The data set contains the details on the microwave calibrations for carbon nanotubes, the variance predictors and responses by the components applying partial least square regression. Also contains a summary of the model fitness for carbon nanotubes quantification and its corresponding statistics. The data set includes the quantification of CNTs in different matrices: soil and sludge. This dataset is associated with the following publication: He, Y., S. Al-Abed, and D. Dionysios. Multivariate calibration for carbon nanotubes in the environment using the microwave induced heating method. Environmental Nanotechnology, Monitoring and Management. Elsevier B.V., Amsterdam, NETHERLANDS, 11: 100204, (2019).

Our data can be used by modeler to develop mathematical models to simulate and predict the fate and transport of the next-generation multifunctional carbon-based metal oxide nanohybrids in the subsurface environments. Furthermore, the data can also be employed to assess the potential environmental impacts and risks associated with the release and transport of carbon-based metal oxide nanohybrids in the subsurface under environmentally relevant physicochemical conditions. This dataset is associated with the following publication: Wang, D., C. Park, A. Masud, N. Aich, and C. Su. Carboxymethylcellulose Mediates the Transport of Carbon Nanotube-Magnetite Nanohybrid Aggregates in Water-Saturated Porous Media. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51: 12405-12415, (2017).

Additional information about the carboxylated SWCNT calibration curve, AFM images, EDS results, solar simulator light and UVB lamp spectra, TEM image of parent carboxylated SWCNTs, XPS spectra of the dark control P3 sample and the irradiated P3 sample, and a table summarizing the kinetic parameters (PDF). This dataset is associated with the following publication: Hou, W., C. He, Y. Wang, D. Wang, and R. Zepp. Phototransformation-Induced Aggregation of Functionalized Single-Walled Carbon Nanotubes: The Importance of Amorphous Carbon. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(7): 3494–3502, (2016).

This dataset is generated to both qualitatively and quantitatively examine the interactions between nano-TiO2 and natural organic matter (NOM). This integrated dataset assemble all data generated in this project through a series of experiments. This dataset is associated with the following publication: Li , S., H. Ma, L. Wallis, M. Etterson , B. Riley , D. Hoff , and S. Diamond. Impact of natural organic matter on particle behavior and phototoxicity of titanium dioxide nanoparticles. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 542: 324-333, (2016).

Transmission electron microscope tomographic data of aligned carbon nanotubes in epoxy at volume fractions of 0.44%, 2.6%, 4%, and 6.9%. Reduced data and analysis are available at https://doi.org/10.1021/acsnano.5b01044 . This is the raw data used to generate the figures in "The evolution of carbon nanotube network structure in unidirectional nanocomposites resolved by quantitative electron tomography", Bharath Natarajan, Noa Lachman, Thomas Lam, Douglas Jacobs, Christian Long, Minhua Zhao, Brian L Wardle, Renu Sharma, J Alexander Liddle, ACS Nano, vol. 9, pp 6050-6058 (2015), and is further analyzed in "Aligned carbon nanotube morphogenesis predicts physical properties of their polymer nanocomposites", Bharath Natarajan, Itai Y. Stein, Noa Lachman, Namiko Yamamoto, Douglas S. Jacobs, Renu Sharma, J. Alexander Liddle and Brian L. Wardle, Nanoscale, vol. 11, pp16327-16335 (2019), and "Modeliing the Electromagnetic Scattering Characteristics of Carbon Nanotube Composites Characterized by 3-D Tomographic Transmission Electron Microscopy", Ahmed M. Hassan, MD Khadimul Islam, Spencer On, Bharath Natarajan, Itai Y. Stein, Noa Lachman, Estelle Cohen, Brian L. Wardle, Renu Sharma, J. Alexander Liddle, and Edward J. Garboczi, IEEE Open Journal of Antennas and Propagation, vol. 1, pp 142-158 (2020). Carbon nanotube (CNT) reinforced polymers are next-generation, high-performance, multifunctional materials with a wide array of promising applications. Successful introduction of such materials is hampered by the lack of a quantitative understanding of process-structure-property relationships. These relationships are developed through the detailed characterization of nanoscale reinforcement morphology within the embedding medium. We reveal the three-dimensional (3D) nanoscale morphology of high volume fraction (Vf) aligned CNT/epoxy-matrix nanocomposites using energy-filtered electron tomography. We present an automated phase-identification method for fast, accurate, representative rendering of the CNT spatial arrangement in these low-contrast bimaterial systems. The resulting nanometer-scale visualizations provide quantitative information on the evolution of CNT morphology and dispersion state with increasing Vf, including network structure, CNT alignment, bundling and waviness. The CNTs exhibit a nonlinear increase in bundling and alignment and a decrease in waviness as a function of increasing Vf. Our findings explain previously observed discrepancies between the modeled and measured trends in bulk mechanical, electrical and thermal properties. The techniques we have developed for morphological quantitation are applicable to many low-contrast material systems. We use new, nanoscale quantitative 3D morphological information and stochastic modeling to re-interpret experimental measurements of continuous aligned carbon nanotube (A-CNT) PNC properties as a function of A-CNT packing/volume fraction. The 3D tortuosity calculated from tomographic reconstructions and its evolution with Vf is used to develop a novel definition of waviness that incorporates the stochastic nature of CNT growth. The importance of using randomly wavy CNTs to model these materials is validated by agreement between simulated and previously-measured PNC elastic moduli. Secondary morphological descriptors such as CNT-CNT junction density and inter-junction distances are measured for transport property predictions. The scaling of the junction density with CNT volume fraction is observed to be non-linear, and this non-linearity is identified as the reason behind the previously unexplained scaling of aligned-CNT PNC longitudinal thermal conductivity. The measured electrical conductivity scales linearly with Vf as it is relatively insensitive to junction density beyond percolation.

There has been growing interest in simulating the fate and transport of engineered nanomaterials in the environment. The Water Quality Analysis Simulation Program (WASP) is one of the most widely used water quality models and has recently been upgraded to WASP8. WASP8 incorporates the algorithms to simulate the fate and transport of nanoparticles in surface waters. This study simulates the fate and transport of graphene oxide (GO) nanomaterials and their major phototransformation product, photoreduced graphene oxide (rGO), for Brier Creek, GA, USA. We specifically explored the influences of three important processes on the fate and transport of GO: (1) light attenuation, (2) phototransformation, and (3) heteroaggregation, and simulated their distributions in the river, including the water column and sediment. This dataset is associated with the following publication: Han, Y., C. Knightes, D. Bouchard, R. Zepp, B. Avant, H. Hsieh, X. Chang, B. Acrey, M. Henderson, and J. Spear. Simulating graphene oxide nanomaterial phototransformation and transport in surface water. Environmental Science: Nano. RSC Publishing, Cambridge, UK, 6: 180, (2019).

Dataset for Nyffeler et al., 'Application of Cell Painting for chemical hazard evaluation in support of screening-level chemical assessments', Toxicology & Applied Pharmacology, Vol 468, 116513, June 1, 2023, DOI https://doi.org/10.1016/j.taap.2023.116513. This dataset is associated with the following publication: Nyffeler, J., C. Willis, F. Harris, M. Foster, B. Chambers, M. Culbreth, R. Brockway, S. Davidson-Fritz, D. Dawson, I. Shah, K. Paul-Friedman, D. Chang, L. Everett, J. Wambaugh, G. Patlewicz, and J. Harrill. Application of Cell Painting for chemical hazard evaluation in support of screening-level chemical assessments. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 468: 116513, (2023).

The dataset describes physical and chemical characterization of four nanohybrids and their growth inhibition effect on alga Thalassiosira pseudonana. This dataset is associated with the following publication: Baek, S., S.H. Joo, C. Su, and M. Toborek. Toxicity of ZnO/TiO2-conjugated carbon-based nanohybrids on the coastal marine alga Thalassiosira pseudonana. ENVIRONMENTAL TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 35(1): 87-96, (2019).

Degradation kinetics of nanocomposite in the environment. Nano-polymer composites are exposed to sunlight and oxidizing conditions that cause weathering of the polymers, leading to degradation and the release of nanoparticles. This dataset is associated with the following publication: Han, C., E. Sahle-Demessie, A. Zhao, T. Richardson, and J. Wang. Environmental aging and degradation of multiwalled carbon nanotube reinforced polypropylene. CARBON. Pergamon Press Ltd., New York, NY, USA, 129: 137-151, (2018).