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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Geometrical and chemical effects on the electrochemistry of single-wall carbon nanotube (SWCNT) network electrodes

Single-wall carbon nanotube (SWCNT) network is a promising electrode material for bio detection. Unfortunately, the associations between their physical as well as chemical properties and observed electrochemical performance are not known. This hinders any systematic optimization of the network properties towards specific analytes. Here we present a consistent physicochemical and electrochemical characterization of differently treated SWCNT networks. The results unambiguously show that (i) even if the electrochemical properties of different electrodes are practically identical when assessed by surface insensitive outer sphere redox (OSR) probes their behavior with inner sphere redox (ISR) probes can be drastically different. Further, (ii) the choice of the modification method (structural, chemical, electrochemical) heavily depends on nature of the target analyte, which are typically ISR probes. Although, (iii) chemical changes in the carbon phase appeared to be minor, effects of different treatments on oxidation states of Fe appeared to have a strong effect on the electrochemical performance of the networks in the case of ISR probes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

SimH 2 : an integrated techno-economic modeling framework for hydrogen pipeline infrastructure and network optimization

Large-scale hydrogen (H 2 ) pipeline transport design and network optimization have seldom been reported due to the lack of a cost model accounting for the relationship between transport cost and hydrogen mass flow rate. Here, this work introduced a system-level cost model for hydrogen pipeline transport at supercritical state and integrated it with an existing CO 2 pipeline network tool, SimCCS, for hydrogen-specific pipeline design and optimization. The Intermountain West (I-West) region of the U.S., historically dependent on fossil fuel-based economies, is chosen to demonstrate the capabilities of our H 2 pipeline cost model and transport network optimization platform called SimH 2 . Two scenarios are examined: one where the pipeline is not allowed to pass through disadvantaged communities and the other where it is permitted. The results highlight that incorporating disadvantaged-community constraints lead to longer pipeline routes and increased transport costs, reflecting the trade-offs involved in equitable infrastructure development. It is demonstrated that the newly developed SimH 2 tool not only enables the efficient design of H 2 transportation pipelines but also optimizes the network by accounting for local terrain and the presence of disadvantaged areas.

08 HYDROGEN↗
DOE OSTI2023

Influence of building heat distribution temperatures on the energy performance and sizing of 5th generation district heating and cooling networks

This paper investigates the energy performance and sizing criteria of 5th generation district heating and cooling (5GDHC) networks as a function of the heat distribution temperature in the building systems connected to the district network. An energy simulation model of a 5GDHC network was developed in Modelica for a case study located in Denmark. Calculations were carried out for four different building heating systems. Simulation results show that reducing the heat distribution temperatures from 70 °C to 23 °C leads to around 40% annual electric energy savings (from 10.4 kWh/m 2 to 6.2 kWh/m 2 ) for the operation of the heat pumps. Heat distribution temperatures of 23 °C cause higher water mass flow rates through the network, leading to annual electric energy consumption for the circulation pumps that are almost doubled (from 0.16 kWh/m 2 to 0.3 kWh/m 2 ) compared to the reference case at 70 °C. Furthermore, the paper discusses how the results obtained from the Danish case study can be generalized and applied to other cases using a simplified mathematical approach. In conclusion, it is found that about 1.5% of electric energy savings can be achieved for each temperature degree reduction in the heat distribution system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Risk-Averse Bi-Level Stochastic Network Interdiction Model for Cyber-Security Risk Management

Security of cyber networks is crucial; recent severe cyber-attacks have had a devastating effect on many large organizations. The attack graph, which maps the potential attack paths of a cyber network, is a popular tool for analyzing cyber system vulnerability. In this study, we propose a bi-level stochastic network interdiction model on an attack graph to enable a risk-averse, resource constrained cyber network defender to optimally deploy security countermeasures that protect against attackers with an uncertain budget. This risk- averse conditional-value-at-risk (CVaR) model minimizes a weighted sum of the expected maximum loss over all scenarios and the expected maximum loss from the most damaging attack scenarios. We develop a customized constraint and column generation algorithm to solve our model as well as several acceleration techniques to improve the computational efficiency. Numerical experiments demonstrate that the acceleration techniques enable the solution of relatively large problems within a reasonable amount of time: applying all the acceleration techniques also reduces the average computation time of the basic algorithm by 71% for 100-node graphs. Using metrics called mean-risk value of stochastic solution and value of risk-aversion, computational results suggest that our stochastic risk-averse model significantly outperforms deterministic and risk-neutral models when 1) the distribution of attacker budget is heavy-right-tailed and 2) the defender is highly risk-averse.

Bhuiyan, Tanveer H.↗
DOE OSTI2017

Diffusion in random networks

The ensemble averaging technique is applied to model mass transport by diffusion in random networks. The system consists of an ensemble of random networks, where each network is made of pockets connected by tortuous channels. Inside a channel, fluid transport is assumed to be governed by the one-dimensional diffusion equation. Mass balance leads to an integro-differential equation for the pocket mass density. The so-called dual-porosity model is found to be equivalent to the leading order approximation of the integration kernel when the diffusion time scale inside the channels is small compared to the macroscopic time scale. As a test problem, we consider the one-dimensional mass diffusion in a semi-infinite domain. Because of the required time to establish the linear concentration profile inside a channel, for early times the similarity variable is xt $-$1/4 rather than xt $-$1/2 as in the traditional theory. We found this early time similarity can be explained by random walk theory through the network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Stochastic solution of population balance equations for reactor networks

This work presents a sequential modular approach to solve a generic network of reactors with a population balance model using a stochastic numerical method. Full-coupling to the gas-phase is achieved through operator-splitting. The convergence of the stochastic particle algorithm in test networks is evaluated as a function of network size, recycle fraction and numerical parameters. These test cases are used to identify methods through which systematic and statistical error may be reduced, including by use of stochastic weighted algorithms. The optimal algorithm was subsequently used to solve a one-dimensional example of silicon nanoparticle synthesis using a multivariate particle model. This example demonstrated the power of stochastic methods in resolving particle structure by investigating the transient and spatial evolution of primary polydispersity, degree of sintering and TEM-style images. Highlights: •An algorithm is presented to solve reactor networks with a population balance model. •A stochastic method is used to solve the population balance equations. •The convergence and efficiency of the reported algorithms are evaluated. •The algorithm is applied to simulate silicon nanoparticle synthesis in a 1D reactor. •Particle structure is reported as a function of reactor length and time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Projected network performance for next-generation xenon monitoring systems

Next-generation radioxenon monitoring systems are reaching maturity and are expected to improve certain aspects of performance in verifying the absence of nuclear tests. To predict the improvement in detecting and locating nuclear releases, thousands of releases all over the globe were simulated and the global detection probability was calculated. This was done for the International Monitoring System network of noble gas samplers as it currently exists (25 certified stations), and how it would be for potential future network sizes of 39 and 79 stations. The probability of detection was calculated for releases ranging from 10 10 Bq to 10 16 Bq of 133 Xe and presented as coverage maps and global integrals for both current and next-generation monitoring systems. Similarly, the number of detecting stations and the number of detecting samples were tabulated to elucidate the possibilities for enhanced location capability. Improvements in global detection coverage are maximized at different release sizes in a way that depends on the station density. For example, for releases of 3×10 14 Bq and 39 stations, the detection probability would rise from 60% to 70% with next-generation systems, while for releases of 10 13 Bq and 79 stations, it would rise from 37% to 52%. Achieving an average of two detecting stations requires a 1015 Bq release for a 39-station network and a 10 14 Bq release for a 79-station network. The largest impact of using next-generation systems may be the confidence, failure tolerance, and location capability that arise from obtaining multiple samples associated with a single release event.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

A comparative study of discrete fracture network and equivalent continuum models for simulating flow and transport in the far field of a hypothetical nuclear waste repository in crystalline host rock

One of the major challenges of simulating flow and transport in the far field of a geologic repository in crystalline host rock is related to reproducing the properties of the fracture network over the large volume of rock with sparse fracture characterization data. Various approaches have been developed to simulate flow and transport through the fractured rock. The approaches can be broadly divided into Discrete Fracture Network (DFN) and Equivalent Continuum Model (ECM). The DFN explicitly represents individual fractures, while the ECM uses fracture properties to determine equivalent continuum parameters. In this paper, we compare DFN and ECM in terms of upscaled observed transport properties through generic fracture networks. The major effort was directed on making the DFN and ECM approaches similar in their conceptual representations. This allows for separating differences related to the interpretation of the test conditions and parameters from the differences between the DFN and ECM approaches. The two models are compared using a benchmark test problem that is constructed to represent the far field (1 × 1 × 1 km 3 ) of a hypothetical repository in fractured crystalline rock. The test problem setting uses generic fracture properties that can be expected in crystalline rocks. The models are compared in terms of the: 1) effective permeability of the domain, and 2) nonreactive solute breakthrough curves through the domain. The principal differences between the models are mesh size, network connectivity, matrix diffusion and anisotropy. We demonstrate how these differences affect the flow and transport. Finally, we identify the factors that should be taken in consideration when selecting an approach most suitable for the site-specific conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Characterization of flow and transport in a fracture network at the EGS Collab field experiment through stochastic modeling of tracer recovery

Energy extraction from subsurface reservoirs is important for addressing the increasing energy demand and environmental concerns such as global warming. However, the characterization of subsurface reservoirs, particularly reservoirs dominated by fracture networks remains a challenge due to the lack of means to directly observe subsurface processes. This study explores the feasibility and efficacy of characterizing fracture flow and transport processes in an enhanced geothermal system (EGS) testbed through stochastic tracer modeling. There are two enabling factors that allow application of stochastic modeling to characterize a subsurface reservoir. First, an abundance of geological and geophysical measurements enables the development of a high-fidelity and well-constrained fracture network model. Second, high-performance computing (HPC) allows running massive realizations efficiently. Six conservative tracer tests were stochastically modeled and produced satisfactory realizations that successfully reproduce field tracer recovery data from each tracer test. The evolution of flow and transport processes in the fracture network was then analyzed from these satisfactory realizations. This work demonstrates that stochastic tracer modeling on a high-fidelity fracture network model is feasible and can provide important insights regarding flow and transport characteristics in subsurface fractured reservoirs.

58 GEOSCIENCES↗
DOE OSTI2023

Dynamics of streamflow permanence in a headwater network: Insights from catchment-scale model simulations

The hillslope and channel dynamics that govern streamflow permanence in headwater systems have important implications for ecosystem functioning and downstream water quality. Recent advancements in process-based, semi-distributed hydrologic models that build upon empirical studies of streamflow permanence in well-monitored headwater catchments show promise for characterizing the dynamics of streamflow permanence in headwater systems. However, few process-based models consider the continuum of hillslope-stream network connectivity as a control on streamflow permanence in headwater systems. The objective of this study was to expand a process-based, catchment-scale hydrologic model to better understand the spatiotemporal dynamics of headwater streamflow permanence and to identify controls of streamflow expansion and contraction in a headwater network. Further, we aimed to develop an approach that enhanced the fidelity of model simulations, yet required little additional data, with the intent that the model might be later transferred to catchments with limited long-term and spatially explicit measurements. This approach facilitated network-scale estimates of the controls of streamflow expansion and contraction, albeit with higher degrees of uncertainty in individual reaches due to data constraints. Our model simulated that streamflow permanence was highly dynamic in first-order reaches with steep slopes and variable contributing areas. The simulated stream network length ranged from nearly 98±2% of the geomorphic channel extent during wet periods to nearly 50±10% during dry periods. The model identified a discharge threshold of approximately 1 mm d –1 , above which the rate of streamflow expansion decreases by nearly an order of magnitude, indicating a lack of sensitivity of streamflow expansion to hydrologic forcing during high-flow periods. Overall, we demonstrate that process-based, catchment-scale models offer important insights on the controls of streamflow permanence, despite uncertainties and limitations of the model. We encourage researchers to increase data collection efforts and develop benchmarks to better evaluate such models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A product data network to enable faster, easier, and better planning of building envelopes

The building envelopes contributes significantly to the energy-efficiency of the building. Building performance simulation has made it possible to compare façade technologies regarding energy demand, daylighting, thermal and visual comfort in detail. Planners, such as architects and engineers, need experience to find product data with the right quality and level of detail, and to process the data to fit the calculation and the application. In the available time, planners can compare only a limited number of products, which means that better solutions could go unnoticed. This paper presents a new concept for making product data easily accessible for building façade planning. The concept consists of a network of databases for the efficient exchange and use of optical and calorimetric data of glazing units, shading devices, and combinations of both. The paper presents the research questions, an analysis of the current challenges, six design goals for the product data network and its implementation together with a discussion. Many product data sources can be connected to many planning software applications via the specified application programming interface. When planning software connects to the product data network, the planning of building envelopes can be much faster because planners do not need to spend so much time to search and process product data manually. The planning of building envelopes can also become much easier, especially for planners with limited experience. They do not need to understand all the details about which data fits which calculation if the software company implements this. The planning of building envelopes can become much more reliable when software companies validate their use of the product data network, because the current manual process is prone to errors. The planning of building envelopes can also improve because more products can be compared in the available time, allowing better solutions to be found.

Maurer, Christoph↗
DOE OSTI2024

Complex multicomponent spectrum analysis with Deep Neural Network

Here, in this paper, we present the use of deep neural networks to estimate physical parameters from complex optical emission spectra of the D β /H β transition. Specifically, we focus on estimating the radio frequency electric field vector of the lower hybrid wave and isotope ratio within the scrape-off-layer plasma of the WEST tokamak. Fitting the spectral data using a traditional non-linear least squares analysis requires many free parameters and is computationally expensive, rendering the data unusable for real-time control. By implementing relatively small neural networks, the physical parameters can be directly extracted from the spectral data with reasonable accuracy in a few milliseconds. The deep neural network prediction can serve as input for a reduced model using least-squares fitting or for real-time control. We show that deep neural networks can be an effective tool for analyzing complex multicomponent spectra, providing a speedup of more than 10 5 times compared to least residual analysis, with an accuracy of 0.5% for the isotope ratio, and 0.09 kV/cm and 0.38 kV/cm for the RF radial and poloidal electric field respectively.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

Li{sub 2}Sr{sub 4}B{sub 12}O{sub 23}: A new alkali and alkaline-earth metal mixed borate with [B{sub 10}O{sub 18}]{sup 6-} network and isolated [B{sub 2}O{sub 5}]{sup 4-} unit

A novel ternary lithium strontium borate Li{sub 2}Sr{sub 4}B{sub 12}O{sub 23} crystal with size up to 20 mm Multiplication-Sign 10 mm Multiplication-Sign 4 mm has been grown via the top-seeded solution growth method below 730 Degree-Sign C. Single-crystal XRD analyses showed that Li{sub 2}Sr{sub 4}B{sub 12}O{sub 23} crystallizes in the monoclinic space group P2{sub 1}/c with a=6.4664(4) A, b=8.4878(4) A, c=15.3337(8) A, {beta}=102.02(3) Degree-Sign , Z=2. The crystal structure is composed of [B{sub 10}O{sub 18}]{sup 6-} network and isolated [B{sub 2}O{sub 5}]{sup 4-} unit. The IR spectrum further confirmed the presence of both BO{sub 3} and BO{sub 4} groups. TG-DSC and Transmission spectrum were reported. Band structures and density of states were calculated. - Graphical abstract: A new phase, Li{sub 2}Sr{sub 4}B{sub 12}O{sub 23}, has been discovered in the ternary M{sub 2}O-M Prime O-B{sub 2}O{sub 3} (M=alkali-metal, M Prime =alkalineearth metal) system. The crystal structure consists of [B{sub 10}O{sub 18}]{sup 6-} network and isolated [B{sub 2}O{sub 5}]{sup 4-} unit. Highlights: Black-Right-Pointing-Pointer Li{sub 2}Sr{sub 4}B{sub 12}O{sub 23} is a a novel borate discovered in the M{sub 2}O-M Prime O-B{sub 2}O{sub 3} (M=alkali-metal, M Prime =alkaline-earth metal) system. Black-Right-Pointing-Pointer Li{sub 2}Sr{sub 4}B{sub 12}O{sub 23} crystal structure has a three-dimensional crystal structure with [B{sub 10}O{sub 18}]{sup 6-} network and isolated [B{sub 2}O{sub 5}]{sup 4-} unit. Black-Right-Pointing-Pointer Sr{sub 1} and Sr{sub 2} are located in two different channels constructed by {sup 3}{sub {infinity}}[B{sub 10}O{sub 18}] network.

36 MATERIALS SCIENCE↗
DOE OSTI2013

High pressure synthesis and crystal structure of a ternary superconductor Ca{sub 2}Al{sub 3}Si{sub 4} containing layer structured calcium sub-network isomorphous with black phosphorus

The Zintl compound CaAl{sub 2}Si{sub 2} is peritectically decomposed to a mixture of Ca{sub 2}Al{sub 3}Si{sub 4} and aluminum metal at temperatures above 600 Degree-Sign C under a pressure of 5 GPa. The new ternary compound Ca{sub 2}Al{sub 3}Sl{sub 4} crystalizes with the space group Cmc2{sub 1} and the lattice parameters a=5.8846(8), b=14.973(1), and c=7.7966(5) A. The structure is composed of aluminum silicide framework [Al{sub 3}Si{sub 4}] and layer structured [Ca{sub 2}] network interpenetrating with each other. The electron probe microanalysis (EPMA) shows the formation of solid solutions Ca{sub 2}Al{sub 3-x}Si{sub 4+x} (x<0.6). The layer structured [Ca{sub 2}] sub-network is isomorphous with black phosphorus. The new ternary compound shows superconductivity with a transition temperature (T{sub c}) of 6.4 K. The band structure calculation suggests that the superconductivity should occur through the conduction bands mainly composed of 3p orbitals of the aluminum silicide framework. - Graphical abstract: A new ternary superconductor Ca{sub 2}Al{sub 3}Si{sub 4} has been prepared under high pressure and high temperature conditions, which includes layer structured calcium sub-network isomorphous with black phosphorus. Highlights: Black-Right-Pointing-Pointer A typical Zintl compound CaAl{sub 2}Si{sub 2} melts congruently at ambient pressure. Black-Right-Pointing-Pointer Under high pressure CaAl{sub 2}Si{sub 2} decomposes to Ca{sub 2}Al{sub 3}Si{sub 4} and Al at {approx}600 Degree-Sign C. Black-Right-Pointing-Pointer Ca{sub 2}Al{sub 3}Si{sub 4} contains Ca sub-network isomorphous with black phosphorus. Black-Right-Pointing-Pointer Ca{sub 2}Al{sub 3}Si{sub 4} shows superconductivity with a transition temperature of 6.4 K.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Layered vanadyl (IV) nitroprusside: Magnetic interaction through a network of hydrogen bonds

The hydrogen bond and π-π stacking are two non-covalent interactions able to support cooperative magnetic ordering between paramagnetic centers. This contribution reports the crystal structure and related magnetic properties for VO[Fe(CN){sub 5}NO]·2H{sub 2}O, which has a layered structure. This solid crystallizes with an orthorhombic unit cell, in the Pna2{sub 1} space group, with cell parameters a=14.1804(2), b=10.4935(1), c=7.1722(8) Å and four molecules per unit cell (Z=4). Its crystal structure was solved and refined from powder X-ray diffraction data. Neighboring layers remain linked through a network of hydrogen bonds involving a water molecule coordinated to the axial position for the V atom and the unbridged axial NO and CN ligands. An uncoordinated water molecule is found forming a triple bridge between these last two ligands and the coordinated water molecule. The magnetic measurements, recorded down to 2 K, shows a ferromagnetic interaction between V atoms located at neighboring layers, with a Curie-Weiss constant of 3.14 K. Such ferromagnetic behavior was interpreted as resulting from a superexchange interaction through the network of strong OH····O{sub H2O}, OH····N{sub CN}, and OH····O{sub NO} hydrogen bonds that connects neighboring layers. The interaction within the layer must be of antiferromagnetic nature and it was detected close to 2 K. - Graphical abstract: Coordination environment for the metals in vanadyl (II) nitroprusside dihydrate. Display Omitted - Highlights: • Crystal structure of vanadyl nitroprusside dehydrate. • Network of hydrogen bonds. • Magnetic interactions through a network of hydrogen bonds. • Layered transition metal nitroprussides.

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

Nanosized precipitates and dislocation networks reinforced C-containing CoCrFeNi high-entropy alloy fabricated by selective laser melting

Highlights: • The SML C-containing CoCrFeNi HEA presents cellular and columnar subgrain structures. • The subgrain boundaries are made of dislocation networks with elements segregations. • The nanosized carbides distribute at grain boundary and subgrain boundaries. • The unique structure of the SLM HEA results in an outstanding yield strength. - Abstract: In this paper, we report a selective laser melted C-containing CoCrFeNi high-entropy alloy (HEA) with unique cellular and columnar subgrain structures. The subgrain boundaries are made of dislocation networks decorated by the segregation of Cr element and nanosized M{sub 23}C{sub 6}-type carbides. Structural characterization of dislocations and dislocation reactions in dislocation networks was conducted using high-resolution transmission electron microscopy. The high strength of the C-containing HEA is attributed to dislocation networks strengthening and nanosized carbides strengthening. These findings can provide a guidance for developing HEAs with superior mechanical properties, particularly high strength.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Three-dimensional interconnected nickel phosphide networks with hollow microstructures and desulfurization performance

Graphical abstract: Three-dimensional interconnected nickel phosphide networks with hollow microstructures and desulfurization performance. - Highlights: • Three-dimensional Ni{sub 2}P has been prepared using foam nickel as a template. • The microstructures interconnected and formed sponge-like porous networks. • Three-dimensional Ni{sub 2}P shows superior hydrodesulfurization activity. - Abstract: Three-dimensional microstructured nickel phosphide (Ni{sub 2}P) was fabricated by the reaction between foam nickel (Ni) and phosphorus red. The as-prepared Ni{sub 2}P samples, as interconnected networks, maintained the original mesh structure of foamed nickel. The crystal structure and morphology of the as-synthesized Ni{sub 2}P were characterized by X-ray diffraction, scanning electron microscopy, automatic mercury porosimetry and X-ray photoelectron spectroscopy. The SEM study showed adjacent hollow branches were mutually interconnected to form sponge-like networks. The investigation on pore structure provided detailed information for the hollow microstructures. The growth mechanism for the three-dimensionally structured Ni{sub 2}P was postulated and discussed in detail. To investigate its catalytic properties, SiO{sub 2} supported three-dimensional Ni{sub 2}P was prepared successfully and evaluated for the hydrodesulfurization (HDS) of dibenzothiophene (DBT). DBT molecules were mostly hydrogenated and then desulfurized by Ni{sub 2}P/SiO{sub 2}.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Gas sensor based on three dimensional Bi2S3 nanowires network for ammonia detection at room temperature

Highlights: • Three dimensional Bi{sub 2}S{sub 3} nanowires networks. • High response to NH{sub 3} gas. • Good selectivity. • Wide linear range. • Work at room temperature. - Abstract: A film containing three dimensional Bi{sub 2}S{sub 3} nanowires network was obtained using Bi(NO{sub 3}){sub 3} and thioacetamide as starting materials through three steps, namely the chemical synthesis of Bi{sub 2}S{sub 3}, preparation of its sol under ultrasonic condition and crystal self-assembly at 25 °C. The nanowires had diameters of 20–100 nm. The formation mechanism of the 3D nanowires network is the anisotropic growth of Bi{sub 2}S{sub 3}. The sensor based on 3D Bi{sub 2}S{sub 3} nanowires network with an excellent response to ammonia at 30 °C. The response mechanism of the sensor for ammonia is a weak coordination adsorption of ammonia molecule on the Bi{sub 2}S{sub 3} nanowires and the electron is partially transferred from ammonia molecule to bismuth (III) ion. The maximum response of the sensor to ammonia was up to 82.3 and had a good linear range from 30 to 350 ppm concentration, indicating its potential applications in the determination and leak alarm of ammonia.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗