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Multivariate data analysis and machine-learning classification become popular tools to extract features without physical models for complex environments recognition. For electronic noses, time sampling over multiple sensors must be a fair…
The motion of a mechanical resonator is intrinsically decomposed over a collection of normal modes of vibration. When the resonator is used as a sensor, its multimode nature often deteriorates or limits its performance and sensitivity. This…
Flutter flight test involves the evaluation of the airframes aeroelastic stability by applying artificial excitation on the aircraft lifting surfaces. The subsequent responses are captured and analyzed to extract the frequencies and damping…
Nanomechanical resonators offer important benefits for the sensing of physical stimuli such as the mass of an added molecule. To map out the local shape properties of the physical stimuli, such as the distribution of the mass density of a…
Olfaction sensing in autonomous robotics faces challenges in dynamic operations, energy efficiency, and edge processing. It necessitates a machine learning algorithm capable of managing real-world odor interference, ensuring resource…
In this work we provide an in-depth analysis of the sensing mechanisms of $NO_{2}$ by lead-sulfide nanocrystals (PbS-NCs). A detailed model for the sorption mechanism is proposed, and the correlation is established between experimental…
We describe a system for interrogating the acoustic properties of sub-nanoliter liquid samples within an open microfluidics platform. Sessile droplets were deposited onto integrated optomechanical sensors, which possess…
This paper introduces a novel model-free approach to synthesize virtual sensors for the estimation of dynamical quantities that are unmeasurable at runtime but are available for design purposes on test benches. After collecting a dataset of…
A combinative approach for chemical analysis makes it possible to distinguish a mixture of a large number of compounds from other mixtures in a single step. This work demonstrates a combinative analysis approach by using surface…
We demonstrate multimode optomechanical sensing of individual nanoparticles with radius of a hundred of nanometers. A semiconductor optomechanical disk resonator is optically driven and detected under ambient conditions, as nebulized…
We present a high-sensitivity measurement technique for mechanical nanoresonators. Due to intrinsic nonlinear effects, different flexural modes of a nanobeam can be coupled while driving each of them on resonance. This mode-coupling scheme…
The problem of locating an odor source in turbulent flows is central to key applications such as environmental monitoring and disaster response. We address this challenge by designing an algorithm based on Bayesian inference, which uses…
We propose a four-component molecular model of bitumen. The model includes realistic chemical constituents and introduces a coarse-graining level that suppresses the highest frequency modes. Molecular dynamics simulations of the model are…
Multi-principal element alloys open large composition spaces for alloy development. The large compositional space necessitates rapid synthesis and characterization to identify promising materials, as well as predictive strategies for alloy…
The characterization of multicomponent signals with a particular emphasis on musical and communication signals is one of the problems studied in the dissertation. In order to provide an efficient analysis of the multicomponent signals, the…
This paper introduces a perspective approach for simulating a memristive sensor tailored for low power biological analyte detection. The necessity for such innovation stems from the increasing demand for efficient biosensing technologies…
In this review article, we focus on emerging nanocantilever based biological sensors and discuss the response of nanocantilevers towards bio-molecules capture. The article guides the reader through various modes of operation (e.g., static…
Volatile organic compounds (VOCs) represent a novel but underexplored modality for emotion recognition. This paper presents a systematic evidence synthesis and exploratory investigation of VOC-based affective computing using low-cost…
In industrial systems, certain process variables that need to be monitored for detecting faults are often difficult or impossible to measure. Soft sensor techniques are widely used to estimate such difficult-to-measure process variables…
Modeling dynamical systems plays a crucial role in capturing and understanding complex physical phenomena. When physical models are not sufficiently accurate or hardly describable by analytical formulas, one can use generic function…