TY - GEN A1 - Shard, A. G. A1 - Hodoroaba, Vasile-Dan A1 - Unger, Wolfgang ED - Hodoroaba, Vasile-Dan ED - Unger, Wolfgang ED - Shard, A. G. T1 - Introduction T2 - Characterization of nanoparticles - Measurement processes for nanoparticles N2 - 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. KW - Nanoparticles KW - Size distribution KW - Shape KW - Chemistry KW - Coating KW - Concentration KW - Standards KW - Charge KW - Characterisation PY - 2020 SN - 978-0-12-814182-3 DO - https://doi.org/10.1016/B978-0-12-814182-3.00001-8 SP - 1 EP - 6 PB - Elsevier CY - Amsterdam AN - OPUS4-50166 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Vladár, A. E. A1 - Hodoroaba, Vasile-Dan ED - Hodoroaba, Vasile-Dan ED - Unger, Wolfgang ED - Shard, A. G. T1 - Characterization of nanoparticles by scanning electron microscopy T2 - Characterization of nanoparticles - Measurement processes for nanoparticles N2 - 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. KW - Nanoparticles KW - Sample preparation KW - Electron microscopy KW - SEM KW - Size measurement KW - Shape KW - Threshold PY - 2020 SN - 978-0-12-814182-3 DO - https://doi.org/10.1016/B978-0-12-814182-3.00002-X SP - 7 EP - 27 PB - Elsevier CY - Amsterdam AN - OPUS4-50120 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Pellegrino, F. A1 - Isopescu, R. A1 - Pellutiè, L. A1 - Sordello, F. A1 - Rossi, A. M. A1 - Ortel, Erik A1 - Martra, G. A1 - Hodoroaba, Vasile-Dan A1 - Maurino, V. T1 - Machine learning approach for elucidating and predicting the role of synthesis parameters on the shape and size of TiO2 nanoparticles JF - Scientific Reports N2 - 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. KW - Machine learning KW - Nanoparticles KW - Titanium dioxide KW - Size KW - Shape KW - Synthesis PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-515084 DO - https://doi.org/10.1038/s41598-020-75967-w VL - 10 IS - 1 SP - 18910 PB - Springer Nature AN - OPUS4-51508 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hodoroaba, Vasile-Dan T1 - EMPIR nPSize - Improved Traceability Chain of Nanoparticle Size Measurement; nPSize offer after 2 Ys N2 - 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. T2 - EMPIR nPSize Training Course "Metrology for Measurement of Nanoparticle Size by Electron Microscopy and Atomic Force Microscopy" CY - Online meeting DA - 27.10.2020 KW - Nanoparticles KW - Size KW - Shape KW - Traceability KW - EMPIR KW - Reference materials KW - VAMAS PY - 2020 AN - OPUS4-51477 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -