Analytical and Characterisation Excellence in nanomaterial risk assessment: A tiered approach

Project Information

ACEnano

Grant agreement ID: 720952

DOI

10.3030/720952

Project closed

EC signature date 22 November 2016

Start date 1 January 2017

End date 30 June 2021

Funded under

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies – Nanotechnologies

Total cost

€ 10 761 803,75

EU contribution

€ 7 000 000,00

Coordinated by

THE UNIVERSITY OF BIRMINGHAM
United Kingdom

Periodic Reporting for period 3 - ACEnano (Analytical and Characterisation Excellence in nanomaterial risk assessment: A tiered approach)

Reporting period: 2019-07-01 to 2021-06-30

Summary of the context and overall objectives of the project

The H2020 ACEnano project worked towards introducing confidence, adaptability and clarity into nanomaterial (NM) risk assessment by developing a widely implementable and robust tiered approach to NM physicochemical characterisation that simplifies and facilitates contextual (hazard or exposure) description and its transcription into a reliable NM grouping framework. This was implemented by the creation of a tiered approach to cost-efficient NM analysis that facilitates decision-making of analytical techniques and protocols. This approach produced the ACEnano toolbox, a virtual knowledge infrastructure and decision tool, which provides access to an extensive library of methods for sample preparation and measurement of all significant physicochemical variables relevant to NM characterisation.

Overall project objectives were: (1) to innovate in a selected set of analytical techniques, instrumentation and equipment for the testing of NM properties/descriptors;
(2) to optimise the existing techniques/instrumentation, miniaturise and simplify where possible and support their use by SMEs through training and documentation;
(3) to provide a one-stop solution to nanomaterial characterization: i.e. the ACEnano toolbox; (4) to benchmark key components of the ACEnano toolbox and set criteria for future benchmarking of further components; (5) to link the methodological advancements of ACEnano to a mechanistic ontology framework;
(6) to embed all the above outputs into quality assurance and risk assessment framework; and finally (7) to ensure dissemination and exploitation of ACEnano project and its innovations and outcomes.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Throughout the project, the ACEnano consortium delivered technological innovations, optimisations and benchmarking, as appropriate, and addressed many other peripheral challenges, such as moving forward with technology implementation, when appropriate via interlaboratory testing and standardization, dissemination and training. A very exciting aspect of ACEnano was the strong collaborative element among technologies developed, interlaboratory comparisons (ILCs) performed, and data and training solutions delivered, including multi-industry partner solutions.

Many ACEnano innovations advanced the state-of-the-art in NM characterization and these have been described in detail in the project deliverable reports. The work in ACEnano also identified 6 new exploitable technologies:
• Single particle-ICP-TOF-MS hyphenated to AF4: TOF pilot workflows to run single particles and cells analysis: this is a software tool for nanoparticle detection in liquid samples and biological tissues, using laser ablation technology;
• The ACENano Knowledge Warehouse and Data Management System (software): a software tool integrating quality assured NM characterisation into a risk assessment framework based on grouping, read-across and safe-by-design strategies;
• Automated sample delivery systems and hyphenated instruments for NM characterisation: Robot-based station for automated preparation of NM suspension: this is a prototype robotic station that enables reproducible automated preparation of NM suspensions for characterisation (Figure 1);
• Analytics and Instruments for Air-Liquid-Interface Systems (ALI): a prototype miniaturised system of the air-liquid interface cell culture model (Figure 2);
• Automated on-chip assays for measuring the reactivity of NMs: this is a prototype of an automated on-a-chip assay (a microfluidic well plate) for the detection of reactivity of NMs (Figure 3);
• A one-stop solution to NM characterisation (ACEnano toolbox): a decision support tool, providing advice on the selection of NM characterisation methods for different scenarios (REACH, risk assessment, labelling etc) and directing users to relevant information resources in the Knowledge Infrastructure.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The ACEnano technologies which delivered advancement of the state of the art were:

NEW HARDWARE AND/OR SOFTWARE DEVELOPED:
- Implementation of different sample introduction systems (syringe pump, autosampler) into PNV software to gain more stability during measurements and higher throughput in ICP-MS studies.
- TofWerk Tofpilot module for single-particle and single-cell analysis developed and now integrated into their instruments – already shipped to first customers.
- Newly designed Vitrocell 12/1 analytical modules (miniaturised ALI system) integrated into the prototype of miniaturised automated exposure station.
- New liquid cell for TERS measurements in liquid developed by Horiba.
- An ultrasound cross-coupling device was developed and successfully integrated into a universal sample introduction system by CSEM.
- Development of a mixing and readout system that encompasses the microfluidic well plate, initiates the mixing and incubation process and automatically measures the absorbance of the 24 reactivity assays.
- Use of hydrogen in helium as the collision cell technology gas for ICP-MS led to a decrease of the limit of detection (LOD) e.g. in the case of iron (Fe, isotope 56), at least an order of magnitude.
- Reduction of false positives/negatives in spICP-MS, e.g. distinguishing accurately dissolved ions from particle events, achieved by developing the nanoCount algorithm further to utilise the shape of particle peaks for the distinction of dissolved ion/particle events.

HYPHENATION OF METHODS:
- FFF-SP-TOF-MS evaluated using the Postnova FFF system.
- Offline coupling of FFF and NTA results show that sample concentration, nature of the solvent and NTA flow rate need to be optimized in order to obtain analytically meaningful results. A preliminary application note has already been drafted.

NEW ASSAYS DEVELOPED:
- A microfluidic well plate allowing to perform 24 assays fully automatically and in parallel assessing NM dissolution and NM reactivity.
- Preliminary TERS measurements of lipid bilayers in liquid using side illumination. This work shows that the NMs are readily absorbed by cell membranes.
- Hydrophobic interaction chromatography using CSEM-owned technology (waveguide interrogated optical sensor) measuring the adhesion of NMs directly on the surface of a chip. Adhesion is promoted by specific hydrophilic and hydrophobic coatings on the chip.
- LA-sp-ICP-MS method successfully applied to soil samples containing Au NPs with various concentrations and sizes. Particle size distributions of Au NP in the soil samples were similar to the particle size distribution of the reference Au NP suspension.


RESULTS OF THE PROJECT AND POTENTIAL IMPACTS
The ACEnano tiered characterization concept and ACEnano Methods Toolbox brought an enhanced efficiency in methods selection, reducing unnecessary costs and efforts, whilst simultaneously increasing the confidence of industry and regulators in the quality, reliability and relevance of the data produced utilising the ACEnano toolbox, either as a virtual guidance tool or through implementation of its analytical recommendations in a laboratory environment. Ultimately the work provided openly accessible virtual guides, tools and methods, thus enhancing public confidence to nanotechnology.

The structure and key elements of the ACEnano virtual analytical toolbox

Figure 2 - Front view of the prototype automated exposure station

ACEnano Logo

Figure 3 -microfluidic lab-on-chip demonstrator instrument

Figure 1 - Robot-based sample preparation station