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NASA NTRS1976

Study of a very low cost air combat maneuvering trainer aircraft

A very low cost aircraft for performing Air Combat Maneuvering (ACM) training was studied using the BD-5J sport plane as a point of departure. The installation of a larger engine and increased fuel capacity were required to meet the performance and mission objectives. Reduced wing area increased the simulation of the ACM engagement, and a comparison with current tactical aircraft is presented. Other factors affecting the training transfer are considered analytically, but a flight evaluation is recommended to determine the concept utility.

Hill, G. C.↗

NASA NTRS2016

Heart Rate Responses to Unaided Orion Side Hatch Egress in the Neutral Buoyancy Laboratory

NASA is developing the Orion capsule as a vehicle for transporting crewmembers to and from the International Space Station (ISS) and for future human space exploration missions. Orion and other commercial vehicles are designed to splash down in the ocean where nominally support personnel will assist crewmembers in egressing the vehicle. However, off-nominal scenarios will require crewmembers to egress the vehicle unaided, deploy survival equipment, and ingress a life raft. PURPOSE: To determine the heart rate (HR) responses to unaided Orion side hatch egress and raft ingress as a part of the NASA Crew Survival Engineering Team's evaluation of the PORT Orion mockup in the Neutral Buoyancy Laboratory (NBL). METHODS: Nineteen test subjects, including four astronauts (N=19, 14 males/5 females, 38.6+/-8.4 y, 174.4+/-9.6 cm, 75.7+/-13.1 kg), completed a graded maximal test on a cycle ergometer to determine VO2peak and HRpeak and were divided into five crews of four members each; one subject served on two crews. Each crew was required to deploy a life raft, egress the Orion vehicle from the side hatch, and ingress the life raft with two 8 kg emergency packs per crew. Each crew performed this activity one to three times; a total of ten full egresses were completed. Subjects wore a suit that was similar in form, mass, and function to the Modified Advanced Crew Escape Suit (MACES) including helmet, gloves, boots, supplemental O2 bottles, and a CO2-inflated life preserver (approx.18 kg); subjects began each trial seated supine in the PORT Orion mockup with seat belts and mockup O2 and communication connections and ended each trial with all four crewmembers inside the life raft. RESULTS: VO2peak was 40.8+/-6.8 mL/kg/min (3.1+/-0.7 L/min); HRpeak was 181+/-10 bpm. Total egress time across trials was 5.0+/-1.6 min (range: 2.8-8.0 min); all subjects were able to successfully complete all trials. Average maximum HR at activity start, at the hatch opening, in the water, and in the raft, was 108, 137, 147, and 153 bpm, respectively; these values corresponded to 59+/-10%, 73+/-8%, 82+/-3%, and 84+/-6% of HRpeak, respectively. The highest HRs were seen after raft ingress and ranged from 72-99% HRpeak. Across all trials, cumulative averages of 5.4, 3.0, 1.1, and 0.2 min were spent at HRs >60%, >70%, >80%, and >90% HRpeak, respectively. CONCLUSION: Unaided Orion side hatch egress in the NBL is a relatively short-duration activity that elicits a high HR response for several min. Although all crewmembers successfully completed this activity, additional factors such as high seas, poor visibility, an incapacitated crewmember, neurovestibular perturbation, and neuromuscular deconditioning characteristic of a true operational environment may increase the physiologic demand (or decrease crewmembers' physiologic capacity) of unaided Orion side hatch egress. Additionally, landing conditions may require the crewmembers to egress from the top hatch, which is expected to be even more physiologically demanding; this condition will be evaluated in subsequent collaborative testing with the NASA Crew Survival Engineering Team.

English, Kirk L.↗

DOE OSTI2024

Computational Approaches for Clean Energy Materials

Currently, 80% of the global final energy consumption occurs in form of fuels and only 20% as electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, a successful energy transition will require enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies. As much as photovoltaic capacities have grown over the past 20 years, it is far from clear that current technologies and materials are up to the task to grow from here by yet another factor 100 until 2050. Therefore, sustained research efforts on emerging inorganic semiconductors for solar electricity and fuels are essential for facing the double challenge of climate change and energy security. Computational materials science can make important contributions, guiding and supporting research activities through both materials search and discovery and through detailed studies that help to develop a mechanistic understanding of materials performance and bottlenecks. This presentation will highlight three recent computational projects with relevance for photovoltaics and solar fuels (1) Defect graph neural networks (dGNN) for materials discovery in solar thermochemical hydrogen (STCH) [1]. The dGNN approach facilitates broad and fast materials screening for defect properties. (2) Modeling highly off-stoichiometric systems by evaluating the free energy of defect interaction [2]. This approach allows quantitative prediction of H2 production in complex STCH oxides. (3) First-principles atomic structure prediction for interfaces [3]. This work showed how an atomically thin CdCl2 interlayer phase enables in principle ideal electron transport across the incommensurate SnO2/CdTe interface. [1] M.D. Witman, A. Goyal, T. Ogitsu, A.H. McDaniel, S. Lany, Nat. Comput. Sci. (2023). https://doi.org/10.1038/s43588-023-00495-2. [2] A. Goyal, M.D. Sanders, R.P. O'Hayre, S. Lany, PRX Energy 3, 013008 (2024). https://doi.org/10.1103/PRXEnergy.3.013008. [3] A. Sharan, M. Nardone, D. Krasikov, N. Singh, S. Lany, Appl. Phys. Rev. 9, 041411 (2022). https://doi.org/10.1063/5.0104008.

density functional theory↗

DOE OSTI2011

Use of wind power forecasting in operational decisions.

The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help efficiently address this challenge, and significant efforts have been invested in developing more accurate wind power forecasts. In this report, we document our work on the use of wind power forecasting in operational decisions.

17 WIND ENERGY↗

DOE OSTI2024

Supramolecular Motion Enables Chondrogenic Bioactivity of a Cyclic Peptide Mimetic of Transforming Growth Factor-β1

Transforming growth factor (TGF)-β1 is a multifunctional protein that is essential in many cellular processes that include fibrosis, inflammation, chondrogenesis, and cartilage repair. In particular, cartilage repair is important to avoid physical disability since this tissue does not have the inherent capacity to regenerate beyond full development. We report here on supramolecular coassemblies of two peptide amphiphile molecules, one containing a TGF-β1 mimetic peptide, and another which is one of two constitutional isomers lacking bioactivity. Using human articular chondrocytes, we investigated the bioactivity of the supramolecular copolymers of each isomer displaying either the previously reported linear form of the mimetic peptide or a novel cyclic analogue. Based on fluorescence depolarization and 1 H NMR spin–lattice relaxation times, we found that coassemblies containing the cyclic compound and the most dynamic isomer exhibited the highest intracellular TGF-β1 signaling and gene expression of cartilage extracellular matrix components. Here, we conclude that control of supramolecular motion is emerging as an important factor in the binding of synthetic molecules to receptors that can be tuned through chemical structure.

Antigens↗

DOE OSTI2023

Historical Pattern Analysis of Global Geothermal Power Capacity Development: Preprint

Between 1913 and 1958, Italy was the only country with an operational geothermal power plant until New Zealand installed its first plant in 1958. At present, 24 countries are involved in the geothermal power market, and they have a combined installed capacity of 16,127 GW. This study analyzes the historical patterns of geothermal power capacity in the world and in individual countries to investigate the ideal global geothermal development pattern by examining the annual cumulative capacity (ACC) and the annual capacity addition (ACA) graphs of the historical development of geothermal power capacity in 24 countries. First, the global patterns are analyzed using these graphs in five periods (1945-1957, 1958-1976, 1977-1991, 1992-2002, and 2003-2020) that are marked by a series of characteristics of ACA peaks separated by two major troughs. Then, five characteristic patterns are developed in five periods globally. These patterns correspond to the early-stage linear, the first acceleration, the first steady-state linear, the second acceleration, and the second steady-state linear developments. A positive relationship exists between global patterns and the 5-year shifted oil-price curve: two major factors influenced global development: 1) increasing oil prices and increasing awareness of global climate change, and 2) global development of geothermal power. Last, we investigate these patterns in each country. The top ten countries, which comprise 93.3% of the world's total installed capacity are separated into five groups based on the availability and characteristics of patterns globally developed in five periods. Group-1 (the United States) has an installed capacity of 3,794 MW, Group-2 (Mexico and Philippines) 963-1935 MW, Group-3 (New Zealand, Italy, Iceland, and Japan) 601-1,037 MW, and Group-4 (Indonesia, Kenya, and Turkiye) 944-2,356 MW. The remaining 14 countries (6.7%), which are called Group 5, are still in an immature stage and have installed capacities of 7-262 MW and are not involved in pattern analysis. Overall, geothermal power in the world is in its third stage of development, which had its peak development after 1977. A fourth development peak may be expected to occur after this through business-as-usual cases. The biggest barrier to the development of the global geothermal power market is the risk associated with exploration and drilling. If risk mitigation systems and funds are employed, the growth of geothermal power production projects could accelerate.

GEOTHERMAL ENERGY↗

DOE OSTI2023

Historical Pattern Analysis of Global Geothermal Power Capacity Development

GEOTHERMAL ENERGY↗

DOE OSTI2025

Insight into the deformation features and capacity loss mechanisms of lithium-ion pouch cells under spherical indentation conditions

Mechanical deformation under extreme conditions is one of the important reasons for the failure of lithium-ion batteries in automotive application. However, the deformation features and component failure of lithium-ion cells to external loading has never been a design consideration. Here, in this study, we conduct spherical indentation tests on a dozen of lithium-ion cells with different capacities under different control mode conditions to investigate their deformation features and capacity loss mechanisms. The experimental results show that, under mechanical deformation conditions, internal faults of cells occur in stages, and energy accumulation and sudden release are two key processes of cell's mechanical failure. The cells' state of charge is the main factor affecting their thermal runaway behaviors. In addition, a finite element model is developed to simulate the deformation features and the failure mechanism of key components of lithium-ion pouch cells; the 3D x-ray computed tomography is employed to demonstrate its internal configuration. With this model, the force-strain response, the deformation features as well as the size of the failure area of lithium-ion cells under spherical indentation conditions are accurately predicted. In 3D x-ray computed tomography images, unique mud cracks in cooper current collector are observed, and the influence mechanisms of the isolated fragments on the cell capacities are revealed. These results may provide useful information for the mechanical structure design of the components of lithium-ion pouch cells.

25 ENERGY STORAGE↗

NASA NTRS2021

Modeling Snow Ablation over the Western United States Mountains: Patterns and Controlling Factors

When compared with differences in snow accumulation predicted by widely used hydrological models, there is a much greater divergence among otherwise “good” models in their simulation of the snow ablation process. Here, we explore differences in the performance of the Variable Infiltration Capacity model (VIC), Noah land surface model with multiparameterization options (Noah-MP), the Catchment model, and the third-generation Simplified Simple Biosphere model (SiB3) in their ability to reproduce observed snow water equivalent (SWE) during the ablation season at 10 Snowpack Telemetry (SNOTEL) stations over 1992–2012. During the ablation period, net radiation generally has stronger correlations with observed melt rates than does air temperature. Average ablation rates tend to be higher (in both model predictions and observations) at stations with a large accumulation of SWE. The differences in the dates of last snow between models and observations range from several days to approximately a month (on average 5.1 days earlier than in observations). If the surface cover in the models is changed from observed vegetation to bare soil in all of the models, only the melt rate of the VIC model increases. The differences in responses of models to canopy removal are directly related to snowpack energy inputs, which are further affected by different algorithms for surface albedo and energy allocation across the models. We also find that the melt rates become higher in VIC and lower in Noah-MP if the shrub/grass present at the observation sites is switched to trees.

Snow↗

DOE OSTI2024

Carbon Capture, Transport, And Storage (CTS) Cost Modeling Of The Onshore Gulf Coast

The onshore Gulf of Mexico region presents significant opportunities for CO2 capture, transport, and storage due to its numerous CO2 sources, such as power plants, refineries, and its substantial CO2 storage potential. However, operators face critical decisions in designing an efficient and cost-effective CO2 pipeline network. This study examines the economic implications of two primary strategies: constructing a trunkline with excess initial capacity versus developing dedicated pipelines incrementally as new CO2 sources come online. Building a trunkline first offers the advantage of future-proofing the network, allowing for the accommodation of increased CO2 volumes from various sources over time. However, this approach incurs higher upfront costs and risks underutilizing the transport capacity in the initial stages, potentially resulting in economic inefficiencies. Conversely, constructing dedicated pipelines for each new CO2 source as it becomes operational may avoid the initial overcapacity issue but fails to capitalize on the economies of scale. This could lead to higher overall costs due to the duplication of infrastructure and increased complexity in network management. This research employs a comprehensive cost-benefit analysis, integrating factors such as capital expenditure, operational costs, projected CO2 volumes, and potential economies of scale. Through this analysis, we aim to provide operators with insights into the most economically viable strategy for CO2 pipeline network design in the region. The findings underscore the importance of strategic planning and highlight the trade-offs between immediate capacity utilization and long-term cost savings, ultimately guiding stakeholders towards informed decision-making in the development of CO2 transport infrastructure. Presented at the 41st USAEE/IAEE North American Conference, 3-6 November 2024, Baton Rouge, LA, United States.

Shih, Chung Yan↗

DOE OSTI2015

Computer model for electrochemical cell performance loss over time in terms of capacity, power, and conductance (CPC)

Available capacity, power, and cell conductance figure centrally into performance characterization of electrochemical cells (such as Li-ion cells) over their service life. For example, capacity loss in Li-ion cells is due to a combination of mechanisms, including loss of free available lithium, loss of active host sites, shifts in the potential-capacity curve, etc. Further distinctions can be made regarding irreversible and reversible capacity loss mechanisms. There are tandem needs for accurate interpretation of capacity at characterization conditions (cycling rate, temperature, etc.) and for robust self-consistent modeling techniques that can be used for diagnostic analysis of cell data as well as forecasting of future performance. Analogous issues exist for aging effects on cell conductance and available power. To address these needs, a modeling capability was developed that provides a systematic analysis of the contributing factors to battery performance loss over aging and to act as a regression/prediction platform for cell performance. The modeling basis is a summation of self-consistent chemical kinetics rate expressions, which as individual expressions each covers a distinct mechanism (e.g., loss of active host sites, lithium loss), but collectively account for the net loss of premier metrics (e.g., capacity) over time for a particular characterization condition. Specifically, sigmoid-based rate expressions are utilized to describe each contribution to performance loss. Through additional mathematical development another tier of expressions is derived and used to perform differential analyses and segregate irreversible versus reversible contributions, as well as to determine concentration profiles over cell aging for affected Li+ ion inventory and fraction of active sites that remain at each time step. Reversible fade components are surmised by comparing fade rates at fast versus slow cycling conditions. The model is easily utilized for predictive calculations so that future capacity performance can be estimated. The invention covers mathematical and theoretical frameworks, and demonstrates application to various Li-ion cells covering test periods that vary in duration, and shows model predictions well past the end of test periods. Version 2.0 Enhancements: the code now covers path-dependent aging scenarios, wherein the framework allows for arbitrarily-chosen aging conditions over a timeline to accommodate prediction of battery aging over a multiplicity of changing conditions. The code framework also allows for cell conductance and power loss evaluations over cell aging, analysis of series strings that contain a thermal anomaly (hot spot), and evaluation of battery thermal management parameters that impact battery lifetimes. Lastly, a comprehensive GUI now resides in the Ver. 2.0 code.

Gering, KevinL.↗

DOE OSTI2017

Mimicking the Bioactivity of Fibroblast Growth Factor-2 Using Supramolecular Nanoribbons

Fibroblast growth factor (FGF-2) is a multifunctional growth factor that has pleiotropic effects in different tissues and organs. In particular, FGF-2 has a special role in angiogenesis, an important process in development, wound healing, cell survival, and differentiation. Therefore, incorporating biological agents like FGF-2 within therapeutic biomaterials is a potential strategy to create angiogenic bioactivity for the repair of damaged tissue caused by trauma or complications that arise from age and/or disease. However, the use of growth factors as therapeutic agents can be costly and does not always bring about efficient tissue repair due to rapid clearance from the targeted site. An alternative would be a stable supramolecular nanostructure with the capacity to activate the FGF-2 receptor that can also assemble into a scaffold deliverable to tissue. We report here on peptide amphiphiles that incorporate a peptide known to activate the FGF-2 receptor and peptide domains that drive its self-assembly into supramolecular nanoribbons. These FGF2-PA nanoribbons displayed the ability to increase the proliferation and migration of the human umbilical vein endothelial cells (HUVECs) in vitro to the same extent as the native FGF-2 protein at certain concentrations. We confirmed that this activity was specific to the FGFR1 signaling pathway by tracking the phosphorylation of downstream signaling effectors such ERK1/2 and pH3. These results indicated the specificity of FGF2-PA nanoribbons in activating the FGF-2 signaling pathway and its potential application as a supramolecular scaffold that can be used in vivo as an alternative to the encapsulation and delivery of the native FGF-2 protein.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Ab Initio Investigation on Electronic, Magnetic, Mechanical, and Thermodynamic Properties of AMO{sub 3} (A = Eu, M = Ga, In) Perovskites

The structural, electronic, magnetic, elastic, and thermodynamic properties of cubic AMO{sub 3} perovskites (A = Eu, M = Ga, In) have been successfully studied within density functional theory using full-potential linearized augmented plane wave (FP-LAPW). The structural study reveals that both the compounds are stable in ferromagnetic states. The GGA + U calculated spin-polarized electronic band and density of states present the half-metallic nature of both the compounds. The magnetic moments calculated with different approximations were found to be approximately 6 μ{sub B} for EuGaO{sub 3} and approximately 7 μ{sub B} for EuInO{sub 3}. From elastic calculation, the three independent elastic constants (C{sub 11}, C{sub 12}, C{sub 44}) have been acquired to yield the mechanical properties like Young modulus (Y ), shear modulus (G), Poisson ratio (ν), and anisotropic factor (A). The calculated values of B/G show that both the compounds are ductile in nature. The thermodynamic study was also accomplished by exploring the thermodynamic parameters like specific heat, heat capacity, thermal expansion, Grüneisen parameter, Debye temperature, etc. within the temperature range 0 to 900 K and pressure range 0 to 50 GPa.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Three-dimensional electronic resistivity mapping of solid electrolyte interphase on Si anode materials

Silicon is a promising candidate for the lithium ion battery (LIB) anode because of the order-of-magnitude improvement in capacity over current state-of-the-art graphite anodes. In systems featuring both C and Si anodes, electronic resistivity of the solid-electrolyte interphase (SEI) layer is a critical factor for preventing continuous electrolyte-decomposition reactions at the electrode/electrolyte interface. However, the in-situ measurement of SEI electronic resistance has been complicated by ion transport and electronic contributions from other parts of the battery circuit. Ex-situ measurements of SEI resistivity at microscopic scales are also lacking. We report on a nanometer-resolution three-dimensional technique that enables ex-situ mapping of electronic resistivity of SEI formed on a model single-crystalline wafer Si anode. Our novel experimental approach uses scanning spreading-resistance microscopy resistance imaging and mechanical depth profiling. In addition to resistance mapping, this method also provides an alternative technique for locating buried interfaces, where mechanical or electronic properties differ sufficiently between layers. Further validation of this method was obtained by resistance mapping of a reference sample with a designed a-Si:H layer stack of different doping concentrations. The results show relatively uniform lateral resistivity distribution of the SEIs but steep decreases in resistivity in the vertical direction. Resistivity vs. depth profiles are highly dependent on cycling conditions, but they generally show a resistivity decrease from the most superficial levels of SEI and a thickness increase with continued cycling prior to SEI stabilization. The most prominent resistivity increase was observed on SEI formed in Gen2 electrolyte (EC:EMC [3:7 by wt.] + 1.2 M LiPF6) with 10 wt% fluoroethylene carbonate additive; this result may partially explain the significant improvements of sustained electrochemical cycling and coulombic efficiency observed with this electrolyte additive. Our approach provides a novel and unparalleled three-dimensional approach in characterizing electronic resistivity, which contributes significantly to understanding SEI formation and the intrinsic properties critical to battery performance.

25 ENERGY STORAGE↗

DOE OSTI2018

Sirtuin 5 overexpression attenuates glucolipotoxicity-induced pancreatic β cells apoptosis and dysfunction

Highlights: • SIRT5 expression significantly diminished in the pancreas of T2DM animals. • SIRT5 reduced apoptotic cell mass and retained glucose-stimulated insulin secretion in β cell lines upon glucolipotoxicity. • SIRT5 plays an essential role in maintaining the β cell mass and function under glucolipotoxicity condition. Recently, SIRT5 was reported to be a predominant desuccinylase and demalonylase in mitochondria. Ablation of SIRT5 enhances the systemic succinylation and malonylation of mitochondrial proteins, including various metabolic enzymes; however, its function in pancreatic β cells has not yet been clarified. In this study, we evaluated the effects of SIRT5 overexpression on glucolipotoxicity-induced apoptosis in β cell lines. Full-length SIRT5, which preferentially targeted to mitochondria and partially to the nucleus and cytoplasm, was overexpressed in NIT-1 cells. Chronic exposure to excess palmitate and glucose (High-PA-G) induced apoptosis and suppressed glucose-stimulated insulin secretion in β cells. SIRT5 overexpression significantly alleviated apoptosis under the High-PA-G condition, accompanied by suppressed Caspase 3 activity and reduced malondialdehyde levels. SIRT5 overexpression also improved β cell secretory capacity in response to glucose under the High-PA-G condition, suggesting its protective role in β cell function. Furthermore, SIRT5 overexpression reversed the decreasing trend of anti-apoptotic factors BCL-2 and BCL-XL expression under High-PA-G condition. Further regulation mechanisms between SIRT5 and these anti-apoptotic factors remains to be explored in future studies. Our data reveal that SIRT5 is a potentially protective factor for pancreatic β cells against glucolipotoxicity-induced apoptosis and cell dysfunction.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Psychosocial experiences are associated with human brain mitochondrial biology

Psychosocial experiences affect brain health and aging trajectories, but the molecular pathways underlying these associations remain unclear. Normal brain function relies on energy transformation by mitochondria oxidative phosphorylation (OxPhos). Two main lines of evidence position mitochondria both as targets and drivers of psychosocial experiences. On the one hand, chronic stress exposure and mood states may alter multiple aspects of mitochondrial biology; on the other hand, functional variations in mitochondrial OxPhos capacity may alter social behavior, stress reactivity, and mood. But are psychosocial exposures and subjective experiences linked to mitochondrial biology in the human brain? By combining longitudinal antemortem assessments of psychosocial factors with postmortem brain (dorsolateral prefrontal cortex) proteomics in older adults, we find that higher well-being is linked to greater abundance of the mitochondrial OxPhos machinery, whereas higher negative mood is linked to lower OxPhos protein content. Combined, positive and negative psychosocial factors explained 18 to 25% of the variance in the abundance of OxPhos complex I, the primary biochemical entry point that energizes brain mitochondria. Moreover, interrogating mitochondrial psychobiological associations in specific neuronal and nonneuronal brain cells with single-nucleus RNA sequencing (RNA-seq) revealed strong cell-type-specific associations for positive psychosocial experiences and mitochondria in glia but opposite associations in neurons. As a result, these “mind-mitochondria” associations were masked in bulk RNA-seq, highlighting the likely underestimation of true psychobiological effect sizes in bulk brain tissues. Thus, self-reported psychosocial experiences are linked to human brain mitochondrial phenotypes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Multi-metallic conduction cooled superconducting radio-frequency cavity with high thermal stability

Superconducting radio-frequency cavities are commonly used in modern particle accelerators for applied and fundamental research. Such cavities are typically made of high-purity, bulk Nb and with cooling by a liquid helium bath at a temperature of ~2 K. The size, cost and complexity of operating a particle accelerator with a liquid helium refrigerator make the current cavity technology not favorable for use in industrial-type accelerators. We have developed a multi-metallic 1.495 GHz elliptical cavity conductively cooled by a cryocooler. The cavity has a ~2 µm thick layer of Nb 3 Sn on the inner surface, exposed to the rf field, deposited on a ~3 mm thick bulk Nb shell and a bulk Cu shell, of thickness $\geqslant\! 5$ mm deposited on the outer surface by electroplating. A bolt-on Cu plate 1.27 cm thick was used to thermally connect the cavity equator to the second stage of a Gifford-McMahon cryocooler with a nominal capacity of 2 W at 4.2 K. The cavity was tested initially in liquid helium at 4.3 K and reached a peak surface magnetic field of ~36 mT with a quality factor of 2 × 10 9 . The cavity cooled by the cryocooler achieved a peak surface magnetic field of ~29 mT, equivalent to an accelerating gradient of 6.5 MV m –1 . The conduction-cooled cavity could be operated in continuous-wave with as high as 5 W dissipation in the cavity for 1 h without any thermal breakdown, because of the Cu outer layer with high thermal conductivity. This result represents a paradigm shift in the technology of superconducting accelerator cavities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2013

A stochastic model of cell survival for high-Z nanoparticle radiotherapy

Purpose: The authors present a stochastic framework for the assessment of cell survival in gold nanoparticle radiotherapy. Methods: The authors derive the equations for the effective macroscopic dose enhancement for a population of cells with nonideal distribution of gold nanoparticles (GNP), allowing different number of GNP per cell and different distances with respect to the cellular target. They use the mixed Poisson distribution formalism to model the impact of the aforementioned physical factors on the effective dose enhancement. Results: The authors show relatively large differences in the estimation of cell survival arising from using approximated formulae. They predict degeneration of the cell killing capacity due to different number of GNP per cell and different distances with respect to the cellular target. Conclusions: The presented stochastic framework can be used in interpretation of experimental cell survival or tumor control probability studies.

60 APPLIED LIFE SCIENCES↗