All courses will be held at the Crowne Plaza Niagara Falls – Fallsview (attached to the Sheraton Fallsview), Niagara Falls, ON.

Designing or Modifying a Laboratory for Trace and Ultra-trace Analyses. Ela Bakowska, Elba Elemental Consulting, PO Box 1050, Corning, NY 14830, ela@bakowska.com
The demand to measure trace and ultra-trace levels of analytes is surging due to emerging applications that require the measurement or control of elemental levels at increasingly lower concentrations. Trace and ultra-trace analyses require the use of instrumentation capable of delivering the desired information; for example, replacing the previously used inductively coupled plasma (ICP) optical emission spectrometer with ICP mass spectrometry (MS) or upgrading an existing ICP-MS instrument to a more sensitive model. However, acquiring the suitable analytical instrumentation is just the beginning of the quest to produce meaningful analytical results. It is critical to evaluate all factors which can impact the quality of analytical results. Different aspects of handling the samples include: the sample itself (the sampling process, its storage, and preparation), laboratory, reagents, analysis, and finally the Analyst. The level of care in sample handling depends upon the concentration levels of the analytes to be determined during the analysis. Specific examples of appropriate reagents and lab supplies will be listed. Cost saving alternatives for lab design and operation will be presented. Sample preparations considerations for different applications (semiconductor, environmental, clinical) will be discussed. Sources of specific elemental contaminations and ways of eliminating or minimizing them will be listed. Guidelines for procurement of a new ICP-MS instrument will be shared with the participants. The course would benefit scientists and managers adapting their current laboratory (renovating or remodeling) or designing a new laboratory to optimize the performance of new or existing ICP-MS instrumentation. Ela Bakowska is Research Associate at Corning RDC and Technical Director at Elba Elemental Consulting and has more than 30 years of experience in ICP-MS.

Single Particle Inductively Coupled Plasma Mass Spectrometry and its Variations. Diane Beauchemin (Department of Chemistry, Queen’s University, Kingston, ON K7L 3N6, Canada, diane.beauchemin@queensu.ca)
This course will go over the principles of the conventional single particle inductively coupled plasma mass spectrometry (spICPMS) approach for the measurement of nanoparticles (NPs) suspended in solution. Its features and limitations will be discussed, along with the effect of settling time on accuracy and the steps involved in data processing to convert the count rate measured by spICPMS into a NP size. Variations of spICPMS will then be described, using flow injection (FI), where a discrete known volume of NPs suspension is injected into a continuous carrier flow, or monosegmented flow analysis (MSFA), where injection is done within an air bubble in a continuous carrier flow. Combining FI or MSFA to spICPMS simplifies the analysis by eliminating the need to measure the sample uptake rate, which is required with the conventional spICPMS method. With either FI-spICPMS or MSFA-spICPMS, the transport efficiency is not required for measurement of NP size, unlike with the conventional spICPMS approach, and is only required for measurement of NPs concentration. Diane Beauchemin is a Full Professor with 40 years of experience in ICPMS, including nearly a decade on spICPMS and its variations.

Validation assessment and ISO/IEC 17025 - an interactive session. Petra Krystek (Deltares, Utrecht, the Netherlands; petra.krystek@deltares.nl)
This course will give an overview about the validation of analytical methods and procedures which is an integral part of any good analytical practice. Method validation is the process used to confirm that the analytical procedure employed for a specific test is suitable for its intended use. Results from method validation can be used to judge the quality, reliability and consistency of analytical results. For making this information as practice relevant as possible, several examples like a procedure for the determination of selected elements in water by ICPMS will be discussed in detail. Special attention will be given to sampling and storage. Other examples from the inorganic analytical field of environmental, food and biological matrices will be covered too. Besides the methodological aspects and the obtained analytical results, the ten most relevant performance characteristics (limit of detection, recovery, repeatability, reproducibility, measuring range, trueness, lack of fit, expanded uncertainty of measurement, robustness and selectivity) are defined, calculated and discussed; also in relation if the analytical method should fulfil of the accreditation standard ISO/IEC 17025. More aspects of the ISO/IEC 17025 will be discussed too. This course will be held as an interactive session. Petra Krystek is a freelance lead assessor at the Dutch Accreditation Council performing ISO/IEC 17025 technical assessments at accredited laboratories in mainly the Netherlands.

Advances in Artificial Intelligence (e.g., via Artificial Neural Networks, Machine Learning, Deep Learning) and Some Applications to ICP-OES and to Microplasma Spectrochemistry, Vassili Karanassios (University of Waterloo, Waterloo, ON N2L 3G1, Canada, vkaranassios@uwaterloo.ca)
Artificial Intelligence (and its variants) are receiving significant attention in the scientific journals and the popular press [1-3] (with expected significant future increases in market size). This short course is divided into two unequal parts. Part 1 deals with an introduction and fundamentals of AI and Part 2 with applications of AI in plasma spectrometry. Vassili Karanassios is Professor of Chemistry and Waterloo Institute for Nanotechnology.

[1] V. Karanassios et al., “Artificial Neural Networks (ANNs) for spectral interference correction using a large-size spectrometer and ANN-based deep learning for a miniature one”, invited open access book chapter, In Tech Publishing, Chapter 12, Pages 227-249, In Tech Publishing, Dec. 20, 2017, DOI: 10.5772/intechopen.71039
[2] Celine Tat and Vassili Karanassios, Artificial intelligence, machine learning, and deep learning in plasma and microplasma spectrochemistry, Next generation Spectroscopic Technologies XV, Proc. SPIE 12516, 1251602 (15 June 2023).
[3] C. Tat and V. Karanassios, “Advances in Artificial intelligence (and its variants, e.g., machine learning, deep learning) as applied to ICP-OES and to microplasma spectrochemistry”, SPI Proc., 2024 (in press).

Keywords: Artificial Intelligence (AI); Deep Learning (DL); Artificial Neural Networks (ANNs); Spectral Interference correction using ANNs; Deep learning Approaches using optical emission data obtained by an ICP and by a microplasma.