Benjamin StadlbauerTU Wien | TU Wien · Institute of Analysis and Scientific Computing
Benjamin Stadlbauer
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9
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Publications (9)
The transport of molecules through nanoscale confined space is relevant in biology, biosensing, and industrial filtration. Microscopically modeling transport through nanopores is required for a fundamental understanding and guiding engineering, but the short duration and low replica number of existing simulation approaches limit statistically relev...
We develop an electrical-impedance tomography (EIT) inverse model problem in an infinite-dimensional setting by introducing a nonlinear elliptic PDE as a new EIT forward model. The new model completes the standard linear model by taking the transport of ionic charge into account, which was ignored in the standard equation. We propose Bayesian inver...
Nanowire field-effect sensors have recently been developed for label-free detection of biomolecules. In this work, we introduce a computational technique based on Bayesian estimation to determine the physical parameters of the sensor and, more importantly, the properties of the analyte molecules. To that end, we first propose a PDE-based model to s...
We present a simulation framework for computing the probability that a single molecule reaches the recognition element in a nanopore sensor. The model consists of the Langevin equation for the diffusive motion of small particles driven by external forces and the Poisson-Nernst-Planck-Stokes equations to compute these forces. The model is applied to...
Massively parallel nanosensor arrays fabricated with low-cost CMOS technology represent powerful platforms for biosensing in the Internet-of-Things (IoT) and Internet-of-Health (IoH) era. They can efficiently acquire “big data” sets of dependable calibrated measurements, representing a solid basis for statistical analysis and parameter estimation....
Nanowire field-effect sensors have recently been developed for label-free detection of biomolecules. In this work, we introduce a computational technique based on Bayesian estimation to determine the physical parameters of the sensor and, more importantly, the properties of the analyte molecules. To that end, we first propose a PDE based model to s...
https://www.siam.org/meetings/uq18/uq18_abstracts.pdf
https://www.siam.org/meetings/uq18/uq18_abstracts.pdf
