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At least 559 records · Page 31

Results from the MISSE 6 Scattered Space Atomic Oxygen Experiment (SSAOE)

Polymers and other oxidizable materials used on the exterior of spacecraft in the low Earth orbit (LEO) space environment can be eroded away by reaction with atomic oxygen (AO). NASA Glenn Research Center developed an active flight experiment, called the Scattered Space Atomic Oxygen Experiment (SSAOE), to characterize AO scattering erosion in space. The SSAOE is comprised of three independent sub-experiments: A two part active experiment to measure both in-situ direct ram AO erosion and in-situ scattered AO erosion within an AO scatterometer; a passive AO scatterometer to measure the angular distribution of LEO AO scattered off an inclined angle; and passive samples for AO erosion yield (Ey) characterization. The SSAOE was originally flown on the Wake Shield Facility (WSF) during the STS-60 shuttle mission, and was later flown as part of the MISSE 6 mission on the exterior of the ISS. During the MISSE-6 mission the SSAOE was exposed to the space environment for 1.45 years. This paper provides an overview of the SSAOE, information on the flight missions, post-flight photographs of the passive flight samples and results on the angular distribution of scattered LEO AO obtained from the passive AO scatterometer sub-experiment. The LEO scattered AO erosion data can be used to improve AO undercutting models and durability predictions of spacecraft components receiving scattered AO.

Atomic oxygen, erosion, undercutting, spaceflight ↗

Flow Boiling and Condensation Experiment: Flow Boiling in a Rectangular Channel with Subcooled Inlet Conditions in Microgravity

Two-phase thermal management subsystems that take advantage of both the sensible and latent heat of a working fluid can potentially yield significant enhancements in overall performance by adopting heat transfer processes that are based on phase transition like boiling and condensation. Performance of terrestrial two-phase flow systems may be predictable because the hydrodynamic and body forces are understood, however, in microgravity, which is predominant during planetary space travel, forces that are masked by the strong body force on Earth (gravitational or buoyancy force) reappear with different magnitude and influence. The need arose for a facility that provides for two-phase flow with phase transition testing in microgravity. The Flow Boiling and Condensation Experiment (FBCE) is a facility that was launched to the International Space Station in August of 2021 and is in operation since February of 2022. This facility enables investigators to perform two-phase flow and phase transition research in flow boiling and condensation. Along with the test module that is experiment specific, the FBCE system consists of the fluid, avionics, and software subsystems. Currently two test modules, namely, the Flow Boiling Module (FBM) and the Condensation Module for Heat Transfer (CM-HT) are available. A third module, the Transfer Line test Module (TL) is being developed. The fluid subsystem conditions and delivers the fluid at the desired thermodynamic state to the test module. It consists of two fluid modules and a heater module that are connected by flex hoses for fluid circulation and by data and electrical cables for control and data acquisition. Two avionics modules acquire pressure and temperature data from various sensors in the flow loop. For FBM, a high-speed camera is available to acquire images of the boiling process. Experiments are operated autonomously by software and are based on an Experiment Parameters Master Table (EPMT) that is uploaded to ISS and is executed by the FBCE flight software. This presentation briefly introduces the objectives of FBCE and provides a system description of the experiment onboard of the ISS/Fluid Integrated Rack (FIR). Results of the test campaign carried out using the FBM are presented. Specifically, microgravity flow boiling of n-perfluorohexane (test fluid) is discussed with subcooled inlet conditions in a single-side-heated rectangular channel of dimensions 114.6-mm heated length, 2.5-mm heated width, and 5.0-mm height. Key operating parameters investigated are mass velocity (199.90 – 3200.13 kg/m2s), inlet subcooling (0.10 – 45.76°C), and inlet pressure (113.30 – 164.29 kPa). Image sequences acquired via high-speed-video are shown to elucidate the interfacial flow physics. The effects of various parameters on flow boiling heat transfer in microgravity, from the onset of boiling to the critical heat flux are discussed. Heat transfer results are presented in terms of flow boiling curves, streamwise profiles of wall temperature and heat transfer coefficient, and parametric trends of local and averaged heat transfer coefficient, and the critical heat flux.

Two-phase flow and phase transition↗

Designing Experiments for SpinSat, A Novel Variable-Gravity-and-Radiation Platform for Deep-Space Science

Conducting experiments to measure the effects of deep-space radiation and reduced gravity on biological and physical systems remains challenging. The result is a substantial knowledge gap that poses risks to our ability to sustain life and conduct critical operations in deep space. The SpinSat spacecraft platform is designed to bridge such gaps by providing low-cost, reliable, and frequent access to deep space. A disk-shaped rotating satellite that can provide artificial gravity and exposure to space radiation simultaneously, SpinSat is designed to accommodate payloads in a CubeSat form factor (with at least 48 “U” volume), providing power, communications, and a benign thermal environment. It is orbit-agnostic, enabling access to a variety of radiation environments (Van Allen belts, deep space, cis-lunar); and can be equipped with shielding to mimic planetary radiation environments, for both short- and long-term experiments. Because of its versatility and prioritization of late loading for biological payloads, it is well suited to host a wide range of ranging from human tissues and organoids to microorganisms, plants, chemistry, and regolith. Here, we present examples of potential experiment concepts for SpinSat, and discuss the details of how experimental designs could interact with the platform. Potential SpinSat studies have diverse applications, including fundamental radiation biology and DNA repair; cancer biology and countermeasure development; space agriculture; bioproduction of nutrients and pharmaceuticals; understanding regolith dynamics in low gravity; prebiotic chemistry and panspermia. We will further highlight ideas for SpinSat-compatible experimental hardware, existing and in development, and experiment-relevant details on SpinSat capabilities including artificial gravity, potential radiation environments, data, and power. This presentation will aim to provide investigators with the high-level technical information necessary to inspire experiments for SpinSat. We also seek to stimulate conversation and to gain community input on accommodations needs to help guide the evolving design of this platform.

experiment design↗

Two-Phase Flow in Filters and Orifices: In preparation for Measurements on ISS Packed Bed Reactor Experiment-Water Recovery Series (PBRE-WRS)

Understanding the hydrodynamics of adiabatic two-phase flows in packed bed reactors offers numerous benefits. It enables the optimization of chemical reactions rates and products, crucial for pharmaceuticals and energy production industries. Additionally, this understanding aids in designing more efficient and compact reactors, reducing space and resource requirements. Insights gained from studying such flows in microgravity contribute to advancements of space technologies and the enhancement of our capabilities for undertaking future long duration safe, and sustainable space exploration missions. The Packed Bed Reactor Experiment-Water Recovery Series (PBRE-WRS) is a flight experiment planned for operation on the Microgravity Science Glove box (MSG) facility of the International Space Station (ISS). The objective of the experiment is to validate hydrodynamic models at a range of gas and liquid flow rates. The microgravity environment allows for measurement and observation of aspects of fluid dynamics that are unique when compared to observations made in full or partial gravity environments. The experiment consists of testing two-phase flow hydrodynamics in three different filters, four (4) orifices and one check valve test articles. The experiment utilizes the hardware of the previously flown PBRE and PBRE-2 with packed beds of different packings materials and sizes. The fluid system of the PBRE-WRS consists of a nitrogen gas delivery and water delivery subsystems. The gas delivery subsystem can accommodate two ranges of gas flow rates, just as for the water delivery system. The nitrogen gas loop is open whereas the water loop is closed. Gas is separated from the water using a gas-liquid phase separator which is located in the water delivery module. Preliminary results from ground testing show the pressure drop increasing at different rates with the liquid and gas flow rates in the Brine filter. In this work, a detailed system description is presented along with a summary of results from ground performance testing of different test sections in an end-to-end preflight testing campaign.

Packed Bed Reactor Experiment↗

Validation Testing for Molten Chloride Reactor Experiment Equipment Removal and Disposal Techniques

The Molten Chloride Reactor Experiment (MCRE) will be the first reactor featuring a fast-spectrum molten chloride circulating nuclear fuel system in the world. Planning for equipment removal and disposal (ERD) of MCRE has identified several technology gaps due to the unique environment of this nuclear experiment. Some of the gaps arise from the application of existing disassembly and/or sizing methods to novel material forms or in novel configurations. Others arise from unknown material behavior. This paper summarizes proposed test plans for ERD validation experiments to address these complicated or unknown equipment removal procedures. At the Waste Management Symposia in 2024, the Idaho National Laboratory (INL) MCRE ERD team presented the challenges associated with hosting multiple nuclear experiments in series with only brief transition periods between systems. Such difficulties include higher dose rates, the presence of radioisotopes infrequently encountered in reactor decommissioning and radioactive waste management, lack of intrinsic remote-operations infrastructure in the test bed, space constraints in the test bed, and contamination minimization requirements. To address these challenges, remote or semi-remote technologies are planned to be implemented in a non-hot cell environment with limited space availability. The team also discussed how a systems engineering approach is being used for conceptual development and design of equipment removal systems to address these challenges. For example, to reduce constraints for the removal of more difficult components, non-activated, noncontaminated elements are planned to be taken out first where possible. Still, there are complexities associated with the remaining components. In this work, the operational framework for MCRE ERD was reviewed for technical gaps and open questions, and test plans were drafted to address these areas. The tests plans were written for the following categories: vision systems, pipe cutting, drill/grout/filler, flush salt, and miscellaneous, with the miscellaneous group consisting of tests like techniques for removing bearings and reflector bricks. The test plans explore material, infrastructure, and staffing requirements needed for test execution. The test plans additionally focus on the evaluation of success. Determining the outcome of a test is imperative - as these explorative actions have the potential to rearrange or re-scope planned ERD activities. Success criteria identified thus far include required tool output, required area(s), debris production and mitigation, and repeatability. Test plans are an essential aspect of the systems engineering approach to MCRE ERD. They are used as the beginning steps in defining use cases for the ERD system. Performance of the validation tests is expected to begin in the summer of 2025 and will take approximately 9 to 12 months to complete. Execution of these plans will be expedited by specifying test needs ahead of time, facilitating efficient interactions with any subcontractors tasked with running the requested tests. Evaluating the outcomes of these tests will inform MCRE ERD procedures and timing and will also identify additional technical constraints for the MCRE ERD System. This upfront process optimization effort will help the project save time and resources at the end of the experiment.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Identifying Nuclear Data Correlated Through Predicting Bias in Integral Experiments via Applying Principal Component Analysis to Random Forest

ABSTRACT Nuclear data (ND) are the input data for neutron‐transport simulations to answer questions related to nuclear technologies. Subsets of ND, here > 20,000 data points, are validated with respect to thousands of criticality experiments that represent various applications on a small scale. The aim of validation with these experiments is to find errors in ND or methods. The key challenge here is that several hundreds of ND are used to simulate one integral value. Hence, one cannot clearly identify what ND are leading to bias in criticality measurements. In fact, a mistake in one nuclear‐data observable can be compensated with an error in another, and the predicted criticality value would still be predicted in agreement with experimental data. Random forest (RF) was previously employed to predict bias in criticality measurements using sensitivities of simulated criticality experiments to ND. The SHapley Additive exPlanations (SHAP) metric was then applied to attribute the importance of each ND experiment and observable to bias prediction. This, however, did not highlight what ND were jointly related to predicting bias. This is important as it could inform us about where compensating errors in ND could hide. We tackle this shortcoming here by first decomposing the ND sensitivities to integral‐experiment simulations into principal components. Then we use principal component projections to predict bias via the RF and SHAP. The SHAP values and principal components are employed to reconstruct detailed SHAP values for each ND observable. We demonstrate that these extended SHAP bias predictions are more robust, less noisy, and more efficient. In addition, we show that this approach accounts for covariance in ND sensitivities and automates the identification of where compensating errors could hide in ND.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The new physics case for beam-dump experiments with accelerated muon beams

As the field examines a future muon collider as a possible successor to the LHC, we must consider how to fully utilize not only the high-energy particle collisions, but also any lower-energy staging facilities necessary in the R&D process. An economical and efficient possibility is to use the accelerated muon beam from either the full experiment or from cooling and acceleration tests in beam-dump experiments. Beam-dump experiments are complementary to the main collider as they achieve sensitivity to very small couplings with minimal instrumentation. We demonstrate the utility of muon beam-dump experiments for new physics searches at energies from 10 GeV to 5 TeV. We find that, even at low energies like those accessible at staging or demonstrator facilities, it is possible to probe new regions of parameter space for a variety of generic BSM models, including muonphilic, leptophilic, L μ − L τ , and dark photon scenarios. Such experiments could therefore provide opportunities for discovery of new physics well before the completion of the full multi-TeV collider.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SPARTA: A flux adjustment methodology to interpret complex experiments

For the accurate determination of reactivity from a detector count rate, correction of spatial effects is of prime importance. This spatial correction is often provided using simulation methodologies, but this may introduce a bias if the result of the experiment is also used as input data for the simulation. Here, this work presents a flux adjustment methodology able to infer experimental reactivity and correction of spatial effects without the need for a simulation. It can process the signal from a complex experiment such as a heat balance measurement in the TREAT reactor, where control rods are continuously adjusted to maintain a constant power. In the present work, this methodology successfully computed the reactivity and the local spatial variation of the flux of a generated signal. It also proved to be robust against noise and errors on kinetic parameters and provides a credible interpretation of a heat balance experiment in TREAT. Efficiency of flux adjustment methods for complex experiment enable a better experiment interpretation less reliant on nuclear data evaluation.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Dynamic modeling of heat pipe integrated thermal battery latent heat storage system experiment validation

A heat pipe integrated thermal battery system has been constructed to investigate a high-temperature latent heat thermal energy storage technology that takes advantage of near isothermal operation of latent heat storage and heat pipes to potentially enable high-energy isothermal heat storage. A dynamic model constructed in Modelica has been validated, showing errors between 2.5 °C–39.7 °C across 10-h to 47-h simulations against experiment results, showing good prediction capability of experiment output, especially against phase change time. Model calibrations showing vessel heat-up capability of 3 kW and heat pipes combining to provide 600 W each during experiment operation validate experiment circumstances including reduced material loading and reduced power capability. The experiment configuration uses an Al-Mg-Zn eutectic metal as the storage material, heated via heat tape wrapped around the vessel and guide tubes to bring the system to operation range (>400 °C) and to simulate charging heat exchange, respectively, with heat rejection occurring through the surfaces of the material and facilitated via guide tubes with less insulation wrapping. The model is available in the open-source repository HYBRID on Github.

25 - ENERGY STORAGE↗

Overview of oxygen opacity experiments at the National Ignition Facility and investigation of potential systematic errors

Experiments to measure oxygen opacity at stellar interior conditions have been performed at the National Ignition Facility in a Discovery Science campaign. These experiments utilize the Opacity-on-NIF platform with a sample comprised of O, Mg, and Si. The spectral data from the Opacity Spectrometer cover the 1000–2000 eV photon energy range showing bound-free continuum absorption from O and line absorption from Mg and Si. DANTE and the Gated X-ray Detector are employed to measure the sample plasma’s temperature and density, respectively. Initial data show lower transmission than expected by theoretical models, raising questions of whether potential background or data uniformity concerns could produce systematic errors in the inferred transmission. Here, we investigate three concerns thought to be important for the oxygen opacity data, including instrumental scattered background, sample self-emission non-uniformity, and backlight continuum non-uniformity. Additionally, we show the effect of a recently developed method to account for 2nd order crystal reflection. The total effect of these concerns on one experiment is found to be small compared to the observed difference between the inferred transmission and a model calculation at the inferred temperature and density. Thus, we conclude that these potential sources of systematic error cannot account for the observed difference, increasing the likelihood of a real effect due to the high temperature and density conditions. However, because this is only a single experiment, we cannot make a firm conclusion. More experiments measuring the opacity and necessary calibrations are needed to assess the reproducibility and uncertainty of this result.

79 ASTRONOMY AND ASTROPHYSICS↗

Integrating HPC simulations and physical experiments to characterize the effects of gamma radiation on seismic protective devices

Seismic protective systems, composed of seismic isolators and dampers, can substantially reduce the effects of earthquake shaking on nuclear power plants and components therein. To enable the use of these devices to protect equipment inside a plant and close to a source of radiation, the U.S. Department of Energy (DOE) funded a project at the Idaho National Laboratory (INL) and the University at Buffalo to characterize the effects of absorbed gamma dose on their mechanical properties. An early task in the project was to determine the exposure time required in the INL Foss Therapy Services (FTS) 60 Co gamma irradiator to achieve a target absorbed dose in the materials used to construct isolators and dampers, including fluids, polymers, composites, and metals. This task required the novel integration of high-performance computing (HPC), Monte Carlo N-Particle (MCNP) simulations, and irradiation experiments using Fricke dosimetry. An MCNP model of the FTS irradiator at INL was developed and validated using Fricke dosimetry. Simulations of three experiments in the irradiator, two with Fricke vials only and one with Fricke vials and a large-size isolator, predicted the Fricke-measured absorbed dose rate to within 15% in all three cases, providing high confidence in the calculation of the gamma dose absorbed in the materials comprising the seismic protective devices. The simulations demonstrated that the effects of photon scattering on absorbed dose rate in the FTS irradiator are negligible for test articles installed close to the cobalt sources and near the rear of the irradiator. The validated MCNP model of the FTS irradiator is being used to support ongoing DOE-funded experiments on seismic protective devices and could be applied to future, non-seismic-related experiments. In conclusion, the novel validation process successfully deployed for the FTS irradiator at INL could be applied to other irradiators, requiring new MCNP models and simulations, and irradiation experiments using dosimeters.

42 - ENGINEERING↗

ESAC (EQ-SANS Assisting Chatbot): Application of large language models and retrieval-augmented generation for enhanced user experience at EQ-SANS

Neutron scattering experiments have played vital roles in exploring materials properties in the past decades. While user interfaces have been improved over time, neutron scattering experiments still require specific knowledge or training by an expert due to the complexity of such advanced instrumentation and the limited number of experiments each person may perform each year. This paper introduces an innovative chatbot application that leverages Large Language Models(LLM) and Retrieval-Augmented Generation (RAG) technologies to significantly enhance the user experience at the EQ-SANS, a small-angle neutron scattering instrument at the Spallation Neutron Source of Oak Ridge National Laboratory. Through a user-centric design approach, the EQ-SANS Assisting Chatbot (ESAC) serves as an interactive reference for users, thereby facilitating the use of the instrument by visiting scientists. By bridging the gap between the users of EQ-SANS and the control systems required to perform their experiments, the ESAC sets a new standard for interactive learning and support for the scientific community using large-scale scientific facilities.

97 MATHEMATICS AND COMPUTING↗

Determining the Conformation of Supported Complexes Using an 17 O TEDOR-like NMR Experiment

Dynamic nuclear polarization surface-enhanced nuclear magnetic resonance (NMR) spectroscopy has enabled the determination of the three-dimensional configuration of surface sites, in particular supported metal complexes of relevance to single-site heterogeneous catalysis. These approaches have chiefly leveraged the application of NMR double-resonance experiments that either reveal the complex conformation via point-to-point intramolecular distances between spin-labeled atoms or the complex-surface orientation via distances between the spins and the surface plane. Either method typically requires expensive isotope labeling and each reports on different structural features. The application of an experiment that simultaneously reveals both types of distances with chemical resolution would be ideal. Here, in this article, we describe an 17 O{ 1 H} pseudo-3D correlation experiment that achieves this goal. Specifically, Si–O–Si and Si–O–M oxygens are well-resolved by 17 O NMR; therefore, distances can be simultaneously measured radially, between Si– 17 O–M and the 1 H’s of the ligands, and vertically to the Si– 17 O–Si linkages of the silica support. We demonstrate the experiment using supported yttrium and zirconium complexes. Good agreement is obtained when comparing the experimental results to theoretical predictions from density functional theory calculations, highlighting the reliability of this relatively simple experiment.

alkyls↗

Physics informed neural network can retrieve rate and state friction parameters from acoustic monitoring of laboratory stick-slip experiments

Various machine learning (ML) and deep learning (DL) techniques have been recently applied to the forecasting of laboratory earthquakes from friction experiments. The magnitude and timing of shear failures in stick-slip cycles are predicted using features extracted from the recorded ultrasonic or acoustic emission (AE) signals. In addition, the Rate and State Friction (RSF) constitutive laws are extensively used to model the frictional behavior of faults. In this work, we use data from shear experiments coupled with passive acoustic (variance, kurtosis, and AE rate) interleaved with active source ultrasonic monitoring (transmitted wave amplitude) to develop physics-informed neural network (PINN) models incorporating the RSF law and AE rate generation equation with wave amplitude serving as a proxy for friction state variable. This PINN framework allows learning RSF parameters from stick-slip experiments rather than measuring them through a series of velocity step experiments. We observe that when the stick-slip cycles are irregular, the PINN models outperform the data-driven DL models. Transfer learning (TL) PINN models are also developed by pre-training on data collected at one normal stress level followed by forecasting shear failures and retrieving RSF parameters at other stress levels (i.e., with different recurrence intervals) after retraining on a limited amount of new data. Our findings suggest that TL models perform better compared to standalone models. Both standalone and TL PINN-estimated RSF parameters and their ground truth values show excellent agreements thus demonstrating that RSF parameters can be retrieved from laboratory stick-slip experiments using the corresponding acoustic data and that the transmitted wave amplitude provides a good representation of the evolving frictional state during stick-slips.

58 GEOSCIENCES↗

Building workflows for an interactive human-in-the-loop automated experiment (hAE) in STEM-EELS

Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron energy-loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). However, the current paradigm of STEM-EELS relies on the classical rectangular grid sampling, in which all surface regions are assumed to be of equal a priori interest. However, this is typically not the case for real-world scenarios, where phenomena of interest are concentrated in a small number of spatial locations, such as interfaces, structural and topological defects, and multi-phase inclusions. One of the foundational problems is the discovery of nanometer- or atomic-scale structures having specific signatures in EELS spectra. Herein, we systematically explore the hyperparameters controlling deep kernel learning (DKL) discovery workflows for STEM-EELS and identify the role of the local structural descriptors and acquisition functions in experiment progression. In agreement with the actual experiment, we observe that for certain parameter combinations the experiment path can be trapped in the local minima. We demonstrate the approaches for monitoring the automated experiment in the real and feature space of the system and knowledge acquisition of the DKL model. Based on these, we construct intervention strategies defining the human-in-the-loop automated experiment (hAE). This approach can be further extended to other techniques including 4D STEM and other forms of spectroscopic imaging. The hAE library is available on Github at https://github.com/utkarshp1161/hAE/tree/main/hAE.

Pratiush, Utkarsh [Univ. of Tennessee, Knoxville, ↗

BigPanDA monitoring system evolution in the ATLAS Experiment

Monitoring services play a crucial role in the day-to-day operation of distributed computing systems. The ATLAS Experiment at LHC uses the Production and Distributed Analysis workload management system (PanDA WMS), which allows a million computational jobs to run daily at over 170 computing centers of the WLCG and opportunistic resources, utilizing 600k cores simultaneously on average. The BigPanDA monitor is an essential part of the monitoring infrastructure for the ATLAS Experiment that provides a wide range of views, from top-level summaries to a single computational job and its logs. Over the past few years of the PanDA WMS advancement in the ATLAS Experiment, several new components were developed, such as Harvester, iDDS, Data Carousel, and Global Shares. Due to its modular architecture, the BigPanDA monitor naturally grew into a platform where the relevant data from all PanDA WMS components and accompanying services are accumulated and displayed in the form of interactive charts and tables. Moreover the system has been adopted by other experiments beyond HEP. In this paper we describe the evolution of the BigPanDA monitor system, the development of new modules, and the integration process into other experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Uncertainty quantification of material parameters in modeling coupled metal and high explosive experiments

Experiments involving the coupling of metal and high explosives (HE) are of notable defense-related interest, and we seek to refine the uncertainty quantification associated with models of such experiments. In particular, our focus is on how uncertainty related to the metal constitutive model challenges our ability to infer high explosive model parameters when analyzing focused science experiments. We consider three focused experiments involving an HE accelerating metal: small plate tests with tantalum/LX-14 and tantalum/LX-17 pairings as well as a tantalum/LX-17 cylinder test. For all three models, we perform sensitivity analysis to ascertain the influence of metal strength on the coupled experimental response. Moreover, we calibrate each model in a Bayesian setting and study the quantification of metal strength on the inference of the HE parameters. Based on our results, we offer guidance for future metal/HE experiments.

36 MATERIALS SCIENCE↗

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↗