Modeling for particle size prediction and mechanism of silicon nitride nanoparticle synthesis by chemical vapor deposition
Particle size is a vital characterization for silicon nitride nanoparticle as its scale determines its application area. Particle size prediction for synthesis of silicon nitride nanoparticle by chemical vapor deposition (CVD) is much needed. In this study, a model is proposed for particle growth du...
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Gespeichert in:
| Autor*in: |
Wen, Yu [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Rechteinformationen: |
Nutzungsrecht: © 2017 American Association for Aerosol Research 2017 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Aerosol science and technology - Philadelphia, Pa. : Taylor & Francis, 1982, 51(2017), 7, Seite 845 |
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| Übergeordnetes Werk: |
volume:51 ; year:2017 ; number:7 ; pages:845 |
| Links: |
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| DOI / URN: |
10.1080/02786826.2017.1307939 |
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| 520 | |a Particle size is a vital characterization for silicon nitride nanoparticle as its scale determines its application area. Particle size prediction for synthesis of silicon nitride nanoparticle by chemical vapor deposition (CVD) is much needed. In this study, a model is proposed for particle growth during silicon nitride nanoparticle synthesis by CVD in order to predict particle size. Comparison between modeling and experimental results validated the model. The modeling results showed that lower pressure in the condensation room would be an effective way of obtaining silicon nitride nanoparticles with smaller particle size. An expression is established to reveal the relation between the mean particle diameter of silicon nitride nanoparticle and pressure in the condensation room based on the modeling. The modeling method is capable of predicting the mean particle size of ultrafine silicon nitride powder to within 3.6% accuracy. Corresponding manufacturing thermal parameters are recommended for silicon nitride nanoparticle production with different mean particle sizes. Modeling and analysis in this article may provide theoretical guidance for production of silicon nitride nanoparticle by CVD. © 2017 American Association for Aerosol Research | ||
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10.1080/02786826.2017.1307939 doi PQ20171228 (DE-627)OLC1994870230 (DE-599)GBVOLC1994870230 (PRQ)i1495-764344f41a9ab8b0850be0143340ae51a556c009684e2234b1a857f719b7cd250 (KEY)0118896820170000051000700845modelingforparticlesizepredictionandmechanismofsil DE-627 ger DE-627 rakwb eng 530 660 DNB 58.00 bkl Wen, Yu verfasserin aut Modeling for particle size prediction and mechanism of silicon nitride nanoparticle synthesis by chemical vapor deposition 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Particle size is a vital characterization for silicon nitride nanoparticle as its scale determines its application area. Particle size prediction for synthesis of silicon nitride nanoparticle by chemical vapor deposition (CVD) is much needed. In this study, a model is proposed for particle growth during silicon nitride nanoparticle synthesis by CVD in order to predict particle size. Comparison between modeling and experimental results validated the model. The modeling results showed that lower pressure in the condensation room would be an effective way of obtaining silicon nitride nanoparticles with smaller particle size. An expression is established to reveal the relation between the mean particle diameter of silicon nitride nanoparticle and pressure in the condensation room based on the modeling. The modeling method is capable of predicting the mean particle size of ultrafine silicon nitride powder to within 3.6% accuracy. Corresponding manufacturing thermal parameters are recommended for silicon nitride nanoparticle production with different mean particle sizes. Modeling and analysis in this article may provide theoretical guidance for production of silicon nitride nanoparticle by CVD. © 2017 American Association for Aerosol Research Nutzungsrecht: © 2017 American Association for Aerosol Research 2017 Nicole Riemer Particle size Synthesis (chemistry) Silicon Aerosols Mathematical models Thermodynamic properties Accuracy Nanoparticles Aerosol research Condensates Silicon nitride Deposition Condensation Predictions Chemical vapor deposition Nanostructure Modelling Ceramics industry Xia, Dehong oth Xuan, Weiwei oth Enthalten in Aerosol science and technology Philadelphia, Pa. : Taylor & Francis, 1982 51(2017), 7, Seite 845 (DE-627)130565857 (DE-600)787246-X (DE-576)016111559 0278-6826 nnns volume:51 year:2017 number:7 pages:845 http://dx.doi.org/10.1080/02786826.2017.1307939 Volltext http://www.tandfonline.com/doi/abs/10.1080/02786826.2017.1307939 https://search.proquest.com/docview/1902118846 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_21 GBV_ILN_32 GBV_ILN_70 GBV_ILN_4313 58.00 AVZ AR 51 2017 7 845 |
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10.1080/02786826.2017.1307939 doi PQ20171228 (DE-627)OLC1994870230 (DE-599)GBVOLC1994870230 (PRQ)i1495-764344f41a9ab8b0850be0143340ae51a556c009684e2234b1a857f719b7cd250 (KEY)0118896820170000051000700845modelingforparticlesizepredictionandmechanismofsil DE-627 ger DE-627 rakwb eng 530 660 DNB 58.00 bkl Wen, Yu verfasserin aut Modeling for particle size prediction and mechanism of silicon nitride nanoparticle synthesis by chemical vapor deposition 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Particle size is a vital characterization for silicon nitride nanoparticle as its scale determines its application area. Particle size prediction for synthesis of silicon nitride nanoparticle by chemical vapor deposition (CVD) is much needed. In this study, a model is proposed for particle growth during silicon nitride nanoparticle synthesis by CVD in order to predict particle size. Comparison between modeling and experimental results validated the model. The modeling results showed that lower pressure in the condensation room would be an effective way of obtaining silicon nitride nanoparticles with smaller particle size. An expression is established to reveal the relation between the mean particle diameter of silicon nitride nanoparticle and pressure in the condensation room based on the modeling. The modeling method is capable of predicting the mean particle size of ultrafine silicon nitride powder to within 3.6% accuracy. Corresponding manufacturing thermal parameters are recommended for silicon nitride nanoparticle production with different mean particle sizes. Modeling and analysis in this article may provide theoretical guidance for production of silicon nitride nanoparticle by CVD. © 2017 American Association for Aerosol Research Nutzungsrecht: © 2017 American Association for Aerosol Research 2017 Nicole Riemer Particle size Synthesis (chemistry) Silicon Aerosols Mathematical models Thermodynamic properties Accuracy Nanoparticles Aerosol research Condensates Silicon nitride Deposition Condensation Predictions Chemical vapor deposition Nanostructure Modelling Ceramics industry Xia, Dehong oth Xuan, Weiwei oth Enthalten in Aerosol science and technology Philadelphia, Pa. : Taylor & Francis, 1982 51(2017), 7, Seite 845 (DE-627)130565857 (DE-600)787246-X (DE-576)016111559 0278-6826 nnns volume:51 year:2017 number:7 pages:845 http://dx.doi.org/10.1080/02786826.2017.1307939 Volltext http://www.tandfonline.com/doi/abs/10.1080/02786826.2017.1307939 https://search.proquest.com/docview/1902118846 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_21 GBV_ILN_32 GBV_ILN_70 GBV_ILN_4313 58.00 AVZ AR 51 2017 7 845 |
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10.1080/02786826.2017.1307939 doi PQ20171228 (DE-627)OLC1994870230 (DE-599)GBVOLC1994870230 (PRQ)i1495-764344f41a9ab8b0850be0143340ae51a556c009684e2234b1a857f719b7cd250 (KEY)0118896820170000051000700845modelingforparticlesizepredictionandmechanismofsil DE-627 ger DE-627 rakwb eng 530 660 DNB 58.00 bkl Wen, Yu verfasserin aut Modeling for particle size prediction and mechanism of silicon nitride nanoparticle synthesis by chemical vapor deposition 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Particle size is a vital characterization for silicon nitride nanoparticle as its scale determines its application area. Particle size prediction for synthesis of silicon nitride nanoparticle by chemical vapor deposition (CVD) is much needed. In this study, a model is proposed for particle growth during silicon nitride nanoparticle synthesis by CVD in order to predict particle size. Comparison between modeling and experimental results validated the model. The modeling results showed that lower pressure in the condensation room would be an effective way of obtaining silicon nitride nanoparticles with smaller particle size. An expression is established to reveal the relation between the mean particle diameter of silicon nitride nanoparticle and pressure in the condensation room based on the modeling. The modeling method is capable of predicting the mean particle size of ultrafine silicon nitride powder to within 3.6% accuracy. Corresponding manufacturing thermal parameters are recommended for silicon nitride nanoparticle production with different mean particle sizes. Modeling and analysis in this article may provide theoretical guidance for production of silicon nitride nanoparticle by CVD. © 2017 American Association for Aerosol Research Nutzungsrecht: © 2017 American Association for Aerosol Research 2017 Nicole Riemer Particle size Synthesis (chemistry) Silicon Aerosols Mathematical models Thermodynamic properties Accuracy Nanoparticles Aerosol research Condensates Silicon nitride Deposition Condensation Predictions Chemical vapor deposition Nanostructure Modelling Ceramics industry Xia, Dehong oth Xuan, Weiwei oth Enthalten in Aerosol science and technology Philadelphia, Pa. : Taylor & Francis, 1982 51(2017), 7, Seite 845 (DE-627)130565857 (DE-600)787246-X (DE-576)016111559 0278-6826 nnns volume:51 year:2017 number:7 pages:845 http://dx.doi.org/10.1080/02786826.2017.1307939 Volltext http://www.tandfonline.com/doi/abs/10.1080/02786826.2017.1307939 https://search.proquest.com/docview/1902118846 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_21 GBV_ILN_32 GBV_ILN_70 GBV_ILN_4313 58.00 AVZ AR 51 2017 7 845 |
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Modeling for particle size prediction and mechanism of silicon nitride nanoparticle synthesis by chemical vapor deposition |
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Particle size is a vital characterization for silicon nitride nanoparticle as its scale determines its application area. Particle size prediction for synthesis of silicon nitride nanoparticle by chemical vapor deposition (CVD) is much needed. In this study, a model is proposed for particle growth during silicon nitride nanoparticle synthesis by CVD in order to predict particle size. Comparison between modeling and experimental results validated the model. The modeling results showed that lower pressure in the condensation room would be an effective way of obtaining silicon nitride nanoparticles with smaller particle size. An expression is established to reveal the relation between the mean particle diameter of silicon nitride nanoparticle and pressure in the condensation room based on the modeling. The modeling method is capable of predicting the mean particle size of ultrafine silicon nitride powder to within 3.6% accuracy. Corresponding manufacturing thermal parameters are recommended for silicon nitride nanoparticle production with different mean particle sizes. Modeling and analysis in this article may provide theoretical guidance for production of silicon nitride nanoparticle by CVD. © 2017 American Association for Aerosol Research |
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Particle size is a vital characterization for silicon nitride nanoparticle as its scale determines its application area. Particle size prediction for synthesis of silicon nitride nanoparticle by chemical vapor deposition (CVD) is much needed. In this study, a model is proposed for particle growth during silicon nitride nanoparticle synthesis by CVD in order to predict particle size. Comparison between modeling and experimental results validated the model. The modeling results showed that lower pressure in the condensation room would be an effective way of obtaining silicon nitride nanoparticles with smaller particle size. An expression is established to reveal the relation between the mean particle diameter of silicon nitride nanoparticle and pressure in the condensation room based on the modeling. The modeling method is capable of predicting the mean particle size of ultrafine silicon nitride powder to within 3.6% accuracy. Corresponding manufacturing thermal parameters are recommended for silicon nitride nanoparticle production with different mean particle sizes. Modeling and analysis in this article may provide theoretical guidance for production of silicon nitride nanoparticle by CVD. © 2017 American Association for Aerosol Research |
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Particle size is a vital characterization for silicon nitride nanoparticle as its scale determines its application area. Particle size prediction for synthesis of silicon nitride nanoparticle by chemical vapor deposition (CVD) is much needed. In this study, a model is proposed for particle growth during silicon nitride nanoparticle synthesis by CVD in order to predict particle size. Comparison between modeling and experimental results validated the model. The modeling results showed that lower pressure in the condensation room would be an effective way of obtaining silicon nitride nanoparticles with smaller particle size. An expression is established to reveal the relation between the mean particle diameter of silicon nitride nanoparticle and pressure in the condensation room based on the modeling. The modeling method is capable of predicting the mean particle size of ultrafine silicon nitride powder to within 3.6% accuracy. Corresponding manufacturing thermal parameters are recommended for silicon nitride nanoparticle production with different mean particle sizes. Modeling and analysis in this article may provide theoretical guidance for production of silicon nitride nanoparticle by CVD. © 2017 American Association for Aerosol Research |
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