day:13 month:12 pages:591-605 https://dx.doi.org/10.1007/s10910-023-01552-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 62 2023 3 13 12 591-605 |
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10.1007/s10910-023-01552-x doi (DE-627)SPR054738032 (SPR)s10910-023-01552-x-e DE-627 ger DE-627 rakwb eng Morales-Bayuelo, Alejandro verfasserin aut Quantifying the distortion by spin–orbit and spin–spin coupling in molecular clusters using Molecular Quantum Similarity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The manuscript discusses the concepts of spin–orbit and spin–spin coupling in atomic physics and Molecular Quantum Similarity (MQS) in molecular clusters. spin–orbit and spin–spin coupling arises from the interaction between an electron's spin and its motion around the nucleus and electron–electron interaction and plays a crucial role in determining energy levels and spectral lines in atoms with heavy nuclei. On the other hand, MQS is a computational approach to compare the electronic density distributions in different molecular systems. In this order of ideas, the study aims to answer questions about electronic and structural differences caused by the spin–orbit and spin–spin coupling from the initial geometry [Steradians (SR) geometry] using the MQS framework. The MQS is based on the Molecular Quantum Similarity Measure (MQSM) using different positive operators such as Dirac delta and Coulomb operators to quantify the similarity between molecular systems. The paper presents tables with MQSM indices and Euclidean distances for different molecular clusters using initial geometry vs. geometry involved spin–orbit and spin–spin coupling. The scalar, spin–orbit and spin–spin relativistic coupling were incorporated using Amsterdam Density Functional code. The results show significant coupling of spin–orbit and spin–spin coupling on the similarity measures between different molecules. The manuscript suggests that understanding the relationship between spin–orbit and spin–spin coupling and quantum similarity could lead to deeper insights into electronic interactions in complex molecular systems and has potential applications in quantum mechanics and molecular physics. Molecular Quantum Similarity indices (dpeaa)DE-He213 Spin–orbit and spin–spin coupling (dpeaa)DE-He213 Coulomb similarity (dpeaa)DE-He213 Overlap similarity (dpeaa)DE-He213 Euclidean distances (dpeaa)DE-He213 Geometry distortion (dpeaa)DE-He213 Enthalten in Journal of mathematical chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987 62(2023), 3 vom: 13. Dez., Seite 591-605 (DE-627)30246879X (DE-600)1491406-2 1572-8897 nnns volume:62 year:2023 number:3 day:13 month:12 pages:591-605 https://dx.doi.org/10.1007/s10910-023-01552-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 62 2023 3 13 12 591-605 |
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Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The manuscript discusses the concepts of spin–orbit and spin–spin coupling in atomic physics and Molecular Quantum Similarity (MQS) in molecular clusters. spin–orbit and spin–spin coupling arises from the interaction between an electron's spin and its motion around the nucleus and electron–electron interaction and plays a crucial role in determining energy levels and spectral lines in atoms with heavy nuclei. On the other hand, MQS is a computational approach to compare the electronic density distributions in different molecular systems. In this order of ideas, the study aims to answer questions about electronic and structural differences caused by the spin–orbit and spin–spin coupling from the initial geometry [Steradians (SR) geometry] using the MQS framework. The MQS is based on the Molecular Quantum Similarity Measure (MQSM) using different positive operators such as Dirac delta and Coulomb operators to quantify the similarity between molecular systems. The paper presents tables with MQSM indices and Euclidean distances for different molecular clusters using initial geometry vs. geometry involved spin–orbit and spin–spin coupling. The scalar, spin–orbit and spin–spin relativistic coupling were incorporated using Amsterdam Density Functional code. The results show significant coupling of spin–orbit and spin–spin coupling on the similarity measures between different molecules. 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Morales-Bayuelo, Alejandro |
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Morales-Bayuelo, Alejandro misc Molecular Quantum Similarity indices misc Spin–orbit and spin–spin coupling misc Coulomb similarity misc Overlap similarity misc Euclidean distances misc Geometry distortion Quantifying the distortion by spin–orbit and spin–spin coupling in molecular clusters using Molecular Quantum Similarity |
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Quantifying the distortion by spin–orbit and spin–spin coupling in molecular clusters using Molecular Quantum Similarity Molecular Quantum Similarity indices (dpeaa)DE-He213 Spin–orbit and spin–spin coupling (dpeaa)DE-He213 Coulomb similarity (dpeaa)DE-He213 Overlap similarity (dpeaa)DE-He213 Euclidean distances (dpeaa)DE-He213 Geometry distortion (dpeaa)DE-He213 |
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Quantifying the distortion by spin–orbit and spin–spin coupling in molecular clusters using Molecular Quantum Similarity |
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quantifying the distortion by spin–orbit and spin–spin coupling in molecular clusters using molecular quantum similarity |
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Quantifying the distortion by spin–orbit and spin–spin coupling in molecular clusters using Molecular Quantum Similarity |
| abstract |
Abstract The manuscript discusses the concepts of spin–orbit and spin–spin coupling in atomic physics and Molecular Quantum Similarity (MQS) in molecular clusters. spin–orbit and spin–spin coupling arises from the interaction between an electron's spin and its motion around the nucleus and electron–electron interaction and plays a crucial role in determining energy levels and spectral lines in atoms with heavy nuclei. On the other hand, MQS is a computational approach to compare the electronic density distributions in different molecular systems. In this order of ideas, the study aims to answer questions about electronic and structural differences caused by the spin–orbit and spin–spin coupling from the initial geometry [Steradians (SR) geometry] using the MQS framework. The MQS is based on the Molecular Quantum Similarity Measure (MQSM) using different positive operators such as Dirac delta and Coulomb operators to quantify the similarity between molecular systems. The paper presents tables with MQSM indices and Euclidean distances for different molecular clusters using initial geometry vs. geometry involved spin–orbit and spin–spin coupling. The scalar, spin–orbit and spin–spin relativistic coupling were incorporated using Amsterdam Density Functional code. The results show significant coupling of spin–orbit and spin–spin coupling on the similarity measures between different molecules. The manuscript suggests that understanding the relationship between spin–orbit and spin–spin coupling and quantum similarity could lead to deeper insights into electronic interactions in complex molecular systems and has potential applications in quantum mechanics and molecular physics. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Abstract The manuscript discusses the concepts of spin–orbit and spin–spin coupling in atomic physics and Molecular Quantum Similarity (MQS) in molecular clusters. spin–orbit and spin–spin coupling arises from the interaction between an electron's spin and its motion around the nucleus and electron–electron interaction and plays a crucial role in determining energy levels and spectral lines in atoms with heavy nuclei. On the other hand, MQS is a computational approach to compare the electronic density distributions in different molecular systems. In this order of ideas, the study aims to answer questions about electronic and structural differences caused by the spin–orbit and spin–spin coupling from the initial geometry [Steradians (SR) geometry] using the MQS framework. The MQS is based on the Molecular Quantum Similarity Measure (MQSM) using different positive operators such as Dirac delta and Coulomb operators to quantify the similarity between molecular systems. The paper presents tables with MQSM indices and Euclidean distances for different molecular clusters using initial geometry vs. geometry involved spin–orbit and spin–spin coupling. The scalar, spin–orbit and spin–spin relativistic coupling were incorporated using Amsterdam Density Functional code. The results show significant coupling of spin–orbit and spin–spin coupling on the similarity measures between different molecules. The manuscript suggests that understanding the relationship between spin–orbit and spin–spin coupling and quantum similarity could lead to deeper insights into electronic interactions in complex molecular systems and has potential applications in quantum mechanics and molecular physics. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract The manuscript discusses the concepts of spin–orbit and spin–spin coupling in atomic physics and Molecular Quantum Similarity (MQS) in molecular clusters. spin–orbit and spin–spin coupling arises from the interaction between an electron's spin and its motion around the nucleus and electron–electron interaction and plays a crucial role in determining energy levels and spectral lines in atoms with heavy nuclei. On the other hand, MQS is a computational approach to compare the electronic density distributions in different molecular systems. In this order of ideas, the study aims to answer questions about electronic and structural differences caused by the spin–orbit and spin–spin coupling from the initial geometry [Steradians (SR) geometry] using the MQS framework. The MQS is based on the Molecular Quantum Similarity Measure (MQSM) using different positive operators such as Dirac delta and Coulomb operators to quantify the similarity between molecular systems. The paper presents tables with MQSM indices and Euclidean distances for different molecular clusters using initial geometry vs. geometry involved spin–orbit and spin–spin coupling. The scalar, spin–orbit and spin–spin relativistic coupling were incorporated using Amsterdam Density Functional code. The results show significant coupling of spin–orbit and spin–spin coupling on the similarity measures between different molecules. The manuscript suggests that understanding the relationship between spin–orbit and spin–spin coupling and quantum similarity could lead to deeper insights into electronic interactions in complex molecular systems and has potential applications in quantum mechanics and molecular physics. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Quantifying the distortion by spin–orbit and spin–spin coupling in molecular clusters using Molecular Quantum Similarity |
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https://dx.doi.org/10.1007/s10910-023-01552-x |
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| score |
7.3994446 |