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The data presented are supplementary to an article [Kim et al., 2019] on synthesis and surface characterization of tethered polyacrylic acid (PAA) layers on polysulfone (PSf) film/membrane surfaces via atmospheric pressure plasma-induced graft polymerization (APPIGP). Data on surface characterization of the synthesized tethered PAA layers includes: AFM topographic surface images and height distributions of surface features, dry layer thickness, chain rupture length distributions determined via AFM based force spectroscopy (AFM-FS), in addition to measurements of water contact angles. Fouling propensity data for ultrafiltration of alginic acid as a model foulant are also provided for native and PAA grafted PSf ultrafiltration (UF) membranes.

The potential environmental impact of nanomaterials is a critical concern and the ability to assess these potential impacts is top priority for the progress of sustainable nanotechnology. Risk assessment tools are needed to enable decision makers to rapidly assess the potential risks that may be imposed by engineered nanomaterials (ENMs), particularly when confronted by the reality of limited hazard or exposure data. In this review, we examine a range of available risk assessment frameworks considering the contexts in which different stakeholders may need to assess the potential environmental impacts of ENMs. Assessment frameworks and tools that are suitable for the different decision analysis scenarios are then identified. In addition, we identify the gaps that currently exist between the needs of decision makers, for a range of decision scenarios, and the abilities of present frameworks and tools to meet those needs.

Engineered nanomaterials (ENMs) are increasingly entering the environment with uncertain consequences including potential ecological effects. Various research communities view differently whether ecotoxicological testing of ENMs should be conducted using environmentally relevant concentrations-where observing outcomes is difficult-versus higher ENM doses, where responses are observable. What exposure conditions are typically used in assessing ENM hazards to populations? What conditions are used to test ecosystem-scale hazards? What is known regarding actual ENMs in the environment, via measurements or modeling simulations? How should exposure conditions, ENM transformation, dose, and body burden be used in interpreting biological and computational findings for assessing risks? These questions were addressed in the context of this critical review. As a result, three main recommendations emerged. First, researchers should improve ecotoxicology of ENMs by choosing test end points, duration, and study conditions-including ENM test concentrations-that align with realistic exposure scenarios. Second, testing should proceed via tiers with iterative feedback that informs experiments at other levels of biological organization. Finally, environmental realism in ENM hazard assessments should involve greater coordination among ENM quantitative analysts, exposure modelers, and ecotoxicologists, across government, industry, and academia.

Understanding the relationships between the physicochemical properties of engineered nanomaterials and their toxicity is critical for environmental and health risk analysis. However, this task is confounded by material diversity, heterogeneity of published data and limited sampling within individual studies. Here, we present an approach for analysing and extracting pertinent knowledge from published studies focusing on the cellular toxicity of cadmium-containing semiconductor quantum dots. From 307 publications, we obtain 1,741 cell viability-related data samples, each with 24 qualitative and quantitative attributes describing the material properties and experimental conditions. Using random forest regression models to analyse the data, we show that toxicity is closely correlated with quantum dot surface properties (including shell, ligand and surface modifications), diameter, assay type and exposure time. Our approach of integrating quantitative and categorical data provides a roadmap for interrogating the wide-ranging toxicity data in the literature and suggests that meta-analysis can help develop methods for predicting the toxicity of engineered nanomaterials.

It has been argued that in vitro toxicity testing of engineered nanoparticles (NPs) should consider delivered dose (i.e., NP mass settled per suspension volume) rather than relying exclusively on administered dose (initial NP mass concentration). Delivered dose calculations require quantification of NP sedimentation in tissue cell culture media, taking into consideration fundamental suspension properties. In this article, we calculate delivered dose using a first-principles "particles in a box" sedimentation model, which accounts for the particle size distribution, fractal dimension, and permeability of agglomerated NPs. The sedimentation model was evaluated against external and our own experimental sedimentation data for metal oxide NPs. We then utilized the model to construct delivered dose-response analysis for a library of metal oxide NPs (previously used for hazard ranking and prediction making) in different cell culture media. Hierarchical hazard ranking of the seven (out of 24) toxic metal oxide NPs in our library, using EC50 calculated on the basis of delivered dose, did not measurably differ from our ranking based on administered dose. In contrast, simplified sedimentation calculations based on the assumption of impermeable NP agglomerates of a single average size significantly underestimated the settled NPs' mass, resulting in misinterpretation of toxicity ranking. It is acknowledged that in vitro dose-response outcomes are likely to be shaped by complex toxicodynamics, which include NP/cellular association, triggering of dynamic cell response pathways involved in NP uptake, and multiple physicochemical parameters that influence NP sedimentation and internalization.

Copper formulations have been used for decades for antimicrobial and antifouling applications. With the development of nanoformulations of copper that are more effective than their ionic and microsized analogues, a key regulatory question is whether these materials should be treated as new or existing materials. To address this issue, here we compare the magnitude and mechanisms of toxicity of a series of Cu species (at concentration ranging from 2 to 250 μg/mL), including nano Cu, nano CuO, nano Cu(OH)2 (CuPro and Kocide), micro Cu, micro CuO, ionic Cu(2+) (CuCl2 and CuSO4) in two species of bacteria (Escherichia coli and Lactobacillus brevis). The primary size of the particles studied ranged from 10 nm to 10 μm. Our results reveal that Cu and CuO nanoparticles (NPs) are more toxic than their microsized counterparts at the same Cu concentration, with toxicities approaching those of the ionic Cu species. Strikingly, these NPs showed distinct differences in their mode of toxicity when compared to the ionic and microsized Cu, highlighting the unique toxicity properties of materials at the nanoscale. In vitro DNA damage assays reveal that both nano Cu and microsized Cu are capable of causing complete degradation of plasmid DNA, but electron tomography results show that only nanoformulations of Cu are internalized as intact intracellular particles. These studies suggest that nano Cu at the concentration of 50 μg/mL may have unique genotoxicity in bacteria compared to ionic and microsized Cu.

For nanotechnology to meet its potential as a game-changing and sustainable technology, it is important to ensure that the engineered nanomaterials and nanoenabled products that gain entry to the marketplace are safe and effective. Tools and methods are needed for regulatory purposes to allow rapid material categorization according to human health and environmental risk potential, so that materials of high concern can be targeted for additional scrutiny, while material categories that pose the least risk can receive expedited review. Using carbon nanotubes as an example, we discuss how data from alternative testing strategies can be used to facilitate engineered nanomaterial categorization according to risk potential and how such an approach could facilitate regulatory decision-making in the future.

An integrated simulation tool was developed for assessing the potential release and environmental distribution of nanomaterials (RedNano) based on a life cycle assessment approach and multimedia compartmental modeling coupled with mechanistic intermedia transport processes. The RedNano simulation tool and its web-based software implementation enables rapid "what-if?" scenario analysis, in order to assess the response of an environmental system to various release scenarios of engineered nanomaterials (ENMs). It also allows for the investigation of the impact of geographical and meteorological parameters on ENM distribution in the environment, comparison of the impact of ENM production and potential releases on different regions, and estimation of source release rates based on monitored ENM concentrations. Moreover, the RedNano simulation tool is suitable for research, academic, and regulatory purposes. Specifically, it has been used in environmental multimedia impact assessment courses at both the undergraduate and graduate levels. The RedNano simulation tool can also serve as a decision support tool to rapidly and critically assess the potential environmental implications of ENMs and thus ensure that nanotechnology is developed in a productive and environmentally responsible manner.

The impact of ZnO and TiO2 manufactured nanoparticles (MNPs) on soil bacterial communities for different exposure periods and MNP doses was explored via data visualization techniques. Interrelationships between MNP treatments and responses of bacterial taxa were illustrated by bipartite graphs, allowing fast identification of important soil bacterial taxa that are susceptible to MNPs. Contribution biplots with subcompositional coherence property were generated via log-ratio analysis (LRA), which jointly display the treatment distribution and the variance (contribution) of bacterial taxa. The LRA contribution biplots and nonmetric multi-dimensional scaling (NMDS) of the dataset, along with hierarchical clustering, demonstrated that high doses of ZnO and TiO2 MNPs caused significant compositional changes in soil bacterial communities. The suitability of family level for MNP taxonomic impact assessment was demonstrated by both the LRA biplots and simplified NMDSs with quantification provided by the distance correlation between MNP impacts summarized at different taxonomic levels. The present study demonstrates that visual exploration could potentially assist in knowledge discovery and interpretation of data on soil bacterial communities exposed to MNPs and thus evaluate the potential for environmental impacts.

The quantity of information on nanomaterial properties and behavior continues to grow rapidly. Without a concerted effort to collect, organize and mine disparate information coming out of current research efforts, the value and effective use of this information will be limited at best. Data will not be translated to knowledge. At worst, erroneous conclusions will be drawn and future research may be misdirected. Nanoinformatics can be a powerful approach to enhance the value of global information in nanoscience and nanotechnology. Much progress has been made through grassroots efforts in nanoinformatics resulting in a multitude of resources and tools for nanoscience researchers. In 2012, the nanoinformatics community believed it was important to critically evaluate and refine currently available nanoinformatics approaches in order to best inform the science and support the future of predictive nanotechnology. The Greener Nano 2012: Nanoinformatics Tools and Resources Workshop brought together informatics groups with materials scientists active in nanoscience research to evaluate and reflect on the tools and resources that have recently emerged in support of predictive nanotechnology. The workshop goals were to establish a better understanding of current nanoinformatics approaches and to clearly define immediate and projected informatics infrastructure needs of the nanotechnology community. The theme of nanotechnology environmental health and safety (nanoEHS) was used to provide real-world, concrete examples on how informatics can be utilized to advance our knowledge and guide nanoscience. The benefit here is that the same properties that impact the performance of products could also be the properties that inform EHS. From a decision management standpoint, the dual use of such data should be considered a priority. Key outcomes include a proposed collaborative framework for data collection, data sharing and information integration.

A phenotype recognition model was developed for high throughput screening (HTS) of engineered Nano-Materials (eNMs) toxicity using zebrafish embryo developmental response classified, from automatically captured images and without manual manipulation of zebrafish positioning, by three basic phenotypes (i.e., hatched, unhatched, and dead). The recognition model was built with a set of vectorial descriptors providing image color and texture information. The best performing model was attained with three image descriptors (color histogram, representative color, and color layout) identified as most suitable from an initial pool of six descriptors. This model had an average recognition accuracy of 97.40±0.95% in a 10-fold cross-validation and 93.75% in a stress test of low quality zebrafish images. The present work has shown that a phenotyping model can be developed with accurate recognition ability suitable for zebrafish-based HTS assays. Although the present methodology was successfully demonstrated for only three basic zebrafish embryonic phenotypes, it can be readily adapted to incorporate more subtle phenotypes.