Automated determination of size and morphology information from soot transmission electron microscope (TEM)-generated images

The thermophoretic sampling of particulates from hot media, coupled with transmission electron microscope (TEM) imaging, is a combined approach that is widely used to derive morphological information. The identification and the measurement of the particulates, however, can be complex when the TEM images are of low contrast, noisy, and have non-uniform background signal level. The image processing method can also be challenging and time consuming, when the samples collected have large variability in shape and size, or have some degree of overlapping. In this work, a three-stage image processing sequence is presented to facilitate time-efficient automated identification and measurement of particulates from the TEM grids. The proposed processing sequence is first applied to soot samples that were thermophoretically sampled from a laminar non-premixed ethylene-air flame. The parameter values that are required to be set to facilitate the automated process are identified, and sensitivity of the results to these parameters is assessed. The same analysis process is also applied to soot samples that were acquired from an externally irradiated laminar non-premixed ethylene-air flame, which have different geometrical characteristics, to assess the morphological dependence of the proposed image processing sequence. Using the optimized parameter values, statistical assessments of the automated results reveal that the largest discrepancies that are associated with the estimated values of primary particle diameter, fractal dimension, and prefactor values of the aggregates for the tested cases, are approximately 3, 1, and 10 %, respectively, when compared with the manual measurements.     

‘You caught me off guard’: Probing the futures of complex engineered nanomaterials

This paper applies principles and methods from the framework of anticipatory governance to the case of what the National Research Council calls “complex engineered nanomaterials” (CENM). This framework does not aim to generate crystal ball visions or definitive answers, but rather provides guidance for uncovering, understanding, and addressing social, ethical, environmental, and policy issues that stem from emerging technologies. Thus, in anticipation of increased CENM research, CENM products, and their different governance challenges, we aim to lay the groundwork for the anticipatory governance of CENMs by mapping out what—according to the engineers and scientists, we interviewed who are working at the research level of these CENMs—will be the main issues and themes that we need to pay attention to in the near future. The structured interviews focused on three groups of questions: (1) potential and/or actual applications and/or products from the participant’s research; (2) environmental health and safety issues pertaining to both the participant’s research and CENMs generally; and (3) the future of CENMs. Without a foundational understanding to build on, social scientists, policymakers, and regulatory agencies will be at a loss about how to govern CENMs before they are widely implemented in society.