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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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156 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Organophosphorus Binding Thermodynamics in Metal–Organic Frameworks: Interplay between Oxidation State, Lewis Acidity, and Node Structure

Organophosphorus compounds, including nerve agents and pesticides, represent a class of toxic chemicals causing harm to troops, civilians, and the environment. Metal–organic frameworks (MOFs) have emerged as a class of highly porous, crystalline, tunable materials adept at both capturing and catalytically neutralizing these harmful toxins. In particular, MOFs whose nodes display strong Lewis acidic character can hydrolyze such chemicals nearly instantaneously. However, without the help of a basic buffer to regenerate the active site, the benign organophosphorus product strongly binds to the node and prevents catalyst turnover. Here, we investigate a series of MOFs whose nodes contain metals of varying Lewis acidities and employ isothermal titration calorimetry (ITC) to directly measure the heat from the binding of an organophosphorus probe molecule, allowing the construction of a full thermodynamic binding profile (ΔH, ΔS, ΔG, K a ). We couple this with potentiometric titrations and solid state 31 P magic angle spinning (MAS) NMR to gain a clearer picture of how node identity, structure, and Lewis acidity interplay to impact binding strength and favorability. Furthermore, this study is the first to integrate these three complementary techniques to investigate binding interactions in MOFs, further showcasing the viability of ITC for probing MOF systems, which is still relatively underexplored.

Lewis acidity↗
DOE OSTI2024

"Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test"

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. We explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

Jang, Kathy↗
DOE OSTI2024

Tritium Extraction from FLiBe using a Permeation Against Vacuum (PAV): Impact of Surface Potentials, Currents, and Coupling PAV to Sacrificial Anodes

Savannah River National Laboratory (SRNL) is exploring a concept of pairing a LiF-BeF2 (FLiBe) immersed Permeation Against Vacuum (PAV) tritium extraction system with a sacrificial anode. Several fusion concepts utilize FLiBe for tritium breeding, and breeding of tritium would occur from neutron interactions with the Li component, creating corrosive TF and/or T2. In absence of a redox buffered system, the TF would be able to attack containment materials until neutralized. One way to neutralize TF is to contact it with an active metal such as Be or Li which would preferentially combine with the fluorine in the TF to form BeF2 or LiF, respectively, and resulting in T2. When the active metal (e.g., Be) is oxidized, it will provide electrons, when T in TF is reduced and forms T2, it needs electrons. SRNL proposes to electrically link these two reactions and with the PAV to help drive the reactions faster than on their own and potentially increase T2 dissociation. In a soluble redox salt buffered system, it is expected that with sufficient buffering, T2, may form more rapidly and the core components would be more protected, but the soluble redox salt buffer would need to be occasionally regenerated, which could be accomplished by again contacting the salt with an active metal such as Be or Li, although in this case the cathodic reaction would be electrons coming from the shift in oxidative state of the redox buffer. The exploration of potential and current effects on the PAV and impacts of redox agents will be discussed.

Olson, Luke C.↗
DOE OSTI2025

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Range-wide population assessments for subalpine fir indicate widespread disturbance-driven decline

Subalpine forests in western North America are threatened by rapid climate change, increased activity by endemic and exotic insects and diseases, and changing wildfire regimes. The interactive effects of these stressors have resulted in pronounced population declines in many subalpine tree species; however, a systematic assessment of the status and trends of subalpine forests is lacking. Subalpine fir (Abies lasiocarpa) is a widespread species across the western United States, with documented population declines in many parts of its distribution. Here we use subalpine fir as an initial leverage point to build a more complete understanding of subalpine forest baseline conditions and responses to environmental change. Specifically, we leverage the USDA Forest Service Forest Inventory and Analysis (FIA) database to (1) ask how subalpine fir populations are changing across the species’ distribution in the western US, (2) assess the drivers of recent subalpine fir population trends, and (3) explore whether those changes imply generalized species-wide and/or system-wide decline. We found that subalpine fir abundance and basal area are declining concurrently across ~ 62% of the species’ distribution, and increasing across ~ 19%. Range-wide, we estimated 25.02 ± 2.74 % subalpine fir mortality between 2000 and 2009 and 2010–2019 FIA inventory periods, with higher mortality concentrated in the eastern Oregon Cascades, central Idaho, and parts of southern Colorado. High regeneration density did not predict positive population trajectories, which were instead associated with higher rates of adult recruitment. While the importance of different mortality agents varied substantially between ecoregions, 83.4% of total range-wide mortality was related to fire or biological disturbance. Declining subalpine fir basal area coincided with declines in the basal area of other co-occurring tree species in 39% of subalpine forest area, and with increases in conspecific basal area in 22% of forest area. Fire disturbance was the single largest cause of subalpine fir mortality; however, even where subalpine fir fire mortality was high, mortality among other species was primarily caused by insects. In conclusion, our results suggest that subalpine fir declines across large portions of the western United States are driven by forest disturbance, and that declines in subalpine fir populations may be indicative of negative change in subalpine forest systems broadly.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Bioinformatic and Mechanistic Analysis of the Palmerolide PKS-NRPS Biosynthetic Pathway From the Microbiome of an Antarctic Ascidian

Complex interactions exist between microbiomes and their hosts. Increasingly, defensive metabolites that have been attributed to host biosynthetic capability are now being recognized as products of host-associated microbes. These unique metabolites often have bioactivity targets in human disease and can be purposed as pharmaceuticals. Polyketides are a complex family of natural products that often serve as defensive metabolites for competitive or pro-survival purposes for the producing organism, while demonstrating bioactivity in human diseases as cholesterol lowering agents, anti-infectives, and anti-tumor agents. Marine invertebrates and microbes are a rich source of polyketides. Palmerolide A, a polyketide isolated from the Antarctic ascidian Synoicum adareanum, is a vacuolar-ATPase inhibitor with potent bioactivity against melanoma cell lines. The biosynthetic gene clusters (BGCs) responsible for production of secondary metabolites are encoded in the genomes of the producers as discrete genomic elements. A candidate palmerolide BGC was identified from a S. adareanum microbiome-metagenome based on a high degree of congruence with a chemical structure-based retrobiosynthetic prediction. Protein family homology analysis, conserved domain searches, active site and motif identification were used to identify and propose the function of the ~75 kbp trans-acyltransferase (AT) polyketide synthase-non-ribosomal synthase (PKS-NRPS) domains responsible for the stepwise synthesis of palmerolide A. Though PKS systems often act in a predictable co-linear sequence, this BGC includes multiple trans-acting enzymatic domains, a non-canonical condensation termination domain, a bacterial luciferase-like monooxygenase (LLM), and is found in multiple copies within the metagenome-assembled genome (MAG). Detailed inspection of the five highly similar pal BGC copies suggests the potential for biosynthesis of other members of the palmerolide chemical family. This is the first delineation of a biosynthetic gene cluster from an Antarctic microbial species, recently proposed as Candidatus Synoicihabitans palmerolidicus. These findings have relevance for fundamental knowledge of PKS combinatorial biosynthesis and could enhance drug development efforts of palmerolide A through heterologous gene expression.

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

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2020

Sea Level Rise in the CESM Large Ensemble: The Role of Individual Climate Forcings and Consequences for the Coming Decades

The emergence of a spatial pattern in the externally forced response (FR) of dynamic sea level (DSL) during the altimeter era has recently been demonstrated using climate models but our understanding of its initial emergence, drivers, and implications for the future is poor. Here the anthropogenic forcings of the DSL pattern are explored using the Community Earth System Model Large Ensemble (CESM-LE) and Single-Forcing Large Ensemble, a newly available set of simulations where values of individual forcing agents remain fixed at 1920 levels, allowing for an estimation of their effects. Statistically significant contributions to the DSL FR are identified for greenhouse gases (GHGs) and industrial aerosols (AERs), with particularly strong contributions resulting from AERs in the mid-twentieth century and GHGs in the late twentieth and twenty-first century. Secondary, but important, contributions are identified for biomass burning aerosols in the equatorial Atlantic Ocean in the mid-twentieth century, and for stratospheric ozone in the Southern Ocean during the late twentieth century. Key to understanding regional DSL patterns are ocean heat content and salinity anomalies, which are driven by surface heat and freshwater fluxes, ocean dynamics, and the spatial structure of seawater thermal expansivity. Finally, potential implications for the interpretation of DSL during the satellite era and the longer records from tide gauges are suggested as a topic for future research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Two distinct rotations of bithiazole DNA intercalation revealed by direct comparison of crystal structures of Co(III)•bleomycin A 2 and B 2 bound to duplex 5'-TAGTT sites

Bleomycins constitute a family of anticancer natural products that bind DNA through intercalation of a C-terminal tail/bithiazole moiety and hydrogen-bonding interactions between the remainder of the drug and the minor groove. The clinical utility of the bleomycins is believed to result from single- and double-strand DNA cleavage mediated by the HOO-Fe(III) form of the drug. The bleomycins also serve as a model system to understand the nature of complex drug-DNA interactions that may guide future DNA-targeted drug discovery. In this study, the impact of the C-terminal tail on bleomycin-DNA interactions was investigated. Toward this goal, we determined two crystal structures of HOO-Co(III)•BLMA 2 “green” (a stable structural analogue of the active HOO-Fe(III) drug) bound to duplex DNA containing 5'-TAGTT, one in which the entire drug is bound (fully bound) and a second with only the C-terminal tail/bithiazole bound (partially bound). The structures reported here were captured by soaking HOO-Co(III)•BLMA 2 into preformed host–guest crystals including a preferred DNA-binding site. While the overall structure of DNA-bound BLMA 2 was found to be similar to those reported earlier at the same DNA site for BLMB 2 , the intercalated bithiazole of BLMB 2 is “flipped” 180° relative to DNA-bound BLMA 2 . Further, this finding highlights an unidentified role for the C-terminal tail in directing the intercalation of the bithiazole. In addition, these analyses identified specific bond rotations within the C-terminal domain of the drug that may be relevant for its reorganization and ability to carry out a double-strand DNA cleavage event.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Revealing ultrafast proton-transfer-mediated autoionization as a source of low-energy electrons in hydrogen-bonded systems

Ionizing radiation can trigger ultrafast proton transfer, a central mechanism in many chemical and biological functions, that in turn can enable or suppress electron relaxation processes and consequently cause abrupt changes in the reaction pathway. This study combines theory and experiment to probe ultrafast relaxation and dissociation in water dimers following inner- and outer-valence photoionization. By tracking electron and nuclear motion simultaneously, we reveal competing fragmentation pathways that produce low-energy electrons, which are key agents in radiation-induced chemistry, including DNA damage. While low-energy electrons are known to arise via intermolecular Coulombic decay, here we identify a faster relaxation mechanism gated by proton transfer following inner-valence ionization, which we call proton-transfer-mediated autoionization. Occurring within 10 femtoseconds, this process alters fragmentation outcomes, yielding either D 3 O + + OD + or D 2 O + + D 2 O + , depending on the interplay of proton migration and hydrogen back-transfer. Our findings underscore the intricate coupling between electronic and nuclear dynamics in hydrogen-bonded systems and establish proton-transfer-mediated autoionization as a significant pathway for low-energy electron generation.

Atomic and molecular interactions with photons↗
DOE OSTI2024

Surface Charge at an Oil/Water Interface Promoting the Enhancement and Assignment of Water Combination Bands

Given the different polarities and distinct chemical structures, it is no wonder that oil and water are incompatible neighbors. They can be forced to cooperate if provided sufficient energy or a suitable intermediary. Emulsions are the result of such a cooperation, where an emulsifying agent (the intermediary) in the form of a surfactant or a cocktail of surface stabilizing compounds allows for the ‘mixing’ of oil and water. Surfactant stabilized emulsions that are nanoscale in size (nanoemulsions) have caught the attention of many because of their newly discovered use in the synthesis of nanomaterials, oil recovery, drug delivery, and food science. Unlike smaller emulsions (e.g. microemulsions with 2-20 nm diameters), very little is known about the molecular level properties of nanoemulsions (NEs) whose diameters are in the 100-500 nm range. One thing that is well known is the macroscopic properties of droplets from these two size regimes are dramatically different, often for reasons not yet fully understood. Nanoemulsions do not form spontaneously and require an external shear beyond ordinary procedures used to create micelles. This shear is required to overcome the effects of surface tension and create droplets in the nanoscale regime. Once formed, however, they can be stable for long periods of time, making them very attractive for commercial and pharmaceutical products requiring a long shelf life. What is not well known is the interfacial molecular processes that lead to the formation and stability of nanoemulsions including those stabilized by surfactants and/or polymers. Such knowledge is important in understanding the molecular structure-function relationship that assists in predicting what additives and solvents are necessary for a specific application. Key to advancing nanoemulsion utility is to develop the needed molecular-level understanding of the structure and bonding interactions present at the surface of these soft nanoparticles.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Simulating nationwide coupled disease and fear spread in an agent-based model

Human cognitive responses, behavioral responses, and disease dynamics co-evolve over the course of any disease outbreak, and can result in complex feedbacks. We present a dynamic agent-based model that explicitly couples the spread of disease with the spread of fear surrounding the disease, implemented within the EpiCast simulation framework. EpiCast models transmission within a realistic synthetic population, capturing individual-level interactions. In our model, fear propagates through both in-person contact and broadcast media, prompting individuals to adopt protective behaviors that reduce disease spread. In order to better understand these coupled dynamics, we create and compare a range of compartmental models to ensure that introducing additional disease states does not prevent the emergence of multiple waves in these simpler models. Additionally, we compare a range of behavioral scenarios within EpiCast, varying the level and intensity of fear and behavior change. Our results show that the addition of asymptomatic, exposed, and pre-symptomatic disease states can impact both the rate at which an outbreak progresses and its overall trajectory in compartmental models. In EpiCast, the combination of non-local fear spread via broadcasters and strong behavioral responses by fearful individuals generally leads to multiple epidemic waves, an outcome that occurs only within a narrow parameter range when fear spreads purely through local contact. Accounting for the coupled spread of fear and disease is critical for understanding disease dynamics and designing timely, targeted responses to emerging infectious threats.

60 APPLIED LIFE SCIENCES↗