Sinead Currivan-Macdonald

Meet Sinead Currivan-Macdonald

Analytical science is a truly exciting multidisciplinary, evolving science. It connects so many fields like forensics and archaeology, to chemistry and proteomics. And yet, it has a bad reputation from users and students. Analytical science is a true culmination of data analytics (mathematical modelling and statistics), engineering (instrumentation), physics (light, fluid dynamics, etc.), as well as chemical/biological (host-site interactions). This makes it a daunting field for novices and purists to approach, but is a haven for those who crave complexity, and creativity in their work. How do we, as the analytical science community, ensure that the field can rise to prominence as a keystone of all good science? It requires a synergistic combination of grass-roots infrastructure and industrial investment. This should be through industrial-sponsored student spaces, sponsored laboratory infrastructure, and the integration of new technologies, such as augmented reality (AR), to bridge the gap between education and experience. As Confucius said: “I hear and I forget. I see and I remember. I do and I understand.”

Analytical science topics are covered by many fields, in lectures and in the lab. Oftentimes, the infrastructure (equipment/instrumentation) to support learning is outdated, obsolete, and with technical failures during laboratory sessions (their primary hands-on experience) it often leads to frustration and a disheartening experience. Students, confronted by the complexity of the topic, reduce their engagement, not realising that most fields in science are heavily reliant on analytical science. The burden of donated equipment leaves aging, tired systems in need of repair, and technical support on the doorsteps of financially crippled institutions. The evolution of analytical technology is rapid, which academic institutions cannot purchase, install, or even maintain due to limited resources. This makes modern/attractive techniques, such as MS-technologies, harder to cover practically. However, here lies an opportunity for local industry to invest, as they will be reliant on well-trained graduates, with relevant skills, to work within their facilities for years to come.

An interactive-hub sponsored by industrial-partners would offer a glimpse at professional/accredited labs. This hub may be fixed or mobile, with AR facilities, with a furnished suite of high-tech analytical instruments, commonly used in industry labs. AR has already been trialled as a method for training staff in the pharmaceutical industry and is used in the semiconductor industry.

When running analyses with AR, the user can see instructions via smart glasses and their actions can be observed via an integrated camera, remotely, offering students unprecedented access to industrial spaces, without the bureaucracy/safety concerns. Alternatively, a centralized hub or mobile unit could be used by several institutions to improve engagement. Merck has launched a physical hub (“curiosity cube”) this year to do this, for STEM and AI. However, a specific analytical hub is needed, where students can interact with instrumentation, run analyses, and with expert guidance, analyze example data – emphasizing the importance of their role within the community, and the field. Combining these two approaches could be pivotal in reshaping the perception of analytical science at the grass-roots level, allowing it to flourish further.