Sensor applications based on nano-and micro-technologies

With more than 100 online participants this event attracted a lot of specialists in the field. The presentations covered an amazing field of applications from the research phase as well as applied methods. Session one covered the applications for healthcare and session two had a focus on Nano-particle detection for nano-safety. Although both topics are not strictly separated.
Read briefly what the talks were about and follow the link to the presentations.

We learned from Prof. Yogendra Kumar Mishra, SDU, about new materials for sensing that base on ZnO in the form of tetrapods with fantastic properties allowing not only 3D structures but also the infiltration with other materials. The sponge-like structures allow the trapping of bacteria and have the potential to detect viruses applying antibodies. (Link to presentation)
Dr. Fabian Lofink, Fraunhofer ISIT, gave us insights on piezoelectric materials and their applications to MEMS sensors and a focus on AlScN and its recently discovered ferroelectricity. (Link to Fraunhofer ISIT)
A presentation by Dag Winther Svendsen, Abena, of integrated sensors and real-time data collection to help patients with incontinence problems gave practical insights into the development at Abena. (Link to webpage)
Lars Blohm, Campton Diagnostics, develops in cooperation with the Fraunhofer ISIT a silicon-based biochip platform that is applicable for a wide range of immunological and molecular-biological based tests. ( find the presentation here and the webpage)
Assoc. Prof. Jacek Fiutowski, SDU, introduced several methods that were investigated in the course of the CheckNano project to detect nanoparticles as they pose possible hazards to humans. To be able to detect them in real-life samples a combination of several methods seems best including separation and enrichment of nanoparticles and then a detection. (find the presentation here)
Dr. Coline Bretz, LS Instruments, introduced the possibilities that Static (SLS) and Dynamic (DLS) Light Scattering offers. New developments were explained, including the Modulated 3D Cross-Correlation technology for sample characterization. ( Link to the webpage .)
Dr. Christoph Johann, Wyatt Technology, is a specialist in asymmetrical Flow-FFF for the characterization of nanoparticles in dilute suspensions. Field-Flow Fractionation has the potential to separate nanoparticles in complex media. (find the presentation here and the webpage )

Template assisted particle assembly as an innovative route for fast sensing

In the CheckNano project, we have developed two alternatives and scalable approaches to engineer multi-scale particle arrays, based on capillary force assisted nanoparticle assembly (CAPA) and rapid template-assisted trapping of silver nanospheres with topographically patterned polydimethylsiloxane moulds (PDMS). The latter is a modified version of the template-assisted self-assembly (TASA) approach, where the overall time of the process was reduced to less than 5 min (rTASA) – Fig. 1. Instead of trapping single particles, which would result in a relatively low signal to noise ratio, we are trapping the particles into close-packed arrangements. Close-packed particle poses rich plasmonic resonances, which enable tailoring the optical response, on both the nano- and the macroscale.
In both assembly methods, topographically structures PDMS moulds of nanosized holes are utilized to direct the assembly of monodisperse nanoparticles into structured cluster arrays. While the CAPA ensures the highest precision in particle positioning, leading to full controlled tailoring of the optical properties (compare also here), the rTASA brings speed and user-friendliness, eliminating steps requiring precise meniscus control.

Figure 1 Rapid Template assisted particle assembly (rTASA)


For demonstration, a mixture of 50 µL of concentrated Ag (5 mg/mL, 50 nm diameter) nanoparticle diluted with 200 µL DI water and 200 µL ethanol was deposited on a two-dimensional square lattice of PDMS. Finally, the optical transmission data of both CAPA and rTASA colloidal patterning were explored in the VIS-NIR spectral range. Depending on the array pitch distance and number of particles per trap, the average transmission drop is between 20 – 80%, which makes the detection possible using the most simple spectroscopic solutions.

Nanoparticle detection with imaging techniques

Fig. 1 Identification of single particles.

Fig.2 Once identified, the algorithm tracks each particle’s motion.

At CCM ELECTRONIC ENGINEERING, they develop a method to distinguish nanoparticles from images taken in darkfield microscopy. The aim is to detect the particles’ speed and determine their size according to the Brownian motion model. Ricky Jacobsen describes the procedure for us.  

Particles are prefiltered and, for example, in a microfluidic chip guided to a microscope that takes darkfield images.  The images clearly show particles, but it is not possible to determine the size directly.

At CCM, Ricky develops an algorithm to track the motion of single particles. The first step reduces the background in the images electronically to be able to follow single particles. The second step tracks the particles, considering proximity and similarity between particles in two images (Fig. 1 and Fig. 2).

This particle tracking is particularly challenging because the particles are very similar, and pattern recognition does not work. Ricky needs to determine suitable parameters for selecting the right particles. Once the tracking has a hit, the algorithm can determine the particle speed. Using Brownian Motion theory, one can subsequently determine the particle size. To achieve the required detection accuracy, the algorithm needs to process many images, increasing the necessary amount of stored and handled data.