SEARCH · Engineering Papers

Results for “sensor selection”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36

All sources NASA NTRS DOE OSTI

DOE OSTI2013

Chemical and biological sensing using liquid crystals

The liquid crystalline state of matter arises from orientation-dependent, non-covalent interactions between molecules within condensed phases. Because the balance of intermolecular forces that underlies the formation of liquid crystals (LCs) is delicate, this state of matter can, in general, be easily perturbed by external stimuli (such as an electric field in a display). In this review, we present an overview of recent efforts that have focused on exploiting the responsiveness of LCs as the basis of chemical and biological sensors. In this application of LCs, the challenge is to design liquid crystalline systems that undergo changes in organization when perturbed by targeted chemical and biological species of interest. The approaches described below revolve around the design of interfaces that selectively bind targeted species, thus leading to surface-driven changes in the organization of the LCs. Because LCs possess anisotropic optical and dielectric properties, a range of different methods can be used to read out the changes in organization of LCs that are caused by targeted chemical and biological species. This review focuses on principles for LC-based sensors that provide an optical output.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Scalable Approaches to Selecting Key Entities in Large Networked Infrastructure Systems

This work aims at bringing advances in discrete optimization algorithms to solving practical engineering problems at scale. Often times, in many engineering design problems, there is a need to select a small set of influential or representative elements from a large ground set of entities in an optimal fashion. Submodular optimization provides for a formal way to solve such problems. Common examples with infrastructure systems involve sensor placement and identification of key entities with certain objectives. However, scaling these approaches to large infrastructure systems can be challenging because of the high computational complexity of the overall framework that include the optimization algorithms as well as high-complexity compute-oracles that provide the necessary objective function values. In this work, we explore a well-studied and widely-applicable paradigm, namely leader-selection in a multi-agent networked setting in the context of scalable methodologies. We demonstrate novel frameworks that utilize variations of accelerated submodular optimization algorithms along with linear-algebraic methods that can help accelerate the oracle computations. We further explore this combination in conjunction with graph partitioning paradigms to take advantage of the accelerated algorithms in a distributed setting. Finally we demonstrate the key findings on a practical problem in an operational setting. For this, we leverage an example road network with approximately 18k nodes and 27k edges in a traffic control application, where we seek a limited number of k=200 key intersections. This problem can be solved in a serial setting in just under 5 hours providing more than 2 orders of magnitude speed-up over methods that do not consider acceleration techniques.

Visweswara Sathanur, Arun↗

DOE OSTI2021

Manipulating cobalt oxide on N-doped aligned electrospun carbon nanofibers towards instant electrochemical detection of dopamine secreted by living cells

A demand exists for the development of miniaturized biosensors with high sensitivity and a wide dynamic range for rapid detecting dopamine (DA) levels. Here, an electrochemical sensor is created by decorating closely packed cobalt oxide (Co 3 O 4 ) nanograins on nitrogen-doped electrospun carbon nanofibers (NECNFs) via a facile electrodeposition method. The carbon nanofiber matrix provides both a scaffold with ultrahigh surface area for homogeneous dispersion of cobalt oxide nanostructures and facilitates the electrochemical conductivity for the hybrid electrode. The sensing principle is based on the redox reaction between DA and DA quinone that generates electrical signal, which is detectable via differential pulse voltammetry (DPV) and chronoamperometry (CA). Owing to a high electroactive surface area and facilitating electron transfer between electrode surface and the target molecule, the electrical sensing platform exhibits superior sensitivity and selectivity toward DA, with an excellent limit of detection (9 nM) over a wide range of concentrations (0.01 to 100 μM). Moreover, based on its excellent sensing properties and biocompatibility, the sensor has been used for the real-time monitoring exogeneous DA released from pheochromocytoma (PC12) cells. This work demonstrates promise of a novel sensor technology that may render rapid point-of-care testing of DA towards early clinical diagnosis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2011

Ranging methods for developing wellbores in subsurface formations

A method for forming two or more wellbores in a subsurface formation includes forming a first wellbore in the formation. A second wellbore is directionally drilled in a selected relationship relative to the first wellbore. At least one magnetic field is provided in the second wellbore using one or more magnets in the second wellbore located on a drilling string used to drill the second wellbore. At least one magnetic field is sensed in the first wellbore using at least two sensors in the first wellbore as the magnetic field passes by the at least two sensors while the second wellbore is being drilled. A position of the second wellbore is continuously assessed relative to the first wellbore using the sensed magnetic field. The direction of drilling of the second wellbore is adjusted so that the second wellbore remains in the selected relationship relative to the first wellbore.

42 ENGINEERING↗

DOE OSTI2017

Characterizing Photon Reabsorption in Quantum Dot-Polymer Composites for Use as Displacement Sensors

The reabsorption of photoluminescence within a medium, an effect known as the inner filter effect (IFE), has been well studied in solutions, but has garnered less attention in regards to solid-state nanocomposites. Photoluminescence from a quantum dot (QD) can selectively excite larger QDs around it resulting in a net red-shift in the reemitted photon. In CdSe/CdS core/shell QD-polymer nanocomposites, we observe a large spectral red-shift of over a third of the line width of the photoluminescence of the nanocomposites over a distance of 100 μm resulting from the IFE. Unlike fluorescent dyes, which do not show a large IFE red-shift, QDs have a component of inhomogeneous broadening that originates from their size distribution and quantum confinement. By controlling the photoluminescence broadening as well as the sample dispersion and concentration, we show that the magnitude of the IFE within the nanocomposite can be tuned. We further demonstrate that this shift can be exploited in order to spectroscopically monitor the vertical displacement of a nanocomposite in a fluorescence microscope. Large energetic shifts in the measured emission with displacement can be maximized, resulting in a displacement sensor with submicrometer resolution. We further show that the composite can be easily attached to biological samples and is able to measure deformations with high temporal and spatial precision.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2025

Remote Americium Detection Using an Optical Sensor: A D-Optimal Strategy for Efficient PLS-Based Modeling

A fiber-optic visible–near-infrared absorption spectroscopy system in a glove box was demonstrated for remote quantification of Am(III) (0–500 µM) and HNO 3 (0.1–9 M) using partial least squares regression (PLSR) models. The sensor platform, featuring a simple plug-and-play spectrophotometer, can enable noninvasive, real-time monitoring of actinide process solutions. To establish a flexible PLSR model calibration strategy, a D-optimal design developed using Nd(III) in previous studies was successfully extended to an actinide system with Am(III) to effectively minimize sample set size while maintaining robust prediction performance. The results suggest strong spectral similarities between Nd(III) and Am(III) and validate Nd(III) as an effective optical surrogate for trivalent actinide species. This work also supports the generalizability of a D-optimal training set selection approach for two-factor systems. The PLS1 models for Am(III) and HNO 3 outperformed a PLS2 model and maintained reasonable performance in the presence of interfering U(VI). The resulting sensor system and multivariate approach provides a flexible and scalable solution for process monitoring, control, and safety in diverse nuclear applications.

actinide↗

DOE OSTI2017

Quantitative decoding of the response a ceramic mixed potential sensor array for engine emissions control and diagnostics

The development of on-board sensors for emissions monitoring is necessary for continuous monitoring of the performance of catalytic systems in automobiles. We have fabricated mixed potential electrochemical gas sensing devices with Pt, La 0.8 Sr 0.2 CrO 3 (LSCO), and Au/Pd alloy electrodes and a porous yttria-stabilized zirconia electrolyte. The three-electrode design takes advantage of the preferential selectivity of the Pt + Au/Pd and Pt + LSCO pairs towards different species of gases and has additional tunable selectivity achieved by applying a current bias to the latter pair. Voltages were recorded in single, binary, and ternary gas streams of NO, NO 2 , C 3 H 8 , and CO. We have also trained artificial neural networks to examine the voltage output from sensors in biased and unbiased modes to both identify which single test gas or binary mixture of two test gases is present in a gas stream as well as extract concentration values. We were then able to identify single and binary mixtures of these gases with accuracy of at least 98%. For determining concentration, the peak in the error distribution for binary mixtures was 5% and 80% of test data fell under <12% error. The sensor stability was also evaluated over the course of over 100 days and the ability to retrain ANNs with a small dataset was demonstrated.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2012

Part-Per-Trillion Level SF6 Detection Using a Quartz Enhanced Photoacoustic Spectroscopy-Based Sensor with Single-Mode Fiber-Coupled Quantum Cascade Laser Excitation

A sensitive spectroscopic sensor based on a hollow-core fiber-coupled quantum cascade laser (QCL) emitting at 10.54 µm and quartz enhanced photoacoustic spectroscopy (QEPAS) technique is reported. The design and realization of mid-infrared fiber and coupler optics has ensured single-mode QCL beam delivery to the QEPAS sensor . The collimation optics was designed to produce a laser beam of significantly reduced beam size and waist so as to prevent illumination of the quartz tuning fork and micro-resonator tubes. SF6 was selected as the target gas. A minimum detection sensitivity of 50 parts per trillion in 1 s was achieved with a QCL power of 18 mW, corresponding to a normalized noise-equivalent absorption of 2.7x10-10 W•cm-1/Hz1/2.

Laser Sensors↗

DOE OSTI2013

Theoretical Studies of Spin Crossover Metal-Organic Frameworks

The research carried out within this grant focused on characterizing spin crossover (SCO) transitions, i.e., the change in spin state, in metal-organic frameworks (MOFs). MOFs are three-dimensional networks in which metal ions or clusters are connected to multidentate ligands. By combining high porosity, large surface area, guest selectivity, structural flexibility, and SCO properties, MOFs provide a promising platform for the development of multifunctional materials, such as molecular switches, memory devices, and chemical sensors. To characterize the SCO properties of MOFs at the molecular level, we have developed a hybrid Monte Carlo / molecular dynamics (MC/MD) method that builds upon the ligand field molecular mechanics (LFMM) model. Within LFMM, conventional molecular mechanics (MM) energy expressions are supplemented with an additional term that effectively represents the ligand field stabilization energy (LFSE) arising from the splitting and different occupation of the d-based molecular orbitals. LFMM thus explicitly includes energy contributions that depend on both the instantaneous coordination geometry and the electronic structure of the metal centers. In our MC/MD method, the original LFMM model is combined with a Monte Carlo scheme based on the Metropolis acceptance/rejection criterion that is used to model spin-crossover transitions in bulk materials with multiple metal centers. We have applied our hybrid MC/MD method to investigate the SCO behavior of {Fe(pz)[Pt(CN) 4 ]}, a prototypical MOF, upon adsorption of various guest molecules. In all cases, excellent agreement was found with the available experimental data, which allowed us to develop a fundamental understanding of the molecular mechanisms that govern spin transitions in MOFs. By correlating molecular-level guest molecule-framework interactions with macroscopic SCO properties, our analysis provides design principles, at the fundamental level, for the development of MOF materials that can efficiently exploit the energy differences between spin states for gas detection and molecular sensing.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Real time numerical computation of corrosion rates from corrosion sensors

A method for determining a corrosion rate includes receiving an input signal including corrosion data from a sensor. A signal-to-noise ratio (SNR) and a type of noise is determined from the input signal. A corrosion rate computation method is selected based on the SNR and the type of noise. The corrosion rate is determined, using a processor, based on a selected corrosion rate computation method.

Klein, Levente I.↗

DOE OSTI2020

Real time numerical computation of corrosion rates from corrosion sensors

36 MATERIALS SCIENCE↗

DOE OSTI2025

Advancing Temperature Monitoring of the Bottom Anode in a Direct Current Electric Arc Furnace Operations with Distributed Optical Fiber Sensors.

The bottom anode in the Direct Current Electric Arc Furnace (DC EAF) is critical for completing the electrical circuit necessary for sustaining the arc within the furnace. For pin-type bottom anodes, monitoring of the temperature of select pins instrumented with thermocouples is performed to track bottom wear in the EAF and inform the operator when the furnace should be removed from service. Furthermore, this work presents the results from a plant trial using distributed temperature monitoring of bottom anode pins in a 165-ton DC EAF over a two-month service period utilizing two optical fiber sensing techniques: fiber Bragg grating (FBG) and Rayleigh backscattering (RBS). The early detection of temperature anomalies along the length of the anode pin through distributed sensing enhances operational safety, providing a robust alternative to traditional thermocouples.

42 ENGINEERING↗

DOE OSTI2023

Direct observation of the local microenvironment in inhomogeneous CO 2 reduction gas diffusion electrodes via versatile pOH imaging

In this study, we report how the micrometer-scale morphology of a carbon dioxide reduction (CO 2 R) gas diffusion electrode (GDE) affects the mass transport properties and with it, the local CO 2 R performance. We developed a technique to probe the microenvironment in a CO 2 R GDE via local pOH imaging with time- and three-dimensional spatial, micrometer-scale resolution. The local activity of hydroxide anions (OH - ), represented by the pOH value, around a GDE in contact with an aqueous electrolyte is a crucial parameter that governs the catalytic activity and CO 2 R selectivity. Here, we use fluorescence confocal laser scanning microscopy (CLSM) to create maps of the local pOH around a copper GDE by combining two ratiometric fluorescent dyes, one of which is demonstrated as a pOH sensor for the first time in this work. We observe that the local pOH decreases when current is applied due to the creation of OH - as a byproduct of CO 2 R. Interestingly, the pOH is lower inside microtrenches compared to the electrode surface and decreases further as trenches become more narrow due to enhanced trapping of OH - . We support our experimental results with multiphysics simulations that correlate exceptionally well with measurements. These simulations additionally suggest that the decreased pOH inside microcavities in the surface of a CO 2 R GDE leads to locally enhanced selectivity towards multicarbon (C 2+ ) products. This study suggests that narrow microstructures on the length scale of 5 μm in a GDE surface serve as local CO 2 R hotspots, and thus highlights the importance of a GDE's micromorphology on the CO 2 R performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Selection of optimal wavelengths for optical soiling modelling and detection in photovoltaic modules

Soiling impacts the photovoltaic (PV) module performance by decreasing the amount of light reaching the photovoltaic cells and by changing their external spectral response. Currently, the soiling monitoring market is moving toward optical sensors that measure transmittance or reflectance, rather than directly measuring the impact of soiling on the performance of photovoltaic modules. These sensors, which use a single optical measurement, are not able to correct the soiling losses that depend on the solar irradiance spectra and on the spectral response of the monitored PV material. This work investigates methods that can improve the optical detection of soiling by extracting the full soiling spectrum profiles using only two or three monochromatic measurements. Spectral transmittance data, measured with a spectrophotometer and collected during a 46-week experimental soiling study carried out in Jaén, Spain, was analysed in this work. The use of a spectral profile for the hemispherical transmittance of soiled PV glass is found to significantly improve the soiling detection, returning the lowest errors independently of the PV materials and irradiance conditions. In addition, this work shows that it is also possible to select the measurement wavelengths to minimize the soiling loss detection error depending on the monitored PV semiconductor material (silicon, CdTe, a-Si, CIGS and a representative perovskite). The approaches discussed in this work are also found to be more robust to potential measurement errors compared to single wavelength measurement techniques.

14 SOLAR ENERGY↗

DOE OSTI2013

Mid-Infrared Fiber-Coupled QCl-QEPAS Sensor

An innovative spectroscopic system based on an external cavity quantum cascade laser (EC-QCL) coupled with a mid-infrared (mid-IR) fiber and quartz enhanced photoacoustic spectroscopy (QEPAS) is described. SF6 has been selected as a target gas in demonstration of the system for trace gas sensing. Single mode laser delivery through the prongs of the quartz tuning fork has been obtained employing a hollow waveguide fiber with inner silver–silver iodine (Ag–AgI) coatings and internal core diameter of 300 lm. A detailed design and realization of the QCL fiber coupling and output collimator system allowed almost practically all (99.4 %) of the laser beam to be transmitted through the spectrophone module. The achieved sensitivity of the system is 50 parts per trillion in 1 s, corresponding to a record for QEPAS normalized noise-equivalent absorption 2.7 9 10-10 W cm-1 Hz-1/2.

External Cavity Quantum Cascade Laser↗

DOE OSTI2023

Thermopile Energy Harvesting for Subsurface Wellbore Sensors (Final Report)

Robust in situ power harvesting underlies all efforts to enable downhole autonomous sensors for real-time and long-term monitoring of CO 2 plume movement and permeance, wellbore health, and induced seismicity. This project evaluated the potential use of downhole thermopile arrays, known as thermoelectric generators (TEGs), as power sources to charge sensors for in situ real-time, long-term data capture and transmission. Real-time downhole monitoring will enable “Big Data” techniques and machine learning, using massive amounts of continuous data from embedded sensors, to quantify short- and long-term stability and safety of enhanced oil recovery and/or commercial-scale geologic CO 2 storage. This project evaluated possible placement of the TEGs at two different wellbore locations: on the outside of the casing; or on the production tubing. TEGs convert heat flux to electrical power, and in the borehole environment, would convert heat flux into or out of the borehole into power for downhole sensors. Such heat flux would be driven by pumping of cold or hot fluids into the borehole—for instance, injecting supercritical CO 2 —creating a thermal pulse that could power the downhole sensors. Hence, wireless power generation could be accomplished with in situ TEG energy harvesting. This final report summarizes the project’s efforts that accomplished the creation of a fully operational thermopile field unit, including selection of materials, laboratory benchtop experiments and thermal-hydrologic modeling for design and optimization of the field-scale power generation test unit. Finally, the report describes the field unit that has been built and presents results of performance and survivability testing. The performance and survivability testing evaluated the following: 1) downhole power generation in response to a thermal gradient produced by pumping a heated fluid down a borehole and through the field unit; and 2) component survivability and operation at elevated temperature and pressure conditions representative of field conditions. The performance and survivability testing show that TEG arrays are viable for generating ample energy to power downhole sensors, although it is important to note that developing or connecting to sensors was beyond the scope of this project. This project’s accomplishments thus traversed from a low Technical Readiness Level (TRL) on fundamental concepts of the application and modeling to TRL-5 via testing of the fully integrated field unit for power generation in relevant environments. A fully issued United States Patent covers the wellbore power harvesting technology and applications developed by this project.

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

Combustion synthesis of LaFeO{sub 3} sensing nanomaterial

Since industrial revolution, human activities drive towards unsustainable global economy due to the overexploitation of natural resources and the unacceptable emissions of pollution and greenhouse gases. In order to address that issue, engineering research has been focusing on gas sensors development for monitoring gas emissions and controlling the combustion process sustainability. Semiconductors metal oxides sensors are attractive technology because they require simple design and fabrication, involving high accessibility, small size and low cost. Perovskite oxides are the most promising sensing materials because sensitivity, selectivity, stability and speed-response can be modulated and optimized by changing the chemical composition. One of the most convenient synthesis process of perovskite is the citrate-nitrate auto-combustion method, in which nitrate is the oxidizing agent and citrate is the fuel and the chelating argent in the same time. Since the sensibility of perovskite oxides depends on the defective crystallographic structure and the nanomorphology, the experimental was designed in order to study the dependence of powder properties on the synthesis conditions, such as the solution acidity and the relative amount of metals, nitrates and citric acid. Crystalline structure was studied in depth for defining the effects of synthesis conditions on size, morphology and crystallographic structure of nanopowders of LaFeO{sub 3}.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

The contributions of microclimatic information in advancing ecosystem science

Drawing upon over 100 years of scholarly work on microclimate, we first present an overview of the history, key references, and critical issues surrounding the collection and utilization of microclimate records in ecosystem studies. We place particular emphasis on addressing specific and pressing issues related to the applications of microclimate at the community-ecosystem-landscape level, excluding those of controlled experiment such as growth chambers and greenhouses. Specifically, we: (1) highlight some key issues concerning the collection, quality assurance/quality control (QA/QC), and utilization of microclimatic data in ecosystem studies; (2) revisit microclimatic responses to the structural changes of ecosystems and landscapes; and (3) emphasize the significance of microclimate in understanding major ecosystem/landscape processes and functions. Vapor pressure deficit (VPD) is particularly emphasized for its calculation and use because of its burgeoning applications in the literature. Case studies for each of the three thematic topics are provided with selected references to demonstrate challenges and solutions. As the scientific community gears up to enhance microclimatic stations, we envision significant increases in the use of smart sensors, wireless access, networking, open databases, and computational capabilities. Understanding and addressing some of the issues raised in this synthesis paper may help advance microclimate research and foster collaboration with other relevant disciplines, such as ecosystem science.

54 ENVIRONMENTAL SCIENCES↗