Sensors play a key role in how formulators monitor and verify that stability. They provide fast, precise, and often non-destructive methods for assessing the physical and chemical conditions of complex formulations.
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The Importance of Stability Testing
A cosmetic product is a chemically intricate system.
Emulsions, suspensions, gels, and anhydrous formulations all respond differently to thermal stress, light exposure, mechanical handling, and microbial challenge. Traditional stability testing relies on visual inspections, panel-based sensory evaluation, and periodic laboratory analysis, which can be slow and subjective.
In 2025, the global cosmetics safety testing market was valued at over $10 billion and is expected to grow annually by 2.8 % through to 2033, reflecting the industry's focus on product safety.
Sensor tech is a central driver of that growth, providing real-time, quantitative data that traditional approaches cannot match.1
Electrochemical Sensors as Molecular Watchdogs
Among the most analytically powerful tools in cosmetic quality control are electrochemical sensors. These devices apply a small electrical potential to a modified electrode immersed in a sample and measure the resulting current response, which reflects the oxidation or reduction behavior of specific molecules.
For example, gold nanoparticles on graphene oxide can detect methyl parabens, a common preservative, at concentrations as low as 0.8 µM.
Additionally, sensors with mesoporous silica films on reduced graphene oxide have been effective in detecting tertiary butylhydroquinone (TBHQ), an antioxidant used to prevent ingredient rancidity, in both cosmetics and edible oils.2
Beyond preservatives and antioxidants, electrochemical nanosensors have been developed to simultaneously measure the concentrations of parabens, triclosan, and oxybenzone derivatives. These three classes of ingredients must remain within regulatory limits to prevent endocrine-disrupting effects.
The efficiency of these sensors to operate with minimal sample preparation and short analysis times makes them valuable at multiple stages, from raw material intake to finished-product release.3
NIR Spectroscopy: Non-Destructive and Real-Time
Near-infrared (NIR) spectroscopy has cemented its place as a high-throughput, non-destructive analytical tool for cosmetic stability monitoring.
NIR spectrometers analyze molecular overtones and combination bands for unique spectral fingerprints that are sensitive to factors like water content, hydroxyl groups, ingredient concentrations, and physical state transitions.
When combined with chemometric models such as partial least squares (PLS) regression and principal component analysis (PCA), NIR delivers quantitative composition data on complex mixtures that would otherwise require separate assays for each component.4
In a recent IEEE paper, researchers developed a compact NIR spectrometer capable of analyzing 99 raw materials and 30 cosmetic products. The device is well-suited for rapid, on-site identity verification with no sample preparation required.
PCA was found to be the most precise technique, capturing 97 % of the variance in cream formulations, indicating clear differences among products.
This is crucial for stability tracking, as even slight changes in water content or wax structures can lead to early detection of formulation issues before visible changes occur.5
Another study published in Infrared Physics & Technology demonstrated that miniaturized NIR spectrometers could continuously monitor skin surface moisture changes in response to different moisturizing products over time.
It highlights the sensitivity of NIR spectroscopy in assessing the stability of emollients and humectants under real-life conditions.6
Interested in cosmetic science? Read this article to find out more.
Zeta Potential and Particle Size Sensors for Emulsion Integrity
Emulsions are among the most structurally sensitive cosmetic systems, as they can easily destabilize under thermodynamic forces, leading to droplet coalescence and phase separation.
To monitor early signs of instability, zeta potential and particle size distribution sensors are used.
Zeta potential measures the electrokinetic potential around the droplets, where a value above 30 mV suggests strong repulsive forces that prevent coalescence. As this value approaches zero, van der Waals attractive forces begin to dominate and instability progresses.7
An exploratory study of three test emulsions found that analyzing zeta potential and droplet size distribution successfully predicted instabilities that were later confirmed by accelerated stability testing.
This study showed that changes in zeta potential from formulation modifications are more informative than absolute values alone since interfacial conditions evolve over time.
Typically, dynamic light scattering (DLS) particle size analyzers are paired with zeta potential measurements in automated stability screening. This combination helps formulators understand the link between Ostwald ripening and flocculation kinetics as the electrostatic double layer changes, providing mechanistic clues rather than simple pass/fail outcomes.7
Paper-Based Microfluidic Sensors: Accessible and Scalable
Paper-based microfluidic analytical devices (μPADs) are affordable tools for testing cosmetic stability and safety, especially in low-resource settings. These devices use capillary action to move fluids through cellulose-fiber channels without the need for pumps or power.
μPADs can detect substances using colorimetric, fluorimetric, chemiluminescent, or electrochemical methods. The color change can be captured with a smartphone camera, allowing for semi-quantitative analysis at nanomolar concentrations.8
Heavy metal contamination by lead, mercury, arsenic, nickel, and cobalt is a serious concern in cosmetics such as lipsticks and sunscreens, as these metals can accumulate over time.
One article published in the RSC Advances reported μPADs for detecting mercury in skin-lightening products and arsenic in water used in cosmetics, achieving sensitivities of 0.1 to 3 ppb and 0.0005 ppm, respectively.
The integration of AI-powered image analysis with μPAD readouts further improves accuracy by adjusting for lighting variations, making it easier to accurately measure contamination in real-world settings.8
Rheological Sensors and Texture Prediction
Physical stability in cosmetics depends heavily on the formulation's rheological structure. Tools like oscillatory rheometers and texture analyzers measure important viscoelastic parameters that affect both structural integrity and user experience.
A predictive model using machine learning and a vast database showed that parameters from large amplitude oscillatory shear (LAOS) and extensional rheology correlate strongly with sensory attributes such as spreadability, thickness, softness, adhesiveness, and stickiness.
These parameters mimic real-world application conditions, proving more predictive than standard small-strain measurements.
By combining rheological and texture data, formulators can identify potentially unstable ingredient combinations early in the development process, significantly shortening the product development cycle.9
Taken together, these sensor modalities form an interconnected analytical framework. Electrochemical sensors track molecular-level chemical degradation, while NIR spectrometers monitor compositional and structural states non-invasively.
Similarly, zeta potential and particle size instruments reveal colloidal instabilities, paper-based microfluidic platforms enable rapid contaminant screening, and rheological sensors decode the mechanical signatures of texture stability.
Each technology interrogates a different layer of the formulation's stability landscape, and their combined use gives cosmetic scientists a clearer, faster, and more complete picture of whether a product will perform exactly as designed, every time it reaches a consumer.
References and Further Reading
- Cosmetics Testing - Testing, Inspection, And Certification Market Statistics. (2025). Grand View Horizon. https://www.grandviewresearch.com/horizon/statistics/testing-inspection-and-certification-market/healthcare/cosmetics-testing/global
- Gibi, C. et al. (2023). Recent Advances on Electrochemical Sensors for Detection of Contaminants of Emerging Concern (CECs). Molecules, 28(23), 7916. DOI:10.3390/molecules28237916. https://www.mdpi.com/1420-3049/28/23/7916
- Aarthi, K. Ms. (2024). Detection of endocrine-disrupting chemicals in personal care products using a Polyhedral Oligomeric Silsesquioxane-based hybrid material. SASTRA Deemed to be University. https://knowledgeconnect.sastra.edu/theses/12/
- Blanco, M. et al. (2007). Quality control of cosmetic mixtures by NIR spectroscopy. Anal Bioanal Chem 389, 1577–1583. DOI:10.1007/s00216-007-1541-3. https://link.springer.com/article/10.1007/s00216-007-1541-3
- Thomas, J. et al. (2024). Identification of Cosmetics Using Near-Infrared Spectroscopy. 2024 17th International Conference on Development in eSystem Engineering (DeSE), Khorfakkan, United Arab Emirates, 2024, pp. 305-309. DOI:10.1109/DeSE63988.2024.10911935. https://ieeexplore.ieee.org/document/10911935
- Shen, X. et al. (2023). Characterization of skin moisture and evaluation of cosmetic moisturizing properties using miniature near-infrared spectrometer. Infrared Physics & Technology, 132, 104759. DOI:10.1016/j.infrared.2023.104759. https://www.sciencedirect.com/science/article/abs/pii/S1350449523002177
- Gasparelo, A. P. et al. (2014). Zeta Potential and Particle Size to Predict Emulsion Stability. Cosmetics & Toiletries. https://www.cosmeticsandtoiletries.com/testing/method-process/article/21835272/zeta-potential-and-particle-size-to-predict-emulsion-stability
- Pai, S. et al. (2025). Advancements of paper-based microfluidics and organ-on-a-chip models in cosmetics hazards. RSC Advances, 15(13), 10319–10335. DOI:10.1039/d4ra07336c. https://pubs.rsc.org/en/content/articlehtml/2025/ra/d4ra07336c
- Lee, H. et al. (2024). Prediction of sensory textures of cosmetics using large amplitude oscillatory shear and extensional rheology. Applied Rheology. DOI:10.1515/arh-2024-0016. https://www.degruyterbrill.com/document/doi/10.1515/arh-2024-0016/html
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