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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Interactions Between Climate and Species Drive Future Forest Carbon and Water Balances

Global change is altering forest carbon and water balances; however, the extent to which tree species shape ecosystem‐scale responses to climate, particularly in biodiverse forests, remains unclear. To address this, we simulated the effects of an envelope of future climate conditions on watershed carbon and water balances and quantified the contributions of tree species based on their xylem anatomy. We accomplished this by incorporating species‐level transpiration calculations into a landscape‐scale ecosystem process model. Our revised model linked the effects of forest succession, species composition, and climate change on water and carbon. Calibration of forest water fluxes using sap flux measurements and catchment water balances captured variability in species transpiration and interannual ET in biodiverse, humid temperate forest catchments in the southern Blue Ridge Mountains, USA. Across wet and dry future climate projections, ET increased, and streamflow and net carbon uptake decreased, particularly under a scenario of increasing drought. Despite accounting for just 30% of current biomass, diffuse‐porous tree species were the main driver of carbon and water flux responses now and in the future, thus intensifying the increase in ET and decline in streamflow. As diffuse‐porous biomass continues to increase, these forests will be increasingly sensitive to drought, amplifying losses of carbon sequestration and freshwater delivery.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Global energy balance simulations of shattered pellet injection

The dynamics of shattered pellet injection (SPI) shutdowns are simulated using a time-dependent global energy balance model, based on a modification of the KPRAD framework. The new SPI particle source in the model calculates the ablation of individual pellet fragments that enter the plasma as a temporally resolved plume, thus capturing the effects of earlier fragments on the ablation of those that follow, which has a significant impact on the overall assimilation. Despite the reduced physics and the global averaging of all quantities, results from a large number of DIII-D, KSTAR, and JET experiments are well reproduced, including the plasma cooling timescales, particle assimilation, and current quench (CQ) rates. Cooling timescales and CQ rates are in good agreement for pellets containing as little as ∼1% neon, while particle assimilations are most accurate for neon fractions above ∼15% by number of atoms. Below this, the assimilation tends to be overestimated due to the lack of radial transport in the particle balance, which becomes important in the low-Z limit. Predictive simulations of mixed-composition dual-SPI shutdowns in ITER are compared against those with the 3D non-linear magnetohydrodynamic code JOREK and are found to reproduce overall trends observed in the higher-fidelity modeling across a range of injection scenarios. The general success of the model points to the critical role of energy balance in determining SPI particle assimilation and the subsequent disruption dynamics and highlights the value of these simulations for experimental interpretation and for optimizing the deployment of computationally expensive, higher-fidelity models.

energy balance model↗
DOE OSTI2022

Renewable Energy and Efficiency Technologies in Scenarios of U.S. Decarbonization in Two Types of Models: Comparison of GCAM Modeling and Sector-Specific Modeling

Energy system projections from analytic models inform actions ranging from short-term and local decisions, such as technology and infrastructure deployment, to global and long-term negotiations and targets. Computational limits require the designers of these models to trade off between coverage and resolution. Some models, such as the Global Change Analysis Model (GCAM), represent all energy sources and uses but at a relatively coarse level of resolution. GCAM balances global supply and demand of all energy carriers by endogenously projecting prices for energy sources and costs of greenhouse gas mitigation while capturing interlinkages between the energy system, water, agriculture and land use, the economy, and the climate. This global model was used to frame the Long-Term Strategy released by the White House in 2021 and has been used to inform national and global economy-wide decarbonization discussions and strategy development for decades. Other models instead focus on a portion of the energy sector with greater detail and resolution. The Regional Energy Deployment System (ReEDS) electricity-sector model, for example, projects capacity expansion with an emphasis on integration of variable renewable energy into the grid of the future. The Transportation Energy and Mobility Pathway Options (TEMPO) transportation-sector model enables analysis of household choices in adoption, charging, and use of electric vehicles. The Scout buildings-sector model supports detailed consideration of the policies and markets that can accelerate the adoption of energy conservation measures in buildings. Such sector-specific models are instrumental in informing technology research, sectoral planning strategies, and sector-specific aspects of greenhouse gas (GHG) mitigation strategies in the United States. These global and sector-specific modeling approaches can complement each other. The global approach ensures consistent, endogenous energy pricing and resource allocation, which can substantially diverge from current conditions in transformative scenarios, while the sector-specific approach facilitates representation of granular details across spatial, temporal, technological, and market dimensions that enable exploration of particular interactions and trade-offs. This report presents the results of recent work to explore the differences and tradeoffs between these approaches by comparing GCAM with the sector-specific ReEDS, TEMPO, and Scout models. The report compares both model structures and results, and discusses their potential relevance and applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Accelerating multicanonical sampling with irreversibility

Flat-histogram Monte Carlo simulations are well-established, robust methods to perform random walks in a physical observable or parameter space, making them suitable for finding ground states or studying phase transitions in complex systems in statistical physics. However, their efficiency can be limited by the time to attain the desired flat distribution, which is generally unknown prior to the simulations. In particular, they might suffer from slowing down towards the end of a simulation due to the diffusive nature of random walks. In this work we apply irreversibility to the multicanonical Monte Carlo method via the lifting approach to alleviate this behavior. We achieve a 2–4 times speedup in ground-state search for a two-dimensional (2D) Ising model, and up to an order of magnitude of speedup for finding the ground-state energy in an Edwards–Anderson spin glass, compared to traditional multicanonical sampling. In conclusion, the round-trip times between ground states show a narrower distribution and are significantly shorter compared to the reversible counterpart, suggesting that a lower convergence time with a smaller time variance is feasible.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Widespread underestimation of rain-induced soil carbon emissions from global drylands

Dryland carbon fluxes, particularly those driven by ecosystem respiration, are highly sensitive to water availability and rain pulses. However, the magnitude of rain-induced carbon emissions remains unclear globally. Here we quantify the impact of rain-pulse events on the carbon balance of global drylands and characterize their spatiotemporal controls. Using eddy-covariance observations of carbon, water and energy fluxes from 34 dryland sites worldwide, we produce an inventory of over 1,800 manually identified rain-induced CO2 pulse events. Based on this inventory, a machine learning algorithm is developed to automatically detect rain-induced CO2 pulse events. Our findings show that existing partitioning methods underestimate ecosystem respiration and photosynthesis by up to 30% during rain-pulse events, which annually contribute 16.9 ± 2.8% of ecosystem respiration and 9.6 ± 2.2% of net ecosystem productivity. We show that the carbon loss intensity correlates most strongly with annual productivity, aridity and soil pH. Finally, we identify a universal decay rate of rain-induced CO2 pulses and use it to bias-correct respiration estimates. Our research highlights the importance of rain-induced carbon emissions for the carbon balance of global drylands and suggests that ecosystem models may largely underrepresent the influence of rain pulses on the carbon cycle of drylands.

Nguyen, Ngoc B↗
DOE OSTI2025

Simulating Pyrocumulonimbus Clouds Using a Multiscale Wildfire Simulation Framework

Pyrocumulonimbus (pyroCb) clouds, driven by extreme fires under favorable meteorological conditions, can inject smoke into the stratosphere at magnitudes comparable to those of moderate volcanic eruptions, potentially altering the global radiative balance and atmospheric composition. However, simulating pyroCb is particularly challenging in Earth system models. Using the Energy Exascale Earth System Model (E3SM), we developed a novel global multiscale framework to model pyroCb events in California, which includes a high‐resolution fire radiative power time series, a one‐dimensional plume‐rise parameterization, a fire‐induced vertical water vapor transport scheme, and a surface wildfire sensible heat flux representation. Our simulation successfully reproduces many pyroCb features, including cloud height, spatiotemporal evolution, and convective intensity in comparison with satellite and ground‐based observations. Sensitivity experiments show that realistic pyroCb simulation depends on vertical water vapor transport. These advances provide a basis for future exploration of pyroCb impacts at regional and global scales within climate models.

E3SM↗
DOE OSTI2025

Size-resolved process understanding of stratospheric sulfate aerosol following the Pinatubo eruption

Stratospheric sulfate aerosol produced by volcanic eruptions plays important roles in atmospheric chemistry and the global radiative balance of the atmosphere. The simulation of stratospheric sulfate concentrations and optical properties is highly dependent on the chemistry scheme and microphysical treatment. In this work, we implemented a sophisticated gas-phase chemistry scheme (full chemistry, FC) and a 5-mode version of the Modal Aerosol Module with Prognostic Stratospheric Aerosol (MAM5-PSA) for the interactive treatment of stratospheric sulfate aerosol in the Department of Energy's Energy Exascale Earth System Model version 2 (E3SMv2) model to better simulate the chemistry-aerosol feedback following the Pinatubo eruption, and to compare it against a simulation using simplified chemistry (SC) and the default 4-mode version of the Modal Aerosol Module (MAM4). MAM5-PSA experiments were found to better capture the stratospheric sulfate burden from the eruption of the volcano to the end of 1992 as compared to the High-resolution Infrared Sounder (HIRS) observations, and the formation of sulfate in MAM5-PSA with FC (with an additional OH replenishment reaction) was significantly faster than in MAM4 with FC. Analyses of microphysical processes indicate that more sulfate aerosol mass was generated in total in FC experiments than in SC experiments. MAM5-PSA performs better than MAM4 in simulation of aerosol optical depth (AOD); AOD anomalies from the MAM5-PSA experiment have better agreement with observations. The simulated largest changes in global mean net radiative flux at the top of the atmosphere following the eruption were about −3 W m −2 in MAM5-PSA experiments and roughly −1.5 W m −2 in MAM4 experiments.

AEROSOL↗
DOE OSTI2025

Exploring Multilayer Network Models to Build a Scientific Basis for Integrated Deterrence: Final Report

The emerging multipolar international security environment represents a fundamental restructuring of global nuclear balance of power to include two nuclear peer competitors, growing non-peer nuclear threats, and concerns of nuclear latency from both allies and adversaries. Conflicts in the grey zone, cyber operations, mis- and disinformation campaigns, and emerging disruptive technologies like drones, and hypersonic missiles are becoming more prevalent. These present a risk of cross-domain and multi-domain conflicts that may not follow known escalatory patterns. In order to prepare for the new deterrence environment, it is critical to have quantitative and qualitative understandings of these cross-domain conflicts, their potential for escalation, and which systems they may impact. To that end, our team created a Multi-Layer Network (MLN) model of ‘integrated deterrence’ where instruments of national power are modeled as individual network graph layers that include efforts from all domains. We then evaluate the potential for escalation against escalation scenarios. Analysis of the escalation scenarios is then used to identify insights of potential risk and escalation within integrated deterrence.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Three-Channel Sunphotometer Cloud Mode Value-Added Product Report

A primary source of uncertainty in Earth system model (ESM) predictions is the representation of cloud processes and associated cloud feedback. Several fundamental cloud properties critical to the understanding of aerosol-cloud interactions are poorly constrained by observations, with key deficiencies in our observations of cloud and precipitation droplet sizes and cloud optical depth. Observations of these cloud properties are often challenging to estimate from remote-sensing platforms and costly to obtain from in situ aircraft. Nevertheless, observations of boundary-layer clouds, and improved knowledge of stratocumulus cloud (Sc) processes, are especially important to ESM advancement. This is because these clouds have extensive coverage and exert controls on boundary-layer dynamics and the global radiative energy balance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Core-edge integrated predictive studies of ST40 and NSTX plasmas with the scrape-off layer box model

The ability to model the interplay between the core and edge of tokamak plasmas is crucial to designing both the plasma operating scenario of a fusion pilot plant and the design of the tokamak itself. Scrape-off-layer (SOL) models that are tailored to integrated scenario modeling need to have fast turn-around time and minimal computational burden to enable wide parameter-space coverage for design scoping. The SOL 0-D Box model is a reduced SOL model based on global power and particle balance that captures the essential physics of SOL transport with little computational cost. The usage of the 0-D Box model in core-edge coupled simulations has been demonstrated in both interpretive and predictive modes on a variety of devices. This paper presents a sensitivity study of the 0-D Box model to the input SOL heat-flux width for an ST40 plasma. This study demonstrates that accurate prediction of this width is crucial to predicting global performance parameters of a plasma scenario, such as energy confinement time and flux consumption. We also present an extension of the Box model to 1-D to allow for parallel variation of plasma parameters along the magnetic field lines. The 1-D Box model is then compared with SOLPS-ITER simulations of an NSTX plasma. Advantages and limitations of the Box model are discussed, and future directions are outlined.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Bringing Inorganic Carbon to Life: Developing Model Metalloenzymes for C1 Conversion Reactions

The global carbon cycle is carefully balanced through the use of specialized enzymes in plants, algae, bacteria, and archaea. A primordial metabolic pathway for the conversion of inorganic carbon into cellular biomass uses a large, nickel-containing enzyme called carbon monoxide dehydrogenase (CODH)/acetyl coenzyme A synthase (ACS). This system fixes carbon dioxide (CO 2 ) into carbon monoxide (CO) at the CODH site. The carbon monoxide is then used to generate acetyl coenzyme A, a biological building block, through a key carbon-carbon bond forming step at the nickel site in ACS. Despite the significance of these processes in the context of energy conversion, the fundamental chemistry underlying these transformations has remained elusive, in part due to the complexity of the natural enzyme. To better understand the principles governing these biological processes, which represent one-carbon (C 1 ) activation reactions, this project will develop functional models of CODH and ACS based on modifications to a small metalloprotein scaffold. Comprehensive characterization of these systems using advanced spectroscopic and biophysical techniques will reveal key elements responsible for conferring high levels of activity to the model systems, with implications for gaining insight into the mechanisms of the natural enzymes. Moreover, the principles learned from this research can be used to guide design of robust catalysts for efficient conversion of CO 2 and CO into liquid fuels.

10 SYNTHETIC FUELS↗
DOE OSTI2025

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers

Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting sustainability. We present LC-Opt, a Sustainable Liquid Cooling (LC) benchmark environment, for reinforcement learning (RL) control strategies in energy-efficient liquid cooling of high-performance computing (HPC) systems. Built on the baseline of a high-fidelity digital twin of Oak Ridge National Lab's Frontier Supercomputer cooling system, LC-Opt provides detailed Modelica-based end-to-end models spanning site-level cooling towers to data center cabinets and server blade groups. RL agents optimize critical thermal controls like liquid supply temperature, flow rate, and granular valve actuation at the IT cabinet level, as well as cooling tower (CT) setpoints through a Gymnasium interface, with dynamic changes in workloads. This environment creates a multi-objective real-time optimization challenge balancing local thermal regulation and global energy efficiency, and also supports additional components like a heat recovery unit (HRU). We benchmark centralized and decentralized multi-agent RL approaches, demonstrate policy distillation into decision and regression trees for interpretable control, and explore LLM-based methods that explain control actions in natural language through an agentic mesh architecture designed to foster user trust and simplify system management. LC-Opt democratizes access to detailed, customizable liquid cooling models, enabling the ML community, operators, and vendors to develop sustainable data center liquid cooling control solutions.

Naug, Avisek [Hewlett Packard Enterprise]↗
DOE OSTI2025

The Dynamic Tripolar Strategic Balance: A Net Assessment (Workshop Summary)

On December 9-10, the Center for Global Security Research (CGSR) at Lawrence Livermore National Laboratory (LLNL) hosted a workshop titled “The Dynamic Tripolar Strategic Balance: A Net Assessment.” The discussion was guided by the following key questions: • By what metrics should the strategic balance be assessed? • How dynamic is the balance? How fragile? • Is the United States gaining strategic advantage, losing it, or holding steady, overall? • In order to gain new advantages or re-gain advantages lost, can or should the United States prioritize some domains and accept more risk in others? If so, which ones?

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Heterotrophic respiration by soil microbes in a changing climate

Soil microbes strongly influence the soil organic carbon (SOC) pool, which globally stores ~2,000 PgC. Specifically, the balance between microbial heterotrophic respiration (R H ), which degrades SOC, and plant–microbe interactions that stabilize SOC determines whether terrestrial ecosystems are a net source or sink of CO 2 to the atmosphere. Here, in this Review, we evaluate how climate change alters these competing processes. R H is approximately half of total soil respiration, at ~50 PgC yr −1 , with 70% occurring in topsoils. Warming accelerates microbial metabolism, with a 10 °C temperature increase estimated to raise R H by ~50%, an effect that is particularly strong in Arctic soils. Warming also reduces soil moisture, further modulating R H , which responds nonlinearly to soil moisture, being limited by saturation and desiccation and meeting a maximum at intermediate levels. Consequently, R H is highly sensitive to future precipitation changes and drought. However, soil management strategies could enhance SOC stocks and persistence under climate change. Bacterial and fungal inoculants can promote SOC production and stabilization, while deep-rooting plants increase SOC inputs to deeper layers that experience lower R H . Agricultural practices and biochar amendments can also enhance SOC and reduce R H . Expanding field trials across regions, climates and soil types would improve empirical understanding of these responses and support better representation of R H in predictive models, enabling more accurate assessments of climate impacts on SOC storage.

Jansson, Janet K. [Pacific Northwest National Labo↗
DOE OSTI2026

Evaluating Polymer Properties with Different Additives for Carbon Capture and Other Applications

Anthropogenic climate change is one of this generation’s most pressing concerns, with the potential to completely alter the delicate balance we’ve struck with nature. Already, global temperatures have risen 1.29°C, leading to disrupted weather systems, extinctions, increased risks of wildfires, and sea level rise, to name a few effects. Carbon dioxide emission from the combustion of fossil fuels and other industrial activity is a large driver of this phenomenon, as it absorbs heat before it can be radiated away from Earth, trapping it. Carbon dioxide has reached unprecedented levels in our atmosphere, showing a 50% increase from preindustrial averages to a whopping 430 ppm. Thus, reducing the amount of carbon dioxide via carbon capture technology is an important endeavor that serves to benefit everyone. The Microencapsulated CO 2 Sorbent (MECS) team at Lawrence Livermore National Laboratory (LLNL) has turned to microencapsulation to approach this endeavor. Microcapsules provide an attractive approach to carbon capture, combining large surface areas for more efficient mass transfer, regenerative abilities, reduced solvent loss, and improved handling. Additionally, while existing carbon capture technology relies on industrial plants, capsules could present a modular approach to carbon capture, reducing the need for extensive physical infrastructure. The MECS team’s design consists of a polymer membrane that contains a liquid carbon sequestering sorbent, aqueous sodium carbonate. The carbon capturing reaction occurs in three distinct steps, the first of which is the dissolution of carbon dioxide into the sorbent solution and its conversion into carbonic acid (H 2 CO 3 ), shown in equations 1 and 2 respectively. Because this step hinges upon the ability of carbon dioxide to reach the solution inside the capsule, it is necessary that the microcapsule shell is permeable to carbon dioxide gas. The MECS team produces these microcapsules using the in-air droplet encapsulation apparatus (IDEA) shown in figure 1, which can produce uniform micron-scale droplets at speeds much faster than traditional single-dispersal microfluidic-based techniques. The IDEA Is 100 times faster than these current techniques and can reach up to 1000 times their speed when incorporating a multi-nozzle design. Additionally, because droplets are produced in-air via vibration, IDEA can decrease post-processing times and material waste by 99% and can fabricate microgels that are 10 to 100 times more viscous than can be produced via traditional microfluidics. While this design represents a breakthrough in the throughput, efficiency, and tunability of microcapsule production, it imposes a major constraint on the microcapsule curing process. Because microcapsule shells are crosslinked with UV light while falling 30 cm through the air, this gives them a reaction window of approximately 0.2 seconds. Thus, the system and shell formulations must be optimized such that the shells can be fully crosslinked within this very narrow window, prompting investigations into curing behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fast and sensitive measurements of sub-3 nm particles using Condensation Particle Counters For Atmospheric Rapid Measurements (CPC FARM)

New particle formation (NPF) is the atmospheric process whereby gas molecules react and nucleate to form detectable particles. NPF has a strong impact on Earth's radiative balance as it produces roughly half of global cloud condensation nuclei. However, the time resolution and sensitivity of current instrumentation are inadequate in measuring the size distribution of sub-3 nm particles, the particles critical for understanding NPF. Here we present the Condensation Particle Counters For Atmospheric Rapid Measurements (CPC FARM), a method to measure the concentrations of freshly nucleated particles. The CPC FARM consists of five CPCs operating in parallel, each configured to operate at different detectable particle sizes between 1–3 nm. This study explores two methods to calculate the size distribution from the differential measurements across the CPC channels. The performance of both inversion methods was tested against the size distribution measured by a pair of stepping particle mobility sizers (SMPSs) during an ambient air sampling study in Pittsburgh, PA. Observational results indicate that the CPC FARM is more accurate with higher time resolution and sensitivity in the sub-3 nm range compared to the SMPS.

Cheng, Darren [Carnegie Mellon Univ., Pittsburgh, ↗
DOE OSTI2025

Global heliospheric termination shock strength in the solar–interstellar interaction

A heliospheric termination shock (HTS) surrounds our Solar System at approximately 100 astronomical units from the Sun, where the expanding solar wind (SW) is compressed and heated before encountering the interstellar medium. HTS-accelerated particles govern the pressure balance with the interstellar medium, but little is known about the global properties of the HTS beyond in situ measurements from Voyager in only two directions of the sky. Here we fill this gap by extracting the HTS strength using particle-in-cell, test particle and magnetohydrodynamic simulations, constrained by Interstellar Boundary Explorer observations of energetic neutral atoms produced from HTS-accelerated particles. Our results reveal there is a higher compression near the poles during solar minimum compared with solar maximum due to the higher Mach number flow. North–south asymmetries arise from the disparate evolution of the polar coronal holes, while minimum compression near the flanks is probably due to SW slowing from mass loading over a greater distance to the HTS. The results imply a strong connection between the HTS strength and the SW and interstellar medium dynamics.

Astrophysical plasmas↗