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Understanding and controlling chirality in inorganic crystalline materials at the nanoscale is crucial in elucidating fundamental chirality-dependent physical and chemical processes as well as advancing new technological prospects, but significant challenges remain due to the lack of material control. Here, we have developed a facile and general bottom-up synthetic strategy for achieving chiral plasmonic Au nanostructures, including nanocubes and nanorods with fine chirality control. The underlying chiral mechanism enabled by the chiral boundary morphology is substantiated by theoretical modeling and finite element method (FEM) simulation. Because of the robustness of induced handedness and their small size, these as-synthesized chiral nanostructures can be further employed as building blocks toward the formation of complex chiral nanostructures. We have demonstrated a new class of chiral hybrid metal-semiconductor nanostructures that can allow integration of chirality with other properties and functionalities. All of these together have paved the way to engineer nanoscale inorganic chirality and thus study various emerging chirality-entangled effects with practical technological applications.
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Electrical double layers play a key role in a variety of electrochemical systems. The mean free path of secondary electrons in aqueous solutions is on the order of a nanometer, making them suitable for probing ultrathin electrical double layers at solid-liquid electrolyte interfaces. Employing graphene as an electron-transparent electrode in a two-electrode electrochemical system, we show that the secondary electron yield of the graphene-liquid interface depends on the ionic strength and concentration of the electrolyte and the applied bias at the remote counter electrode. These observations have been related to polarization-induced changes in the potential distribution within the electrical double layer and demonstrate the feasibility of using scanning electron microscopy to examine and map electrified liquid-solid interfaces.
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This paper reports high-throughput, light-based, through-focus scanning optical microscopy (TSOM) for detecting industrially relevant sub-50 nm tall nanoscale contaminants. Measurement parameter optimization to maximize the TSOM signal using optical simulations made it possible to detect the nanoscale contaminants. Atomic force and scanning electron microscopies were used as reference methods for comparison.
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Single particle inductively coupled plasma-mass spectrometry (spICP-MS) is an emerging technique capable of simultaneously measuring nanoparticle size and number concentration of metal-containing nanoparticles (NPs) at environmental levels. single particle ICP-MS will become an established measurement method once the metrological quality of the measurement results it produces have been proven incontrovertibly. This Article presents the first validation of spICP-MS capabilities for measuring mean NP size and number size distribution of gold nanoparticles (AuNPs). The validation is achieved by (i) calibration based on the consensus value for particle size derived from six different sizing techniques applied to National Institute of Standards and Technology (NIST) Reference Material (RM) 8013; (ii) comparison with high-resolution scanning electron microscopy (HR-SEM) used as a reference method, which is linked to the International System of Units (SI) through a calibration standard characterized by the NIST metrological atomic force microscope; and (iii) evaluation of the uncertainty associated with the measurement of the mean particle size to enable comparison of the spICP-MS and HR-SEM methods. After establishing HR-SEM and spICP-MS measurement protocols, both methods were used to characterize commercial AuNP suspensions of three different sizes (30, 60, and 100 nm) with four different coatings and surface charge at pH 7. Single particle ICP-MS measurements (corroborated by HR-SEM) revealed the existence of two distinct subpopulations of particles in the number size distributions for four of the 60 nm commercial suspensions, a fact that was not apparent in the measurement results supplied by the vendor using transmission electron microscopy. This finding illustrates the utility of spICP-MS for routine characterization of commercial AuNP suspensions regardless of size or coating.
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Low-cost, high-throughput and nondestructive metrology of truly three-dimensional (3-D) targets for process control/monitoring is a critically needed enabling technology for high-volume manufacturing (HVM) of nano/micro technologies in multi-disciplinary areas. In particular, a survey of the typically used metrology tools indicates the lack of a tool that truly satisfies the HVM metrology needs of 3-D targets, such as high aspect ratio (HAR) targets. Using HAR targets here we demonstrate that through-focus scanning optical microscopy (TSOM) is a strong contender to fill the gap for 3-D shape metrology. Differential TSOM (D-TSOM) images are extremely sensitive to small and/or dissimilar types of 3-D shape variations. Based on this here we propose a TSOM method that involves creating a database of cross-sectional profiles of the HAR targets along with their respective D-TSOM signals. Using the database, we present a simple-to-use, low-cost, high-throughput and nondestructive process-monitoring method suitable for HVM of truly 3-D targets, which also does not require optical simulations, making its use straightforward and automatable. Even though HAR targets are used for this demonstration, the similar process can be applied to any truly 3-D targets with dimensions ranging from micro-scale to nano-scale. The TSOM method couples the advantage of analyzing truly isolated targets with the ability to simultaneously analyze many targets present in the large field-of-view of a conventional optical microscope.
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Nanocellulose is a high value material that has gained increasing attention because of its high strength, stiffness, unique photonic and piezoelectric properties, high stability and uniform structure. Through utilization of a biorefinery concept, nanocellulose can be produced in large volumes from wood at relatively low cost via ionizing radiation processing. Ionizing radiation causes significant break down of the polysaccharide and leads to the production of potentially useful gaseous products such as H2 and CO. The application of radiation processing to the production of nanocellulose from woody and non-wood sources, such as field grasses, bio-refining byproducts, industrial pulp waste, and agricultural surplus materials remains an open field, ripe for innovation and application. Elucidating the mechanisms of the radiolytic decomposition of cellulose and the mass generation of nanocellulose by radiation processing is key to tapping into this source of nanocelluose for the growth of nanocellulostic-product development. More importantly, understanding the structural break-up of the cell walls as a function of radiation exposure is a key goal and only through careful, detailed characterization and dimensional metrology can this be achieved at the level of detail that is needed to further the growth of large scale radiation processing of plant materials. This work is resulting from strong collaborations between NIST and its academic partners who are pursuing the unique demonstration of applied ionizing radiation processing to plant materials as well as the development of manufacturing metrology for novel nanomaterials.
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Three-dimensional (3D) reconstruction of a sample surface from scanning electron microscope (SEM) images taken at two perspectives has been known for decades. Nowadays, there exist several commercially available stereophotogrammetry software packages. For testing these software packages, in this study we used Monte Carlo simulated SEM images of virtual samples. A virtual sample is a model in a computer, and its true dimensions are known exactly, which is impossible for real SEM samples due to measurement uncertainty. The simulated SEM images can be used for algorithm testing, development, and validation. We tested two stereophotogrammetry software packages and compared their reconstructed 3D models with the known geometry of the virtual samples used to create the simulated SEM images. Both packages performed relatively well with simulated SEM images of a sample with a rough surface. However, in a sample containing nearly uniform and therefore low-contrast zones, the height reconstruction error was ≈46%. The present stereophotogrammetry software packages need further improvement before they can be used reliably with SEM images with uniform zones.
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Dimensional measurements from secondary electron (SE) images were compared with those from backscattered electron (BSE) and low-loss electron (LLE) images. With the commonly used 50% threshold criterion, the lines consistently appeared larger in the SE images. As the images were acquired simultaneously by an instrument with the capability to operate detectors for both signals at the same time, the differences cannot be explained by the assumption that contamination or drift between images affected the SE, BSE, or LLE images differently. Simulations with JMONSEL, an electron microscope simulator, indicate that the nanometer-scale differences observed on this sample can be explained by the different convolution effects of a beam with finite size on signals with different symmetry (the SE signal's characteristic peak versus the BSE or LLE signal's characteristic step). This effect is too small to explain the >100 nm discrepancies that were observed in earlier work on different samples. Additional modeling indicates that those discrepancies can be explained by the much larger sidewall angles of the earlier samples, coupled with the different response of SE versus BSE/LLE profiles to such wall angles.
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Hybrid metrology, e.g., the combination of several measurement techniques to determine critical dimensions, is an increasingly important approach to meet the needs of the semiconductor industry. A proper use of hybrid metrology may yield not only more reliable estimates for the quantitative characterization of 3-D structures but also a more realistic estimation of the corresponding uncertainties. Recent developments at the National Institute of Standards and Technology (NIST) feature the combination of optical critical dimension (OCD) measurements and scanning electron microscope (SEM) results. The hybrid methodology offers the potential to make measurements of essential 3-D attributes that may not be otherwise feasible. However, combining techniques gives rise to essential challenges in error analysis and comparing results from different instrument models, especially the effect of systematic and highly correlated errors in the measurement on the χ2 function that is minimized. Both hypothetical examples and measurement data are used to illustrate solutions to these challenges.
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Despite many studies of subsurface imaging of carbon nanotube (CNT)-polymer composites via scanning electron microscopy (SEM), significant controversy exists concerning the imaging depth and contrast mechanisms. We studied CNT-polyimide composites and, by three-dimensional reconstructions of captured stereo-pair images, determined that the maximum SEM imaging depth was typically hundreds of nanometers. The contrast mechanisms were investigated over a broad range of beam accelerating voltages from 0.3 to 30 kV, and ascribed to modulation by embedded CNTs of the effective secondary electron (SE) emission yield at the polymer surface. This modulation of the SE yield is due to non-uniform surface potential distribution resulting from current flows due to leakage and electron beam induced current. The importance of an external electric field on SEM subsurface imaging was also demonstrated. The insights gained from this study can be generally applied to SEM nondestructive subsurface imaging of conducting nanostructures embedded in dielectric matrices such as graphene-polymer composites, silicon-based single electron transistors, high resolution SEM overlay metrology or e-beam lithography, and have significant implications in nanotechnology.
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This is the fourth part of a series of tutorial papers discussing various causes of measurement uncertainty in scanned particle beam instruments, and some of the solutions researched and developed at NIST and other research institutions. Scanned particle beam instruments especially the scanning electron microscope (SEM) have gone through tremendous evolution to become indispensable tools for many and diverse scientific and industrial applications. These improvements have significantly enhanced their performance and made them far easier to operate. But, the ease of operation has also fostered operator complacency. In addition, the user-friendliness has reduced the apparent need for extensive operator training. Unfortunately, this has led to the idea that the SEM is just another expensive "digital camera" or another peripheral device connected to a computer and that all of the problems in obtaining good quality images and data have been solved. Hence, one using these instruments may be lulled into thinking that all of the potential pitfalls have been fully eliminated and believing that, everything one sees on the micrograph is always correct. But, as described in this and the earlier papers, this may not be the case. Care must always be taken when reliable quantitative data are being sought. The first paper in this series discussed some of the issues related to signal generation in the SEM, including instrument calibration, electron beam-sample interactions and the need for physics-based modeling to understand the actual image formation mechanisms to properly interpret SEM images. The second paper has discussed another major issue confronting the microscopist: specimen contamination and methods to eliminate it. The third paper discussed mechanical vibration and stage drift and some useful solutions to mitigate the problems caused by them, and here, in this the fourth contribution, the issues related to specimen "charging" and its mitigation are discussed relative to dimensional metrology.
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This is the fourth part of a series of tutorial papers discussing various causes of measurement uncertainty in scanned particle beam instruments, and some of the solutions researched and developed at NIST and other research institutions. Scanned particle beam instruments, especially the scanning electron microscope (SEM), have gone through tremendous evolution to become indispensable tools for many and diverse scientifc and industrial applications. These improvements have significantly enhanced their performance and made them far easier to operate. But, the ease of operation has also fostered operator complacency. In addition, the user-friendliness has reduced the apparent need for extensive operator training. Unfortunately, this has led to the idea that the SEM is just another expensive "digital camera" or another peripheral device connected to a computer and that all of the problems in obtaining good quality images and data have been solved. Hence, one using these instruments may be lulled into thinking that all of the potential pitfalls have been fully eliminated and believing that, everything one sees on the micrograph is always correct. But, as described in this and the earlier papers, this may not be the case. Care must always be taken when reliable quantitative data are being sought. The first paper in this series discussed some of the issues related to signal generation in the SEM, including instrument calibration, electron beam-sample interactions and the need for physics-based modeling to understand the actual image formation mechanisms to properly interpret SEM images. The second paper has discussed another major issue confronting the microscopist: specimen contamination and methods to eliminate it. The third paper discussed mechanical vibration and stage drift and some useful solutions to mitigate the problems caused by them, and here, in this the fourth contribution, the issues related to specimen "charging" and its mitigation are discussed relative to dimensional metrology.
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This paper discusses a two step enhancement technique applicable to noisy Helium Ion Microscope images in which background structures are not easily discernible due to a weak signal. The method is based on a preliminary adaptive histogram equalization, followed by 'slow motion' low-exponent Lévy fractional diffusion smoothing. This combined approach is unexpectedly effective, resulting in a companion enhanced image in which background structures are rendered much more visible, and noise is significantly reduced, all with minimal loss of image sharpness. The method also provides useful enhancements of scanning charged-particle microscopy images obtained by composing multiple drift-corrected 'fast scan' frames. The paper includes software routines, written in Interactive Data Language (IDL),(1) that can perform the above image processing tasks.
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The scanning electron microscope (SEM) has gone through a tremendous evolution to become indispensable for many and diverse scientific and industrial applications. The improvements have significantly enriched and augmented the overall SEM performance and have made the instrument far easier to operate. But, the ease of operation also might lead, through operator complacency, to poor results. In addition, the user friendliness has seemingly reduced the need for thorough operator training for using these complex instruments. One might then conclude that the SEM is just a very expensive digital camera or another peripheral device for a computer. Hence, a person using the instrument may be lulled into thinking that all of the potential pitfalls have been eliminated and they believe everything they see on the micrograph is always correct. But, this may not be the case. An earlier paper (Part 1), discussed some of the potential issues related to signal generation in the SEM, instrument calibration, electron beam interactions and the need for physics-based modeling to understand the actual image formation mechanisms. All these were summed together in a discussion of how these issues effect measurements made with the instrument. This second paper discusses another major issue confronting the microscopist: electron-beam-induced specimen contamination. Over the years, NIST has done a great deal of research into the issue of sample contamination and its removal and elimination and some of this work is reviewed and discussed here.
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Optical microscopy is sensitive both to arrays of nanoscale features and to their imperfections. Optimizing scattered electromagnetic field intensities from deep sub-wavelength nanometer scale structures represents an important element of optical metrology. Current, well-established optical methods used to identify defects in semiconductor patterning are in jeopardy by upcoming sub-20 nm device dimensions. A novel volumetric analysis for processing focus-resolved images of defects is presented using simulated and experimental examples. This new method allows defects as narrow as (16 ± 2) nm (k = 1) to be revealed using 193 nm light with focus and illumination conditions optimized for three-dimensional data analysis. Quantitative metrics to compare two-dimensional and three-dimensional imaging indicate possible fourfold improvements in sensitivity using these methods.
Asunto(s)
Algoritmos , Interpretación de Imagen Asistida por Computador/métodos , Imagenología Tridimensional/métodos , Ensayo de Materiales/métodos , Microscopía/métodos , Nanopartículas/ultraestructura , Reconocimiento de Normas Patrones Automatizadas/métodos , Aumento de la Imagen/métodos , Sensibilidad y EspecificidadRESUMEN
The scanning electron microscope (SEM) has gone through a tremendous evolution to become a critical tool for many and diverse scientific and industrial applications. The high resolution of the SEM is especially suited for both qualitative and quantitative applications especially for nanotechnology and nanomanufacturing. Quantitatively, measurement, or metrology is one of the main uses. It is likely that one of the first questions asked before even the first scanning electron micrograph was ever recorded was: " how big is that?" The quality of that answer has improved a great deal over the past few years especially since today these instruments are being used as a primary measurement tool on semiconductor processing lines to monitor the manufacturing processes. The well-articulated needs of semiconductor production prompted a rapid evolution of the instrument and its capabilities. Over the past 20 years or so, instrument manufacturers, through substantial semiconductor industry investment of research and development (R&D) money, have vastly improved the performance of these instruments. All users have benefited from this investment, especially where quantitative measurements with an SEM are concerned. But, how good are these data? This article discusses some of the most important aspects and larger issues associated with imaging and measurements with the SEM that every user should know, and understand before any critical quantitative work is attempted.
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This paper reports an interlaboratory comparison that evaluated a protocol for measuring and analysing the particle size distribution of discrete, metallic, spheroidal nanoparticles using transmission electron microscopy (TEM). The study was focused on automated image capture and automated particle analysis. NIST RM8012 gold nanoparticles (30 nm nominal diameter) were measured for area-equivalent diameter distributions by eight laboratories. Statistical analysis was used to (1) assess the data quality without using size distribution reference models, (2) determine reference model parameters for different size distribution reference models and non-linear regression fitting methods and (3) assess the measurement uncertainty of a size distribution parameter by using its coefficient of variation. The interlaboratory area-equivalent diameter mean, 27.6 nm ± 2.4 nm (computed based on a normal distribution), was quite similar to the area-equivalent diameter, 27.6 nm, assigned to NIST RM8012. The lognormal reference model was the preferred choice for these particle size distributions as, for all laboratories, its parameters had lower relative standard errors (RSEs) than the other size distribution reference models tested (normal, Weibull and Rosin-Rammler-Bennett). The RSEs for the fitted standard deviations were two orders of magnitude higher than those for the fitted means, suggesting that most of the parameter estimate errors were associated with estimating the breadth of the distributions. The coefficients of variation for the interlaboratory statistics also confirmed the lognormal reference model as the preferred choice. From quasi-linear plots, the typical range for good fits between the model and cumulative number-based distributions was 1.9 fitted standard deviations less than the mean to 2.3 fitted standard deviations above the mean. Automated image capture, automated particle analysis and statistical evaluation of the data and fitting coefficients provide a framework for assessing nanoparticle size distributions using TEM for image acquisition.
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Helium ion microscopes (HIM) are capable of acquiring images with better than 1 nm resolution, and HIM images are particularly rich in morphological surface details. However, such images are generally quite noisy. A major challenge is to denoise these images while preserving delicate surface information. This paper presents a powerful slow motion denoising technique, based on solving linear fractional diffusion equations forward in time. The method is easily implemented computationally, using fast Fourier transform (FFT) algorithms. When applied to actual HIM images, the method is found to reproduce the essential surface morphology of the sample with high fidelity. In contrast, such highly sophisticated methodologies as Curvelet Transform denoising, and Total Variation denoising using split Bregman iterations, are found to eliminate vital fine scale information, along with the noise. Image Lipschitz exponents are a useful image metrology tool for quantifying the fine structure content in an image. In this paper, this tool is applied to rank order the above three distinct denoising approaches, in terms of their texture preserving properties. In several denoising experiments on actual HIM images, it was found that fractional diffusion smoothing performed noticeably better than split Bregman TV, which in turn, performed slightly better than Curvelet denoising.
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A review of the evolution of modeling for accurate dimensional scanning electron microscopy is presented with an emphasis on developments in the Monte Carlo technique for modeling the generation of the electrons used for imaging and measurement. The progress of modeling for accurate metrology is discussed through a schematic technology timeline. In addition, a discussion of a future vision for accurate SEM dimensional metrology and the requirements to achieve it are presented.