Statistical approach to modeling relationships of composition – structure – property I: Alkaline earth phosphate glasses
This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phospha...
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| Autor*in: |
Zhang, L.Y. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018transfer abstract |
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| Schlagwörter: |
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| Umfang: |
9 |
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| Übergeordnetes Werk: |
Enthalten in: Factors associated with canine resource guarding behaviour in the presence of people: A cross-sectional survey of dog owners - Jacobs, Jacquelyn A. ELSEVIER, 2017, JAL : an interdisciplinary journal of materials science and solid-state chemistry and physics, Lausanne |
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| Übergeordnetes Werk: |
volume:734 ; year:2018 ; day:15 ; month:02 ; pages:163-171 ; extent:9 |
| Links: |
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| DOI / URN: |
10.1016/j.jallcom.2017.11.007 |
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| 245 | 1 | 0 | |a Statistical approach to modeling relationships of composition – structure – property I: Alkaline earth phosphate glasses |
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| 520 | |a This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. | ||
| 520 | |a This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. | ||
| 650 | 7 | |a NMR |2 Elsevier | |
| 650 | 7 | |a Statistical modeling |2 Elsevier | |
| 650 | 7 | |a Composition-structure-property correlation |2 Elsevier | |
| 650 | 7 | |a Phosphate glass |2 Elsevier | |
| 650 | 7 | |a Model based property simulation |2 Elsevier | |
| 700 | 1 | |a Li, H. |4 oth | |
| 700 | 1 | |a Hu, L.L. |4 oth | |
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10.1016/j.jallcom.2017.11.007 doi GBV00000000000359.pica (DE-627)ELV041172558 (ELSEVIER)S0925-8388(17)33739-8 DE-627 ger DE-627 rakwb eng 630 VZ Zhang, L.Y. verfasserin aut Statistical approach to modeling relationships of composition – structure – property I: Alkaline earth phosphate glasses 2018transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. NMR Elsevier Statistical modeling Elsevier Composition-structure-property correlation Elsevier Phosphate glass Elsevier Model based property simulation Elsevier Li, H. oth Hu, L.L. oth Enthalten in Elsevier Jacobs, Jacquelyn A. ELSEVIER Factors associated with canine resource guarding behaviour in the presence of people: A cross-sectional survey of dog owners 2017 JAL : an interdisciplinary journal of materials science and solid-state chemistry and physics Lausanne (DE-627)ELV001115774 volume:734 year:2018 day:15 month:02 pages:163-171 extent:9 https://doi.org/10.1016/j.jallcom.2017.11.007 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 734 2018 15 0215 163-171 9 |
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10.1016/j.jallcom.2017.11.007 doi GBV00000000000359.pica (DE-627)ELV041172558 (ELSEVIER)S0925-8388(17)33739-8 DE-627 ger DE-627 rakwb eng 630 VZ Zhang, L.Y. verfasserin aut Statistical approach to modeling relationships of composition – structure – property I: Alkaline earth phosphate glasses 2018transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. NMR Elsevier Statistical modeling Elsevier Composition-structure-property correlation Elsevier Phosphate glass Elsevier Model based property simulation Elsevier Li, H. oth Hu, L.L. oth Enthalten in Elsevier Jacobs, Jacquelyn A. ELSEVIER Factors associated with canine resource guarding behaviour in the presence of people: A cross-sectional survey of dog owners 2017 JAL : an interdisciplinary journal of materials science and solid-state chemistry and physics Lausanne (DE-627)ELV001115774 volume:734 year:2018 day:15 month:02 pages:163-171 extent:9 https://doi.org/10.1016/j.jallcom.2017.11.007 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 734 2018 15 0215 163-171 9 |
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10.1016/j.jallcom.2017.11.007 doi GBV00000000000359.pica (DE-627)ELV041172558 (ELSEVIER)S0925-8388(17)33739-8 DE-627 ger DE-627 rakwb eng 630 VZ Zhang, L.Y. verfasserin aut Statistical approach to modeling relationships of composition – structure – property I: Alkaline earth phosphate glasses 2018transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. NMR Elsevier Statistical modeling Elsevier Composition-structure-property correlation Elsevier Phosphate glass Elsevier Model based property simulation Elsevier Li, H. oth Hu, L.L. oth Enthalten in Elsevier Jacobs, Jacquelyn A. ELSEVIER Factors associated with canine resource guarding behaviour in the presence of people: A cross-sectional survey of dog owners 2017 JAL : an interdisciplinary journal of materials science and solid-state chemistry and physics Lausanne (DE-627)ELV001115774 volume:734 year:2018 day:15 month:02 pages:163-171 extent:9 https://doi.org/10.1016/j.jallcom.2017.11.007 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 734 2018 15 0215 163-171 9 |
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10.1016/j.jallcom.2017.11.007 doi GBV00000000000359.pica (DE-627)ELV041172558 (ELSEVIER)S0925-8388(17)33739-8 DE-627 ger DE-627 rakwb eng 630 VZ Zhang, L.Y. verfasserin aut Statistical approach to modeling relationships of composition – structure – property I: Alkaline earth phosphate glasses 2018transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. NMR Elsevier Statistical modeling Elsevier Composition-structure-property correlation Elsevier Phosphate glass Elsevier Model based property simulation Elsevier Li, H. oth Hu, L.L. oth Enthalten in Elsevier Jacobs, Jacquelyn A. ELSEVIER Factors associated with canine resource guarding behaviour in the presence of people: A cross-sectional survey of dog owners 2017 JAL : an interdisciplinary journal of materials science and solid-state chemistry and physics Lausanne (DE-627)ELV001115774 volume:734 year:2018 day:15 month:02 pages:163-171 extent:9 https://doi.org/10.1016/j.jallcom.2017.11.007 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 734 2018 15 0215 163-171 9 |
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10.1016/j.jallcom.2017.11.007 doi GBV00000000000359.pica (DE-627)ELV041172558 (ELSEVIER)S0925-8388(17)33739-8 DE-627 ger DE-627 rakwb eng 630 VZ Zhang, L.Y. verfasserin aut Statistical approach to modeling relationships of composition – structure – property I: Alkaline earth phosphate glasses 2018transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. NMR Elsevier Statistical modeling Elsevier Composition-structure-property correlation Elsevier Phosphate glass Elsevier Model based property simulation Elsevier Li, H. oth Hu, L.L. oth Enthalten in Elsevier Jacobs, Jacquelyn A. ELSEVIER Factors associated with canine resource guarding behaviour in the presence of people: A cross-sectional survey of dog owners 2017 JAL : an interdisciplinary journal of materials science and solid-state chemistry and physics Lausanne (DE-627)ELV001115774 volume:734 year:2018 day:15 month:02 pages:163-171 extent:9 https://doi.org/10.1016/j.jallcom.2017.11.007 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 734 2018 15 0215 163-171 9 |
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Statistical approach to modeling relationships of composition – structure – property I: Alkaline earth phosphate glasses |
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This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. |
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This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. |
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This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. |
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