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Coating, stabilization layers, functionalization of particles or simple contamination are common variants of a core-shell system. For smaller nanoparticles this is of major importance. A particle with 16 nm diameter and a usual surface layer of 2 nm will have the same volume for the core as for the shell. In this case the material of the particle doesn’t have a clear definition. It is a common case that a particle consists of four different layers: Core, shell, stabilization layer and contamination. The properties of the particles differ according to this structure. For example silver particles might have a different dissolution rate for pure particles and for particles which are grown on top of a core.
Different solubility or defined other properties of materials is a common reason for producing core-shell systems. Gold cores are surrounded by silica to stabilize them or to get a defined distance between the cores. Silica might be surrounded by gold and the silica dissolved afterwards. This delivers hollow shells. Another important example for core-shell systems are quantum dots. A small core is surrounded by a different material for increasing the photoluminescence. Furthermore there a stabilization layer is needed. The smallest part of the final particles is the initial core. The photoluminescence is based on this core, but the shells contain much more material. Categorization should address this.
Core-shell systems are not covered by most of the existing decision trees for grouping. They are either regarded as special case or a singular layer. This disqualifies core-shell systems for grouping within the common models. There might be a very easy way to avoid this problem and even to combine some of the different decision trees. Starting the decision tree with the solubility of the outer shell and subsequently addressing the inner layers will be a pragmatic approach to solve the problem. If there is no shell, the categorization can start with a tiered approach or with the proposed “stawman” chemical categorization. If a shell is covering the surface there is a need to check if the shell is stable. If it is stable, the particle can be categorized based on this shell. If it is soluble, the ions need to be addressed as in the classic case. Furthermore the shell might increase the uptake by the cells. If the ions and the uptake are not critical the categorization can continue with the next layer.
With this not perfect but pragmatic approach, the surface layers can be addressed with very limited additional efforts. Most criteria are based on classically tabulated data. Including a rating system like the precautionary matrix approach might even address the fact that some parameters are not always Yes/No, e.g. solubility, ion toxicity and uptake.
Nanomaterials may have brought many beneficial innovations with them in our daily lives and and have become indispensable for the society. However, one needs to be concerned of the risks which are still unknown and not sufficietly studied and therefore there is a need for a nanorisk governance. At the core of nanorisk governance is gathering, processing and analysing reliable data which will be used for decision making. The challenge is to assure data reliability and transform it into knowledge. To address this challenge, we used analogy to technology readiness level (TRL) approach (developed by NASA), and elaborated knowledge readiness level (KaRL). KaRL is a nine-scale system to categorize data and knowledge (documents) into levels of readiness for particular purposes and to enhance readiness level by using quality and completeness filters, compliance requirements, nanorisk-related tools, stakeholders’ input. By our approach we addressed key issues in nanotechnology such as societal and ethical concerns, circular economy and sustainability, traceability of data, knowledge and decisions.
Regulatory decisions require reliable data and knowledge derived from this. Among stakeholders in nanotechnology, however, there is often uncertainty about the quality of data for regulatory purposes. In addition, the general public often finds itself excluded from nanoregulation and policy decisions. This creates uncertainty in the nanotechnology field and also in other branches of technology and leads to concerns among the society.
To address these issues, NANORIGO elaborates a framework to support decision making as well as data, information and knowledge sharing and use. We refer to “reliability” of data and knowledge as a degree of readiness or maturity. According to these criteria we worked out a 9-level scale in analogy to TRL (technology readiness level), the KaRL system (Knowledge, Data and Information Readiness Level). KaRL allows assessment of knowledge readiness for decision making by applying defined quality criteria for each level. It also provides guidance on how to enhance the readiness level by the help of available tools and procedures. KaRL addresses SEIN[1] principles, circular economy and thus involves the public concerns in regulation. A specialized nanorisk governance council (being under development in NANORIGO) is suggested to perform quality check of an actionable document, thus, aiding in consensus on the reliability (maturity) of knowledge for decision making. Moreover, KaRL facilitates traceability of knowledge before its use in decision making. This enables the transparency demanded by all stakeholders.
Both essential aspects of the surface of solid matter, its morphology and chemistry, are studied traditionally at BAM starting in the 60’s with different cyclical research focus areas, mostly related either to applicative research or method development. In the recent years, the focus has shifted almost exclusively to the nano-analytics of advanced materials such as complex nanoparticles, (ultra)thin films/coatings, nanocomposites, 2D materials, energy materials, etc. This is also the reason why BAM has established recently the new Competence Center nano@BAM (www.bam.de/Navigation/DE/Themen/Material/Nanotechnologie/sichere-nanomaterialien.html) with the five sub-fields nanoCharacterisation, nanoMaterial, nanoSafety, nanoData and nanoTechnology. The link to the BAM central guidelines to the safety in technology and chemistry is given by the development of reference products such as reference measurement procedures, reference (nano)materials, and newly reference data sets. Thus, an internationally well-networked group in surface analysis has been established @BAM, with regular contributions to integral analytical characterization with metrological and standardization background.
Examples of newly developed methodical approaches will be given with an emphasis on correlative nano-analysis of morphology and chemistry of nanomaterials. Correlative imaging by STEM-in-SEM with high-resolution SEM and EDX, and further with AFM or the new technique TKD (Transmission Kikuchi Diffraction) will be explained on various examples of nanostructures, both as starting materials and embedded/functionalized nanoparticles in products. The unique analytical benefits of the Auger electron probe as a veritable nano-tool for surface chemistry will be highlighted. The panoply of advanced surface characterization methods @BAM is completed by discussing examples of hybrid analysis of the bulk of nanomaterials by X-ray Spectroscopy with the highest surface-sensitive methods X-ray Photoelectron Spectroscopy (XPS) and Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS). Particularly for the analysis of the surface chemistry of nanostructures, such as the completeness of the shells of core-shell nanoparticles or in-depth and lateral gradients of chemistry within mesoporous thin layers, the latter methods are inherent.
Other special developments like approaches for the quantitative determination of the roughness of particle surface by electron microscopy or for the quantitative determination of the porosity of thin mesoporous layers by electron probe microanalysis (EPMA) with SEM will be presented.
Both essential aspects of the surface of solid matter, its morphology and chemistry, are studied traditionally at BAM starting in the 60’s with different cyclical research focus areas, mostly related either to applicative research or method development. In the recent years, the focus has shifted almost exclusively to the nano-analytics of advanced materials such as complex nanoparticles, (ultra)thin films/coatings, nanocomposites, 2D materials, energy materials, etc. This is also the reason why BAM has established recently the new Competence Center nano@BAM (www.bam.de/Navigation/DE/Themen/Material/Nanotechnologie/sichere-nanomaterialien.html) with the five sub-fields nanoCharacterisation, nanoMaterial, nanoSafety, nanoData and nanoTechnology. The link to the BAM central guidelines to the safety in technology and chemistry is given by the development of reference products such as reference measurement procedures, reference (nano)materials, and newly reference data sets. Thus, an internationally well-networked group in surface analysis has been established @BAM, with regular contributions to integral analytical characterization with metrological and standardization background.
Examples of newly developed methodical approaches will be given with an emphasis on correlative nano-analysis of morphology and chemistry of nanomaterials. Correlative imaging by STEM-in-SEM with high-resolution SEM and EDX, and further with AFM or the new technique TKD (Transmission Kikuchi Diffraction) will be explained on various examples of nanostructures, both as starting materials and embedded/functionalized nanoparticles in products. The unique analytical benefits of the Auger electron probe as a veritable nano-tool for surface chemistry will be highlighted. The panoply of advanced surface characterization methods @BAM is completed by discussing examples of hybrid analysis of the bulk of nanomaterials by X-ray Spectroscopy with the highest surface-sensitive methods X-ray Photoelectron Spectroscopy (XPS) and Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS). Particularly for the analysis of the surface chemistry of nanostructures, such as the completeness of the shells of core-shell nanoparticles or in-depth and lateral gradients of chemistry within mesoporous thin layers, the latter methods are inherent.
Other special developments like approaches for the quantitative determination of the roughness of particle surface by electron microscopy or for the quantitative determination of the porosity of thin mesoporous layers by electron probe microanalysis (EPMA) with SEM will be presented in conjunction with the corresponding advanced materials studied.
Current research projects, promising ideas, including ongoing (pre-)standardization activities in the field of the challenging nano/surface analysis will be touched systematically, with the open goal of identifying future bilateral cooperation possibilities between EMPA and BAM.
You Ask – ACEnano Replies
(2020)
The workshop starts with introductory information about the workshop and the H2020 project ACEnano, followed by two expert round tables, focussing on how the project could address regulator and industry needs, respectively. This is be followed by parallel sessions on tools (based on preferences expressed by those registered to attend, see “Questions”) and finally a question-and-answer session with the attendees.
The experts invited in Round Table 1 have been prepared to answer to questions related to obstacles and advantages for stakeholders such as SMEs to use the ACEnano approaches/tools. Standardisation needs are discussed.
The publicly available document encapsulates the first version of the Catalogue of Services of the future EC4Safenano Centre (CoS 2019).
The CoS 2019 is structured in 12 Service Categories and 27 Service Topics, for each of the 12 categories considered. This architecture configures a 12 x 27 matrix that allows ordering the potential EC4Safenano offer in 324 types of services/groups of services.
Each type of service/group of services is described, in a simple and friendly way, by means of a specific service sheet: the EC4Safenano - Service Data Sheet (EC4-SDS). These EC4-SDSs allow structuring and summarizing the information of each service, providing the customer with a concise view of characteristics of the service and also the contact details with the service provider.
The CoS 2019 deploys a map of services consisting of a set of 100 EC4-SDSs, covering 7 of the 12 Service Categories and 17 of the 27 Service Topics.
The harmonization of services is visualized as a future necessary step in EC4Safenano, in order to strengthen the offer and provide added value to customers with a growing offer of harmonized services in future versions of the CoS.
The information contained in this document is structured in 3 main sections, as follows:
• Catalogue structure. This section describes in short the main characteristics of the CoS 2019.
• Catalogue content. This section represents the core part of the document and encapsulates the set of 100 SDSs displaying the offer proposed by the CoS 2019.
• Online Catalogue. This section describes the resources implemented by EC4Safenano to facilitate the on-line consultation of the CoS 2019 by customers and other interested parties.
Blueprint for a sustainable new European Centre to support safe innovation for nanotechnology
(2020)
This paper presents the blueprint for the operation of a sustainable and permanent European Centre of collaborating reference laboratories and research centres, to establish a one-stop shop for a wide variety of nanosafety related services, and to provide a central contact point for questions about nanosafety in Europe. The Centre aims to harmonise service provision, and bring novel risk assessment and management approaches closer to practice.
How much do we, the small-angle scatterers, influence the results of an investigation? What uncertainty do we add by our human diversity in thoughts and approaches, and is this significant compared to the uncertainty from the instrumental measurement factors?
After our previous Round Robin on data collection, we know that many laboratories can collect reasonably consistent small-angle scattering data on easy samples1. To investigate the next, human component, we compiled four existing datasets from globular (roughly spherical) scatterers, each exhibiting a common complication, and asked the participants to apply their usual methods and toolset to the quantification of the results https://lookingatnothing.com/index.php/archives/3274).
Accompanying the datasets was a modicum of accompanying information to help with the interpretation of the data, similar to what we normally receive from our collaborators. More than 30 participants reported back with volume fractions, mean sizes and size distribution widths of the particle populations in the samples, as well as information on their self-assessed level of experience and years in the field.
While the Round Robin is still underway (until the 25th of April, 2022), the initial results already show significant spread in the results. Some of these are due to the variety in interpretation of the meaning of the requested parameters, as well as simple human errors, both of which are easy to correct for. Nevertheless, even after correcting for these differences in understanding, a significant spread remains. This highlights an urgent challenge to our community: how can we better help ourselves and our colleagues obtain more reliable results, how could we take the human factor out of the equation, so to speak?
In this talk, we will introduce the four datasets, their origins and challenges. Hot off the press, we will summarize the anonymized, quantified results of the Data Analysis Round Robin. (Incidentally, we will also see if a correlation exists between experience and proximity of the result to the median). Lastly, potential avenues for improving our field will be offered based on the findings, ranging from low-effort yet somehow controversial improvements, to high-effort foundational considerations.
In contrast to the crisp, clear images you can get from electron microscopy, small-angle X-ray scattering (SAXS) patterns are rather featureless. These patterns, however, contain averaged structural information of all of the finest material structures that were illuminated by the X-ray beam. With careful and precise investigation, and supplementary information from complementary techniques, this bulk material structure can be quantified to reveal structural information spanning four or even five decades in size. Additionally, while the data correction and analysis is complex, sample preparation is very straightforward, also allowing for in-situ and operando measurements to be performed without breaking a sweat. In the right hands, then, this technique can be the most powerful tool in your analytical arsenal.