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The characteristics of TiO2 coatings can greatly influence their final performance in large‐scale applications. In the present study, self‐assembly of TiO2 nanoparticles (NPs) in multiple layers was selected as a deposition procedure on various substrates. For this, the main prerequisite constitutes the surface modification of both NPs and substrate with, for example, silane coupling agents. A set of functionalized TiO2 NPs has been produced by reaction with either (3‐aminopropyl)triethoxysilane (APTES) or (3‐aminopropyl)phosphonic acid (APPA) to functionalize the NP surface with free amino‐groups. Then, the complementary functionalized NP set can be obtained from an aliquot of the first one, through the conversion of free surface amino groups to aldehydes by reaction with glutaraldehyde (GA). Several types of TiO2 NPs differing in size, shape, and specific surface area have been functionalized. Fourier‐transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), SEM/ energy‐dispersive X‐ray spectroscopy (EDS), XPS, Auger electron spectroscopy (AES), and Time‐of‐Flight (ToF)‐SIMS analyses have been carried out to evaluate the degree of functionalization, all the analytical methods employed demonstrating successful functionalization of TiO2 NP surface with APTES or APPA and GA.
Accurate and reproducible measurement of the structure and properties of high-value nanoparticles is extremely important for their commercialization. A significant proportion of engineered nanoparticle systems consist of some form of nominally core-shell structure, whether by design or unintentionally. Often, these do not form an ideal core-shell structure, with typical deviations including polydispersity of the core or shell, uneven or incomplete shells, noncentral cores, and others. Such systems may be created with or without intent, and in either case an understanding of the conditions for formation of such particles is desirable. Precise determination of the structure, composition, size, and shell thickness of such particles can prove challenging without the use of a suitable range of characterization techniques. Here, the authors present two such polymer core-shell nanoparticle systems, consisting of polytetrafluoroethylene cores coated with a range of thicknesses of either polymethylmethacrylate or polystyrene. By consideration of surface energy, it is shown that these particles are expected to possess distinctly differing coating structures, with the polystyrene coating being incomplete. A comprehensive characterization of these systems is demonstrated, using a selection of complementary techniques including scanning electron microscopy, scanning transmission electron microscopy, thermogravimetric analysis, dynamic light scattering, differential centrifugal sedimentation, and X-ray photoelectron spectroscopy. By combining the results provided by these techniques, it is possible to achieve superior characterization and understanding of the particle structure than could be obtained by considering results separately.
A variety of methods used to prepare nano-objects for surface analysis are described along with information about when they might be best applied. Intrinsic properties of NPs which complicate their characterization and need to be considered when planning for surface or other analyses of NPs are identified, including challenges associated with reproducible synthesis and functionalization of the particles as well as their dynamic nature. The relevant information about the sample preparation processes, along with analysis details and data that need to be added to the collection of material provenance information is identified. Examples of protocols that have been successfully used for preparation of nano-objects for surface analysis are included in an annex.
This chapter provides an introduction in secondary ion mass spectrometry as one of the leading surface chemical analysis and imaging techniques with molecular specificity in the field of material sciences. The physical basics of the technique are explained along with a description of the typical instrumental setups and their modes of operation. The application paragraph specifically focuses on nanoparticle analysis by SIMS in terms of surface spectrometry, imaging, analysis in organic and complex media, and depth profiling.
A review of the existing literature is provided, and selected studies are showcased. Limitations and pitfalls as well as current technical developments of SIMS application in nanoparticle surface chemical analysis are equally discussed.
Introduction
(2020)
The purpose of this book is to provide a comprehensive collection of analytical methods that are commonly used to measure nanoparticles, providing information on one, or more, property of importance. The chapters provide up-to-date information and guidance on the use of these techniques, detailing the manner in which they may be reliably employed. Within this chapter, we detail the rationale and context of the whole book, which is driven by the observation of a low level of reproducibility in nanoparticle research. The aim of the book is to encourage awareness of both the strengths and weaknesses of the various methods used to measure nanoparticles and raise awareness of the range of methods that are available. The editors of the book have, for many years, been engaged in European projects and standardization activities concerned with nanoparticle analysis and have identified authors who are experts in the various methods included within the book. This has produced a book that can be used as a definitive guide to current best practice in nanoparticle measurement.
In this chapter sample preparation, image acquisition, and nanoparticle size and shape characterization methods using the scanning electron microscope (SEM) in reflective and transmitted working modes are described. These help in obtaining reliable, highly repeatable results. The best solutions vary case-by-case and depend on the raw (powdered or suspension) nanoparticle material, the required measurement uncertainty and on the performance of the SEM.
Characterization of nanomaterials by transmission electron microscopy - Measurement procedures
(2020)
In this chapter, approaches are proposed for the descriptive and quantitative characterization of nano-objects with nanometer resolution. Measurements are based on the analysis of the characteristics of 2D projections of individual particles visualized on transmission electron micrographs.
Incorporation of spectroscopic methods (EDS and EELS) for elemental analysis of nano-objects is recommended to identify subpopulations of nano-objects in mixtures based on their chemical composition. The focus lies on the determination of physicochemical properties which are essential in a legislatory and regulatory context to define the material as a nanomaterial (NM), and to assess its safety and toxicological potential, using widely accessible equipment.
Auger electron spectroscopy
(2020)
An introduction in the application of Auger Electron Spectroscopy to surface chemical analysis of nanoparticles is given. Auger Electron Spectroscopy is a mature method in the field of surface chemical analysis. The chapter addresses the physical basis of the method, the principal design of recent instruments together with modes of operation and options for the presentation of spectra, as well as different approaches for qualitative (including identification of chemical species) and quantitative surface analysis of elements. An application paragraph on surface chemical analysis of nanoparticles by AES or SAM introduces the different measurement approaches and sample preparation strategies applied by analysts. The analysis of nanoparticle ensembles, the so-called selected point analysis where a narrow primary electron beam is centered on an individual nanoparticle, and chemical mapping of individual nanoparticles (or a line scan across) are addressed. Existing literature is reviewed and informative case studies presented. Limitations and pitfalls in the application of AES in surface chemical analysis of nanoparticles are also addressed.
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.
NanoDefiner e-Tool: An Implemented Decision Support Framework for Nanomaterial Identification
(2019)
The European Commission’s recommendation on the definition of nanomaterial (2011/696/EU) established an applicable standard for material categorization. However, manufacturers face regulatory challenges during registration of their products. Reliable categorization is difficult and requires considerable expertise in existing measurement techniques (MTs). Additionally, organizational complexity is increased as different authorities’ registration processes require distinct reporting.
The NanoDefine project tackled these obstacles by providing the NanoDefiner e-tool: A decision support expert system for nanomaterial identification in a regulatory context. It providesMT recommendations for categorization of specific materials using a tiered approach (screening/confirmatory), and was constructed with experts from academia and industry to be extensible, interoperable, and adaptable for forthcoming revisions of the nanomaterial definition. An implemented MT-driven material categorization scheme allows detailed description. Its guided workflow is suitable for a variety of user groups. Direct feedback and explanation enable transparent decisions. Expert knowledge is Held in a knowledge base for representation of MT performance criteria and physicochemical particle type
properties. Continuous revision ensured data quality and validity. Recommendations were validated by independent case studies on industry-relevant particulate materials. Besides supporting material identification and registration, the free and open-source e-tool may serve as template for other expert systems within the nanoscience domain.