Core C: Modeling and Risk Forecasting

Formulation and Validation of a Functional Assay-Driven Model of Nanoparticle Aquatic Transport

N. K. Geitner, Bossa, N. , and Wiesner, M. R. , “Formulation and Validation of a Functional Assay-Driven Model of Nanoparticle Aquatic Transport”, Environmental Science & Technology, 2019.

Nanotechnology for sustainable food production: promising opportunities and scientific challenges

S. M. Rodrigues, Demokritou, P. , Dokoozlian, N. , Hendren, C. O. , Karn, B. , Mauter, M. S. , Sadik, O. A. , Safarpour, M. , Unrine, J. M. , and Viers, J. , “Nanotechnology for sustainable food production: promising opportunities and scientific challenges”, Environmental Science: NanoEnvironmental Science: Nano, vol. 4, pp. 767-781, 2017.

Comparative Persistence of Engineered Nanoparticles in a Complex Aquatic Ecosystem

B. P. Espinasse, Geitner, N. K. , Schierz, A. , Therezien, M. , Richardson, C. J. , Lowry, G. V. , Ferguson, L. , and Wiesner, M. R. , “Comparative Persistence of Engineered Nanoparticles in a Complex Aquatic Ecosystem”, Environmental Science & Technology, 2018.

Measuring Nanoparticle Attachment Efficiency in Complex Systems

N. K. Geitner, O’Brien, N. J. , Turner, A. A. , Cummins, E. J. , and Wiesner, M. R. , “Measuring Nanoparticle Attachment Efficiency in Complex Systems”, Environmental Science & Technology, 2017.

Time and Nanoparticle Concentration Affect the Extractability of Cu from CuO NP-Amended Soil

X. Gao, Spielman-Sun, E. , Rodrigues, S. M. , Casman, E. A. , and Lowry, G. V. , “Time and Nanoparticle Concentration Affect the Extractability of Cu from CuO NP-Amended Soil”, Environmental Science & TechnologyEnvironmental Science & Technology, 2017.

Accurate and fast numerical algorithms for tracking particle size distributions during nanoparticle aggregation and dissolution

A. L. Dale, Lowry, G. V. , and Casman, E. A. , “Accurate and fast numerical algorithms for tracking particle size distributions during nanoparticle aggregation and dissolution”, Environmental Science: NanoEnvironmental Science: Nano, vol. 4, pp. 89-104, 2016.

Nanoparticle Surface Affinity as a Predictor of Trophic Transfer

N. K. Geitner, Marinakos, S. M. , Guo, C. , O’Brien, N. , and Wiesner, M. R. , “Nanoparticle Surface Affinity as a Predictor of Trophic Transfer”, Environmental Science & Technology, vol. 50, no. 13, pp. 6663 - 6669, 2016.

Modeling Nanomaterial Environmental Fate in Aquatic Systems

A. L. Dale, Casman, E. A. , Lowry, G. V. , Lead, J. R. , Viparelli, E. , and Baalousha, M. , “Modeling Nanomaterial Environmental Fate in Aquatic Systems”, Environmental Science & Technology, vol. 49, no. 5, pp. 2587 - 2593, 2015.

A functional assay-based strategy for nanomaterial risk forecasting

C. O. Hendren, Lowry, G. V. , Unrine, J. M. , and Wiesner, M. R. , “A functional assay-based strategy for nanomaterial risk forecasting”, Science of The Total Environment, 2015.

Getting from Data to Knowledge in the CEINT NanoInformatics Knowledge Commons (NIKC)

Research Topic: 
Core C: Modeling and Risk Forecasting

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2015

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