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Due to the extremely high specific surface area of nanoparticles and corresponding potential for adsorption, the results of surface analysis can be highly dependent on the history of the particles, particularly regarding sample preparation and storage. The sample preparation method has, therefore, the potential to have a significant influence on the results. This report describes an interlaboratory comparison (ILC) with the aim of assessing which sample preparation methods for ToF-SIMS analysis of nanoparticles provided the most intra- and interlaboratory consistency and the least amount of sample contamination. The BAM reference material BAM-P110 (TiO2 nanoparticles with a mean Feret diameter of 19 nm) was used as a sample representing typical nanoparticles. A total of 11 participants returned ToF-SIMS data,in positive and (optionally) negative polarity, using sample preparation methods of “stick-and-go” as well as optionally “drop-dry” and “spin-coat.” The results showed that the largest sources of variation within the entire data set were caused by adventitious hydrocarbon contamination or insufficient sample coverage, with the spin-coating protocol applied in this ILC showing a tendency toward insufficient sample coverage; the sample preparation method or the participant had a lesser influence on results.
There is an urgent demand for reliable data on microplastic analysis, particularly on its physico-chemical properties as well as validated methodology to obtain such data. Through interlaboratory comparisons (ILCs) it becomes possible to assess accuracy and precision of methods by involving many laboratories around the world. At BAM, my tasks focused around organisation of an ILC on physico-chemical characterisation of microplastic detection methods under the international pre-standardisation platform VAMAS (www.vamas.org/twa45/) as Project 2 “Development of standardized methodologies for characterisation of microplastics with microscopy and spectroscopy methods” under the Technical Working Area TWA 45 “Micro and Nano Plastics in the Environment”.
With a proud number of 84 participants this ILC is able to provide superior statistical results. Thermoanalytical (Py-GC/MS and TED-GC/MS) and vibrational (µ-IR and µ-Raman) methods were asked for identification and quantification of microplastic test samples according to mass or particle number. Preliminary results indicate which methods show a higher accuracy and precision and reveal some sample preparation ideas which work best for microplastics characterisation. At the end of the ILC an overall plausibility of the results will be assessed.
This contributions shows the first results of the ongoing interlaboratory comparisons under VAMAS/TWA 34 Nanoparticle populations related on the determination of pasrticle size distribution and relative concentration of nanoparticles and an example of an ILC running under VAMAS/TWA 41 Graphene and Related 2D Materials on the determination of the lateral diemsnions of graphene oxide flakes by Scanning Electron Microscopy. The link to related standardisation projects at ISO/TC Nanotechnologies are explained.
Advanced materials, such as nanomaterials, 2D materials, or thin films, play a crucial role in driving economic development and addressing major challenges in the coming years. These challenges include mitigating the impact of climate change, advancing lightweight engineering, enhancing catalysis, and improving medical applications.
To comprehend the performance of these materials and ensure their acceptance across various sectors as safe and sustainable for both humans and the environment, the availability of reference procedures, materials, and data is essential. One versatile tool for establishing such references and evaluating the proficiency of individual laboratories and their competencies is through (international) interlaboratory comparisons (ILC). Notably, initiatives like the Versailles Project on Advanced Materials and Standards (VAMAS) provide a platform for conducting ILCs.
This webinar will showcase various examples of interlaboratory comparisons, illustrating their impact on the development of reference products.
The progress of the VAMAS interlaboratory comparison Project P13 "Lateral size of graphene oxide flakes by SEM" within the Technical Working Area 41 "Graphene and Related 2D Materials" is presented. The challenges at sample preparation on substrates for accurate measurement and image analysis as well as two different analysis approaches, containing exact guidance how to measure the main descriptors for the lateral size measurement of the imaged graphene oxide flakes with Scanning Electron Microscopy are highlighted. The implementation of the results into the corresponding ISO technical specification AWI/TS 23879 is also discussed and planned, in relation with the AFM part.
Following points are presented and discussed: i) nPSize as an EMPIR project on the nanoparticle size and shape distribution of (more) complex particles including sample preparation and machine learning approaches; ii) parallel development of ISO 21363 (PSSD by TEM), ISO 19749 (PSSD by SEM), ISO 22292 (3D TEM), ISO 52408 (NP Prep for AFM and EM), iii) VAMAS and pre-standardisation, TWA 34 „Nanoparticle Populations“ with two nPSize ILC projects P15 & P16 – results to be published and integrated in ISO 21363 (PSSD by TEM); iv) Remaining challenges: platelets, 2D materials (TiO2 and GR2M); v) Reference data sets as part of a complete Characterisation Workflow.
The VAMAS/TWA 45 Project 2 “Development of standardized methodologies for characterisation of microplastics with microscopy and spectroscopy methods” involving 85 participants around the world is primarily discussed with respect to the results received and a first data evaluation. Status of the Project "Guidelines for defining reference materials for plastic degradation in marine environment" is reported and two new project proposals are presented: "Development of standardized methodologies for characterisation of nanoplastics (starting soon, BAM as leader?) and "Development of analytical protocols for the identification and quantification of microplastics of fibrous shape (still in negotiation)".
Traceable morphological and chemical characterization of nanomaterials with respect to the various possible sizes, size distributions, shapes, and concentrations of real-world nanoparticles (NPs) is a challenging task. Particularly for the nonspherical, non-monodisperse nanoparticles – as typically for most of the commercial particles, including their strong tendency to agglomerate, there is a lack of standard operation procedures providing accurate nanoparticle characterisation.
In the framework of the pre-standardisation framework of VAMAS (Versailles Project on Advanced Materials and Standards, www.vamas.org) two interlaboratory comparison (ILC) studies are being carried out under the Technical Working Area (TWA) 34 “Nanoparticle Populations”:i) Project #15 addresses the analysis of the size and shape distribution of TiO2 bipyramidal NPs by traceable imaging methods such as TEM, SEM, STEM-in-SEM, AFM as well as with SAXS as an ensemble method. This ILC is thought as the next level development of the case studies exemplified in the published ISO standards ISO 21363 and ISO 19749. It was agreed to complete the first ILC with the NPs already prepared according to the same procedure on a TEM grid, and, at a later stage, to carry out second ILCs with the same NPs distributed to the participants as liquid suspensions together with protocols for the uniform NP deposition on suited substrates - as developed and optimized within the European project nPSize. Once having good deposition protocols available, the door for automated image analysis gets opened. Corresponding image analysis protocols and reporting templates have been distributed to the ILC participants, too.
ii) Project #16: two spherical SiO2 NP samples with bi-modal size distributions in two nominal relative number concentrations were prepared and distributed also as liquid suspensions accompanied by sample preparation, measurement, and image analysis protocols and reporting templates. Here, the NP concentration is the primary parameter to be measured. For the imaging methods it is targeted to
measure the relative nanoparticle concentrations (relative populations of the two modes).
The results of all the participating laboratories, in both ILCs, compiled in comparative representations will be shown and discussed for the first time. The reduction of the measurement uncertainties associated to the size, shape and number-concentration results induced by the significant improvement of the sample preparation on substrates (as single particles with a high-density coverage), combined with welldefined image analysis procedures will be highlighted.
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.
This is a remote presentation I gave at the 2022 Small-angle Scattering conference in Campinas, Brazil. The video has been obtained from the conference organisers with their explicit permission for use on YouTube. I've tried to spruce up the audio from the remote recording the best I could.
The conference abstract for this talk was:
"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 samples[1]. 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.ph....
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."