Evaluation of classification methods for identifying multiwalled carbon nanotubes collected on mixed cellulose ester filter media.

Enhanced darkfield microscopy (EDFM) and hyperspectral imaging (HSI) are being evaluated as a potential rapid screening modality to reduce the time-to-knowledge for direct visualisation and analysis of filter media used to sample nanoparticulate from work environments, as compared to the current analytical gold standard of transmission electron microscopy (TEM). Here, we compare accuracy, specificity, and sensitivity of several hyperspectral classification models and data preprocessing techniques to determine how to most effectively identify multiwalled carbon nanotubes (MWCNTs) in hyperspectral images. Several classification schemes were identified that are capable of classifying pixels as MWCNT(+) or MWCNT(-) in hyperspectral images with specificity and sensitivity over 99% on the test dataset. Functional principal component analysis (FPCA) was identified as an appropriate data preprocessing technique, testing optimally when coupled with a quadratic discriminant analysis (QDA) model with forward stepwise variable selection and with a support vector machines (SVM) model. The success of these methods suggests that EDFM-HSI may be reliably employed to assess filter media exposed to MWCNTs. Future work will evaluate the ability of EDFM-HSI to quantify MWCNTs collected on filter media using this classification algorithm framework using the best-performing model identified here - quadratic discriminant analysis with forward stepwise selection on functional principal component data - on an expanded sample set.

Occupational exposure to airborne nanomaterials: An assessment of worker exposure to aerosolized metal oxide nanoparticles in a semiconductor fab and subfab.

This occupational exposure assessment study characterized potential inhalation exposures of workers to engineered nanomaterials associated with chemical mechanical planarization wafer polishing processes in a semiconductor research and development facility. Air sampling methodology was designed to capture airborne metal oxide nanoparticles for characterization. The research team obtained air samples in the fab and subfab areas using a combination of filter-based capture methods to determine particle morphology and elemental composition and real-time direct-reading instruments to determine airborne particle counts. Filter-based samples were analyzed by electron microscopy and energy-dispersive x-ray spectroscopy while real-time particle counting data underwent statistical analysis. Sampling was conducted during worker tasks associated with preventive maintenance and quality control that were identified as having medium to high potential for inhalation exposure based on qualitative assessments. For each sampling event, data was collected for comparison between the background, task area, and personal breathing zone. Sampling conducted over nine months included five discrete sampling series events in coordination with on-site employees under real working conditions. The number of filter-based samples captured was: eight from worker personal breathing zones; seven from task areas; and five from backgrounds. A complementary suite of direct-reading instruments collected data for seven sample collection periods in the task area and six in the background. Engineered nanomaterials of interest (Si, Al, Ce) were identified in filter-based samples from all areas of collection, existing as agglomerates (>500 nm) and nanoparticles (100-500 nm). Particle counts showed an increase in number concentration above background during a subset of the job tasks, but particle counts in the task areas were otherwise not significantly higher than background. Additional data is needed to support further statistical analysis and determine trends; however, this initial investigation suggests that nanoparticles used or generated by the wafer polishing process become aerosolized and may be accessible for inhalation exposures by workers performing tasks in the subfab and fab. Additional research is needed to further quantify the degree of exposure and link these findings to related hazard research.

NIOSH field studies team assessment: Worker exposure to aerosolized metal oxide nanoparticles in a semiconductor fabrication facility.

The ubiquitous use of engineered nanomaterials-particulate materials measuring approximately 1-100 nanometers (nm) on their smallest axis, intentionally engineered to express novel properties-in semiconductor fabrication poses unique issues for protecting worker health and safety. Use of new substances or substances in a new form may present hazards that have yet to be characterized for their acute or chronic health effects. Uncharacterized or emerging occupational health hazards may exist when there is insufficient validated hazard data available to make a decision on potential hazard and risk to exposed workers under condition of use. To advance the knowledge of potential worker exposure to engineered nanomaterials, the National Institute for Occupational Safety and Health Nanotechnology Field Studies Team conducted an on-site field evaluation in collaboration with on-site researchers at a semiconductor research and development facility on April 18-21, 2011. The Nanomaterial Exposure Assessment Technique (2.0) was used to perform a complete exposure assessment. A combination of filter-based sampling and direct-reading instruments was used to identify, characterize, and quantify the potential for worker inhalation exposure to airborne alumina and amorphous silica nanoparticles associated with th e chemical mechanical planarization wafer polishing process. Engineering controls and work practices were evaluated to characterize tasks that might contribute to potential exposures and to assess existing engineering controls. Metal oxide structures were identified in all sampling areas, as individual nanoparticles and agglomerates ranging in size from 60 nm to >1,000 nm, with varying structure morphology, from long and narrow to compact. Filter-based samples indicated very little aerosolized material in task areas or worker breathing zone. Direct-reading instrument data indicated increased particle counts relative to background in the wastewater treatment area; however, particle counts were very low overall, indicating a well-controlled working environment. Recommendations for employees handling or potentially exposed to engineered nanomaterials include hazard communication, standard operating procedures, conservative ventilation systems, and prevention through design in locations where engineered nanomaterials are used or stored, and routine air sampling for occupational exposure assessment and analysis.

Occupational Exposure to Airborne Nanomaterials: An Assessment of Worker Exposure to Aerosolized Metal Oxide Nanoparticles in Semiconductor Wastewater Treatment.

This study characterized potential inhalation exposures of workers to nanometal oxides associated with industrial wastewater treatment processes in a semiconductor research and development facility. Exposure assessment methodology was designed to capture aerosolized engineered nanomaterials associated with the chemical mechanical planarization wafer polishing process that were accessible for worker contact via inhalation in the on-site wastewater treatment facility. The research team conducted air sampling using a combination of filter-based capture methods for particle identification and characterization and real-time direct-reading instruments for semi-quantitation of particle number concentration. Filter-based samples were analyzed using electron microscopy and energy-dispersive x-ray spectroscopy while real-time particle counting data underwent statistical analysis. Sampling conducted over 14 months included 5 discrete sampling series events for 7 job tasks in coordination with on-site employees. The number of filter-based samples captured for analysis by electron microscopy was: 5 from personal breathing zone, 4 from task areas, and 3 from the background. Direct-reading instruments collected data for 5 sample collection periods in the task area and the background, and 2 extended background collection periods. Engineered nanomaterials of interest (Si, Al, Ce) were identified by electron microscopy in filter-based samples from all areas of collection, existing as agglomerates (>500 nm) and nanoparticles (100 nm-500 nm). Particle counts showed an increase in number concentration during and after selected tasks above background. While additional data is needed to support further statistical analysis and determine trends, this initial investigation suggests that nanoparticles used or generated by chemical mechanical planarization become aerosolized and may be accessible for inhalation exposures by workers in wastewater treatment facilities. Additional research is needed to further quantify the level of exposure and determine the potential human health impacts.

Results of the 2019 Survey of Engineered Nanomaterial Occupational Health and Safety Practices.

In collaboration with RTI International, the U.S. National Institute for Occupational Safety and Health (NIOSH) administered a survey to North American companies working with nanomaterials to assess health and safety practices. The results would contribute to understanding the impact of the efforts made by the NIOSH Nanotechnology Research Center (NTRC) in communicating occupational health and safety (OHS) considerations for workers when handling these materials. The survey, developed by RAND Corporation, was conducted online from September 2019-December 2019. Forty-five companies or organizations in the U.S. and Canada that fabricate, manufacture, handle, dispose, or otherwise use nanomaterials completed the survey. The survey was designed to answer research questions regarding the nanomaterials in use, which resources the companies have consulted for OHS guidance, and the overall OHS culture at the companies. Other questions specifically addressed whether the companies interacted with NIOSH or NIOSH resources to inform OHS policies and practices. Among participating companies, 57.8% had a maximum of 50 employees. Gold nanoparticles and polymers were most common (n = 20; 45.5% each), followed by graphene (36.4%), carbon nanotubes and nanofibers (34.1%), and zinc oxide nanoparticles (31.8%). Environmental monitoring was performed by 31.8% of the companies. While 88.9% of the companies had laminar flow cabinets, only 67.5% required it to be used with ENMs. Information and training programs were indicated by 90% of the sample, and only 29.6% performed specific health surveillance for ENM workers. Personal protective equipment primarily included gloves (100%) and eye/face protection (97.7%). More than a third (37.8%) of the respondents reported using at least one NIOSH resource to acquire information about safe handling of ENMs. The small number of companies that responded to and completed the survey is a considerable limitation to this study. However, the survey data are valuable for gauging the reach and influence of the NIOSH NTRC on nano OHS and for informing future outreach, particularly to small businesses.

Evaluation of enhanced darkfield microscopy and hyperspectral imaging for rapid screening of TiO2 and SiO2 nanoscale particles captured on filter media.

Here we report on initial efforts to evaluate enhanced darkfield microscopy (EDFM) and light scattering Vis-NIR hyperspectral imaging (HSI) as a rapid screening tool for the offline analysis of mixed cellulose ester (MCE) filter media used to collect airborne nanoparticulate from work environments. For this study, the materials of interest were nanoscale titanium dioxide (TiO2 ) and silicon dioxide (SiO2 ; silica), chosen for their frequent use in consumer products. TiO2 and SiO2 nanoscale particles (NPs) were collected on MCE filter media and were imaged and analyzed via EDFM-HSI. When visualized by EDFM, TiO2 and SiO2 NPs were readily apparent as bright spherical structures against a dark background. Moreover, TiO2 and SiO2 NPs were identified in hyperspectral images. EDFM-HSI images and data were compared to scanning transmission electron microscopy (STEM), a NIST-traceable technique for particle size analysis, and the current gold standard for offline analysis of filter media. As expected, STEM provided more accurate sizing and morphology data when compared to EDFM-HSI, but is not ideal for rapid screening of the presence of NPs of interest since it is a costly, low-throughput technique. In this study, we demonstrate the utility of EDFM-HSI in rapidly visualizing and identifying TiO2 and SiO2 NPs on MCE filters. This screening method may prove useful in expediting time-to-knowledge compared to electron microscopy. Future work will expand this evaluation to other industrially relevant NPs, other filter media types, and real-world filter samples from occupational exposure assessments.

Exposures during wet production and use processes of nanomaterials: a summary of 11 worksite evaluations.

From 2011-2015, the National Institute for Occupational Safety and Health Nanotechnology Field Studies Team conducted 11 evaluations at worksites that either produced engineered nanomaterials (ENMs) via a wet process or used ENMs in a wetted, suspended, or slurry form. Wet handling or processing of ENMs reduces potential exposure compared to dry handling or processing; however, air sampling data indicated exposures may still occur. Information was gathered about each company, production processes, ENMs of interest, and control measures. Exposure assessments included air sampling using filter media, surface wipe sampling, and real-time particle counting by direct-reading instruments. Electron microscopy analysis of air filters confirmed the presence of ENMs of interest (10 of 11 sites). When a method was available, chemical analysis of filters was also used to detect the presence of ENMs (nine of 11 sites). Wipe samples were collected at four of the 11 sites, and, in each case, confirmed the presence of ENMs on surfaces. Direct-reading data showed potential nanomaterial emissions (nine of 11 sites). Engineering controls included fume hoods, cleanrooms, and enclosed processes. Personal protective equipment was required during all 11 evaluations. Recommendations to address potential exposures were provided to each company following the hierarchy of controls.

Sample preparation method for visualization of nanoparticulate captured on mixed cellulose ester filter media by enhanced darkfield microscopy and hyperspectral imaging.

A significant hurdle in conducting effective health and safety hazard analysis and risk assessment for the nanotechnology workforce is the lack of a rapid method for the direct visualization and analysis of filter media used to sample nanomaterials from work environments that represent potential worker exposure. Current best-known methods include transmission electron microscopy (TEM) coupled with energy dispersive x-ray spectroscopy (EDS) for elemental identification. TEM-EDS is considerably time-, cost-, and resource-intensive, which may prevent timely health and safety recommendations and corrective actions. A rapid screening method is currently being explored using enhanced darkfield microscopy with hyperspectral imaging (EDFM-HSI). For this approach to be effective, rapid, and easy, sample preparation that is amenable to the analytical technique is needed. Here, we compare the sample preparation steps for mixed cellulose ester (MCE) filter media specified in NIOSH Method 7400-Asbestos and Other Fibers by Phase Contrast Microscopy (PCM)-against a new method, which involves saturation of the filter media with acetone. NIOSH Method 7400 was chosen as a starting point since it is an established technique for preparing transparent MCE filters for optical microscopy. Limitations in this method led to the development and comparison of a new method. The new method was faster, easier, and rendered filters more transparent, resulting in improved visualization and analysis of nanomaterials via EDFM-HSI. This new method is suitable for a rapid screening protocol due to its speed, ease of use, and the improvement in image acquisition and analysis.

Hyperspectral data influenced by sample matrix: the importance of building relevant reference spectral libraries to map materials of interest.

Hyperspectral imaging (HSI) and mapping are increasingly used for visualization and identification of nanoparticles (NPs) in a variety of matrices, including aqueous suspensions and biological samples. Reference spectral libraries (RSLs) contain hyperspectral data collected from materials of known composition and are used to detect the known materials in experimental samples through a one-to-one pixel "mapping" process. In some HSI studies, RSLs created from raw NPs were used to map NPs in experimental samples in a different matrix; for example, RSLs created from NPs in suspension to map NPs in biological tissue. Others have utilized RSLs created from NPs in the same matrix. However, few studies have systematically compared hyperspectral data as a function of the matrix in which the NPs are found and its impact on mapping results. The objective of this study is to compare RSLs created from metal oxide NPs in aqueous suspensions to RSLs created from the same NPs in rat tissues following in vivo inhalation exposure, and to investigate the differences in mapping that result from the use of each RSL. Results demonstrate that the spectral profiles of these NPs are matrix dependent: RSLs created from NPs in positive control tissues mapped to experimental tissues more appropriately than RSLs created from NPs in suspension. Aqueous suspension RSLs mapped 0-602 out of 500,424 pixels per tissue image while tissue RSLs mapped 689-18,435 pixels for the same images. This study underscores the need for appropriate positive controls for the creation of RSLs for mapping NPs in experimental samples.

Hyperspectral imaging of nanoparticles in biological samples: Simultaneous visualization and elemental identification.

While engineered nanomaterials (ENMs) are increasingly incorporated into industrial processes and consumer products, the potential biological effects and health outcomes of exposure remain unknown. Novel advanced direct visualization techniques that require less time, cost, and resource investment than electron microscopy (EM) are needed for identifying and locating ENMs in biological samples. Hyperspectral imaging (HSI) combines spectrophotometry and imaging, using advanced optics and algorithms to capture a spectrum from 400 to 1000 nm at each pixel in an enhanced dark-field microscopic (EDFM) image. HSI-EDFM can be used to confirm the identity of the materials of interest in a sample and generate an image "mapping" their presence and location in a sample. Hyperspectral mapping is particularly important for biological samples, where ENM morphology is visually indistinct from surrounding tissue structures. While use of HSI (without mapping) is increasing, no studies to date have compared results from hyperspectral mapping with conventional methods. Thus, the objective of this study was to utilize EDFM-HSI to locate, identify, and map metal oxide ENMs in ex vivo histological porcine skin tissues, a toxicological model of cutaneous exposure, and compare findings with those of Raman spectroscopy (RS), energy-dispersive X-ray spectroscopy (EDS), and scanning electron microscopy (SEM). Results demonstrate that EDFM-HSI mapping is capable of locating and identifying ENMs in tissue, as confirmed by conventional methods. This study serves as initial confirmation of EDFM-HSI mapping as a novel and higher throughput technique for ENM identification in biological samples, and serves as the basis for further protocol development utilizing EDFM-HSI for semiquantitation of ENMs.

Biodistribution of inhaled metal oxide nanoparticles mimicking occupational exposure: a preliminary investigation using enhanced darkfield microscopy.

Inhalation exposure to engineered nanomaterials (ENMs) may result in adverse pulmonary and/or systemic health effects. In this study, enhanced darkfield microscopy (EDFM) was used as a novel approach to visualizing industrial metal oxide nanoparticles (NPs) (silica, ceria, or alumina) in multiple tissue types following inhalation in rats mimicking occupational exposures. Advantages of EDFM over electron microscopy (EM) include reduced cost, time, and ease of sample preparation and operation. Following 4-6 hour inhalation exposures at three concentrations (3.5-34.0 mg/m3 ), lungs and secondary organs were harvested at 24 hours or 7 days post-exposure and prepared for brightfield (BF) microscopy and EDFM. NPs were visualized within the lung and associated lymphatic tissues and in major organs of excretion (liver, spleen, kidney). EDFM also revealed NPs within pulmonary blood vessels and localization within specific regions of toxicological relevance in liver and kidney, indicating pathways of excretion. Results demonstrate the utility of EDFM for rapid direct visualization of NPs in various tissue types and suggest the potential for metal oxide NPs to distribute to secondary tissues following inhalation exposure. Confirmation of the composition, distribution, and relative abundance of inhaled NPs will be pursued by combining EDFM with hyperspectral imaging (HSI) and mapping.

SEM analysis of particle size during conventional treatment of CMP process wastewater.

Engineered nanomaterials (ENMs) are currently employed by many industries and have different physical and chemical properties from their bulk counterparts that may confer different toxicity. Nanoparticles used or generated in semiconductor manufacturing have the potential to enter the municipal waste stream via wastewater and their ultimate fate in the ecosystem is currently unknown. This study investigates the fate of ENMs used in chemical mechanical planarization (CMP), a polishing process repeatedly utilized in semiconductor manufacturing. Wastewater sampling was conducted throughout the wastewater treatment (WWT) process at the fabrication plant's on-site wastewater treatment facility. The goal of this study was to assess whether the WWT processes resulted in size-dependent filtration of particles in the nanoscale regime by analyzing samples using scanning electron microscopy (SEM). Statistical analysis demonstrated no significant differences in particle size between sampling points, indicating low or no selectivity of WWT methods for nanoparticles based on size. All nanoparticles appeared to be of similar morphology (near-spherical), with a high variability in particle size. EDX verified nanoparticles composition of silicon- and/or aluminum-oxide. Nanoparticle sizing data compared between sampling points, including the final sampling point before discharge from the facility, suggested that nanoparticles could be released to the municipal waste stream from industrial sources.

Hyperspectral microscopy as an analytical tool for nanomaterials.

Hyperspectral microscopy is an advanced visualization technique that combines hyperspectral imaging with state-of-the-art optics and computer software to enable the rapid identification of materials at the micro- and nanoscales. Achieving this level of resolution has traditionally required time-consuming and costly electron microscopy techniques. While hyperspectral microscopy has already been applied to the analysis of bulk materials and biologicals, it shows extraordinary promise as an analytical tool to locate individual nanoparticles and aggregates in complex samples through rapid optical and spectroscopic identification. This technique can be used to not only screen for the presence of nanomaterials, but also to locate, identify, and characterize them. It could also be used to identify a subset of samples that would then move on for further analysis via other advanced metrology. This review will describe the science and origins of hyperspectral microscopy, examine current and emerging applications in life science, and examine potential applications of this technology that could improve research efficiency or lead to novel discoveries.

Identification of Metal Oxide Nanoparticles in Histological Samples by Enhanced Darkfield Microscopy and Hyperspectral Mapping.

Nanomaterials are increasingly prevalent throughout industry, manufacturing, and biomedical research. The need for tools and techniques that aid in the identification, localization, and characterization of nanoscale materials in biological samples is on the rise. Currently available methods, such as electron microscopy, tend to be resource-intensive, making their use prohibitive for much of the research community. Enhanced darkfield microscopy complemented with a hyperspectral imaging system may provide a solution to this bottleneck by enabling rapid and less expensive characterization of nanoparticles in histological samples. This method allows for high-contrast nanoscale imaging as well as nanomaterial identification. For this technique, histological tissue samples are prepared as they would be for light-based microscopy. First, positive control samples are analyzed to generate the reference spectra that will enable the detection of a material of interest in the sample. Negative controls without the material of interest are also analyzed in order to improve specificity (reduce false positives). Samples can then be imaged and analyzed using methods and software for hyperspectral microscopy or matched against these reference spectra in order to provide maps of the location of materials of interest in a sample. The technique is particularly well-suited for materials with highly unique reflectance spectra, such as noble metals, but is also applicable to other materials, such as semi-metallic oxides. This technique provides information that is difficult to acquire from histological samples without the use of electron microscopy techniques, which may provide higher sensitivity and resolution, but are vastly more resource-intensive and time-consuming than light microscopy.