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Based on practical examples of analysis with Electron Microscopy and Energy-Dispersive X-ray Spectroscopy, the minimum information requirements for reliable and reproducible nanomaterial characterization data such as particle size and shape distribution and elemental analysis are presented and discussed.
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.
In this paper one refined approach is applied to determine the exact orientation of bipyramidal TiO2 nanoparticles prepared with good dispersion as almost isolated particles on a carbon TEM grid. The advantages of the recently developed high-throughput Transmission Kikuchi Diffraction (TKD) are used to identify quickly and reliably the geometrical orientation of the crystalline TiO2 nanoparticle bipyramids (anatase) on a statistically relevant number of particles.
The present study addresses the capability of measurement of relative particle number concentration by scanning electron microscopy for model bimodal silica and gold samples prepared in the frame of the European research project “nPSize - Improved traceability chain of nanoparticle size measurements” as candidate reference nanoparticles.
In this work, we present various promising sample preparation procedures aiming to avoid drying artifacts and guarantee homogeneously distributed NP samples for imaging techniques like TEM, SEM or AFM. This involves retarded drying in an environment of high relative humidity as well as spin coating or freeze drying of the sample on the substrate.
Depending on the type of the NPs, different techniques are successful in obtaining homogenous sample deposition. Simple drying at ambient conditions often results in heavily agglomerated NPs densely packed in coffee ring traces. Retardation of the drying speed in an environment of high relative humidity, however, yields homogeneous NP deposition in the case of bimodal SiO2 and bimodal gold NP’s. In contrast, a sample of bipyramidal TiO2, heavily agglomerated when commonly dried, is successfully dispersed by spin coating the suspension on the substrate. The analysis of the particle size distribution of the bimodal silica and gold samples yielded number ratios resembling the nominal number ratios. The reliable measurement of the NP concentration of polydisperse samples by electron microscopy, even if relative, is new and of special relevance because up to now only the size of the particles, i.e. the abscissa of the PSD, can be measured reliably.
Various promising sample preparation procedures aiming to avoid drying artifacts and guarantee homogeneously distributed NP samples for imaging techniques like TEM, SEM or AFM are presented. This involves retarded drying in an environment of high relative humidity as well as spin coating or freeze drying of the sample on the substrate.
Depending on the type of the NPs, different techniques are successful in obtaining homogenous sample deposition. Simple drying at ambient conditions often results in heavily agglomerated NPs densely packed in coffee ring traces. Retardation of the drying speed in an environment of high relative humidity, however, yields homogeneous NP deposition in the case of bimodal SiO2 and bimodal gold NP’s. In contrast, a sample of bipyramidal TiO2, heavily agglomerated when commonly dried, is successfully dispersed by spin coating the suspension on the substrate.
The analysis of the particle size distribution of the bimodal silica and gold samples yielded number ratios resembling the nominal number ratios. The reliable measurement of the NP concentration of polydisperse samples by electron microscopy, even if relative, is new and of special relevance because up to now only the size of the particles, i.e. the abscissa of the PSD, can be measured reliably.
A series of different nanoparticle suspensions (Gold, Latex, and SiO2 in varying concentrations) were microprinted onto TEM grids in a 4 x 4 array in the concentration range 7x10^8 to 1x10^11 NP/mL and imaged with SEM and TSEM. Concentrations and printing conditions (temperature, relative humidity) were varied in order to minimize the coffee ring effect.
Nanoparticles (NP) have become important materials for a variety of chemical technologies. The enhance surface-area-to-volume ratio of NPs is very high, making them excellent for use as catalyst, in analytical assays, and for antimicrobial applications.
Nickel NPs have exhibited immense potential as important catalyst for the Sabatier reaction, i.e. converting waste to energy via transformation of CO2 into CH4, and could replace the rare earth elements such as Ru, PT, or Rh. In this work we describe the solvothermal synthesis of monometallic and bimetallic nickel nanoparticles.
Monodisperse monometallic Ni nanoparticles were synthesized using Oleylamin as solvent and reducing agent. The nanoparticles were investigated using small angle scattering (SAXS), scanning transmission electron microscopy (STEM) and energy dispersive X-ray spectroscopy (EDX), showing that the catalytically active sites are accessible. However, Ni has a high propensity to undergo oxidation, and becoming deactivated by coke formation. Hence, we further explore the preparation of bimetallic NPs, where a second metal is added to stabilize the Ni.
Bimetallic Cu-Ni NPs were synthesized by simultaneous solvothermal reduction. These bimetallic NPs exhibit excellent catalytic properties are promising candidates to be used as catalysts for efficient energy storage.
The main outcomes of the EMPIR project nPSize are presented and the suitability of the new capabilities (e.g. reference materials, measurement procedures, VAMAS inter-laboratory comparisons) to be standardized and implemented in accredited analytical laboratories is discussed. Complementation and/or filling gaps of published and ongoing standardisation projects on size, shape and number concentration measurements under ISO/TC 229/JWG 2 are offered.
In the present work a series of design rules are developed in order to tune the morphology of TiO2 nanoparticles through hydrothermal process. Through a careful experimental design, the influence of relevant process parameters on the synthesis outcome are studied, reaching to the develop predictive models by using Machine Learning methods. The models, after the validation and training, are able to predict with high accuracy the synthesis outcome in terms of nanoparticle size, polydispersity and aspect ratio. Furthermore, they are implemented by reverse engineering approach to do the inverse process, i.e. obtain the optimal synthesis parameters given a specific product characteristic. For the first time, it is presented a synthesis method that allows continuous and precise control of NPs morphology with the possibility to tune the aspect ratio over a large range from 1.4 (perfect truncated bipyramids) to 6 (elongated nanoparticles) and the length from 20 to 140 nm.