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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

The reaction O((3)P) + HOBr: Temperature dependence of the rate constant and importance of the reaction as an HOBr stratospheric loss process

The absolute rate constant for the reaction O((3)P) + HOBr has been measured between T = 233K and 423K using the discharge-flow kinetic technique coupled to mass spectrometric detection. The value of the rate coefficient at room temperature is (2.5 +/- 0.6) x 10(exp -11)cu cm/molecule/s and the derived Arrhenius expression is (1.4 +/- 0.5) x 10(exp -10) exp((-430 +/- 260)/T)cu cm/molecule/s. From these rate data the atmospheric lifetime of HOBr with respect to reaction with O((3)P) is about 0.6h at z = 25 km which is comparable to the photolysis lifetime based on recent measurements of the UV cross section for HOBr. Implications for HOBr loss in the stratosphere have been tested using a 1D photochemical box model. With the inclusion of the rate parameters and products for the O + HOBr reaction, calculated concentration profiles of BrO increase by up to 33% around z = 35 km. This result indicates that the inclusion of the O + HOBr reaction in global atmospheric chemistry models may have an impact on bromine partitioning in the middle atmosphere.

Nesbitt, F. L.↗
DOE OSTI2026

Understanding Adsorption and Reactions at Aqueous Oxide Interfaces with Neural Network Potential Molecular Dynamics

Chemical processes at metal oxide−water interfaces are of central importance in geochemistry, biology, and energy technologies. A better understanding of these processes would allow us to make a significant step toward optimizing and controlling them, which could in turn lead to broader impacts. Computational modeling is indispensable to accomplishing this task because complexity and disorder often make it difficult to extract atomistic information from experiments. Balancing computational cost and accuracy, simulation schemes based on efficient machine learning representations of the potential energy surface (PES) predicted by ab initio calculations have become increasingly popular over the past decade. In particular, several studies have demonstrated the ability of machine learning models to accurately reproduce the complex ab initio PESs of aqueous oxide interfaces, allowing simulations of systems and processes that are not accessible with ab initio methods. In this Account, we review our recent efforts to understand adsorption processes and reactions at aqueous oxide interfaces using deep potential molecular dynamics (DPMD), a simulation scheme employing deep neural networks (DNNs), which has proven to be quite successful in accurately describing many different systems in the condensed phase. After summarizing the DPMD methodology, we first review our work on the acid−base chemistry of oxide surfaces in contact with water, a fundamental characteristic that controls proton transfer and surface charge at the interface. We focus on the aqueous interface of rutile IrO 2 , an oxide material thus far considered the best catalyst for the oxygen evolution reaction (OER). We show that this interface is characterized by a large fraction of dissociated water and a strong Brønsted acidity of the surface sites, in good agreement with the experimentally measured value of the point of zero proton charge. In our second example, we investigate how the adsorption of organic species from ambient air or water affects the structure and wettability of the aqueous interfaces of TiO 2 , a prototypical photocatalytic material. This is a question that is relevant to understanding the UV-induced hydrophilicity of TiO 2 surfaces, a property at the basis of self-cleaning windows and related applications. Specifically focusing on formic and acetic acids, the two most common atmospheric organic acids, our simulations reveal that these acids control the wettability of TiO 2 largely through acid−base chemistry at the interface rather than chemisorption on the oxide surface, a finding that could help improve the design of self-cleaning surfaces and photocatalytic devices. Finally, we review our recent study of methanol at TiO 2 −water interfaces, a system whose interest is largely motivated by the role of methanol in enhancing photocatalytic hydrogen evolution on TiO 2 . Our simulations provide mechanistic insights into the coupled roles of the organic adsorbate and water at the TiO 2 interface, with implications for how methanol enhances the activity of H 2 evolution.

adsorption↗
DOE OSTI2026

Opportunities and challenges in process modeling and simulation of electrochemical systems

Electrochemical technologies have garnered intense interest in both academic research and industrial applications due to their potential to increase energy efficiency and reduce carbon footprint. However, electrochemical process fundamentals have been absent from the chemical process simulators available to millions of chemical engineers worldwide. To expedite process research and development of electrochemical technologies in the chemical industry, it is imperative that essential electrochemical process fundamentals be incorporated into process simulators to support modeling and simulation of electrochemical processes. Here, this study examines three process fundamentals key to the research and development of electrochemical processes: electrochemical reaction kinetics, electrolyte thermodynamics, and heat and mass transfer. It further illustrates application of these process fundamentals with a case study modeling an electrochemical process for the conversion of acrylonitrile to adiponitrile. The modeling example highlights the roles of applied voltage on reaction rates, and electron flow rates on the performance of electrochemical processes. It suggests that the applied voltage and electron flow rates are two unique concepts that should be included in simulators for electrochemical processes.

09 BIOMASS FUELS↗
NASA NTRS2003

Theoretical Studies of Chemical Reactions following Electronic Excitation

The use of multi-configurational wave functions is demonstrated for several processes: tautomerization reactions in the ground and excited states of the DNA base adenine, dissociation of glycine molecule after electronic excitation, and decomposition/deformation of novel rare gas molecules HRgF. These processes involve bond brealung/formation and require multi-configurational approaches that include dynamic correlation.

Chaban, Galina M.↗
DOE OSTI2025

Rapid and low‐temperature synthesis of MoAlB MAB phase by using stress‐induced Al‐particles

Abstract Currently, MoAlB particles are produced at 1000°C and higher temperatures. In this manuscript, we report the rapid synthesis of MoAlB by altering the stress of Al particles to affect Al reactivity. The Al particles were purposefully stress‐altered to reduce their threshold for reaction. The stress‐altering process consisted of annealing followed by quenching of the aluminum powder. The combined process caused a reaction at a lower temperature between Mo, B, and Al to form MoAlB. The stress‐altering of Al particles (i.e., Al [TT‐treated]) was effective in producing >95 wt.% MoAlB after reaction at only 700°C for 10 min, a significant reduction in temperature. Based on these results, we can further project that this process can be used for manufacturing Al‐based compositions at significantly lower temperatures.

Dey, Maharshi [Department of Mechanical Engineerin↗
DOE OSTI2026

Spatiotemporal and Statistical Mapping of Transition Metal Equilibria in Alkaline Media

Transition metal dissolution and redeposition (D/R) kinetics in alkaline media play a critical role in various chemical and electrochemical processes. Competitive reaction kinetics between different transition metals can modulate individual metal behavior in these processes. To date, these phenomena have remained largely unmeasured, and even when captured, they are difficult to statistically characterize due to their dynamic nature, simultaneous occurrence, and spatially heterogeneous nature. Here, in this study, we develop a statistical analysis framework based on in situ and operando X-ray fluorescence microscopy (XFM) to investigate the relative D/R kinetics of multiple transition metals in alkaline media. By employing statistical analysis, we quantify the spatial distribution of D/R species and assess the rate at which the system reaches equilibrium under varying reaction conditions. We show that pH does not simply change the rate of dissolution and redeposition, but reorganizes the cross-element kinetic correlations among Ni, Fe, and Mn and accelerates the spatial equilibration of D/R events, as quantified through correlation analysis, reaction-rate estimation, probability function distributions, and texture-based monitoring statistics. Additionally, we demonstrate how modifying the solvent environment can influence D/R kinetics, providing a pathway for tuning materials synthesis and process optimization. Our study offers valuable insights into the complex interplay between different transition metals and provides a reliable statistical framework for spatial analysis of diverse imaging data sets, enabling deeper extraction of latent information across multiple modalities.

36 MATERIALS SCIENCE↗
NASA NTRS1979

Formation of porous surface layers in reaction bonded silicon nitride during processing

An effort was undertaken to determine if the formation of the generally observed layer of large porosity adjacent to the as-nitride surfaces of reaction bonded silicon nitrides could be prevented during processing. Isostatically pressed test bars were prepared from wet vibratory milled Si powder. Sintering and nitriding were each done under three different conditions:(1) bars directly exposed to the furnance atmosphere; (2) bars packed in Si powder; (3) bars packed in Si3N4 powder. Packing the bars in either Si of Si3N4 powder during sintering retarded formation of the layer of large porosity. Only packing the bars in Si prevented formation of the layer during nitridation. The strongest bars (316 MPa) were those sintered in Si and nitrided in Si3N4 despite their having a layer of large surface porosity; failure initiated at very large pores and inclusions. The alpha/beta ratio was found to be directly proportional to the oxygen content; a possible explanation for this relationship is discussed.

Shaw, N. J.↗
NASA NTRS1982

Mathematical and physical modelling of materials processing

Mathematical and physical modeling of turbulence phenomena in metals processing, electromagnetically driven flows in materials processing, gas-solid reactions, rapid solidification processes, the electroslag casting process, the role of cathodic depolarizers in the corrosion of aluminum in sea water, and predicting viscoelastic flows are described.

Source record↗
DOE OSTI2021

Processing and microstructure of ZrB 2 –SiC composite prepared by reactive spark plasma sintering

In-situ formation of ZrB 2 –SiC composites was investigated by reactive spark plasma sintering of precursor powders according to the reaction B4C + 2ZrC + 3Si → 3SiC + 2ZrB 2 . The reaction and process presented here involves a diffusion reaction between B4C and ZrC which facilitates the formation of ZrB 2 , while liquid phase sintering of silicon facilitates atomic diffusion and combines with free C from the B4C and ZrC reaction to form SiC within minutes of heating and there were some residual unreacted precursor materials. An interpenetrating matrix of ZrB 2 –SiC was formed that shows increased fracture toughness (6.03 ± 0.45 MPa m 1/2 ) despite relatively low density (95 %).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nitrogen-doped char as a catalyst for wet oxidation of phenol-contaminated water

Catalytic wet oxidation (CWO) of aqueous effluents rich in organic compounds is a very promising technology for the treatment of liquid wastes from biomass conversion processes. CWO reactions occur through the formation of free radical species, produced in the presence of an oxidant, which act on organic contaminates in the effluent. Although the reaction is well known, there exists a lack of affordable catalysts to conduct this process at the lower temperatures and pressures in novel bioenergy processes. Here, this study assessed the catalytic effect of nitrogen-doped chars as such an option. Phenol in aqueous solution was used as a model waste effluent. Treatment was conducted at moderate temperatures (190 to 260 °C), oxygen partial pressure of 1 MPa, and reaction times of 15, 30, and 45 min in stainless steel and glass-lined tube reactors. High pressure liquid chromatography (HPLC) analyses of the products quantified phenol and by-product concentrations used in the calculation of reaction activation energy. The char catalyst was studied by X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), and scanning electron microscopy (SEM) in order to gain insight into its structure and surface composition. The results indicate that nitrogen-doped char catalysts accelerate the oxidation of phenol by decreasing its reaction activation energy from 82.2 kJ/mol (non-catalyzed) to 40.4 kJ/mol (catalyzed). An analysis from first principles using density functional theory (DFT) was conducted to ascertain which N functional group has the most significant impact on free radical formation in the presence of oxygen. Among all the N functional groups studied, the dipyridinic functional groups showed the most promising characteristics to facilitate the formation of hydroxyl free radicals.

Advanced Oxidation Processes for Organic Pollutant↗
NASA NTRS2011

Network-Capable Application Process and Wireless Intelligent Sensors for ISHM

Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This invention enables wide-area sensing and employs numerous globally distributed sensing devices that observe the physical world through the existing sensor network. This innovation enables distributed storage, distributed processing, distributed intelligence, and the availability of DiaK (Data, Information, and Knowledge) to any element as needed. It also enables the simultaneous execution of multiple processes, and represents models that contribute to the determination of the condition and health of each element in the system. The NCAP (intelligent process) can configure data-collection and filtering processes in reaction to sensed data, allowing it to decide when and how to adapt collection and processing with regard to sophisticated analysis of data derived from multiple sensors. The user will be able to view the sensing device network as a single unit that supports a high-level query language. Each query would be able to operate over data collected from across the global sensor network just as a search query encompasses millions of Web pages. The sensor web can preserve ubiquitous information access between the querier and the queried data. Pervasive monitoring of the physical world raises significant data and privacy concerns. This innovation enables different authorities to control portions of the sensing infrastructure, and sensor service authors may wish to compose services across authority boundaries.

Figueroa, Fernando↗
DOE OSTI2026

Kinetic model development for single step ethanol to butene rich olefin process over Cu-Y/Beta catalysts

Here, this study presents the first intrinsic kinetic model for the single-step conversion of ethanol to butene-rich olefins over bifunctional Cu-Y/Beta catalysts, addressing a critical gap in the design and scale-up of Sustainable Aviation Fuel (SAF) processes. The reaction network comprises ten global steps involving dehydrogenation, aldol condensation, hydrogenation, and dehydration reactions, distributed across Cu and rare-earth (Y) active sites. The model incorporates dual-site functionality (Cu and Y site) and explicitly accounts for key intermediates such as crotonaldehyde and butanal. Reaction rates are formulated using Langmuir–Hinshelwood–Hougen–Watson (LHHW) kinetics. Kinetic parameters are extracted by fitting the model to lab-scale packed-bed reactor data across a wide range of temperatures and space velocities, demonstrating strong agreement in ethanol conversion and product selectivity. The reaction kinetics developed in this work provide a foundational basis for constructing reactor models that enable process optimization and scale-up of ethanol-to-jet fuel technologies.

Cu-Y/Beta catalyst↗
NASA NTRS1973

Wash water recovery system

The Wash Water Recovery System (WWRS) is intended for use in processing shower bath water onboard a spacecraft. The WWRS utilizes flash evaporation, vapor compression, and pyrolytic reaction to process the wash water to allow recovery of potable water. Wash water flashing and foaming characteristics, are evaluated physical properties, of concentrated wash water are determined, and a long term feasibility study on the system is performed. In addition, a computer analysis of the system and a detail design of a 10 lb/hr vortex-type water vapor compressor were completed. The computer analysis also sized remaining system components on the basis of the new vortex compressor design.

Deckman, G.↗
DOE OSTI2022

Methods for the production of cathode materials for lithium ion batteries

The present disclosure provides methods for producing cathode materials for lithium ion batteries. Cathode materials that contain manganese are emphasized. Representative materials include LixNi1-y-zMnyCozO2 (NMC) (where x is in the range from 0.80 to 1.3, y is in the range from 0.01 to 0.5, and z is in the range from 0.01 to 0.5), LixMn2O4 (LM), and LixMn2-yNiyO2 (LMN) (where x is in the range from 0.8 to 1.3 and y is in the range from 0.0 to 0.8). The process includes reactions of carboxylate precursors of nickel, manganese, and/or cobalt and lithiation with a lithium precursor. The carboxylate precursors are made from reactions of pure metals or metal compounds with carboxylic acids. The manganese precursor contains bivalent manganese and the process controls the oxidation state of manganese to avoid formation of higher oxidation states of manganese.

Huang, Baoquan↗
DOE OSTI2022

Methods for the production of cathode materials for lithium ion batteries

The present disclosure provides methods for producing cathode materials for lithium ion batteries. Cathode materials that contain manganese are emphasized. Representative materials include Li x Ni 1-y-z Mn y Co z O 2M (NMC) (where x is in the range from 0.80 to 1.3, y is in the range from 0.01 to 0.5, and z is in the range from 0.01 to 0.5), Li x Mn 2 O 4 (LM), and Li x Ni 1-y Mn y O 2 (LMN) (where x is in the range from 0.8 to 1.3 and y is in the range from 0.0 to 0.8). The process includes reactions of carboxylate precursors of nickel, manganese, and/or cobalt and lithiation with a lithium precursor. The carboxylate precursors are made from reactions of pure metals or metal compounds with carboxylic acids. The manganese precursor contains bivalent manganese and the process controls the oxidation state of manganese to avoid formation of higher oxidation states of manganese.

Huang, Baoquan↗
DOE OSTI2023

Methods for the production of cathode materials for lithium ion batteries

The present disclosure provides methods for producing cathode materials for lithium ion batteries. Cathode materials that contain manganese are emphasized. Representative materials include Li x Ni 1−y−z Mn y Co z O 2 (NMC) (where x is in the range from 0.80 to 1.3, y is in the range from 0.01 to 0.5, and z is in the range from 0.01 to 0.5), Li x Mn 2 O 4 (LM), and Li x Ni 1−y Mn y O 2 (LMN) (where x is in the range from 0.8 to 1.3 and y is in the range from 0.0 to 0.8). The process includes reactions of carboxylate precursors of nickel, manganese, and/or cobalt and lithiation with a lithium precursor. The carboxylate precursors are made from reactions of pure metals or metal compounds with carboxylic acids. The manganese precursor contains bivalent manganese and the process controls the oxidation state of manganese to avoid formation of higher oxidation states of manganese.

Huang, Baoquan↗
DOE OSTI2021

Data-driven chemical kinetic reaction mechanism for F-24 jet fuel ignition

A data-driven chemical kinetic mechanism for the military version of Jet A, F-24, is developed for numerical simulations of the ignition process. The main purpose of this study is to obtain a practical F-24 mechanism across wide temperature and equivalence ratio ranges, with a particular focus on the negative temperature coefficient and low temperature regions. The new mechanism (ARLMech-HC-F24) is based on the HyChem model of a similar fuel and optimized using a micro-genetic algorithm against an experimental ignition delay data set of the target fuel. The development and optimization processes include reaction selection, population creation, shuffled tournament implementation based on a merit function, and child-individual creation for the next generation. Several techniques and parameters are proposed to generate an accurate mechanism through an efficient process. The newly introduced data-driven mechanism based on these techniques shows better merit value convergence and represents the ignition behavior more accurately than that without the techniques. This practical mechanism is suitable for the numerical simulations of the F-24 or Jet A ignition problem, and the suggested strategies can be employed in similar problems of rate coefficients estimation.

42 ENGINEERING↗