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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.

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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A high-temperature mixed potential CO gas sensor for in situ combustion control

An in situ, accurate and robust sensor that can sustain a high temperature of above 1000 °C is needed for on-site combustion monitoring because it can give real-time and local data to the control system to adjust the overall combustion efficiency. In this work, we find that nickel oxide (NiO) is a promising sensing material for CO which is a direct indicator of the status of the combustion process of a power plant. Under the conditions of 0.5–3% O 2 and 1000 °C, the fabricated yttrium-stabilized zirconia (YSZ)-based mixed potential sensor using porous NiO demonstrates good sensitivity to CO, showing a signal as high as 36 mV to 1000 ppm CO. The effects of gas transport, structure and geometry of the NiO electrode on the sensing performance are studied. Results show that fast gas transport is much beneficial to improved sensitivity. NiO having a porous structure is much more sensitive to CO than that having a dense structure. But the t90 (time to achieve 90% final signal magnitude) of the former is much longer due to slower gas diffusion inside the pores. It's worth noting that the NiO sensor exhibits a positive relationship with the CO content, opposite to other reported results of mixed potential sensors to detect CO. We find that this might be due to the electrochemical reduction, instead of oxidation of CO during the interaction with NiO at 1000 °C. Selectivity tests on how CO 2 , CH 4 and steam affect CO sensing are also demonstrated. NiO is insensitive to even 10% CO 2 . CH 4 does not shift the average value of the CO sensing response. However, it makes the sensing signal fluctuate more intensively. 2% steam exerts a great influence on NiO sensitivity to CO: it magnifies the sensitivity of the porous NiO electrode to a low CO range of 0–100 ppm, but inhibits its sensitivity to a CO range of 100 ppm to 1000 ppm. Lastly, an 11 day stability test demonstrates the promising stability property of the proposed NiO-based YSZ sensor.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2015

A Novel Energy-Aware Distributed Clustering Algorithm for Heterogeneous Wireless Sensor Networks in the Mobile Environment

In order to prolong the network lifetime, energy-efficient protocols adapted to the features of wireless sensor networks should be used. This paper explores in depth the nature of heterogeneous wireless sensor networks, and finally proposes an algorithm to address the problem of finding an effective pathway for heterogeneous clustering energy. The proposed algorithm implements cluster head selection according to the degree of energy attenuation during the network’s running and the degree of candidate nodes’ effective coverage on the whole network, so as to obtain an even energy consumption over the whole network for the situation with high degree of coverage. Simulation results show that the proposed clustering protocol has better adaptability to heterogeneous environments than existing clustering algorithms in prolonging the network lifetime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developed will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve these two formulations were developed and validated. For a given OSP problem the computation efficiency largely depends on the “size” of the problem. Initially a simplified 1-D gasifier model assuming axial and azimuthal symmetry was used to test out various OSP algorithms. Finally these algorithms were used to design the optimal sensor network for condition monitoring of IGCC gasifier refractory wear and RSC fouling. The sensors type and locations obtained as solution to the OSP problem were validated using model based sensing approach. The OSP algorithm has been developed in a modular form and has been packaged as a software tool for OSP design where a designer can explore various OSP design algorithm is a user friendly way. The OSP software tool is implemented in Matlab/Simulink© in-house. The tool also uses few optimization routines that are freely available on World Wide Web. In addition a modular Extended Kalman Filter (EKF) block has also been developed in Matlab/Simulink© which can be utilized for model based sensing of important process variables that are not directly measured through combining the online sensors with model based estimation once the hardware sensor and their locations has been finalized. The OSP algorithm details and the results of applying these algorithms to obtain optimal sensor location for condition monitoring of gasifier refractory wear and RSC fouling profile are summarized in this final report.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2013

Facile synthesis of Cu/Cu{sub x}O nanoarchitectures with adjustable phase composition for effective NO{sub x} gas sensor at room temperature

Graphical abstract: The Cu/Cu{sub x}O nanoarchitectures with 30–70 nm hollow nanospheres reduced by 3 mmol NaBH{sub 4} exhibits excellent gas-sensing property to low-concentration NO{sub x} gas at room temperature. - Highlights: • The Cu/Cu{sub x}O nanoarchitectures with hollow nanospheres are successfully synthesized. • The method is used for preparing the with Cu/Cu{sub x}O adjustable phase composition. • The C3 sample exhibites excellent gas-sensing propertie to NO{sub x} at room temperation. • The Cu/Cu{sub x}O nanoarchitectures have significant for application of gas sensor. - Abstract: The Cu/Cu{sub x}O nanoarchitectures with 30–70 nm hollow nanospheres are successfully synthesized by a facile wet chemical method. The synthesized products have been studied by X-ray powder diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and thermo gravimetric-differential scanning calorimetry (TG-DSC) analysis. The Cu/Cu{sub x}O sensors based on the nanoarchitectures are used to detect the NO{sub x} at room temperature. The results demonstrate that the obtained Cu/Cu{sub x}O nanoarchitectures reduced by 3 mmol NaBH{sub 4} exhibits excellent gas-sensing properties: low detection limit of 0.97 ppm, relatively high sensitivity, short response time, broad linear range and high selectivity. The reasons for gas-sensing activity enhancement on Cu/Cu{sub x}O nanoarchitectures are discussed. The Cu/Cu{sub x}O nanocrystalline with the hierarchical pores structure and tunable compositions have significant for application of gas sensor.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Continuous snow depth and temperature measurements from dense network of above-ground distributed temperature profiling systems from 2021-09-23 to 2024-08-23, Seward Peninsula, Alaska

The dataset contains temperature measurements from distributed temperature profiling (DTP) systems (Dafflon et al., 2022; Wielandt et al., 2022; Wang et al., 2024a; Fiolleau et al., 2024) deployed vertically above the ground surface at a large number of locations from 2021 to 2024. The research is designed to improve understanding of the local heterogeneity in snow depth and snow thermal insulation dynamics, as well as their interactions in a discontinuous permafrost region (Wang et al., 2025). The DTP systems were deployed at 96 locations in a watershed along the Nome-Teller road at mile marker 27 (T27) and at 54 locations on a hillslope along the Kougarok road at mile marker 64 (K64) in the Seward Peninsula, Alaska. The probe location information is stored in Probe_locations_T27.csv and Probe_locations_K64.csv. Temperature measurements were recorded at 15-minute intervals using high-precision digital sensors (accuracy: ±0.1°C, resolution: 0.0078°C). The temperature probes, either 1.4 m or 1.6 m long, contain sensors spaced every 5 cm or 10 cm along their length. The temperature data are stored in compressed files following the format: DTP_snow_air_temperature_(site)_(start)_(end).zip, where site is either T27 or K64, and start and end represent the time series period. Within each ZIP file, individual CSV files are named by probe ID and contain temperature records at different heights above the ground surface.This dataset also includes derived snow depth time series over three snow seasons, estimated from temperature measurements. Snow depth was estimated by identifying the consecutive sensor pair that exhibited the largest drop in high-frequency temperature fluctuations (detailed in the methods). These data are stored in: Snow_depths_flags_(site)_(start)_(end).csv, which includes snow depth time series and corresponding quality flags (defined in the methods) from different probes. Additionally, the dataset includes derived metrics and supporting measurements at selected locations over two snow seasons, contributing to the manuscript of Wang et al., 2025. These locations were chosen based on the availability of high-quality snow depth time series during both seasons. The additional data include: (1) Air temperature proxies measured from the top sensors on the pole when they were not buried by snow, stored in Air_temperature_proxies_(site)_(start)_(end).csv (2) Ground interface temperature, recorded at 3 cm above the ground, stored in Ground_interface_temperature_(site)_(start)_(end).csv (3) Site characteristics, including vegetation height, elevation, and the topographic position index (TPI) within a 50 m radius, stored in Selected_probe_locations_gps_vegheight_tpi_elevation_(site).csv. These metrics were derived from 1 m resolution summer LiDAR-based digital elevation models and digital surface models from Singhania et al., 2023, DOI:10.5440/1832016. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv.This dataset is an updated version of a previous archive (Wang et al., 2024b, DOI: 10.15485/2475020), incorporating multiple seasons and improved snow depth estimation. Please note that due to large amount of information present in this dataset, many specificities associated with the acquisition of snow temperature, air temperature proxy and estimation of snow depth, and the future archiving of additional datasets on the soil temperature, thaw depth and soil characteristics at these locations, the author would welcome being contacted by people planning to use this dataset.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Concept of Operations for Nuclear Warhead Embedded Sensors

Embedded arms-control-sensors provide a powerful new paradigm for managing compliance with future nuclear weapons treaties, where deployed warhead numbers will be reduced to 1000 or less. The CONOPS (Concept of Operations) for use with these sensors is a practical tool with which one may help define design parameters, including size, power, resolution, communications, and physical structure. How frequently must data be acquired and must a human be present? Will such data be acquired for only stored weapons or will it be required of deployed weapons as well? Will tactical weapons be subject to such monitoring or will only strategic weapons apply? Which data will be most crucial? Will OSI's be a component of embedded sensor data management or will these sensors stand alone in their data extraction processes? The problem space is massive, but can be constrained by extrapolating to a reasonable future treaty regime and examining the bounded options this scenario poses. Arms control verification sensors, embedded within the warhead case or aeroshell, must provide sufficient but not excessively detailed data, confirming that the item is a nuclear warhead and that it is a particular warhead without revealing sensitive information. Geolocation will be provided by an intermediate transceiver used to acquire the data and to forward the data to a central processing location. Past Chain-of-Custody projects have included such devices and will be primarily responsible for adding such indicators in the future. For the purposes of a treaty regime a TLI will be verified as a nuclear warhead by knowledge of (a) the presence and mass of SNM, (b) the presence of HE, and (c) the reporting of a unique tag ID. All of these parameters can be obtained via neutron correlation measurements, Raman spectroscopy, and fiber optic grating fabrication, respectively. Data from these sensors will be pushed out monthly and acquired nearly daily, providing one of several verification layers in depth, including on-site inspections, NTM, declarations, and semi-annual BCC meetings. Human intervention will not be necessary. The sheer numbers, small size, and wide distribution of warhead TLIs will mandate the added level of remote monitoring that Embedded Sensors can provide. This multilayer protection will limit the need to increase the frequency of OSIs, by adding confidence that declared TLIs remain as declared and that no undeclared items enter the regime without the other States Party's knowledge. Acceptance of Embedded arms control Sensor technologies will require joint development by all State's Parties involved. Principles of operation and robustness of technologies must be individually evaluated to sustain confidence in the strength of this system against attack. Weapons designers must be assured that these sensors will in no way impact weapon performance and operation, will not affect weapons security and safety, and will have a neutral impact upon weapon system surety. Each State's Party will need to conduct an in depth review of their weapons lifecycle to determine where moves may be reduced to minimize vulnerabilities and where random selection may be used to minimize the ability to make undeclared changes. In the end Verification is a political measure, not a technical one. If the potential users can gain sufficient confidence in the application of Embedded arms control Sensors, they could constitute the final layer of glue to hold together the next Nuclear Arms Control agreement.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2014

Development of an X-ray pixel detector with multi-port charge-coupled device for X-ray free-electron laser experiments

This paper presents development of an X-ray pixel detector with a multi-port charge-coupled device (MPCCD) for X-ray Free-Electron laser experiments. The fabrication process of the CCD was selected based on the X-ray radiation hardness against the estimated annual dose of 1.6 × 10{sup 14} photon/mm{sup 2}. The sensor device was optimized by maximizing the full well capacity as high as 5 Me- within 50 μm square pixels while keeping the single photon detection capability for X-ray photons higher than 6 keV and a readout speed of 60 frames/s. The system development also included a detector system for the MPCCD sensor. This paper summarizes the performance, calibration methods, and operation status.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

W{sub 18}O{sub 49} nanorods decorated with Ag/AgCl nanoparticles as highly-sensitive gas-sensing material and visible-light-driven photocatalyst

A novel gas-sensing material and photocatalyst was successfully obtained by decorating Ag/AgCl nanoparticles on the W{sub 18}O{sub 49} nanorods through a clean photochemical route. The as-prepared samples were characterized using combined techniques of X-ray diffractometry, electron microscopy, energy dispersive X-ray spectrometry, and X-ray photoelectron spectroscopy. Gas-sensing measurements indicate that the Ag/AgCl/W{sub 18}O{sub 49} NRs sensors exhibit superior reducing gas-sensing properties to those of bare W{sub 18}O{sub 49} NRs, and they are highly selective and sensitive to NH{sub 3}, acetone, and H{sub 2}S with short response and recovery times. The Ag/AgCl/W{sub 18}O{sub 49} NRs photocatlysts also possess higher photocatalytic performance than bare W{sub 18}O{sub 49} NRs for degradation of methyl orange under simulated sunlight irradiation. Possible mechanisms concerning the enhancement of gas-sensing and photocatalytic activities of the Ag/AgCl/W{sub 18}O{sub 49} NRs composite were proposed. - Graphical Abstract: The Ag/AgCl nanoparticles adhered well to the W{sub 18}O{sub 49} nanorod. The Ag could act as transfer center of the photoexcited carriers, prohibiting their recombinations in both W{sub 18}O{sub 49} and AgCl. Highlights: > Ag/AgCl/W{sub 18}O{sub 49} NRs were successfully obtained via a clean photochemical route. > The Ag/AgCl nanoparticles decorated on the W{sub 18}O{sub 49} NRs possessed cladding structure. > The Ag/AgCl/W{sub 18}O{sub 49} NRs exhibited excellent gas-sensing and photocatalytic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Hybrid DC Fault Primary Protection Algorithm for Multi-Terminal HVdc Systems

Protection against dc faults is one of the main technical hurdles faced when operating converter-based HVdc systems. Protection becomes even more challenging for multi-terminal dc (MTdc) systems with more than two terminals/converter stations. In this paper, a hybrid primary fault detection algorithm for MTdc systems is proposed to detect a broad range of failures. Sensor measurements, i.e., line currents and dc reactor voltages measured at local terminals, are first processed by a top-level context clustering algorithm. For each cluster, the best fault detector is selected among a detector pool according to a rule resulting from a learning algorithm. The detector pool consists of several existing detection algorithms, each performing differently across fault scenarios. The proposed hybrid primary detection algorithm: i) offers superior performance compared to an individual detector through a data-driven approach; ii) detects all major fault types including pole-to-pole (P2P), pole-to-ground (P2G), and external dc faults; iii) identifies faults with various fault locations and impedances; iv) is more robust to noisy sensor measurements compared to existing methods; v) does not require exhaustive simulation and sampling for training the model. Performance and effectiveness of the proposed algorithm are evaluated and verified based on time-domain simulations in the PSCAD/EMTDC software environment. The results confirm satisfactory operation, accuracy, and detection speed of the proposed algorithm under various fault scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

A Laser-Based Optical Sensor for Broad-Band Measurements of Building Earthquake Drift

Accurate measurements of the time-dependent deformations of a building during earthquake excitation are essential for interpretation of the dynamic response of the as-built system and for quantifying the seismic demands. Traditional approaches for monitoring building systems are based on strong motion accelerometers mounted at selected elevations. However, accelerometer-based systems do not directly measure the deformations of the structure, and can have significant limitations that make it challenging to correctly measure deformations, particularly permanent deformations from inelastic response. In the study described herein, computational simulations and experiments were combined to evaluate the potential of a new optically based sensor to directly measure time-dependent deformations of a building, including inelastic deformations. The sensor methodology includes corrections for localized structural member rotations and can provide estimates of the absolute accelerations at each floor. A laser-based system utilizing a recently developed discrete diode position sensor (DDPS) is evaluated, and the ability of such a system to measure earthquake induced transient deformations characterized by building interstory drift is demonstrated.

58 GEOSCIENCES↗
DOE OSTI2012

Electrochemical Sensors Based on Nanomaterials for Environmental Monitoring

This article review work relevant to the two fastest growing nanomaterials in electrochemical sensing of metal ions: organically modified ordered mesoporous silicas (OMSs) and carbon nanotubes (CNTs). Nanostructured self-assembled monolayers on mesoporous silicas (SAMMS) materials are highly effective as electrode modifiers; they can be either mixed with conductive materials or spin-cast as a thin-film on electrode surface. The interfacial chemistry of SAMMS can be fine-tuned to selectively preconcentrate the specific metal ions of interest. The functional groups on SAMMS materials enable the preconcentration to be done without mercury, supporting electrolytes, applied potential, and solution degassing, all of which are often required in conventional adsorptive stripping voltammetric sensors. Since it was first introduced in 1991, CNTs have been widely investigated for electrochemical sensors of many important biomolecules because of their electrocatalytic and antifouling properties, biocompatibility, high surface, and mechanical strength. For trace metal analysis, CNT thin-film created by drop-coating of CNT-solvent suspensions on electrode surfaces has been explored in order to develop mercury-free sensors by exploiting the bulk properties of the CNTs. Array of low-site-density aligned carbon nanotubes has been grown on metal substrates by a non-lithographic method. Each CNT serves as a nanoelectrode which normally has greater mass transfer rate and higher mass sensitivity than conventional macroelectrodes. The array of millions of CNT nanoelectrodes provides magnified voltammetric signals for trace metal ions without the need for a signal amplifier.

Electrochemical Sensors↗
DOE OSTI2016

Enhanced grid operation and optimized PV penetration utilizing highly distributed sensor data

This task describes R&D activities to establish methods to cost-effectively achieve very high PV penetration scenarios (well beyond 100% of peak load at the feeder level) by leveraging distributed inverters to increase situational awareness and provide local voltage support. The grid performance and reliability objectives (SI vision) of this proposal were selected to enhance feeder planning models that can better characterize and quantify the electric power system including the secondary system servicing customers. The Communication objective was selected to demonstrate how visibility and control of behind-the-meter systems and distributed storage at large scale can be optimized to address system reliability and variability impacts, and to maximize the value of solar in high PV penetration scenarios. The goal of this project was to achieve enhanced grid operation and optimized PV penetration utilizing highly distributed sensor data via three subtasks 1.1-1.3.

14 SOLAR ENERGY↗
DOE OSTI2016

Plasma jet printing for flexible substrates

Recent interest in flexible electronics and wearable devices has created a demand for fast and highly repeatable printing processes suitable for device manufacturing. Robust printing technology is critical for the integration of sensors and other devices on flexible substrates such as paper and textile. An atmospheric pressure plasma-based printing process has been developed to deposit different types of nanomaterials on flexible substrates. Multiwalled carbon nanotubes were deposited on paper to demonstrate site-selective deposition as well as direct printing without any type of patterning. Plasma-printed nanotubes were compared with non-plasma-printed samples under similar gas flow and other experimental conditions and found to be denser with higher conductivity. The utility of the nanotubes on the paper substrate as a biosensor and chemical sensor was demonstrated by the detection of dopamine, a neurotransmitter, and ammonia, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Glycosylated Peptoid Nanosheets as a Multivalent Scaffold for Protein Recognition

Glycoproteins adhered on the cellular membrane play an important role in a wide range of cellular functions. Their significance is particularly relevant in the recognition process between infectious pathogens (such as viruses, bacteria, toxins) and their host cells. Multivalent interactions at the pathogen-cell interfaces govern binding events and can result in a strong and specific interaction. Here in this paper, we report an approach to mimic the cell surface presentation of carbohydrate ligands by the multivalent display of sugars on the surface of peptoid nanosheets. The constructs provide a highly organized 2D platform for recognition of carbohydrate-binding proteins. The sugars were displayed using different linker lengths or within loops containing 2-6 hydrophilic peptoid monomers. Both the linkers and the loops contained one alkyne-bearing monomer, to which different saccharides were attached by copper-catalyzed azide-alkyne cycloaddition reactions. Peptoid nanosheets functionalized with different saccharide groups were able to selectively bind multivalent lectins, Concanavalin A and Wheat Germ Agglutinin, as observed by fluorescence microscopy and a homogeneous Förster resonance energy transfer (FRET)-based binding assay. To evaluate the potential of this system as sensor for threat agents, the ability of functionalized peptoid nanosheets to bind Shiga toxin was also studied. Peptoid nanosheets were functionalized with globotriose, the natural ligand of Shiga toxin, and the effective binding of the nanomaterial was verified by the FRET-based binding assay. In all cases, evidence for multivalent binding was observed by systematic variation of the ligand display density on the nanosheet surface. These cell surface mimetic nanomaterials may find utility in the inactivation of pathogens or as selective molecular recognition elements.

bioinspired polymers↗
DOE OSTI2017

Solution-Processed Nanoporous Organic Semiconductor Thin Films: Toward Health and Environmental Monitoring of Volatile Markers

Porous materials are ubiquitous in nature and have found a wide range of applications because of their unique absorption, optical, mechanical, and catalytic properties. Large surface-area-to-volume ratio is deemed a key factor contributing to their catalytic properties. Here, it is shown that introducing tunable nanopores (50–700 nm) to organic semiconductor thin films enhances their reactivity with volatile organic compounds by up to an order of magnitude, while the surface-area-to-volume ratio is almost unchanged. Mechanistic investigations show that nanopores grant direct access to the highly reactive sites otherwise buried in the conductive channel of the transistor. The high reactivity of nanoporous organic field-effect transistors leads to unprecedented ultrasensitive, ultrafast, selective chemical sensing below the 1 ppb level on a hundred millisecond time scale, enabling a wide range of health and environmental applications. Flexible sensor chip for monitoring breath ammonia is further demonstrated; this is a potential biomarker for chronic kidney disease.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Stepwise Assembly of Turn‐on Fluorescence Sensors in Multicomponent Metal–Organic Frameworks for in Vitro Cyanide Detection

Abstract The controlled synthesis of multicomponent metal–organic frameworks (MOFs) allows for the precise placement of multiple cooperative functional groups within a framework, leading to emergent synergistic effects. Herein, we demonstrate that turn‐on fluorescence sensors can be assembled by combining a fluorophore and a recognition moiety within a complex cavity of a multicomponent MOF. An anthracene‐based fluorescent linker and a hemicyanine‐containing CN − ‐responsive linker were sequentially installed into the lattice of PCN‐700. The selective binding of CN − to hemicyanine inhibited the energy transfer between the two moieties, resulting in a fluorescence turn‐on effect. Taking advantage of the high tunability of the MOF platform, the ratio between anthracene and the hemicyanine moiety could be fine‐tuned in order to maximize the sensitivity of the overall framework. The optimized MOF‐sensor had a CN − ‐detection limit of 0.05 μ m , which is much lower than traditional CN − fluorescent sensors (about 0.2 μ m ).

Li, Jialuo↗
DOE OSTI2017

Gold nano-particle formation from crystalline AuCN: Comparison of thermal, plasma- and ion-beam activated decomposition

In this work, in addition to the conventional thermal process, two non-conventional ways, the plasma and ion beam activations are described for preparing gold nanoparticles from microcrystalline AuCN precursor. The phase formation at plasma and ion beam treatments was compared with that at thermal treatments and the products and transformations were characterized by thermogravimetry-mass-spectrometry (TG-MS), X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM). TG-MS measurements in Ar atmosphere revealed that AuCN decomposition starts at 400 °C and completes at ≈700 °C with evolution of gaseous (CN){sub 2}. XPS and TEM show that in heat treatment at 450 °C for 1 h in Ar, loss of nitrogen and carbon occurs and small, 5–30 nm gold particles forms. Heating at 450 °C for 10 h in sealed ampoule, much larger, 60–200 nm size and well faceted Au particles develop together with a fibrous (CN){sub n} polymer phase, and the Au crystallites are covered by a 3–5 nm thick polymer shell. Low pressure Ar plasma treatment at 300 eV energy results in 4–20 nm size Au particles and removes most of the nitrogen and part of carbon. During Ar{sup +} ion bombardment with 2500 eV energy, 5–30 nm size Au crystallites form already in 10 min, with preferential loss of nitrogen and with increased amount of carbon residue. The results suggest that plasma and ion beam activation, acting similarly to thermal treatment, may be used to prepare Au nanoparticles from AuCN on selected surface areas either by depositing AuCN precursors on selected regions or by focusing the applied ionized radiation. Thus they may offer alternative ways for preparing tailor-made catalysts, electronic devices and sensors for different applications. - Graphical abstract: Proposed scheme of the decomposition mechanism of AuCN samples: heat treatment in Ar flow (a) and in sealed ampoule (b); Ar{sup +} ion treatment at 300 eV (c) and at 2500 eV (d). Cross section sketches illustrate the Au phase formation and the corresponding TEM micrographs are shown as top views. The dotted lines represent the original boundaries of the AuCN crystals. - Highlights: • AuCN decomposes between 400 and 700 °C with evolution of gaseous (CN){sub 2}. • Epitaxial relationship is established between Au and parent AuCN crystals. • Ar plasma treatment results in similar phase transition than the thermal treatment. • Plasma and ion-beam activation offer alternative way for preparing Au nanocrystals. • Reaction mechanisms of Au particle formation at the three treatments are proposed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗