Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “CHEMICAL FIELD”

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.

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

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Selective detection of heavy metal ions by self assembled chemical field effect transistors

Multiple layer-by-layer sensor material modifications were designed and implemented to achieve selectivity of semiconductor based chemical field effect transistors (ChemFETs) to particular heavy metal ions. The ChemFET sensors were fabricated and modified in three ways, with the intent to initially target first mercury and lead ions and then chromium ions, respectively. Sensor characterization was performed with the gate regions of the sensor elements exposed to different concentrations of target heavy metal ion solutions. A minimum detection level in the range of 0.1 ppm and a 10%–90% response time of less than 10 s were demonstrated. By combining layer-by-layer gold nanoparticles and lead ionophores, a sensor is produced that is sensitive and selective not only to chromium but also to Cr{sup 3+} and Cr{sup 6+}. This result supports the claim that high selectivity can be achieved by designing self-assembled bonding for lead, arsenic, chromium, cesium, mercury, and cadmium.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2004

Measurements of HNO3, SO2 High Resolution Aerosol SO4 (sup 2-), and Selected Aerosol Species Aboard the NASA DC-8 Aircraft: During the Transport and Chemical Evolution Over the Pacific Airborne Mission (TRACE-P)

The UNH investigation during TRACE-P provided measurements of selected acidic gases and aerosol species aboard the NASA DC-8 research aircraft. Our investigation focused on measuring HNO3, SO2, and fine (less than 2 microns) aerosol SO4(sup 2-) with two minute time resolution in near-real-time. We also quantified mixing ratios of aerosol ionic species, and aerosol (210)Pb and (7)Be collected onto bulk filters at better than 10 minute resolution. This suite of measurements contributed extensively to achieving the principal objectives of TRACE-P. In the context of the full data set collected by experimental teams on the DC-8, our observations provide a solid basis for assessing decadal changes in the chemical composition and source strength of Asian continental outflow. This region of the Pacific should be impacted profoundly by Asian emissions at this time with significant degradation of air quality over the next few decades. Atmospheric measurements in the western Pacific region will provide a valuable time series to help quantify the impact of Asian anthropogenic activities. Our data also provide important insight into the chemical and physical processes transforming Asian outflow during transport over the Pacific, particularly uptake and reactions of soluble gases on aerosol particles. In addition, the TRACE-P data set provide strong constraints for assessing and improving the chemical fields simulated by chemical transport models.

Talbot, Robert W.↗
NASA NTRS2017

Quantifying the Causes of Differences in Tropospheric OH Within Global Models

The hydroxyl radical (OH) is the primary daytime oxidant in the troposphere and provides the main loss mechanism for many pollutants and greenhouse gases, including methane (CH4). Global mean tropospheric OH differs by as much as 80% among various global models, for reasons that are not well understood. We use neural networks (NNs), trained using archived output from eight chemical transport models (CTMs) that participated in the Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols and Transport Model Intercomparison Project (POLMIP), to quantify the factors responsible for differences in tropospheric OH and resulting CH4 lifetime (Tau CH4) between these models. Annual average Tau CH4, for loss by OH only, ranges from 8.0 to 11.6 years for the eight POLMIP CTMs. The factors driving these differences were quantified by inputting 3-D chemical fields from one CTM into the trained NN of another CTM. Across all CTMs, the largest mean differences in Tau CH4 (Delta Tau CH4) result from variations in chemical mechanisms (Delta Tau CH4 = 0.46 years), the photolysis frequency (J) of O3 yields O(D-1) (0.31 years), local O3 (0.30 years), and CO (0.23 years). The Delta Tau CH4 due to CTM differences in NO(x) (NO + NO2) is relatively low (0.17 years), although large regional variation in OH between the CTMs is attributed to NO(x). Differences in isoprene and J(NO2) have negligible overall effect on globally averaged tropospheric OH, although the extent of OH variations due to each factor depends on the model being examined. This study demonstrates that NNs can serve as a useful tool for quantifying why tropospheric OH varies between global models, provided that essential chemical fields are archived.

Surface Measurements and Models↗
DOE OSTI2024

Generative Physics-Informed Neural Network Solving Multi-Scale and Multi-Phase Plasma Chemical Flow Field

Low-temperature plasmas (LTPs) are non-equilibrium systems with near-room-temperature gas and highly energetic electrons. This makes them ideal for delicate applications in biomedicine and semiconductor manufacturing, enabling processes like wound healing, sterilization, etching, and plasma-enhanced chemical vapor deposition without thermal damage. However, LTPs involve complex chemistries, with hundreds of species and thousands of reactions, complicating their diagnosis, prediction, and control. Conventional diagnostics, such as Fourier-transform infrared spectroscopy (FTIR), laser-induced fluorescence (LIF), and optical emission spectroscopy (OES), offer limited species detection, while mass spectrometry (MS) struggles with low-sensitivity species. Additionally, LTP simulations face multi-scale challenges, as macroscopic fluid dynamics and microscopic particle collisions operate on vastly different timescales. To address these issues, we developed an artificial intelligence (AI) based diagnostic system: a generative physics-informed neural network (PINN-Gen) that can predict spatially resolved species concentrations and temperatures in LTPs by integrating experimental data from planar LIF with microscopic plasma chemical kinetics and macroscopic fluid mechanics, including plasma-liquid interactions at the interface between two phases. PINN-Gen solves no equations but checks the errors of physical laws by substituting the output from neural network, and the comparison with the experimental results. Thus, it naturally avoids the multi-scale difficulty of numerical simulations and predicts the results of conventionally unsolvable multi-scale and multi-phase problems. The real-time prediction will be robust due to the physical information used in the training of such a neural network, and only very limited input of condition required due to its generative feature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Support to DHS Chemical Detection Field Testing and Countermeasures Studies: Report to Sponsors

This document reports on work that Lawrence Berkeley National Laboratory performed to support the Department of Homeland Security's testing of ARFCAM and LACIS systems. In the sections that follow, LBNL lists the scope of work, field analyses conducted, and preliminary results. LBNL developed a model of the Port Gaston building at the Nevada Test Site and calibrated it using data from field experiments, both blower door and tracer gas tests. Model development and comparison to data show very good agreement. The model was developed to (1) support the interpretation of data from field trials performed by Signature Science LLC, (2) support the placement of sampler equipment, and (3) predict if meteorological differences between the Wet-Run/Dry-Run and the Hot-Run might adversely affect the development of the Hot Run Test Plan. LBNL reported its findings on each task to the experiment team at scheduled planning meetings. In the end, we note that the model was used limitedly because the data from the Wet-Run/Dry Run were if such high quality. Lastly, LBNL conducted a research experiment at the end of the Wet-Run/Dry-Run to study if, and to what degree, specific TICs sorb and desorb on indoor surfaces. We found that several of the TICs either sorb onto surfaces or are lost through chemical reactions. These findings may have important implications on determining sheltering-in-place concepts of operation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Overview of the Alaskan Layered Pollution and Chemical Analysis (ALPACA) Field Experiment

The Alaskan Layered Pollution And Chemical Analysis (ALPACA) field experiment was a collaborative study designed to improve understanding of pollution sources and chemical processes during winter (cold climate and low-photochemical activity), to investigate indoor pollution, and to study dispersion of pollution as affected by frequent temperature inversions. A number of the research goals were motivated by questions raised by residents of Fairbanks, Alaska, where the study was held. This paper describes the measurement strategies and the conditions encountered during the January and February 2022 field experiment, and reports early examples of how the measurements addressed research goals, particularly those of interest to the residents. Outdoor air measurements showed high concentrations of particulate matter and pollutant gases including volatile organic carbon species. During pollution events, low winds and extremely stable atmospheric conditions trapped pollution below 73 m, an extremely shallow vertical scale. Tethered-balloon-based measurements intercepted plumes aloft, which were associated with power plant point sources through transport modeling. Because cold climate residents spend much of their time indoors, the study included an indoor air quality component, where measurements were made inside and outside a house to study infiltration and indoor sources. In the absence of indoor activities such as cooking and/or heating with a pellet stove, indoor particulate matter concentrations were lower than outdoors; however, cooking and pellet stove burns often caused higher indoor particulate matter concentrations than outdoors. The mass-normalized particulate matter oxidative potential, a health-relevant property measured here by the reactivity with dithiothreiol, of indoor particles varied by source, with cooking particles having less oxidative potential per mass than pellet stove particles.

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

Seebeck coefficient and thermal conductivity of doped armchair graphene nanoribbon in the presence of magnetic field

Highlights: • Theoretical calculation of Seebeck coefficient and thermal conductivity of electrons on grapheme nanoribbon. • The investigation of the effect of magnetic field and ribbon width on temperature dependence of thermoelectric properties of nanoribbon. • The study of thermopower as a function of magnetic field and temperature. - Abstract: We address the thermal conductivity and Seebeck coefficient of armchair graphene nanoribbon within tight binding model Hamiltonian in the presence of magnetic field. The possible effects of ribbon width, magnetic field chemical potential on thermoelectric properties are investigated. Green's function approach has been employed in order to calculate transport coefficients of the system. We have also found the temperature dependence of the thermal conductivity for various ribbon widths and chemical potentials. Our results show a peak appears in temperature dependence of thermal conductivity of insulator nanoribbon for low magnetic fields. Upon increasing magnetic field, thermal conductivity shows a monotonic decreasing behavior and peak disappears. Our results show the increase of chemical potential causes to decreasing behavior for thermal conductivity. Moreover we study the effects of magnetic field on temperature behavior of thermopower of insulator graphene nanoribbon in details.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS2004

[Using Molecular Simulations to Understand Complex Nanoscale Dynamic Phenomena in Polymer Solutions]

The first half of the project concentrated on molecular simulation studies of the translocation of model molecules for single-stranded DNA through a nanosized pore. This has resulted in the publication, Translocation of a polymer chain across a nanopore: A Brownian dynamics simulation study, by Pu Tian and Grant D. Smith, JOURNAL OF CHEMICAL PHYSICS VOLUME 119, NUMBER 21 1 DECEMBER 2003, which is attached to this report. In this work we carried out Brownian dynamics simulation studies of the translocation of single polymer chains across a nanosized pore under the driving of an applied field (chemical potential gradient) designed to mimic an electrostatic field. The translocation process can be either dominated by the entropic barrier resulted from restricted motion of flexible polymer chains or by applied forces (or chemical gradient). We focused on the latter case in our studies. Calculation of radius of gyration of the translocating chain at the two opposite sides of the wall shows that the polymer chains are not in equilibrium during the translocation process. Despite this fact, our results show that the one-dimensional diffusion and the nucleation model provide an excellent description of the dependence of average translocation time on the chemical potential gradients, the polymer chain length and the solvent viscosity. In good agreement with experimental results and theoretical predictions, the translocation time distribution of our simple model shows strong non-Gaussian characteristics. It is observed that even for this simple tube-like pore geometry, more than one peak of translocation time distribution can be generated for proper pore diameter and applied field strengths. Both repulsive Weeks-Chandler-Anderson and attractive Lennard-Jones polymer-nanopore interaction were studied. Attraction facilitates the translocation process by shortening the total translocation time and dramatically improve the capturing of polymer chain. The width of the translocation time distribution was found to decrease with increasing temperature, increasing field strength, and decreasing pore diameter.

Smith, Grant↗
DOE OSTI2019

The transmittance and sheet resistance of chemically and heat reduced graphene oxide film

The graphene oxide (GO) sheets were prepared from Hummer’s method. The reduced process is important to graphene related materials for widely functional use in many photoelectric fields. Chemically and heat reduced treatment are carried out in this research and the electrical and optical properties of reduced GO films are measured. The size of GO sheets was examined by transmission electron microscopy with a size of about 5–6 µm. The chemically converted graphene (CCG) film are made by spin coating method. We used different GO concentration and different spin coating times to investigate the properties of graphene transparent conductive films. As the decrease of the GO concentration of solution and the times of spin coating, the transmittance is higher. The electrical property of the mixing of GO and CCG is more stable than the GO sheets only, this is discussed in this research and it is cause by the stacking condition of sheets. The conductivity of reduced graphene oxide film come from GO is lower than that come from CCG, we suppose that is because that the overlapping is less (i.e. film-forming ability) in the former, the transmittance and sheet resistance are 56 T% and 50 kohm/sq.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Spatial profiles of photon chemical potential in near-field thermophotovoltaic cells

Emitted photons stemming from the radiative recombination of electron–hole pairs carry chemical potential in radiative energy converters. This luminescent effect can substantially alter the local net photogeneration in near-field thermophotovoltaic cells. Several assumptions involving the luminescent effect are commonly made in modeling photovoltaic devices; in particular, the photon chemical potential is assumed to be zero or a constant prescribed by the bias voltage. The significance of photon chemical potential depends upon the emitter temperature, the semiconductor properties, and the injection level. Hence, these assumptions are questionable in near-field thermophotovoltaic devices with nanoscale separation distances between the emitter and the cell. In the present work, an iterative solver that combines fluctuational electrodynamics with the drift-diffusion model is developed to tackle the coupled photon and charge transport problem, enabling the determination of the spatial profile of photon chemical potential beyond the detailed balance approach. Here, the difference between the results obtained by allowing the photon chemical potential to vary spatially and by assuming a constant value demonstrates the limitations of the conventional approaches. This study is critically important for performance evaluation of near-field thermophotovoltaic systems with nanoscale vacuum gaps.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2018

Flowback verses first-flush: new information on the geochemistry of produced water from mandatory reporting

Unconventional oil and gas development uses the subsurface injection of large amounts of a variety of industrial chemicals, and there are concerns about the return of these chemical to the surface with water produced with oil and gas from stimulated wells. Produced water, including any flowback of injected fluids, must be managed so as to protect human health and the environment, and understanding the chemistry of produced water from stimulated wells is necessary to ensure the safe management of produced water. In 2014, California instituted mandatory reporting for all well stimulations, including sampling produced water two times and comprehensive chemical characterization of fluids injected and fluids recovered from stimulated wells. In this study, we analyzed data from mandatory reporting with the objective of closing previously identified data gaps concerning oil-field chemical practices and the nature of flowback and produced water from stimulated wells. It was found that the plug-flow conceptual model of flowback developed in shale formations, where salinity increases over time as produced water is extracted, was not appropriate for characterizing produced water from unconventional wells in these oil reservoirs, which are predominately diatomite and sandstones. In these formations stimulation caused a "first-flush" phenomena, where salts and metals were initially high and then decreased in concentration over time, as more produced water was extracted. Although widely applied to meet regulatory requirements, total carbohydrate measurement was not found to be a good chemical indicator of hydraulic fracturing flowback. In conclusion, mandatory reporting closed data-gaps concerning chemical use, provided new information on acid treatments, and allowed more detailed analysis of hydraulic fracturing practices, including comparison of water use by geological formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Unraveling the magnetic properties of BiFe{sub 0.5}Cr{sub 0.5}O{sub 3} thin films

We investigate the structural, chemical, and magnetic properties on BiFe{sub 0.5}Cr{sub 0.5}O{sub 3} (BFCO) thin films grown on (001) (110) and (111) oriented SrTiO{sub 3} (STO) substrates by x-ray magnetic circular dichroism and x-ray diffraction. We show how highly pure BFCO films, differently from the theoretically expected ferrimagnetic behavior, present a very weak dichroic signal at Cr and Fe edges, with both moments aligned with the external field. Chemically sensitive hysteresis loops show no hysteretic behavior and no saturation up to 6.8 T. The linear responses are induced by the tilting of the Cr and Fe moments along the applied magnetic field.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rapid Adaptation of Chemical Named Entity Recognition Using Few-Shot Learning and LLM Distillation

Named entity recognition (NER) has been widely used in chemical text mining for the automatic identification and extraction of chemical entities. However, existing chemical NER systems primarily focus on scenarios with abundant training data, requiring significant human effort on annotations. This poses challenges for applications in the chemical field, such as catalysis, where many advancements have traditionally relied on trial-and-error investigations and incremental adjustment of variables. This hinders catalysis science and technology progress in addressing emerging energy and environmental crises. In this work, we propose a few-shot NER model that can quickly adapt to extract new types of chemical entities by using only a limited number of annotated examples. Our model employs a metric-learning approach to transfer entity similarity knowledge from high-resource chemical domains (with abundant annotations) to enable effective entity recognition in low-resource specialized domains (limited annotation). We validate the effectiveness of our model on a few-shot chemical NER benchmark built based on six existing chemical NER data sets. Experiments show that the proposed few-shot NER model can achieve reasonable performance with only 5 examples per entity type and shows consistent improvement as the number of examples increases. Furthermore, we demonstrate how the proposed model can be trained with large language model (LLM) annotated data, opening a new pathway for rapid adaptation of NER systems. Furthermore, our approach leverages the knowledge broadness of large language models for chemistry while distilling this knowledge into a lightweight model suitable for efficient and in-house use.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2003

Translocation of a Polymer Chain across a Nanopore: A Brownian Dynamics Simulation Study

We carried out Brownian dynamics simulation studies of the translocation of single polymer chains across a nanosized pore under the driving of an applied field (chemical potential gradient). The translocation process can be either dominated by the entropic barrier resulted from restricted motion of flexible polymer chains or by applied forces (or chemical gradient across the wall), we focused on the latter case in our studies. Calculation of radius of gyrations at the two opposite sides of the wall shows that the polymer chains are not in equilibrium during the translocation process. Despite this fact, our results show that the one-dimensional diffusion and the nucleation model provide an excellent description of the dependence of average translocation time on the chemical potential gradients, the polymer chain length and the solvent viscosity. In good agreement with experimental results and theoretical predictions, the translocation time distribution of our simple model shows strong non-Gaussian characteristics. It is observed that even for this simple tubelike pore geometry, more than one peak of translocation time distribution can be generated for proper pore diameter and applied field strengths. Both repulsive Weeks-Chandler-Anderson and attractive Lennard-Jones polymer-nanopore interaction were studied, attraction facilitates the translocation process by shortening the total translocation time and dramatically improve the capturing of polymer chain. The width of the translocation time distribution was found to decrease with increasing temperature, increasing field strength, and decreasing pore diameter.

Tian, Pu↗
DOE OSTI2020

NWPEsSe: an Adaptive-Learning Global Optimization Algorithm for Nanosized Cluster Systems

Global optimization constitutes an important and fundamental problem in theoretical studies in many chemical fields, such as catalysis, materials or separations problems. In this paper, a novel algorithm has been developed for the global optimization of large systems including neat and ligated clusters in gas phase, and supported clusters in periodic boundary conditions. The method is based on an updated artificial bee colony (ABC) algorithm method, that allows for adaptive-learning during the search process. The new algorithm is tested against four classes of systems of diverse chemical nature: gas phase Au_55, ligated Au_8^(2+), Au_8 supported on graphene oxide and defected rutile, and a large cluster assembly ?[Co?_6 Te_8 (PEt_3 )_6][C_60 ]_n, with sizes ranging between 1 to 3 nm and containing up to 1300 atoms. Reliable global minima (GMs) are obtained for all cases, either confirming published data or reporting new lower energy structures. The algorithm and interface to other codes in the form of an independent program, Northwest Potential Energy Search Engine (NWPEsSe), is freely available and it provides a powerful and efficient approach for global optimization of nanosized cluster systems. The work described in this publication was performed at Pacific Northwest National Laboratory (PNNL), which is operated by Battelle for the United States Department of Energy (DOE) under Contract DE-AC05-76RL0180. J. Z. and V.-A. G. acknowledge support from DOE, Office of Science, Office of Basic Energy Sci-ences, Chemical, Geological and Biological Sciences Division and computing resources from PNNL’s Research Computing Facility and the National Energy Research Scientific Computing Center.

Zhang, Jun↗
NASA NTRS2006

Theory of Radiation Transfer in Neutron Star Atmospheres

The possibility for direct investigation of thermal emission from isolated neutron stars opened about a quarter of century ago with the launch of the first X-ray observatories Einstein and EXOSAT stimulated developing models of the neutron star surface radiation which began at the end of 80's. Confronting observational data with theoretical models of thermal emission allows one to infer the surface temperatures, magnetic fields, chemical composition, and neutron star masses and radii. This information, supplemented with the model equations of state and neutron star cooling models, provides an opportunity to understand the fundamental properties of the superdense matter in the stars' interiors. Almost all available models are based on the assumption that thermal radiation emitted by a neutron star is formed in the superficial star's layers--atmosphere. The neutron star atmospheres are very different from those of usual stars due to the immense gravity and huge magnetic fields. In this presentation we review the current status of the neutron star atmosphere modeling, present most important results, discuss problems and possible future developments.

Zavlin, Vyacheslav↗