Jonathan V. Sweedler

Meet Jonathan V. Sweedler

Attracting talent… There are many talented undergraduate students interested in the research that analytical chemists perform. What is not to like about chemists that work on real world problems related to health and disease, environmental science and many other important areas? The same is true for graduate students. Analytical chemistry traditionally has not had problems convincing graduate students to study our field. For me, the issue is not a lack of interest but making sure that our field remains attractive throughout their careers. For a professor, I can reframe this: how do we keep the interest of our students and postdoctoral associates? I have noticed a few research groups that have multiple students change fields, and others that keep the students interested in the analytical sciences. The common theme in the latter is that everyone enjoys their research and education. If we, as mentors and leaders, spend our time complaining – about funding, about research, about competitors – then those we mentor have the takeaway message that we don’t like our jobs. Why should they stay involved in analytical chemistry? I am not suggesting that we hide the truth. While we all have aspects of our jobs that are less exciting and fun, I greatly enjoy the profession and I want to communicate my enjoyment to my students. If we stay excited and let students know why analytical chemistry remains a fulfilling field, we will not lack talented scientists.

Most exciting development or trend?? Many of the subfields of analytical measurement science are collecting greater amounts of multiparameter data at a higher throughput than in the past. Certainly in mass spectrometry, instruments have greater resolution, additional degrees of freedom such as ion mobility hyphenated to tandem MS, spatial information on our samples via mass spectrometry imaging and many other information types. Our datafiles are in the gigabyte to terabyte range. The same is true for many other analytical chemistry subfields. How do we efficiently shift through these mountains of data to extract the knowledge we need? A new generation of machine learning, artificial intelligence and other tools are being created. ChatGPT and other large language model AI systems certainly have a place in the analytical sciences, but what that place is has not fully been answered. As a field, we need to determine how best to use these new informatics and AI tools and we need to include training for our students.