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Label-free electrical detection of consecutive deoxyribonucleic acid (DNA) hybridization/denaturation by means of an array of individually addressable field-effect-based nanoplate silicon-on-insulator (SOI) capacitors modified with gold nanoparticles (Au-NP) is investigated. The proposed device detects charge changes on Au-NP/DNA hybrids induced by the hybridization or denaturation event. DNA hybridization was performed in a high ionic-strength solution to provide a high hybridization efficiency. On the other hand, to reduce the screening of the DNA charge by counter ions and to achieve a high sensitivity, the sensor signal induced by the hybridization and denaturation events was measured in a low ionic-strength solution. High sensor signals of about 120, 90, and 80 mV were registered after the DNA hybridization, denaturation, and re-hybridization events, respectively. Fluorescence microscopy has been applied as reference method to verify the DNA immobilization, hybridization, and denaturation processes. An electrostatic charge-plane model for potential changes at the gate surface of a nanoplate field-effect sensor induced by the DNA hybridization has been developed taking into account both the Debye length and the distance of the DNA charge from the gate surface.
Three-dimensional (3D) full-field measurements provide a comprehensive and accurate validation of finite element (FE) models. For the validation, the result of the model and measurements are compared based on two respective point-sets and this requires the point-sets to be registered in one coordinate system. Point-set registration is a non-convex optimization problem that has widely been solved by the ordinary iterative closest point algorithm. However, this approach necessitates a good initialization without which it easily returns a local optimum, i.e. an erroneous registration. The globally optimal iterative closest point (Go-ICP) algorithm has overcome this drawback and forms the basis for the presented open-source tool that can be used for the validation of FE models using 3D full-field measurements. The capability of the tool is demonstrated using an application example from the field of biomechanics. Methodological problems that arise in real-world data and the respective implemented solution approaches are discussed.