Design Of Efficient Sensors Research Articles

다중 혈중 성분 농도 예측을 위한 비침습형 센서 기반 멀티 아웃풋 네트워크

In healthcare industries, non-invasive sensor technology has played an important role in gathering biometric information without blood sampling for each patient. Existing studies have attempted to predict blood component levels based on non-invasive sensor coupled with machine learning models. However, they focused on constructing a single output model that predicts only one blood component level. In this study, we propose a multi-output predictive model that can predict the multiple blood components levels simultaneously based on non-invasive impedance sensor data. Results show that our method improves predictive performance compared to the single output models. Furthermore, we use Shapley additive explanation to identify important sensor variables that achieve efficient sensor design reducing the cost of data collection. To the best of our knowledge, this study is the first attempt to use non-invasive impedance sensor data to predict multiple blood components levels.

UV-activated gold decorated rGO/ZnO heterostructured nanocomposite sensor for efficient room temperature H2 detection

Extended surface area in addition to higher conductivity and abundant free electrons/holes generation has been key players for any efficient sensor design. Therefore, contribution from graphene as highest conductive material and plasmonics from gold (Au) were expected to facilitate efficient zinc oxides (ZnO) nanostructures-based Hydrogen gas detection. We have presented herewith a facile route to synthesize ZnO nanosheets from elongated nanoblocks of the same in presence of reduced graphene oxide (rGO) under laser ablation environment. Au decorated such rGO/ZnO heterostructured nanosheets were found to be highly selective and sensitive to H2 detection under ultraviolet radiation at room temperature (RT). A detailed investigation was carried out to confirm topographic evolution through high resolution scanning electron microscopy. Optical band gap and infrared absorption of as-synthesized specimens at different stages were investigated further in addition to structural confirmation using X-ray diffraction analysis. Raman spectroscopy, a complementary technique was utilized to investigate the specimens at different stages too. SEM-aided elemental analysis inferred that gold nanoparticles were homogeneously distributed over the rGO/ZnO heterostructure. A custom-made setup designed at our disposal were utilized to understand the selectivity and sensitivity of as-fabricated heterostructure for H2 detection. The H2 gas sensing properties of Au nanoparticles decorated rGO/ZnO heterostructure were investigated at RT under UV irradiation and compared with those observed using pristine ZnO nanostructure at high working temperature. A plausible mechanism was illustrated with reference to well-known ‘spell-over’ scenario usually observed in plasmonic sensors.

Impurity invisibility in graphene: Symmetry guidelines for the design of efficient sensors

Renowned for its sensitivity to detect the presence of numerous substances, graphene is an excellent chemical sensor. Unfortunately, which general features a dopant must have in order to enter the list of substances detectable by graphene are not exactly known. Here we demonstrate with a simple model calculation implemented in three different ways that one of such features is the symmetry properties of the impurity binding to graphene. In particular, we show that electronic scattering is suppressed when dopants are bound symmetrically to both graphene sub-lattices, giving rise to impurity invisibility. In contrast, dopants that affect the two sublattices asymmetrically are more strongly scattered and therefore the most likely candidates to being chemically sensed by graphene. Furthermore, we demonstrate that impurity invisibility is lifted with the introduction of a symmetry-breaking perturbation such as uniaxial strain. In this case, graphene with sublattice-symmetric dopants will function as efficient strain sensors. We argue that by classifying dopants through their bonding symmetry leads to a more efficient way of identifying suitable components for graphene-based sensors.

Ultrafast FRET at fiber tips: Potential applications in sensitive remote sensing of molecular interaction

Förster resonance energy transfer (FRET) strategy is well adopted in fiber-optics for efficient sensor design. However, resonance type energy transfer from one molecule (donor) to other (acceptor) should meet few key properties including donor to acceptor energy migration in non-radiative way, which is hard to conclude from simply emission quenching of the donor, rather needs careful investigation of excited state lifetime of the donor molecule. In the present study, we have shown that the evanescent field of an optical fiber can be coupled to covalently attached donor (dansyl) molecules at the fiber tip. By using picosecond resolved time correlated single photon counting (TCSPC) we have demonstrated that dansyl at the fiber tip transfers energy to a well known DNA-intercalating dye ethidium upon surface adsorption of DNA at the fiber tip. Our ultrafast detection scheme selectively distinguishes the probe (dansyl) emission from the intrinsic emission of the fiber. The validation of the energy transfer mechanism to be of resonance type (FRET), allows us to estimate the distance between the probe dansyl and the surface adsorbed DNA. We have also used the setup for the remote sensing of the dielectric constant (polarity) of an environment as the excited state lifetime of the probe dansyl heavily depends on the polarity of the immediate host environment. FRET signal from a used fiber tip immediately after adsorption of DNA reveals stepwise surface desorption of the biomolecule in saline solution. The reusability of the fiber tip for sensing has also been demonstrated.

Label-free electrochemiluminescent enantioselective sensor for distinguishing between chiral metallosupramolecular complexes.

Chiral molecular recognition of DNA is important for rational drug design and for developing structural probes of DNA conformation. Developing a convenient and inexpensive assay for sensitive and selective identification of DNA-specific binding compounds with rapid, easy manipulation is in ever-increasing demand. Here, we present a "turn-on" and label-free electrochemiluminescent (ECL) biosensor for distinguishing chiral metallosupramolecular complexes based on DNA three-way junction formation selectively induced by the analyte. The fabricated ECL sensor shows excellent performance in the chiral discrimination of two enantiomers with an enantioselective recognition ratio of up to 4.4. More importantly, as a "turn-on" detection system, the ECL chiral sensor does not suffer from false positives and limited signal range of "signal-off" systems. Therefore, this concept may provide a new insight into the design of efficient sensors for distinguishing chiral molecules and for investigating the interactions between DNA and small molecules.

Adsorption of 2,3,7,8-tetrochlorodibenzo-p-dioxins on intrinsic, defected, and Ti (N, Ag) doped graphene: a DFT study

As one of the most hazardous substances in the world, dioxins have received continuous interest in chemistry, materials, and environmental sciences. The rapid detection and capture of carcinogenic 2,3,7,8-tetrochlorodibenzo-p-dioxin (TCDD) are particularly challenging in the fields of materials and environmental sciences. In this study, density functional theory (DFT) method was applied to systematically investigate the interactions between TCDD and different types of graphene samples. The results reveal that the initial configuration of TCDD affects the interactions to a certain extent. As TCDD molecule is parallel to the graphene sheets, the interactions are the largest for all three types of graphene samples (intrinsic, defected and doped). In addition, the "TCDD" capture ability of graphene can be greatly improved by Ti doping. Our study facilitates the rational design of efficient sensors for a variety of applications in environmental science and engineering.

Double integrating sphere measurements for estimating optical properties of pig subcutaneous adipose tissue

Abstract Optical properties of pig subcutaneous adipose tissue were estimated using double integrating sphere (DIS) measurements in combination with an inverse adding doubling (IAD) light propagation model. Total reflectance, total transmittance and unscattered transmittance were measured for the wavelength range 1150–2250 nm with 10 nm resolution. These measurements were used to estimate the bulk optical properties (absorption coefficient, scattering coefficient and anisotropy factor) of 10 Iberian pig adipose tissue samples. The estimated absorption coefficient spectra were dominated by water and lipid absorption bands, the main chemical components of the adipose tissue. These values showed a suitable match with the theoretical values calculated based on the average composition of the tissue. The obtained scattering coefficient spectra showed a smooth decrease with increasing wavelength, which is typical for biological tissues. The anisotropy factor spectra of adipose tissue were obtained, which describe the angular scattering pattern, instead of using a fixed value for the estimation procedure. The optical characterization described in this paper is crucial for a better understanding of the impact of pure absorption and scattering on the NIR spectra collected by a single measurement in the laboratory, process line at the slaughterhouse or on the farm. Moreover, the estimated data reported in this study would promote a more efficient sensor design and data processing optimization. Industrial relevance This paper provides an optical characterization (absorption, scattering and angular scattering distribution) of pig adipose tissues in a wide near-infrared wavelength range (1150–2250 nm) based on a novel spectroscopic setup. The estimated data reported are relevant to promote the design of innovative NIRS sensors and the development of new modeling procedures in order to optimize the non-destructive analysis of intact adipose tissues. This can have an important impact on the implementation of NIRS quality control systems in the agro-industry.

Efficient sensor for robust low-power design in nano-CMOS technologies

Conventional design methods add pessimistic safety margins to mitigate increased variability in scaled technologies that incur high power and performance losses. An efficient sensor design is presented that can significantly reduce design margins yet provide robust circuit operation. The proposed design uses the delay of the master latch of a conventional flip-flop to predetect timing failures and enable low-power error-free operation. HSPICE simulation of a 45 nm 16×16 carry save multiplier indicates a 37% reduction in the total power consumption for the proposed design compared to a conventional worst case design when subjected to high statistical variability. Similarly, gate level simulations show a 26% reduction in the total power consumption of a 32 nm 32-bit carry select adder when subjected to temperature variations.

On the computer-aided modelling of analyte–receptor interactions for an efficient sensor design

The fundamental understanding of the interaction between analytes and receptor surface in a sensing chain system is crucial in order to guide the design of appropriate materials for sensor devices. The interaction analyte–receptor generates a signal, which is amplified and correlated with analyte concentration. The platform is usually composed of a chemical sensing and a pattern-recognition system, thus providing sensitivity, specificity, and performances of such sensors. Each analyte captured by the sensing system produces a signature or “fingerprint”. Our goal is to develop computational approaches, in order to improve the design of polymer-receptor in biosensors. In order to investigate the influence of the architecture of the polymeric film used as a receptor, we have conducted simulation employing Monte Carlo ballistic deposition method for an analyte with four types of macromolecules: linear, two brushes configurations and star. The results of the simulations showed that the polymeric architectures play a crucial role in the time response, specificity, sensitivity, and stability of the biosensor.