The development and optimization of cleaning formulations and protocols require detailed insights into the interactions between cleaning agents, target soils, and surfaces under given conditions such as pH and temperature. Traditional analysis methods, which often focus on before-and-after assessments, lack the capability to provide time-resolved mechanistic information on the cleaning process. QSense® QCM-D technology addresses this challenge by offering time-resolved, nanoscale analysis of detergent activity and cleaning dynamics. By integrating QCM-D into the development workflow, formulators and chemists can make informed decisions, ultimately leading to superior cleaning products.
Development and optimization of cleaning formulation and cleaning protocols with respect to a desired outcome in terms of e.g. cleaning efficiency at certain conditions, such as pH and temperature, requires detailed information on the complex interaction between the target soil, the cleaning component, and the surface on which the soil is residing at those specific condition. To move forward with the design work, the formulator or chemist need to understand, for example
To obtain the necessary information to guide design and development work, a range of analytical methods must be employed. These methods typically include before-and-after techniques, such as optical methods for characterizing the soiled surface of interest, combined with formulation-specific characterization like wetting efficiency tests. Conducting tests with multiple methods takes time, and while the combined information from all analyses can illuminate product or protocol performance, the information guiding design and development remains limited. For example, a before-and-after analysis approach lacks a temporal aspect and does not provide insights into the dynamics of the cleaning process, Fig. 1. Additionally, there is no detailed mechanistic information on how the cleaning agent, or its components interact with the soil, nor on how the cleaning process evolves, such as in terms of soil wetting and dissolution. Furthermore, the methods used often have relatively low sensitivity, meaning processes like surface etching or redeposition may not be detected until their impact is significant.
The lack of analytical methods that provide detailed mechanistic information on the entire cleaning process from start to finish risks wasting unnecessary amounts of time and may obscure the path forward toward achieving the targeted product performance and desired outcomes, as the information on which design and development decisions are based is limited.
Figure 1. Schematic illustration of information provided by before-and-after methods where information regarding cleaning product-soil interaction, soil removal dynamics such as wetting and soil removal rate, are missing.
Quartz Crystal Microbalance with Dissipation monitoring, QCM-D, is a surface sensitive technology which has been used to analyze molecule - surface interaction for more than two decades. The method has for example been used to study the surface interaction dynamics of surfactants, polymers, and nanoparticles, as well as complex mixtures of different components, in a range of cleaning applications within homecare, CMP, food production, and pharma. The QCM-D method provides time-resolved information on mass, thickness, and viscoelastic properties of layers at the sensor surface, and allows for analysis of molecular adsorption, desorption, and structural rearrangement of surface adhering layers. Thanks to its high sensitivity and flexibility of substrate materials, solvent conditions and wide temperature range, QCM-D technology offers a fast and low-sample approach to study molecule-surface interactions at the nanoscale and get detailed information of component-soil or component-surface interaction as well as a mechanistic understanding of how the interaction evolves overtime, revealing for example wetting, soil removal, surface etching, and soil redeposition. The detailed insight into the surface interaction phenomena and cleaning process dynamics, Fig. 2, can provide key information that helps guide the product or protocol design and development in an efficient way, and help point out the path towards desired product or protocol performance.
Figure 2. A) Detailed mechanistic view of fat soil removal using three different full formulations A, B and C, using pure water as a reference. The QCM-D data is presented as soil thickness as a function of time. The measurement starts with the soil in pure water whereafter the cleaning products are introduced, and the measurement ends with a rinse step. The graph shows distinctly different behaviors between the three products where product A immediately reduces the soil thickness, product B initially swells the soil about 10% before it starts removing soil, and product C swells the soil significantly. In the rinse step, both A and B remove all soil that remains at the surface, and product C reduces the swelled soil thickness to ~90%.
Information and parameters provided by QCM-D
The time-resolved and nanoscale mechanistic information provided by QCM-D analysis offers insight into molecular interaction and cleaning process dynamics in terms rates and amount. More specifically, each measurement trace provides the following parameters, Fig. 3.
As discussed above, QSense QCM-D technology has offered insight into molecular interactions at surfaces and interfaces for more than two decades, providing detailed insights into processes taking place at the solid-liquid interface in a range of different application fields. In the context of cleaning performance analysis, development and optimization, there are several aspects that will impact the outcome such as single component soil interaction dynamics, exposure time, impact of conditions such as temperature, pH, and water hardness. There could also be other aspects such as surface etching and component deposition, i.e. residual remaining at the surface after the cleaning step, to consider. The QCM-D method offers an efficient way to assess all these different aspects to get detailed information on both cleaning product and single component interaction dynamics which can serve as a foundation for solid decision making on the way forward towards a targeted cleaning product performance. The approach can both help shorten the product development time and reduce the risk of going astray due to lack of detailed mechanistic insight into the product performance.
QCM-D analysis can provide an understanding of
To demonstrate the capabilities of the QCM-D technology, we performed three case studies addressing different aspects relevant for cleaning performance and efficiency analysis, namely assessment of A) cleaning process dynamics, B) etching process dynamics, and C) residual remaining at the surface after process exposure. The experiments selected in the respective scenario are the following
Download technical whitepaper to read the three case studies.
Yousra is an Application Scientist at Biolin Scientific. She has a strong interdisciplinary research background and deep technical expertise in laboratory technologies, with a particular focus on surface science instruments. Holding a Ph.D. in Biology and Biochemistry, Yousra has extensive experience in diverse fields, including biomaterials, microbiology, and surface chemistry.
%201.png?width=200&name=yousra%20runt%20(1)%201.png)