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Controlled transport of biological cells in biomedical applications such as sorting, cell sequencing, and assembly of multicellular structures is a technological challenge. Research areas such as drug delivery or tissue engineering can benefit from precise cell location resulting in faster response rates or more complex tissue structures. Using computational methods, different soft magnetic elements with curved edges are designed to form a transport network, enabling transport and all functionalities for the manipulation of microbeads and cells on surfaces by rotational magnetic fields. Building blocks with bimodal functionalities due to segments of differently curved edges permit breakpoints as well as switchable transport via splitting and combining elements. Connecting the elements, networked paths are realized which allow variable movement patterns of magnetic carriers and cells. The direction of magnetic field rotation is altered to direct the beads and cells into different transport lines, and the exact timing is not critical. The networks are used to achieve deterministic movement of microbeads and cells with minimal intervention. Programmed transport over one millimeter with cell transport velocities of several micrometers per s is demonstrated. Based on scalable microchip technology, the networks can be integrated with CMOS‐compatible materials and straightforwardly combined with sensing and diagnostic structures. [ABSTRACT FROM AUTHOR]

Precise movement control is a key feature for the use of superparamagnetic microbeads in medical and biological lab-on-chip applications. We demonstrate the unidirectional transport of magnetic and biological carriers along a chain of oval shaped magnetic thin film elements by in-plane rotating magnetic fields, enabling controllable manipulation and separation schemes. The same fundamental unidirectional movement is realized independent of the sense of magnetic field rotation and orientation of the magnetic pathway. The flowless directional transport of magnetically labeled rat embryonic fibroblasts is presented, validating the applicability of the structures for biological purposes. The lined up ferromagnetic structures are a critical building block for the construction of flexible pathways for biological lab-on-a-chip applications. [ABSTRACT FROM AUTHOR]

Measurements of Young’s moduli are mostly evaluated using strong assumptions, such as sample homogeneity and isotropy. At the same time, descriptions of measurement parameters often lack detailed specifications. Many of these assumptions are, for soft hydrogels especially, not completely valid and the complexity of hydrogel microindentation demands more sophisticated experimental procedures in order to describe their elastic properties more accurately. We created an algorithm that automates indentation data analysis as a basis for the evaluation of large data sets with consideration of the influence of indentation depth on the measured Young’s modulus. The algorithm automatically determines the Young’s modulus in indentation regions where it becomes independent of the indentation depth and furthermore minimizes the error from fitting an elastic model to the data. This approach is independent of the chosen elastic fitting model and indentation device. With this, we are able to evaluate large amounts of indentation curves recorded on many different sample positions and can therefore apply statistical methods to overcome deviations due to sample inhomogeneities. To prove the applicability of our algorithm, we carried out a systematic analysis of how the indentation speed, indenter size and sample thickness affect the determination of Young’s modulus from atomic force microscope (AFM) indentation curves on polyacrylamide (PAAm) samples. We chose the Hertz model as the elastic fitting model for this proof of principle of our algorithm and found that all of these parameters influence the measured Young’s moduli to a certain extent. Hence, it is essential to clearly state the experimental parameters used in microindentation experiments to ensure reproducibility and comparability of data. [ABSTRACT FROM AUTHOR]