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Is part of the Bibliography
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The coupling of charged molecules, nanoparticles, and more generally, inorganic/organic nanohybrids with semiconductor field-effect devices based on an electrolyte–insulator–semiconductor (EIS) system represents a very promising strategy for the active tuning of electrochemical properties of these devices and, thus, opening new opportunities for label-free biosensing by the intrinsic charge of molecules. The simplest field-effect sensor is a capacitive EIS sensor, which represents a (bio-)chemically sensitive capacitor. In this chapter, selected examples of recent developments in the field of label-free biosensing using nanomaterial-modified capacitive EIS sensors are summarized. In the first part, we present applications of EIS sensors modified with negatively charged gold nanoparticles for the label-free electrostatic detection of positively charged small proteins and macromolecules, for monitoring the layer-by-layer formation of oppositely charged polyelectrolyte (PE) multilayers as well as for the development of an enzyme-based biomolecular logic gate. In the second part, examples of a label-free detection by means of EIS sensors modified with a positively charged weak PE layer are demonstrated. These include electrical detection of on-chip and in-solution hybridized DNA (deoxyribonucleic acid) as well as an EIS sensor with pH-responsive weak PE/enzyme multilayers for enhanced field-effect biosensing.
Enzyme-based logic gates and circuits - analytical applications and interfacing with electronics
(2017)
The paper is an overview of enzyme-based logic gates and their short circuits, with specific examples of Boolean AND and OR gates, and concatenated logic gates composed of multi-step enzyme-biocatalyzed reactions. Noise formation in the biocatalytic reactions and its decrease by adding a “filter” system, converting convex to sigmoid response function, are discussed. Despite the fact that the enzyme-based logic gates are primarily considered as components of future biomolecular computing systems, their biosensing applications are promising for immediate practical use. Analytical use of the enzyme logic systems in biomedical and forensic applications is discussed and exemplified with the logic analysis of biomarkers of various injuries, e.g., liver injury, and with analysis of biomarkers characteristic of different ethnicity found in blood samples on a crime scene. Interfacing of enzyme logic systems with modified electrodes and semiconductor devices is discussed, giving particular attention to the interfaces functionalized with signal-responsive materials. Future perspectives in the design of the biomolecular logic systems and their applications are discussed in the conclusion.
Detection of Adrenaline Based on Bioelectrocatalytical System to Support Tumor Diagnostic Technology
(2017)
A graphene-functionalized carbon fiber electrode was modified with adsorbed polyethylenimine to introduce amino functionalities and then with trigonelline and 4-carboxyphenylboronic acid covalently bound to the amino groups. The trigonelline species containing quarterized pyridine groups produced positive charge on the electrode surface regardless of the pH value, while the phenylboronic acid species were neutral below pH 8 and negatively charged above pH 9 (note that their pKa=8.4). The total charge on the monolayer-modified electrode was positive at the neutral pH and negative at pH > 9. Note that 4-carboxyphenylboronic acid was attached to the electrode surface in molar excess to trigonelline, thus allowing the negative charge to dominate on the electrode surface at basic pH. Negatively charged fluorescent dye-labeled insulin (insulin-FITC) was loaded on the modified electrode surface at pH 7.0 due to its electrostatic attraction to the positively charged interface. The local pH in close vicinity to the electrode surface was increased to ca. 9–10 due to consumption of H+ ions upon electrochemical reduction of oxygen proceeding at the potential of −1.0 V (vs. Ag/AgCl) applied on the modified electrode. The process resulted in recharging of the electrode surface to the negative value due to the formation of the negative charge on the phenylboronic acid groups, thus resulting in the electrostatic repulsion of insulin-FITC and stimulating its release from the electrode surface. The insulin release was characterized by fluorescence spectroscopy (using the FITC-labeled insulin), by electrochemical measurements on an iridium oxide, IrOx, electrode and by mass spectrometry. The graphene-functionalized carbon fiber electrode demonstrated significant advantages in the signal-stimulated insulin release comparing with the carbon fiber electrode without the graphene species.
In this study, polyelectrolyte-modified field-effect-based electrolyte-insulator-semiconductor (EIS) devices have been used for the label-free electrical detection of double-stranded deoxyribonucleic acid (dsDNA)molecules. The sensor-chip functionalization with a positively charged polyelectrolyte layer provides the possibility of direct adsorptive binding of negatively charged target DNA oligonucleotides onto theSiO2-chip surface.EIS sensors can be utilized as a tool to detect surface-charge changes; the electrostatic adsorption of oligonucleotides onto the polyelectrolyte layer leads to a measureable surface-potential change. Signals of 39mV have been recorded after the incubation with the oligonucleotide solution. Besides the electrochemical experiments, the successful adsorption of dsDNA onto the polyelectrolyte layer has been verified via fluorescence microscopy. The presented results demonstrate that the signal recording of EISchips, which are modified with a polyelectrolyte layer, canbe used as a favorable approach for a fast, cheap and simple detection method for dsDNA.
Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure.