The Top Four Focus Areas in Analytical Spectroscopy

The Winter Conference on Plasma Spectrochemistry that took place in Tucson, Arizona, from January 11–17^th, 2026. At the conference, attendees and researchers delivered talks that highlighted the latest trends and developments in spectroscopy.¹

Although much of the conversation focused on atomic spectroscopy and plasma-based methods, there were several application areas or hot topics that were repeated throughout the week. Unsurprisingly, artificial intelligence (AI) and its adoption in analytical workflows and data processes was touched upon. Algorithms now automate preprocessing, classification, and quantitation, and can even infer molecular structures directly from spectra, shifting interpretation from expert-driven to data-driven processes.² Some of the other areas that were covered include energy-related topics, microplastics, and single-particle analysis.

In this feature article, we explore these topics more fully, spotlighting the trends experts are paying attention to in 2026 and moving forward.

Topic #1: Artificial Intelligence

Currently, the global economy has been upended by AI. If you were to go on most major news websites, articles about AI resulting in massive layoffs are populating the online space.^3,4 What makes AI more intimidating than other technologies is that it is not impacting just one industry. And scientific research is not immune to it.

Gerardo Gamez, a professor of chemistry and biochemistry and Graduate Advisor at Texas Tech University, at Texas Tech University, said that right now, AI is impacting one area of scientific research significantly, and that is data analysis.

“The more immediate developments have been in data analysis, but I think more and more we're going to start seeing developments in the automation and optimization of the experiments,” Gamez said to Spectroscopy.⁵

Although these digital tools significantly enhance the speed and accuracy of medicolegal investigations, the consensus is that they are only intended to support human experts rather than replace them—at least for now.

It may begin with data analysis, but the automation capabilities will most likely expand, rendering some human tasks unnecessary.

“I think more and more we're going to start seeing developments in the automation and optimization of the experiments,” Gamez said.⁵

Sarah Theiner, a Sales Manager at Nu Instruments and Spectroscopy’s 2026 Emerging Leader in Atomic Spectroscopy award recipient, concurred with the above sentiment, also adding that machine learning (ML) will play a huge role in data analysis automation.

“Now with the upcoming of artificial intelligence and the wealth of data we generate with our methods, especially for example, now with inductively coupled plasma–time of flight–mass spectrometry (ICP-TOF-MS), that's a future trend that we need machine learning approaches and AI-driven approaches that are able to handle these complex data sets we generate,” Theiner said.⁵

Topic #2: ICP-MS and Other Hyphenated Techniques

Another trend that we are seeing is spectroscopy being integrated with other chromatography or mass spectrometry methods, creating more opportunities for hyphenated techniques to take advantage of the strengths both techniques offer.⁶ One of the emerging hyphenated techniques being used regularly is ICP-MS.

David Clases, an associate professor at the University of Graz in Vienna, Austria, is encouraged by this trend.

“I really hope that 2026 is a year where more communities will discover inductively coupled plasma–mass spectrometry (ICP-MS) as a very potential platform which can actually tackle pressing questions of our time,” Clases said.⁸

These hyphenated techniques are being used in industries, such as biomedical research, drug analysis, and food analysis.⁹ In particular, the energy industry has benefitted from the use of hyphenated techniques. Various analytical methods, such as ICP-MS and ICP–optical emission spectroscopy (ICP-OES) have been used, for example, to study the components of lithium-ion batteries (LIBs).¹⁰ As a result, ICP-MS and ICP-OES are actively contributing to the energy industry transitioning toward a more sustainable and technologically advanced power grid.¹⁰

“I think there's going to be a particular focus on energy-related topics. And so, for example, like nuclear science and technology and with specific towards spectroscopy for isotopic analysis,” Clases said.

Topic #3: Microplastics

Microplastic analysis is a hot topic in spectroscopy. Because of increased industrial production, microplastic pollution is becoming a huge problem.^11–13 One of the main considerations is how microplastics can disrupt physiological functions in the human body and negatively impact the health of living organisms.¹³ As a result, researchers have been using spectroscopic techniques, such as Fourier transform infrared (FT-IR) and Raman spectroscopy, to study the composition and distribution of microplastics. What makes these techniques valuable in this space in that they are effective at chemical identification, allow for fast bulk measurement and analysis, and are nondestructive techniques, meaning that the samples do not have to be destroyed in order to be analyzed.¹¹

However, given that microplastics can vary wildly in size, it is often that one technique is not enough. Martin Resano, a Coordinator of the Rapid Analysis Methods with Spectroscopic Techniques (MARTE) group and as part of the Aragon Institute for Engineering Research (I3A) at the University of Zaragoza, explains how this will be the basis of future research in microplastic analysis.

“We consider microplastic as something between 100 nanometers (nm) to 5 mm,” Resano said.^5,14 “This is a huge range. So, there is not only one technique that can cover everything and we have to use different optical techniques and our massive spectrometry techniques and, and particularly when we go to a small size, it is still very challenging to see below 1 micron (µm).”

Topic #4: Single-Particle Analysis

In atomic spectroscopy, researchers have been shifting their focus toward the study of individual particles rather than bulk materials. This specialized approach allows scientists to examine particulate matter and biological tissues in their original state without destroying the sample through chemical dissolution. By maintaining the physical integrity of a particle, analysts can capture essential data that would otherwise be lost if the substance were broken down.

Ken Marcus, a Robert Adger Bowen Professor of Chemistry at Clemson University, explains how this works.

“In atomic spectroscopy, it's all about either doing the analysis of particulate matter of whatever sources or doing spatially resolved analysis in biological systems, the distribution of metals and tissues,” Marcus said.⁶ “For example, we are looking more at the single particle approach where again, if you have a single particle, you want to get as much information from that particle as an intact particle. You don't have the opportunity to do any chemistry of it to say if you have multiple species in a particle that would interfere with each other or if you dissolve the particle, you've lost the essence of the particle.”

Conclusion

Despite all these changes taking place in analytical spectroscopy. There are several recurring themes that have remained stable during this period of uncertainty. For one, the spectroscopy community remains as engaged and collaborative as it ever was. This collaborative atmosphere, Clases said, will lead to some interesting collaborations that span various industries.

“I think that teams will become more and more interdisciplinary, and we will see teams which consist of data scientists, geochemists, analytical chemists, engineers, and so on,” Clases said.⁸

References

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9. Wilson, J. V.; Karthikeyan, L. V.; Parida, S. K. et al. Recent Advances and Developments in Hyphenated Techniques and Their Applications. J. Pharm. Res. Int. 2021, 32, 58–68. DOI: 10.9734/jpri/2020/v32i4331070
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