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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Traveling Weather Disturbances in Mars Southern Extratropics: Sway of the Great Impact Basins

As on Earth, between late autumn and early spring on Mars middle and high latitudes within its atmosphere support strong mean thermal contrasts between the equator and poles (i.e. "baroclinicity"). Data collected during the Viking era and observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that this strong baroclinicity supports vigorous, large-scale eastward traveling weather systems (i.e. transient synoptic-period waves). Within a rapidly rotating, differentially heated, shallow atmosphere such as on Earth and Mars, such large-scale, extratropical weather disturbances are critical components of the global circulation. These wave-like disturbances act as agents in the transport of heat and momentum, and moreover generalized tracer quantities (e.g., atmospheric dust, water vapor and water-ice clouds) between low and high latitudes of the planet. The character of large-scale, traveling extratropical synoptic-period disturbances in Mars' southern hemisphere during late winter through early spring is investigated using a high-resolution Mars global climate model (Mars GCM). This global circulation model imposes interactively lifted (and radiatively active) dust based on a threshold value of the instantaneous surface stress. Compared to observations, the model exhibits a reasonable "dust cycle" (i.e. globally averaged, a more dusty atmosphere during southern spring and summer occurs). In contrast to their northern-hemisphere counterparts, southern synoptic-period weather disturbances and accompanying frontal waves have smaller meridional and zonal scales, and are far less intense synoptically. Influences of the zonally asymmetric (i.e. east-west varying) topography on southern large-scale weather disturbances are examined. Simulations that adapt Mars' full topography compared to simulations that utilize synthetic topographies emulating essential large-scale features of the southern middle latitudes indicate that Mars' transient barotropic/baroclinic eddies are significantly influenced by the great impact basins of this hemisphere (e.g., Argyre and Hellas). In addition, the occurrence of a southern storm zone in late winter and early spring is keyed particularly to the western hemisphere via orographic influences arising from the Tharsis highlands, and the Argyre and Hellas impact basins. Geographically localized transient-wave activity diagnostics are constructed that illuminate fundamental differences amongst such simulations and these are described.

Weather disturbances↗
NASA NTRSDate not supplied

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight frameworks is paramount for establishing an effective architecture for autonomous systems. Hardware test flights are time-consuming and cost prohibitive during early system design and development. Simulation environments can be useful tools to accelerate algorithm development and testing. However, transitions from simulation to flight (sim-to-flight) can be challenging, unless systems are designed with this transition in mind and with the necessary capabilities built into the architecture and framework. One of the objectives of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. ATTRACTOR’s objective was to construct computational concepts of trustworthiness and justifiable trust in multi-agent autonomous teams, to inform future certification of safety-critical and time-critical autonomous systems in aviation. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation (ModSim) environment for test and evaluation of autonomous systems. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single-and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. The Autonomous Entity Operational Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications, enabling sim-to-flight with minimal configuration changes. Using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley↗
DOE OSTI2022

Adsorption and exchange reactions of iodine molecules at the alumina surface: modelling alumina-iodine reaction mechanisms

Harnessing aluminum oxidation energy requires navigating the particle's passivation shell composed of alumina. The shell is a barrier to aluminum oxidation but can also exothermically react with halogenated species and therefore contribute to the overall energy generated during aluminum particle combustion. Fluorination reactions with alumina have been studied because fluorine is abundant in binder formulations that commonly surround aluminum particles in an energetic mixture. However, iodine has emerged as an alternative halogenated-based binder or oxidizer because iodine gas provides ancillary benefits such as chemical neutralization of biological agents or sterilization of contaminated environments. Furthermore, this study used density functional theory (DFT) calculations to evaluate potential reaction pathways for aluminum–iodine combustion. Relative to fluorinated fragments such as HF and F – , the adsorption energies associated with HI and I– are nearly triple the exchange reaction energy available from fluorination reactions with alumina (–189 and –278 kJ mol –1 for HI and I – , respectively). However, exchange reactions between iodinated species and the alumina surface are energetically unfavorable. These results explain that through adsorption, alumina surface exothermic reactions with iodine are more energetic than with fluorine fragments. Experiments performed with differential scanning calorimetry (DSC) confirm the higher magnitude of energy generated for iodination compared with fluorination reactions with alumina. Additionally, strong adsorption energies can promote synthesis of new shell chemistries. Adsorption in solution will promote alumina dissolution and iodine precipitation reactions to produce hydroxyl complexes and iodinated species synthesized on the surface of the particle, thereby replacing alumina with alternative passivation shell chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Pedestrian-Involved Traffic Signal Optimization Using Decentralized Graph-based Multi-Agent Reinforcement Learning

Incorporating pedestrian movements in traffic signal timing optimization is essential for ensuring smooth and safe urban transportation systems. To develop an effective signal timing plan, it is crucial to comprehend how various pedestrian accommodation strategies impact both vehicle and pedestrian flow. This study explores the application of the Decentralized Graph-based Multi-Agent Reinforcement Learning (DGMARL) method for signal timing optimization. It considers both pedestrian and vehicle traffic state and assesses the effects of fixed and adaptive pedestrian request response on traffic and signal timing. The evaluation of DGMARL encompasses vehicles Eco_PI which is fuel consumption impact related to vehicle stops and stop delay, and pedestrian waiting time to ensure overall system efficiency. The proposed approach was evaluated using a Digital Twin microscopic traffic simulation model of MLK Smart Corridor in Chattanooga, Tennessee. The evaluation outcomes of vehicles Eco_PI, pedestrian waiting time and serving time are compared with the actuated and DGMARL signal timing with fixed pedestrian recall and minimum recall to determine the most suitable approaches for various traffic conditions. The results indicated that, on average, the strategy of Signal timing optimization with adaptive pedestrian request response improved the Eco_PI by 32.43%, and Signal timing optimization with both automated pedestrian traffic demand and adaptive pedestrian request response improved the Eco_PI by 31.62% compared to the actuated and DGMARL signal timing with fixed pedestrian recall and minimum recall.

K Kumarasamy, Vijayalakshmi↗
NASA NTRS2015

An Integrated Framework for Modeling Air Carrier Behavior, Policy, and Impacts in the U.S. Air Transportation System

The implementation of the Next Generation Air Transportation System (NextGen) in the United States is an ongoing challenge for policymakers due to the complexity of the air transportation system (ATS) with its broad array of stakeholders and dynamic interdependencies between them. The successful implementation of NextGen has a hard dependency on the active participation of U.S. commercial airlines. To assist policymakers in identifying potential policy designs that facilitate the implementation of NextGen, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework called the Air Transportation System Evolutionary Simulation (ATS-EVOS). This framework integrates large empirical data sets with multiple specialized models to simulate the evolution of the airline response to potential future policies and explore consequential impacts on ATS performance and market dynamics. In the ATS-EVOS configuration presented here, we leverage the Transportation Systems Analysis Model (TSAM), the Airline Evolutionary Simulation (AIRLINE-EVOS), the Airspace Concept Evaluation System (ACES), and the Aviation Environmental Design Tool (AEDT), all of which enable this research to comprehensively represent the complex facets of the ATS and its participants. We validated this baseline configuration of ATS-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments that explored potential implementations of a carbon tax, congestion pricing policy, and the dynamics for equipage of new technology by airlines. These experiments demonstrated ATS-EVOS's capabilities in responding to a wide range of potential NextGen-related policies and utility for decision makers to gain insights for effective policy design.

Horio, Brant M.↗
NASA NTRSDate not supplied

Development of Micro Pulse Lidar Network (MPLNET) Level 3 Satellite Validation Products in Advance of the EarthCARE Mission

Assessing the cirrus cloud radiative effect is crucial to establish their feedback on the Earth- atmosphere system. For this reason, cirrus clouds are of paramount importance in climate. Moreover, these tiny ice clouds are the most common cloud gene, continuously covering 30% of the Earth’s surface, peaking to 70% in the tropical and equatorial regions. The same authors, in three different recent studies, assessed the yearly cirrus cloud radiative effects characteristics for different NASA MPLNET permanent observational sites, deployed at different latitudes, e. g. Goddard Space Flight Center, Singapore, and Fairbanks Alaska. The analysis put in evidence that the cirrus cloud can be both cooling or warming agents of the Earth-atmosphere system during the daytime, depending on their latitude. The cirrus clouds are warming agents in equatorial/tropical regions because of the higher averaged solar zenith angle, and become neutral at mid-latitudes. At polar latitudes instead, cirrus clouds become cooling agents because of the lower solar zenith angle. In this analysis instead, using the Fu-Liou-Gu radiative transfer model, we assess how the cirrus cloud radiative effects, both at the top of the atmosphere and surface, changed over twenty years. The analysis is extended also to evaluate also changes in cloud optical depth over the same period. This is unprecedented research, because to our knowledge, no other analysis has been carried out from ground-based measurement for such a long period. As a future perspective, the analysis will be repeated for the different observational sites of the MPLNET lidar network to evaluate cirrus cloud radiative effects at a global scale.

Jasper R. Lewis↗
DOE OSTI2025

Nanolipoprotein particle (NLP) vaccine confers protection against Yersinia pestis aerosol challenge in a BALB/c mouse model

Introduction: Yersinia pestis is the etiological agent of plague, a disease that remains a concern as demonstrated by recent outbreaks in Madagascar. Infection with Y. pestis results in a rapidly progressing illness that can only be successfully treated with antibiotics given shortly after symptom onset. Live attenuated or whole cell inactivated vaccines confer protection against bubonic plague, but pneumonic plague has been more difficult to prevent. Novel effective subunit vaccine formulations may circumvent some of these shortfalls. Here, we compare the immunogenicity generated by an advanced subunit vaccine (F1V fusion protein) and a nanolipoprotein particle (NLP)-based vaccine. Methods: The NLP, a high-density lipoprotein mimetic, provides a nanoscale delivery platform for recombinant Y. pestis antigens LcrV (V) and F1. BALB/c mice were immunized via subcutaneous injection twice, three or four weeks apart. Four weeks later, splenocytes and sera were collected for immune profiling, and mice were challenged with aerosolized Y. pestis CO92. Results: Both formulations induced a strong IgG response against the F1 and V proteins, along with a robust memory B cell response and a balanced cell-mediated immune response as evidenced by both Th1- and Th2-related cytokines. The NLP-based vaccine induced a stronger cytokine response against F1, V, and F1V proteins relative to the F1V vaccine. As with F1V, the inclusion of Alhydrogel (Alu) in NLP vaccine formulations was critical for enhanced immunogenicity and protective efficacy. Mice that received two doses of F1:V:NLP + Alu and CpG were completely protected from a challenge with approximately eight median lethal doses of aerosolized Y. pestis CO92 and this protection confirmed the well-documented synergy between the F1 and V antigens in context of pneumonic plague. The NLPs have defined regions of polarity that facilitates the incorporation of a wide range of adjuvants and antigens with distinct physicochemical properties and are an excellent candidate platform for the development of multi-antigen vaccines.

F1↗
DOE OSTI2020

Mechanism of Catalysis by L -Asparaginase

Two bacterial type II L -asparaginases, from Escherichia coli and Dickeya chrysanthemi, have played a critical role for more than 40 years as therapeutic agents against juvenile leukemias and lymphomas. Despite a long history of successful pharmacological applications and the apparent simplicity of the catalytic reaction, controversies still exist regarding major steps of the mechanism. In this report, we provide a detailed description of the reaction catalyzed by E. coli type II L -asparaginase (EcAII). Our model was developed on the basis of new structural and biochemical experiments combined with previously published data. The proposed mechanism is supported by quantum chemistry calculations based on density functional theory. In this work, we provide strong evidence that EcAII catalyzes the reaction according to the double-displacement (ping-pong) mechanism, with formation of a covalent intermediate. Several steps of catalysis by EcAII are unique when compared to reactions catalyzed by other known hydrolytic enzymes. Here, the reaction is initiated by a weak nucleophile, threonine, without direct assistance of a general base, although a distant general base is identified. Furthermore, tetrahedral intermediates formed during the catalytic process are stabilized by a never previously described motif. Although the scheme of the catalytic mechanism was developed only on the basis of data obtained from EcAII and its variants, this novel mechanism of enzymatic hydrolysis could potentially apply to most (and possibly all) L -asparaginases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure

Disease surveillance systems allow public health agencies to respond to emerging diseases before they become widespread. Developing such systems requires identifying optimal ways to monitor in the context of an epidemic outbreak; this problem is known as sensor selection. Contact networks represent the dynamics of interaction in a population and are used to model how a disease spreads in a population and to explore strategies of sensor selection. We evaluated five sensor selection strategies on their ability to provide an early warning of a COVID-like outbreak in synthetic contact networks encapsulated in four network scenarios. Three of these scenarios assessed different aspects of community structure. The fourth scenario employed a contact network representing the population and interactions of 6.8 million people in New York City, constructed from an agent-based simulation using census and transportation data. This scenario exemplifies how sensor selection strategies may perform in a real-world, urban context. Our findings suggest that the choice of the optimal strategy depends heavily on the community structure of the network. Strategies that select highly connected nodes or maximize network coverage are the optimal surveillance strategy for outbreak detection in many network community structures. However, a naive implementation of these strategies may fail to provide an early warning at all—including in the New York City scenario. Moreover, these methods are impractical for real-world use as they require knowledge of the underlying contact network. Instead, a selection strategy that starts with a set of random nodes and then performs a random walk through a chain of neighbors reliably provides early warnings without requiring prior knowledge of the network. We find this method, called “random chain”, to be the most pragmatic for implementation in a real-world disease surveillance context.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1972

Mechanisms of deterioration of intermediate moisture food systems

A study of shelf stability in intermediate moisture foods was made. Major efforts were made to control lipid oxidation and nonenzymatic browning. In order to determine means of preventing these reactions, model systems were developed having the same water activity content relationship of intermediate moisture foods. Models were based on a cellulose-lipid and protein-lipid system with glycerol added as the humectant. Experiments with both systems indicate that lipid oxidation is promoted significantly in the intermediate moisture range. The effect appeared to be related to increased mobility of either reactants or catalysts, since when the amount of water in the system reached a level where capillary condensation occurred and thus free water was present, the rates of oxidation increased. With added glycerol, which is water soluble and thus increases the amount of mobile phase, the increase in oxidation rate occurs at a lower relative humidity. The rates of oxidation were maximized at 61% RH and decreased again at 75% RH probably due to dilution. No significant non-enzymatic browning occurred in the protein-lipid systems. Prevention of oxidation by the use of metal chelating agents was enhanced in the cellulose system, whereas, with protein present, the lipid soluble chain terminating antioxidants (such as BHA) worked equally as well. Preliminary studies of foods adjusted to the intermediate moisture range bear out the results of oxidation in model systems. It can be concluded that for most fat containing intermediate moisture foods, rancidity will be the reaction most limiting stability.

Labuza, T. P.↗
NASA NTRS2002

Purification method for recombinant proteins based on a fusion between the target protein and the C-terminus of calmodulin

Calmodulin (CaM) was used as an affinity tail to facilitate the purification of the green fluorescent protein (GFP), which was used as a model target protein. The protein GFP was fused to the C-terminus of CaM, and a factor Xa cleavage site was introduced between the two proteins. A CaM-GFP fusion protein was expressed in E. coli and purified on a phenothiazine-derivatized silica column. CaM binds to the phenothiazine on the column in a Ca(2+)-dependent fashion and it was, therefore, used as an affinity tail for the purification of GFP. The fusion protein bound to the affinity column was then subjected to a proteolytic digestion with factor Xa. Pure GFP was eluted with a Ca(2+)-containing buffer, while CaM was eluted later with a buffer containing the Ca(2+)-chelating agent EGTA. The purity of the isolated GFP was verified by SDS-PAGE, and the fluorescence properties of the purified GFP were characterized.

Non-NASA Center↗
NASA NTRS1989

A prototype autonomous agent for crew and equipment retrieval in space

The ground-based demonstration of Extra Vehicular Activity (EVA) Retriever, a voice-supervised, intelligent, free-flying robot, is designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The EVA Retriever software is required to autonomously plan and execute a target rendezvous, grapple, and return to base while avoiding stationary and moving obstacles. The software architecture incorporates a hierarchical decomposition of the control system that is horizontally partitioned into five major functional subsystems: perception, world model, reasoning, sensing, and acting. The design provides for supervised autonomy as the primary mode of operation with teleoperation as the backup mode. It is intended to be an evolutionary system improving in capability over time and as it earns crew trust through reliable operation.

Erickson, J. D.↗
DOE OSTI2026

Surrogates for Valve-Controlled Pipe Flow: Accelerating Nuclear Reactor Design

Neural surrogate models are developed to replace expensive steady-state RANS CFD simulations for valve-controlled pipe flow in nuclear reactor design. Using parametric CFD data generated with MOOSE Pronghorn across a range of valve geometry and flow conditions, three approaches are compared: a POD-based reduced-order model, a structured UNet on a cylindrical grid, and unstructured models (DeepONet and BiStride MeshGraphNet) on nondimensionalized point clouds. POD achieves the highest accuracy (99%) with fast inference but requires storing all solution snapshots, while the DeepONet and BSMS-GNN both achieve ~89% accuracy at sub-second inference, with the BSMS-GNN offering superior geometric generalizability. These surrogates enable rapid ranking of candidate valve designs and can warm-start CFD solvers to accelerate convergence, supporting agentic design iteration on the Prometheus platform.

42 - ENGINEERING↗
DOE OSTI2020

Estimation of Large-Scale Wind Field Characteristics Using Supervisory Control and Data: Preprint

As the wind energy industry continues to pushfor increased power production and lower cost of energy, thefocus of research has expanded from individual turbines toentire wind farms. Among a host of interesting problems to besolved when considering the wind farm as a whole, we considerthe challenge of scalar field estimation, based on informationalready collected at the individual turbine level. We aim toestimate the large-scale, low-frequency characteristics of thewind field, such as the mean wind direction and the overalldecrease in wind speed across the farm, and employ a Kalmanfilter that models the wind field using a polynomial function.We compare the proposed method’s performance to both asimple averaging technique and filtering of individual turbinemeasurements. The method presented is not limited to windturbines and is applicable in other situations where multipleremote agents are used to estimate a scalar field.

large scale↗
DOE OSTI2020

Localization of fluorescent targets in deep tissue with expanded beam illumination for studies of cancer and the brain

Imaging fluorescence through millimeters or centimeters of tissue has important in vivo applications, such as guiding surgery and studying the brain. Often, the important information is the location of one of more optical reporters, rather than the specifics of the local geometry, motivating the need for a localization method that provides this information. We present an optimization approach based on a diffusion model for the fast localization of fluorescent inhomogeneities in deep tissue with expanded beam illumination that simplifies the experiment and the reconstruction. We show that the position of a fluorescent inhomogeneity can be estimated while assuming homogeneous tissue parameters and without having to model the excitation profile, reducing the computational burden and improving the utility of the method. We perform two experiments as a demonstration. First, a tumor in a mouse is localized using a near infrared folate-targeted fluorescent agent (OTL38). This result shows that localization can quickly provide tumor depth information, which could reduce damage to healthy tissue during fluorescence-guided surgery. Second, another near infrared fluorescent agent (ATTO647N) is injected into the brain of a rat, and localized through the intact skull and surface tissue. This result will enable studies of protein aggregation and neuron signaling.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2003

Principles for Integrating Mars Analog Science, Operations, and Technology Research

During the Apollo program, the scientific community and NASA used terrestrial analog sites for understanding planetary features and for training astronauts to be scientists. Human factors studies (Harrison, Clearwater, & McKay 1991; Stuster 1996) have focused on the effects of isolation in extreme environments. More recently, with the advent of wireless computing, we have prototyped advanced EVA technologies for navigation, scheduling, and science data logging (Clancey 2002b; Clancey et al., in press). Combining these interests in a single expedition enables tremendous synergy and authenticity, as pioneered by Pascal Lee's Haughton-Mars Project (Lee 2001; Clancey 2000a) and the Mars Society s research stations on a crater rim on Devon Island in the High Canadian Arctic (Clancey 2000b; 2001b) and the Morrison Formation of southeast Utah (Clancey 2002a). Based on this experience, the following principles are proposed for conducting an integrated science, operations, and technology research program at analog sites: 1) Authentic work; 2) PI-based projects; 3) Unencumbered baseline studies; 4) Closed simulations; and 5) Observation and documentation. Following these principles, we have been integrating field science, operations research, and technology development at analog sites on Devon Island and in Utah over the past five years. Analytic methods include work practice simulation (Clancey 2002c; Sierhuis et a]., 2000a;b), by which the interaction of human behavior, facilities, geography, tools, and procedures are formalized in computer models. These models are then converted into the runtime EVA system we call mobile agents (Clancey 2002b; Clancey et al., in press). Furthermore, we have found that the Apollo Lunar Surface Journal (Jones, 1999) provides a vast repository or understanding astronaut and CapCom interactions, serving as a baseline for Mars operations and quickly highlighting opportunities for computer automation (Clancey, in press).

Clancey, William J.↗
NASA NTRS2021

Developing a Set of Indicators to Identify, Monitor, and Track Impacts and Change in Forests of the United States

United States forestland is an important ecosystem type, land cover, land use, and economic resource that is facing several drivers of change including climatic. Because of its significance, forestland was identified through the National Climate Assessment(NCA) as a key sector and system of concern to be included in a system of climate indicators as part of a sustained assessment effort. Here, we describe 11 informative core indicators of forests and climate change impacts with metrics available or nearly available for use in the NCA efforts. The recommended indicators are based on a comprehensive conceptual model which recognizes forests as a land use, an ecosystem, and an economic sector. The indicators cover major forest attributes such as extent, structural components such as biomass, functions such as growth and productivity, and ecosystem services such as biodiversity and outdoor recreation. Interactions between humans and forests are represented through indicators focused on the wildland-urban interface, cost to mitigate wildfire risk, and energy produced from forest-based biomass. Selected indicators also include drought and disturbance from both wildfires and biotic agents. The forest indicators presented are an initial set that will need further refinement in coordination with other NCA indicator teams. Our effort ideally will initiate the collection of critical measurements and observations and lead to additional research on forest-climate indicators.

U.S. forests↗
DOE OSTI2022

In Situ EXAFS-Based Nanothermometry of Heterodimer Nanocrystals under Induction Heating

The ability to heat nanocrystalline materials through magnetic induction has been used in the fields of catalysis, biomedical sciences, and polymer degradation. However, the working temperature to which the inductively coupled material rises is still poorly understood. Herein, we use extended X-ray absorption fine structure spectroscopy in conjunction with thermal imaging to improve the understanding of heating in inductively coupled systems. After extraction of the Debye–Waller factor from the spectroscopy, we obtain the temperature of inductively heated nanocrystals from the correlated Debye model. We combine carbon-supported iron oxide nanocrystals as induction heating agents with platinum nanocrystals as thermal probes. By testing these nanocrystal species as both unattached nanocrystals and heterodimers, we report that nanostructured systems show a significant temperature difference of up to 73.60 °C when compared to their local support environment. Furthermore, this result has implications for inductively heated catalysis, magnetic hyperthermia for targeted cell death, and polymer synthesis.

09 BIOMASS FUELS↗