Highlights from What’s Nu in June 2026

Last month, our “What’s Nu” newsletter explored some of the current hot topics in analytical spectroscopy. From atomic barcodes to lithium-ion battery analysis, the articles and historical insights included in last month’s newsletter showcase how spectroscopy is being used in materials science, battery analysis, and other industries.

In this Q&A overview, we recap last month’s “What’s Nu” newsletter, inviting you to explore these topics more in depth.

How were the foundations of modern atomic spectroscopy established?

In 1859–1860, physicist Gustav Kirchhoff and chemist Robert Bunsen established the foundations of modern atomic spectroscopy by demonstrating that every chemical element emits and absorbs light at specific wavelengths, producing a unique pattern of spectral lines that functions like an atomic “barcode.”^1,2 Using a spectroscope and the clean, high-temperature flame of the Bunsen burner, they showed that these spectral signatures could be used to identify elements with exceptional sensitivity.^1,2 Their work led to the discovery of the elements cesium and rubidium and established spectroscopy as a powerful tool for chemical analysis.^1,2 Kirchhoff also recognized that the dark Fraunhofer lines in the Sun’s spectrum matched the wavelengths emitted by elements on Earth, proving that the same elements exist throughout the universe.^1,2 This breakthrough gave rise to astrophysical spectroscopy, enabling scientists to determine the chemical composition of the Sun and distant stars from Earth. Today, techniques such as atomic emission spectroscopy, inductively coupled plasma–optical emission spectroscopy (ICP-OES), and astronomical spectroscopy all trace their origins to these pioneering discoveries made more than 165 years ago.

What else did June’s issue of What’s Nu cover?

Last month’s newsletter also covered lithium-ion battery production and the importance of maintaining chemical purity. Scaling production from small-batch laboratory reagents to bulk gigafactory feedstocks introduces significant risks of material variability. This variability often results in cell-to-cell differences in energy density, capacitance, and lifetime, which reduces the yield of high-grade "Class A" batteries.³ Although raw material suppliers provide certificates of analysis, these typically only list known analytes; unmonitored impurities can vary between batches and negatively impact performance.³ As technologies advance, purity demands are evolving from the conventional 99.5% metals basis to 99.9%, with some applications expected to require 99.999% purity in the coming years.³

What’s Nu also explored some of the latest advancements in Raman spectroscopy, especially in battery analysis. Why is covering Raman spectroscopy in the context of characterizing battery materials important?

Raman spectroscopy is seen as an important technique in battery analysis because of its sensitivity. Raman spectroscopy provides sensitive structural fingerprints for crystalline and amorphous solids, making it ideal for verifying the phase purity of nickel manganese cobalt oxide, LiNi_x​Mn_y​Co_z​O₂ (​NMC) and lithium iron phosphate, LiFePO₄​ (LFP) cathodes.^3,4 Its most scientifically rich application is operando monitoring, where custom optical cells allow researchers to watch electrode phase transitions and lithium de-intercalation in real-time during electrochemical cycling.⁴ Additionally, Raman is uniquely suited to detect the solid electrolyte interface (SEI) and the presence of hydrated lithium salts, which can lead to the formation of corrosive hydrofluoric acid (HF).⁴

What’s Nu also discussed how artificial intelligence (AI) and machine learning (ML) tie into battery analysis. What is the importance of these tools in current battery diagnostics?

Modern battery analysis relies on AI and ML to interpret massive, complex spectral datasets that are difficult to analyze manually. For example, Gaussian process models trained on over 20,000 electrochemical impedance spectroscopy (EIS) spectra can accurately predict a battery's remaining useful life without full knowledge of its operating history.⁴ Furthermore, unsupervised learning, such as variational autoencoders, can identify specific degradation patterns, such as solid electrolyte interphase (SEI) growth or lithium plating, from impedance data alone.⁴

And finally, What’s Nu explored the applicability of particle-correlated Raman spectroscopy (PCRS) in material science. What’s the benefit of PCRS in this space?

PCRS creates a particle-centric data structure that permanently links high-resolution optical images and morphological descriptors (such as size and shape) with chemical assignments.⁵ This workflow enables the automated, statistically meaningful interrogation of up to 10,000 particles without assuming sample homogeneity.⁵ In energy storage, PCRS allows scientists to differentiate between chemically distinct carbon additives or degradation products that may appear morphologically identical under standard optical inspection.⁵ This ensures that physical characteristics are always tied directly to a confident chemical identity.

References

1. Kirchhoff, G.; Bunsen, R. Chemische Analyse durch Spectralbeobachtungen. J. Prakt. Chem. 1860, 80, 449–477. https://doi.org/10.1002/prac.18600800151
2. Kirchhoff, G.; Bunsen, R. On Chemical Analysis by Spectrum-Observations. Q. J. Chem. Soc. Lond. 1861, 13, 270–289. https://doi.org/10.1039/QJ8611300270
3. Kroukamp, E.; Metzger, M.; Hobold, G. M.; Baumann, S.; Rivera, C. From Bench to Factory: The Role of Chemical Purity and Process Control in Lithium-Ion Battery Innovation. Spectroscopy Online, 2026. https://www.spectroscopyonline.com/view/from-bench-to-factory-the-role-of-chemical-purity-and-process-control-in-lithium-ion-battery-innovation (accessed June 26, 2026).
4. Workman, Jr., J.; Wetzel, W. Lithium-Ion Battery Analysis: Four Years of Spectroscopic Advances in Research, Manufacturing, and Quality Assessment. Spectroscopy Online, 2026. https://www.spectroscopyonline.com/view/lithium-ion-battery-analysis-four-years-of-spectroscopic-advances-in-research-manufacturing-and-quality-assessment (accessed June 26, 2026).
5. Sestak, M. Particle Correlated Raman Spectroscopy (PCRS): A Workflow for Correlating Particle Morphology with Chemical Identification. Spectroscopy Online, 2026. https://www.spectroscopyonline.com/view/particle-correlated-raman-spectroscopy-pcrs-a-workflow-for-correlating-particle-morphology-with-chemical-identification (accessed June 30, 2026).