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Luminescence lifetimes are an attractive analytical method for detection due to its high sensitivity and stability. Iridium probes exhibit luminescence with long excited-state lifetimes, which are sensitive to the local environment. Perfluorooctanoic acid (PFOA) is listed as a chemical of high concern regarding its toxicity and is classified as a “forever chemical”. In addition to strict limits on the presence of PFOA in drinking water, environmental contamination from industrial effluent or chemical spills requires rapid, simple, accurate, and cost-effective analysis in order to aid containment. Herein, we report the fabrication and function of a novel and facile luminescence sensor for PFOA based on iridium modified on gold surfaces. These surfaces were modified with lipophilic iridium complexes bearing alkyl chains, namely, IrC6 and IrC12, and Zonyl-FSA surfactant. Upon addition of PFOA, the modified surfaces IrC6-FSA@Au and IrC12-FSA @Au show the largest change in the red luminescence signal with changes in the luminescence lifetime that allow monitoring of PFOA concentrations in aqueous solutions. The platform was tested for the measurement of PFOA in aqueous samples spiked with known concentrations of PFOA and demonstrated the capacity to determine PFOA at concentrations >100 μg/L (240 nM).
Here, we elucidate nonclassical multistep crystallization pathways of transition metal phosphates from aqueous solutions. We followed precipitation processes of M-struvites, NH4MPO4·6H2O, and M-phosphate octahydrates, M3(PO4)2·8H2O, where M = Ni, Co, or NixCo1–x, by using in situ scattering and spectroscopy-based techniques, supported by elemental mass spectrometry analyses and advanced electron microscopy. Ni and Co phosphates crystallize via intermediate colloidal amorphous nanophases, which change their complex structures while agglomerating, condensing, and densifying throughout the extended reaction times. We reconstructed the three-dimensional morphology of these precursors by employing cryo-electron tomography (cryo-ET). We found that the complex interplay between metastable amorphous colloids and protocrystalline units determines the reaction pathways. Ultimately, the same crystalline structure, such as struvite, is formed. However, the multistep process stages vary in complexity and can last from a few minutes to several hours depending on the selected transition metal(s), their concentration, and the Ni/Co ratio.
Iron Oxide Nanocubes as a New Certified Reference Material for Nanoparticle Size Measurements
(2023)
The rational design and increasing industrial use of nanomaterials require a reliable characterization of their physicochemical key properties like size, size distribution, shape, and surface chemistry. This calls for nanoscale reference materials (nanoRMs) for the validation and standardization of commonly used characterization methods closely matching real-world nonspherical nano-objects. This encouraged us to develop a nonspherical nanoRM of very small size consisting of 8 nm iron oxide nanocubes (BAM-N012) to complement spherical gold, silica, and polymer nanoRMs. In the following, the development and production of this nanoRM are highlighted including the characterization by transmission electron microscopy (TEM) and small-angle X-ray scattering (SAXS) as complementary methods for size and shape parameters, homogeneity and stability studies, and calculation of a complete uncertainty budget of the size features. The determination of the nanocubes’ edge length by TEM and SAXS allows a method comparison. In addition, SAXS measurements can also provide the mean particle number density and the mass concentration. The certified size parameters, area equivalent circular diameter and square edge length, determined by TEM with a relative expanded uncertainty below 9%, are metrologically traceable to a natural constant for length, the very precisely known (111) lattice spacing of silicon. Cubic BAM-N012 qualifies as a certified nanoRM for estimating the precision and trueness, validation, and quality assurance of particle size and shape measurements with electron microscopy and SAXS as well as other sizing methods suitable for nanomaterials. The production of this new iron oxide nanocube RM presents an important achievement for the nanomaterial community, nanomaterial manufacturers, and regulators.
Since its isolation, graphene has received growing attention from academia and industry due to its unique properties. However, the “what is my material” barrier hinders further commercialization. X-ray photoelectron spectroscopy (XPS) is considered as a method of choice for the determination of the elemental and chemical composition. In this work the influence of the morphology of graphene particles on the XPS results is studied and investigated as a function of X-ray energy, using conventional XPS with Al K𝜶 radiation and hard X-ray photoemission spectroscopy (HAXPES) using Cr K𝜶 radiation. Thereby, the information depth is varied between 10 and 30 nm. For this purpose, two commercial powders containing graphene nanoplatelets with lateral dimensions of either ≈100 nm or in the micrometer range are compared. These larger ones exist as stack of graphene layers which is inspected with scanning electron microscopy. Both kinds of particles are then functionalized with either oxygen or fluorine. The size of the graphene particles is found to influence the degree of functionalization. Only the combination of XPS and HAXPES allows to detect the functionalization at the outermost surface of the particles or even of the stacks and to provide new insights into the functionalization process.
The datasets from (Hard Energy) X-ray photoelectron spectroscopy, X-ray diffraction and Scanning Electron Microsopy are related to the publication
G. Chemello, X. Knigge, D. Ciornii, B.P. Reed, A.J. Pollard, C.A. Clifford, T. Howe, N. Vyas, V.-D. Hodoroaba, J. Radnik
"Influence of the morphology on the functionalization of graphene nanoplatelets analyzed by comparative photoelectron spectroscopy with soft and hard X-rays"
Advanced Materials Interfaces (2023), DOI: 10.1002/admi.202300116.
Functionalized Ti3C2Tx nanosheets based biosensor for point-of-care detection of SARS-CoV‑2 antigen
(2023)
MXenes are considered a promising class of two-dimensional materials with extraordinary physical and electrochemical properties. Distinguished features like high specific surface area and outstanding electrical conductivity make them suitable for electrochemical biosensing applications. Here, we report the development of a biosensor involving the functionalized MXene−titanium carbide nanosheets (Ti3C2Tx-NS) and monoclonal antibodies against the SARS-CoV-2 nucleocapsid protein (anti-SARS-CoV-2 mAb) to design a point-of-care device for detection of the SARS-CoV-2 nucleocapsid protein (SARS-CoV-2 NP) antigen. Few-layered titanium carbide nanosheets (denoted as FL-Ti3C2Tx-NS) have been synthesized using a single-step etching and delamination method and characterized using optical and electron microscopy techniques revealing the suitability for immunosensing applications. Binding studies revealed the excellent affinity between the biosensor and the SARS-CoV-2 NP. Electrochemical detection of SARS-CoV-2 NP is performed using differential pulse voltammetry and read by a smartphone-based user interface. The proposed FL-Ti3C2Tx-NS based biosensor offers the detection of SARS-CoV-2 NP with a limit of detection of 0.91 nM in a wide detection range in spiked saliva samples. Additionally, there is no cross-reactivity in the presence of potential interferants like SARS-CoV-2 spike glycoprotein and bovine serum albumin. These findings demonstrate the potential of MXenes in developing a rapid and reliable tool for SARS-CoV-2 NP detection. While we report the biosensing of SARS-CoV-2 NP, our system also paves the way for the detection of other SARS-CoV-2 antigens like spike protein or other biomolecules based on antigen−antibody interactions.
Binary photoluminescent semiconductor nanocrystals (quantum dots, QDs) are one of the best studied fluorescent nanomaterials, and their unique optoelectronic properties paved the road to many applications in (bio)nanophotonics, optoelectronics, and photovoltaics. However, concerns related to their toxic constituents like cadmium or lead and the emerging interest in greener chemistry synthesis approaches hamper their future applicability. Interesting alternatives for some applications like biosensing or bioimaging are heavy-metal-free ternary QDs like AgInS2 (AIS), CuInS2 (CIS), and quaternary QDs such as AIS-ZnS (ZAIS). In this context, we explored the effect of ligand denticity on the organic-to-aqueous phase transfer of oleylamine-stabilized ZAIS QDs with the hydrophilic ligands mercaptopropionic acid (MPA), dihydrolipoic acid (DHLA), and 3-mercapto-2,2-bis(mercaptomethyl)propanoic acid (3MPA), bearing mono-, bi-, and trialkyl thiol groups. Spectroscopic studies of the resulting water-dispersible ZAIS QDs revealed a considerable influence of ligand denticity and ligand-to-QD ratio on the spectral position and width (FWHM; full width at half-maximum) of the photoluminescence (PL) bands, the PL quantum yields (PL QY), and the PL decay kinetics. Thiol capping and phase transfer resulted in a loss in PL by at least a factor of 2. The ligand-induced PL quenching observed particularly for ligands bearing two or three thiol groups was attributed to the facilitated formation of surface-bound disulfides. The best colloidal stability under high dilution conditions was observed for 3MPA.
In the present talk the basics of the Raman spectroscopy and particularly of Raman microscopy are explained. Advantages and disadvantages of the method are highlighted through selected case studies. In the second part of the lecture examples of correlative imaging with electron, X-ray, ion and optical microscopies from micro- to the nanoscale are highlighted.
For test laboratories operating under accreditation schemes like ISO/IEC 17025 (ISO/IEC 17025), as the international reference for testing and calibration laboratories wanting to demonstrate their capacity to deliver reliable results, a periodical control of the critical instrumental parameters of an Energy-Dispersive X-ray Spectrometer (EDS) is required.
This periodical check of an EDS is specified with exact procedures and materials in the ISO 15632:2021 ”Microbeam Analysis – Selected instrumental performance parameters for the specification and checking of energy-dispersive X-ray spectrometers for use in electron probe microanalysis” (ISO 15632). The EDS check can be simplified to the acquisition of only one 10 kV spectrum from a dedicated test material, EDS-TM002, which is made available by BAM since 2009 (https://webshop.bam.de/webshop_en/). The optional BAM software “EDX spectrometer check” is destined to automatically evaluate this spectrum and determine the performance of the EDS in terms of energy resolution and calibration, as well as possible alteration of low-energy efficiency due to detector contamination. Nearly 200 laboratories have the EDS-TM and associated software package in use.
Practical examples based on various types of artifacts occurred in the EDS spectra and a long-term (>10 years) meticulous observation of the own spectrometers will be discussed. Different types of EDS spectrometers are considered, e.g. Si(Li) and SDD, of various window types (AP, the recent one Si3N4 or even windowless), and with different front contact layers (Au and Ni) (Hodoroaba and Procop, 2014). Evaluation of other parameters or effects such as the deadtime at different count rates or pileup effects is also explained with examples.
CS particles show unique properties by merging individual characteristics of the core and the shell materials. An alteration particularly in their surface roughness affects the final performance of the particles in the targeted application. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task employing microscopic techniques being scarce and showing large differences in terms of methodology and results.
In our previous work, we have reported a systematic study with a reliable analysis tool, which evaluates profile roughness quantitatively, for individual core-shell microparticles using electron microscopy (EM) images of both types, Scanning Electron Microscopy (SEM) and transmission mode SEM (or TSEM). The SEM images contain two-dimensional (2D) information, therefore, provide profile roughness data only from the projection in the horizontal plane (in other words, from the “belly”) of a spherical particle. The present study offers a practical procedure to give access to more information by tilting the sample holder and hence allowing images of a single particle to be recorded at different orientations under the same view angle. From the analysis of these images, extended information on surface roughness of the particle can be extracted. Thus, instead of obtaining 2D information from a single SEM image, three-dimensional (3D) information is obtained from 2D projections recorded at different particle orientations.
Catalysts are important components in chemical processes because they lower the activation energy and thus determine the rate, efficiency and selectivity of a chemical reaction. This property plays an important role in many of today’s processes, including the electrochemical splitting of water. Due to the continuous development of catalyst materials, they are becoming more complex, which makes a reliable evaluation of physicochemical properties challenging even for modern analytical measurement techniques and industrial manufacturing.
We present a fast, vacuum-free and non-destructive analytical approach using multi-sample spectroscopic ellipsometry to determine relevant material parameters such as film thickness, porosity and composition of mesoporous IrOx–TiOy films. Mesoporous IrOx–TiOy films were deposited on Si wafers by sol–gel synthesis, varying the composition of the mixed oxide films between 0 and 100 wt%Ir. The ellipsometric modeling is based on an anisotropic Bruggeman effective medium approximation (a-BEMA) to determine the film thickness and volume fraction of the material and pores. The volume fraction of the material was again modeled using a Bruggeman EMA to determine the chemical composition of the materials. The ellipsometric fitting results were compared with complementary methods, such as scanning electron microscopy (SEM), electron probe microanalysis (EPMA) as well as environmental ellipsometric porosimetry (EEP).
Morpho-Chemical Characterisation of Me-TiO2 Nanoparticles for Enhanced Photocatalytical Activity
(2022)
The conversion of solar energy into electricity and solar fuels is of crucial importance for a green and sustainable future. Water splitting using semiconductor photo-catalysts is considered a sustainable method to produce clean hydrogen (H2) fuel. Nevertheless, H2 photo-production efficiency remains still low, although extensive research works to understand better the mechanisms of the Hydrogen Evolution Reaction (HER) and the Oxygen Evolution Reaction (OER) are being carried out. In this respect, TiO2 is a key photoactive material, usually employed with a co-catalyst deposited onto the surface to enhance charge carriers’ separation and catalyze surface charge transfer reactions. The deposition of a co-catalyst on the TiO2 nanoparticle surface represents one successful way to enhance the activity of the photocatalyst through a modification of its surface and redox properties. In this context, high-resolution scanning electron microscopy coupled with elemental analysis by energy-dispersive X-ray spectroscopy (EDS) is fundamental for studying and understanding the effect of the nanoparticle morphology on the functional properties of shape-controlled TiO2 crystals (bipyramides, platelets, and elongated particles). Different types of metal-semiconductor combinations, TiO2 shapes and dopant metals (Ag, Pt, etc) and metal concentrations will be discussed.
microscopy (AFM), or X-ray reflectometry. For the additional determination of thin film composition, techniques like X-ray photoelectron spectroscopy (XPS) or mass spectrometry-based techniques can be used. An alternative non-destructive technique is electron probe microanalysis (EPMA). This method assumes a sample of homogenous (bulk) chemical composition, so that it cannot be usually applied to thin film samples. However, in combination with the thin film software StrataGEM, the thickness as well as the composition of such films on a substrate can be determined.
This has been demonstrated for FeNi on Si and SiGe on Al2O3 film systems. For both systems five samples with different elemental composition and a reference were produced and characterised by Korean research institute KRISS using inductively coupled plasma mass spectrometry (ICP-MS), Rutherford backscattering (RBS), and transmission electron microscopy (TEM). These samples were used for an international round robin test.
In 2021, a new and open-source thin film evaluation programme called BadgerFilm has been released. It can also be used to determine thin film composition and thickness from intensity ratios of the unknown sample and standards (k-ratios).
In this contribution, we re-evaluated the data acquired for the FeNi and SiGe systems using the BadgerFilm software package and compared the resulting composition and thickness with the results of the established StrataGEM software and other reference methods. With the current evaluation, the BadgerFilm software shows good agreement with the composition and thickness calculated by StrataGEM and as the reference values provided by the KRISS.
Core-shell (CS) particles have been increasingly used for a wide range of applications due to their unique properties by merging individual characteristics of the core and the shell materials. The functionality of the designed particles is strongly influenced by their surface roughness. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task for Scanning Electron Microscopy (SEM).
The SEM images contain two-dimensional (2D) information providing contour roughness data only from the projection of the particle in the horizontal plane. This study presents a practical procedure to achieve more information by tilting the sample holder, hence allowing images of different areas of a single particle to be recorded at different orientations under the same view angle. From the analysis of these images, quasi three-dimensional (3D) information is obtained.
Three types of home-made particles were investigated: i) bare polystyrene (PS) particles, ii) PS particles decorated with a first magnetic iron oxide (Fe3O4) nanoparticle shell forming CS microbeads, iii) PS/Fe3O4 particles closed with a second silica (SiO2) shell forming core-shell-shell (CSS) microbeads. A series images of a single particle were taken with stepwise tilted sample holder up to 10° by an SEM with high-resolution and surface sensitive SE-InLens® mode.
A reliable analysis tool has been developed by a script in Python to analyze SEM images automatically and to evaluate profile roughness quantitatively, for individual core-shell microparticles. Image analysis consists of segmentation of the images, identifying contour and the centre of the particle, and extracting the root mean squared roughness value (RMS-RQ) of the contour profile from the particle projection within a few seconds.
The variation in roughness from batch-to-batch was determined with the purpose to set the method as a routine quality check procedure. Flow cytometry measurements provided complementary data. Measurement uncertainties associated to various particle orientations were also estimated.
Whereas the characterization of nanomaterials using different analytical techniques is often highly automated and standardized, the sample preparation that precedes it causes a bottleneck in nanomaterial analysis as it is performed manually. Usually, this pretreatment depends on the skills and experience of the analysts. Furthermore, adequate reporting of the sample preparation is often missing. In this overview, some solutions for techniques widely used in nano-analytics to overcome this problem are discussed. Two examples of sample preparation optimization by au-tomation are presented, which demonstrate that this approach is leading to increased analytical confidence. Our first example is motivated by the need to exclude human bias and focuses on the development of automation in sample introduction. To this end, a robotic system has been de-veloped, which can prepare stable and homogeneous nanomaterial suspensions amenable to a variety of well-established analytical methods, such as dynamic light scattering (DLS), small-angle X-ray scattering (SAXS), field-flow fractionation (FFF) or single-particle inductively coupled mass spectrometry (sp-ICP-MS). Our second example addresses biological samples, such as cells exposed to nanomaterials, which are still challenging for reliable analysis. An air–liquid interface has been developed for the exposure of biological samples to nanomaterial-containing aerosols. The system exposes transmission electron microscopy (TEM) grids under reproducible conditions, whilst also allowing characterization of aerosol composition with mass spectrometry. Such an approach enables correlative measurements combining biological with physicochemical analysis. These case studies demonstrate that standardization and automation of sample preparation setups, combined with appropriate measurement processes and data reduction are crucial steps towards more reliable and reproducible data.
The roughness as a property of core–shell (CS) microparticles plays a key role in their functionality. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task with approaches using electron microscopy images being scarce and showing pronounced differences in terms of methodology and results. This work presents a generalized method for the reliable roughness determination of nonplanar specimens such as CS particles from electron microscopic images, the method being robust and reproducible with a high accuracy. It involves a self-written software package (Python) that analyzes the recorded images, extracts corresponding data, and calculates the roughness based on the deviation of the identified contour. Images of single particles are taken by a dual mode scanning electron microscopy (SEM) setup which permits imaging of the same field-of-view of the sample with high resolution and surface sensitive in SE InLens mode as well as in transmission mode (TSEM). Herein, a new type of polystyrene core–iron oxide shell–silica shell particles is developed to serve as a set of lower micrometer-sized study objects with different surface roughness; the analysis of their images by the semiautomatic workflow is demonstrating that the particles’ profile roughness can be quantitatively obtained.
Ellipsometry-based approach for the characterization of mesoporous thin films for H2 technologies
(2021)
Porous thin layer materials are gaining importance in different fields of technology and pose a challenge to the accurate determination of materials properties important for their function. In this work, we demonstrate a hybrid measurement technique using ellipsometry together with other independent methods for validation. Ellipsometry provides information about the porosity of different mesoporous films (PtRuNP/OMC = 45%; IrOx = 46%) as well as about the pore size (pore radius of ca. 5 nm for PtRuNP/OMC). In addition, the electronic structure of a material, such as intraband transitions of a mesoporous IrOx film, can be identified, which can be used to better understand the mechanisms of chemical processes. In addition, we show that ellipsometry can be used as a scalable imaging and visualization method for quality assurance in production. These require accurate and traceable measurements, with reference materials playing an important role that include porosity and other related properties. We show that our novel analytical methods are useful for improving analytical work in this entire field.
A particle roughness analysis tool, based on electron microscopy images (SEM and TEM). The influence of various parameters on the calculated roughness was also investigated: the setting of the proper threshold, accelerating voltage, etc. The samples were gradually tilted to extend imaging information of more than only one projection. Furthermore, the measurement uncertainty of the profile roughness of particles associated to various orientations was estimated.
A case study on the TEM analysis of the size and shape distribution of TiO2 bipyramidal nanoparticles prepared on TEM grids was included in the recently published ISO standard ISO 21363. It was agreed to organize at a later stage a second inter-lab comparison with the nanoparticles distributed to the participants as a liquid suspension. Protocols for uniform nanoparticle deposition on suited supports developed and optimized within the EMPIR nPSize project are also prepared to be distributed. For this, we have chosen the VAMAS platform (www.vamas.org) which offers an excellent international infrastructure of laboratories with high competence in nanoparticle measurement. The VAMAS technical working area dedicated to nanoparticle measurement is TWA 34 ‘Nanoparticle populations’. For this type of nanoparticles, the size and shape distributions are the primary parameters to be reported. Due to the good deposition protocols developed, an automated image analysis is enabled (in contrast to the manual analysis of irregular TiO2 nanoparticles.
In parallel with the TiO2 nanoparticle exercise, two spherical SiO2 nanoparticle samples with bi-modal size distributions (nominal relative number concentrations of 1:1 and 10:1) are prepared for a second VAMAS inter-lab comparison. Here, the nanoparticle concentration is the primary parameter to be measured. For the imaging methods it is targeted to measure the relative nanoparticle concentrations of the two modes. For the absolute nanoparticle concentration to be measured by imaging methods it is necessary to control the volume of the liquid suspension deposited on the substrate and to obtain such a homogeneous nanoparticle deposition on the substrate which allows to count (or extrapolate) all the deposited particles.
Electrochemical methods offer great promise in meeting the demand for user-friendly on-site devices for Monitoring important parameters. The food industry often runs own lab procedures, for example, for mycotoxin analysis, but it is a major goal to simplify analysis, linking analytical methods with smart technologies. Enzyme-linked immunosorbent assays, with photometric detection of 3,3’,5,5’-tetramethylbenzidine (TMB),form a good basis for sensitive detection. To provide a straightforward approach for the miniaturization of the detectionstep, we have studied the pitfalls of the electrochemical TMB detection. By cyclic voltammetry it was found that the TMB electrochemistry is strongly dependent on the pH and the electrode material. A stable electrode response to TMB could be achieved at pH 1 on gold electrodes. We created a smartphonebased, electrochemical, immunomagnetic assay for the detection of ochratoxin A in real samples, providing a solid basis forsensing of further analytes.
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.
The coming years are expected to bring rapid changes in the nanotechnology regulatory landscape, with the establishment of a new framework for nano-risk governance, in silico approaches for characterisation and Risk assessment of nanomaterials, and novel procedures for the early identification and management of nanomaterial risks. In this context, Safe(r)-by-Design (SbD) emerges as a powerful preventive approach to support the development of safe and sustainable (SSbD) nanotechnology-based products and processes throughout the life cycle. This paper summarises the work undertaken to develop a blueprint for the deployment and operation of a permanent European Centre of collaborating laboratories and research organisations supporting safe Innovation in nanotechnologies. The proposed entity, referred to as “the Centre”, will establish a ‘one-stop shop’ for nanosafety-related services and a central contact point for addressing stakeholder questions about nanosafety. Its operation will rely on significant business, legal and market knowledge, as well as other tools developed and acquired through the EU-funded EC4SafeNano project and subsequent ongoing activities. The proposed blueprint adopts a demand-driven service update scheme to allow the necessary vigilance and flexibility to identify opportunities and adjust its activities and services in the rapidly evolving regulatory and nano risk governance landscape.
The proposed Centre will play a major role as a conduit to transfer scientific knowledge between the Research and commercial laboratories or consultants able to provide high quality nanosafety services, and the end-users of such services (e.g., industry, SMEs, consultancy firms, and regulatory authorities). The Centre will harmonise service provision, and bring novel risk assessment and management approaches, e.g. in silico methodologies, closer to practice, notably through SbD/SSbD, and decisively support safe and sustainable innovation of industrial production in the nanotechnology industry according to the European Chemicals Strategy for Sustainability.
As part of the development of a library of accurate and efficient methods for measurement of nanoparticle properties, we develop and optimize a method for the efficient analysis of nanoparticle size distribution from suspensions via microprinting and digital analysis of electron microscopy (SEM and TEM) images, with the ultimate aim of automated quantitative concentration analysis (calculated from drop volume). A series of different nanoparticle suspensions (gold, latex, and SiO2 in varying sizes and concentrations) were printed onto TEM grids in a 4 x 4 array in the concentration range 7x10^8 to 1x10^11 nanoparticles/mL and imaged with SEM. Concentrations and printing conditions (temperature, relative humidity) were varied in order to minimize the coffee-ring effect.
Biofilm formation and microbially influenced corrosion of the iron-reducing microorganism Shewanella putrefaciens were investigated on stainless steel surfaces preconditioned in the absence and presence of flavin molecules by means of XANES (X-ray absorption near-edge structure) analysis and electrochemical methods. The results indicate that biofilm formation was promoted on samples preconditioned in electrolytes containing minute amounts of flavins. On the basis of the XANES results, the corrosion processes are controlled by the iron-rich outer layer of the passive film. Biofilm formation resulted in a cathodic shift of the open circuit potential and a protective effect in terms of pitting corrosion. The samples preconditioned in the absence of flavins have shown delayed pitting and the samples preconditioned in the presence of flavins did not show any pitting in a window of −0.3- to +0.0-V overpotential in the bacterial medium. The results indicate that changes in the passive film chemistry induced by the presence of minute amounts of flavins during a mild anodic polarization can change the susceptibility of stainless steel surfaces to microbially influenced corrosion.
In this breakout session first, an introduction is given on the planning and organisation of an inter-laboratory comparison (ILC) under the pre-standardisation plattform VAMAS within the newly formed technical working area TWA 45 Micro and Nano Plastics in the Environment. An update with the ILCs on micro- and nanoplastic performed so far is also given. In the third part, the requirements for a reference materials are presented. The needs from the different H2020 micro- and nanoplastic projects are collected and compiled in an ILC matrix for joint activities as the next steps.
The main outcomes of the EMPIR project nPSize are presented and the suitability of the new capabilities (e.g. reference materials, measurement procedures, inter-laboratory comparisons) as pertinent contributions to normative projects within CEN/TC 352 Nanotechnologies are discussed. E.g. the first technical report of nPSize on full algorithm sequences for nanoparticle detection and size measurement as developed on both a physical basis (SEM, TSEM, AFM and SAXS) and by machine learning is put at disposal.
This dataset accompanies the following publication, first published in Scientific Reports (www.nature.com/articles/s41598-021-84287-6):
B. Ruehle, J. Krumrey, V.-D. Hodoroaba, Scientific Reports, Workflow towards Automated Segmentation of Agglomerated, Non-Spherical Particles from Electron Microscopy Images using Artificial Neural Networks, DOI: 10.1038/s41598-021-84287-6
It contains electron microscopy micrographs of TiO2 particles, the corresponding segmentation masks, and their classifications into different categories depending on their visibility/occlusion. Please refer to the publication and its supporting information for more details on the acquisition and contents of the dataset, as well as the GitHub repository at https://github.com/BAMresearch/automatic-sem-image-segmentation
Low-cost, high-efficient catalysts for water splitting can be potentially fulfilled by developing earthabundant metal oxides. In this work, surface galvanic formation of Co-OH on K0.45MnO2 (KMO) was achieved via the redox reaction of hydrated Co2+ with crystalline Mn4+. The synthesis method takes place at ambient temperature without using any surfactant agent or organic solvent, providing a clean, green route for the design of highly efficient catalysts. The redox reaction resulted in the formation of ultrathin Co-OH nanoflakes with high electrochemical surface area. X-ray absorption spectroscopy (XAS) and X-ray photoelectron spectroscopy (XPS) analysis confirmed the changes in the oxidation state of the bulk and
surface species on the Co-OH nanoflakes supported on the KMO. The effect of the anions, such as chloride, nitrate and sulfate, on the preparation of the catalyst was evaluated by electrochemical and spectrochemical means. XPS and Time of flight secondary ion mass spectrometry (ToF-SIMS) analysis demonstrated that the layer of CoOxHy deposited on the KMO and its electronic structure strongly depend on the anion of the precursor used during the synthesis of the catalyst. In particular, it was found that Cl- favors the formation of Co-OH, changing the rate-determining step of the reaction, which enhances the catalytic activity towards the OER, producing the most active OER catalyst in alkaline media.
We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from electron microscopy images “from scratch”, without the need for large training data sets of manually annotated images. This is achieved by using unsupervised learning for most of the training dataset generation, making heavy use of generative adversarial networks and especially unpaired image-to-image translation via cycle-consistent adversarial networks. The whole process only requires about 15 minutes of hands-on time by a user and can typically be finished within less than 12 hours when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds, and the segmented images can be used for automatically extracting and calculating various other particle size and shape descriptors.
The minimum information requirements needed to guarantee high-quality surface Analysis data of nanomaterials are described with the aim to provide reliable and traceable Information about size, shape, elemental composition and surface chemistry for risk assessment approaches.
The widespread surface analysis methods electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectrometry (SIMS) were considered. The complete analysis sequence from sample preparation, over measurements, to data analysis and data format for reporting and archiving is outlined. All selected methods are used in surface analysis since many years so that many aspects of the analysis (including (meta)data formats) are already standardized. As a practical analysis use case, two coated TiO2 reference nanoparticulate samples, which are available on the Joint Research Centre (JRC) repository, were selected. The added value of the complementary analysis is highlighted based on the minimum information requirements, which are well-defined for the analysis methods selected. The present paper is supposed to serve primarily as a source of understanding of the high standardization level already available for the high-quality data in surface analysis of nanomaterials as reliable input for the nanosafety community.
We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from scanning electron microscopy images “from scratch”, without the need for large training data sets of manually annotated images. The whole process only requires about 15 minutes of hands-on time by a user and can typically be finished within less than 12 hours when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds. This is achieved by using unsupervised learning for most of the training dataset generation, making heavy use of generative adversarial networks and especially unpaired image-to-image translation via cycle-consistent adversarial networks. We compare the segmentation masks obtained with our suggested workflow qualitatively and quantitatively to state-of-the-art methods using various metrics. Finally, we used the segmentation masks for automatically extracting particle size distributions from the SEM images of TiO2 particles, which were in excellent agreement with particle size distributions obtained manually but could be obtained in a fraction of the time.
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.
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.
Efficient water electrolysis requires highly active electrodes. The activity of corresponding catalytic coatings strongly depends on material properties such as film thickness, crystallinity, electrical conductivity, and chemical surface speciation. Measuring these properties with high accuracy in vacuum-free and nondestructive methods facilitates the elucidation of structure−activity relationships in realistic environments. Here, we report a novel approach to analyze the optical and electrical properties of highly active oxygen evolution reaction (OER) catalysts via spectroscopic ellipsometry (SE). Using a series of differently calcined, mesoporous, templated iridium oxide films as an example, we assess the film thickness, porosity, electrical resistivity, electron concentration, electron mobility, and interband and intraband transition energies by modeling of the optical spectra. Independently performed analyses using scanning electron microscopy, energy-dispersive X-ray spectroscopy, ellipsometric porosimetry, X-ray reflectometry, and absorption spectroscopy indicate a high accuracy of the deduced material properties. A comparison of the derived analytical data from SE, resonant photoemission spectroscopy, X-ray absorption spectroscopy, and X-ray photoelectron spectroscopy with activity measurements of the OER suggests that the intrinsic activity of iridium oxides scales with a shift of the Ir 5d t2g sub-level and an increase of p−d interband transition energies caused by a transition of μ1-OH to μ3-O species.
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.
This presentation is structured in two parts: i) Hybrid metrology by combining SEM with AFM (N. Feltin) and ii) hybridization and corelative microscopy by SEM, STEM-in-SEM, TEM, EDS, Auger Electron Microscopy, TKD and more (D. Hodoroaba).
The first part is focused on the metrological part of the hybrid measurement SEM-AFM, the second part offers some further possibilities of correlative microscopy of nanoparticles based on practical examples.
The progress in activities on Microbeam Analysis under VAMAS/TWA 37 is reviewed. Particularly the liaison with the new projects within the ISO technical committee TC 202 is presented and discussed with respect to the possibility of identifying and launching related VAMAS projects. Need of more promotion for the engagement of more participants from industry and academia at national, European and international level is highlighted. Also, the competition with the other technical working areas (on 'nano' or materials-related) is critically discussed.
Gold nanocubes with a monodispersed size distribution (edge = 55 nm) deposited on a silicon wafer. These tiny uniform cubes were produced as reference nanoparticles within the EMPIR project nPSize - Improved traceability chain of nanoparticle size measurements. SEM image acquired at 10 kV with an in-lens secondary electron detector. Image colored in ImageJ using LUT “Orange hot.” Published in Microscopy and Microanalysis 25(S2) (2019) 2328.
Gold nanocubes with a monodispersed size distribution (edge = 55 nm) deposited on a silicon wafer. These tiny uniform cubes were produced as reference nanoparticles in the frame of the European project nPSize - Improved traceability chain of nanoparticle size measurements. SEM Image acquired at 10 kV with an in-lens secondary electron detector. Image colored in ImageJ using LUT “Orange hot.” Published in Microscopy and Microanalysis 25(S2) (2019) 2328.
Understanding the correlation between the morphological and functional properties of particulate materials is crucial across all fields of physical and natural sciences. This manuscript reports on the investigation of the effect of polyethylene glycol (PEG) employed as a capping Agent in the synthesis of SrTiO3 crystals. The crucial influence of PEG on both the shape and size of the strontium titanate particles is revealed, highlighting the effect on the photocurrents measured under
UV–Vis irradiation.
Identifying nanomaterials (NMs) according to European Union Legislation is challenging, as there is an enormous variety of materials, with different physico-chemical properties. The NanoDefiner Framework and its Decision Support Flow Scheme (DSFS) allow choosing the optimal method to measure the particle size distribution by matching the material properties and the performance of the particular measurement techniques. The DSFS leads to a reliable and economic decision whether a material is an NM or not based on scientific criteria and respecting regulatory requirements. The DSFS starts beyond regulatory requirements by identifying non-NMs by a proxy Approach based on their volume-specific surface area. In a second step, it identifies NMs. The DSFS is tested on real-world materials and is implemented in an e-tool. The DSFS is compared with a decision flowchart of the European Commission’s (EC) Joint Research Centre (JRC), which rigorously follows the explicit criteria of the EC NM definition with the focus on identifying NMs, and non-NMs are identified by exclusion. The two approaches build on the same scientific basis and measurement methods, but start from opposite ends: the JRC Flowchart starts by identifying NMs, whereas the NanoDefiner Framework first identifies non-NMs.
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.
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.
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.