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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Confronting Earth System Model trends with observations

Anthropogenically forced climate change signals are emerging from the noise of internal variability in observations, and the impacts on society are growing. For decades, Climate or Earth System Models have been predicting how these climate change signals will unfold. While challenges remain, given the growing forced trends and the lengthening observational record, the climate science community is now in a position to confront the signals, as represented by historical trends, in models with observations. This review covers the state of the science on the ability of models to represent historical trends in the climate system. It also outlines robust procedures that should be used when comparing modeled and observed trends and how to move beyond quantification into understanding. Finally, this review discusses cutting-edge methods for identifying sources of discrepancies and the importance of future confrontations.

58 GEOSCIENCES↗
DOE OSTI2025

Shrub Expansion Simulations at Trail Valley Creek Tundra site using E3SM Land Model (ELM) Arctic-focused Version

The warming of the Arctic is causing substantial compositional, structural, and functional changes in tundra vegetation including shrub and densification in parts of the Arctic. Assessing the impact of these changes in vegetation composition on the Arctic’s carbon and energy budgets is important to constrain projected local and global surface-atmosphere exchanges. We conduct a sensitivity analysis of the projected surface energy fluxes, soil carbon pools, and carbon dioxide fluxes (net ecosystem exchange, gross primary production, and ecosystem respiration) between present day and 2100 to different shrub expansion rates and air temperature increases under future emission scenarios (intermediate – RCP4.5, and high – RCP8.5) using the Arctic-focused version of the Energy Exascale Earth System Model (E3SM) Land Model (ELM). We focus on Trail Valley Creek (TVC), a mineral upland tundra site located in the western Canadian Arctic, which is experiencing tall shrub densification and expansion. In this study, we run TVC under two different warming scenarios RCP4.5 and RCP 8.5 and simulate different shrubification rates projected until year 2100. In this repository, we include all the forcing, input, parameters, and output data corresponding to all the simulations performed. flmd.csv includes a detailed description of the datasets files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Policy implications of net-zero emissions: A multi-model analysis of United States emissions and energy system impacts

Many countries, subnational jurisdictions, and companies are setting net-zero emissions goals; however, questions remain about strategies to reach these targets, policy measures, technology gaps, and economic impacts. Here, we investigate the potential policy implications of reaching economy-wide net-zero CO 2 emissions across the United States by 2050 using results from a multi-model comparison with 14 energy-economic models. Model results suggest that achieving net-zero CO 2 targets depends on policies that accelerate deployment of zero- and low-emitting technologies that have seen rapid cost reductions in recent years (including wind, solar, battery storage, and electric vehicles) as well as relatively nascent options (including carbon capture and storage, advanced biofuels, low-carbon hydrogen, advanced nuclear, and long-duration energy storage). While net-zero policies are likely to lower fossil fuel consumption, including considerable coal and petroleum reductions, achieving net-zero emissions does not necessarily mean phasing out all fossil fuels. Model results indicate that the Inflation Reduction Act’s energy and climate provisions amplify near-term decarbonization but that net-zero policies have larger impacts on long-run outcomes. Stringent climate policy can have large fiscal impacts on tax revenue and government spending—revenues from carbon pricing and subsidies for carbon removal range from 0.1 % to 3.7 % of GDP in 2050 across models. Each dollar per metric ton carbon price leads to a 0.06 % to 0.31 % reduction in economy-wide CO 2 emissions relative to a reference scenario with current policies. Spending on energy across the economy decreases relative to today for many models under reference and net-zero policies, especially as a share of GDP, due primarily to end-use electrification and energy efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Data-Agnostic, Continuous Machine Learning Framework for Application in High Energy Physics and Beyond: Phase 1 Final Scientific/Technical Report

This Phase 1 effort has focused on the development of continual learning frameworks for use in machine learning, specifically in the applied context of High Energy Physics (HEP). Machine learning (ML) is a transformative technology by which computers, typically through the use of neural networks, are able to perform tasks with proficiency that rivals or surpasses that of human users. Model Degradation & Catastrophic Forgetting are two undesired phenomena which can occur in ML where the performance of a model degrades when either deployed on novel data streams, or trained on novel data which are sufficiently different than the data the models were initially trained on. A natural example where these sorts of effects can be observed is in the performance of detectors in harsh environments, where the detector signature may change over the lifetime of the detector as it ages and deteriorates — precisely what occurs in the experiments conducted in HEP. Real world HEP data is therefore an excellent test-ground and use-case for Continual Learning paradigms, which are techniques used in ML to counteract these problems. Ensemble learning is one such technique, where multiple smaller models are trained on subsets of the overall data and are ensembled together during inference. The intuition behind this technique is that, although there are shifts in the distributions which govern the incoming data streams, these shifts are not expected to be homogeneous or global. If a sufficient diversity in solutions within the various sub-models has been achieved, then at least one sub-model is expected to retain its performance within the overall ensemble. One further strength of this approach is that the architectures of the various models do not need to be identical, and in fact even different modalities of data can naturally be combined in this way. This work focused on applying ensemble learning techniques to derive results using two main datasets, anomaly detection in HEP data & time-series forecasting in semiconductor manufacturing data. Semiconductor manufacturing involves data with surprising similarity to that of HEP (e.g. wafer maps look very similar to digi-occupancy maps) and Cerium Lab’s prominence within the semiconductor industry makes semiconductor manufacturing a natural opportunity for commercialization of this work. Our efforts have led to two strong results. The first is that we evaluated the proposed ensembling techniques using previously proposed machine learning architectures for use in anomaly detection, namely AutoEncoder based models and their derivatives. We also developed new architectures which have not been evaluated in this context before. In fact, this work marks the first use of Vision Transformers for anomaly detection in HEP. Second, we demonstrated that ensemble learning significantly improves model performance in scenarios prone to degradation, validating its effectiveness across both HEP and semiconductor datasets. These results further support ensemble learning as a powerful strategy for mitigating catastrophic forgetting and maintaining robust performance in evolving data environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1996

Strategies for "minimal growth maintenance" of cell cultures: a perspective on management for extended duration experimentation in the microgravity environment of a Space station

How cells manage without gravity and how they change in the absence of gravity are basic questions that only prolonged life on a Space station will enable us to answer. We know from investigations carried out on various kinds of Space vehicles and stations that profound physiological effects can and often to occur. We need to know more of the basic biochemistry and biophysics both of cells and of whole organisms in conditions of reduced gravity. The unique environment of Space affords plant scientists an unusual opportunity to carry out experiments in microgravity, but some major challenges must be faced before this can be done with confidence. Various laboratory activities that are routine on Earth take on special significance and offer problems that need imaginative resolution before even a relatively simple experiment can be reliably executed on a Space station. For example, scientists might wish to investigate whether adaptive or other changes that have occurred in the environment of Space are retained after return to Earth-normal conditions. Investigators seeking to carry out experiments in the low-gravity environment of Space using cultured cells will need to solve the problem of keeping cultures quiescent for protracted periods before an experiment is initiated, after periodic sampling is carried out, and after the experiment is completed. This review gives an evaluation of a range of strategies that can enable one to manipulate cell physiology and curtail growth dramatically toward this end. These strategies include cryopreservation, chilling, reduced oxygen, gel entrapment strategies, osmotic adjustment, nutrient starvation, pH manipulation, and the use of mitotic inhibitors and growth-retarding chemicals. Cells not only need to be rendered quiescent for protracted periods but they also must be recoverable and further grown if it is so desired. Elaboration of satisfactory procedures for management of cells and tissues at "near zero or minimal growth" will have great value and practical consequences for experimentation on Earth as well as in Space. All of the parameters and conditions and procedural details needed to meet all the specific objectives will be the basis of the design and fabrication of cell culture units for use in the Space environment. It is expected that this will be an evolutionary process.

STS-61A Shuttle Project↗
DOE OSTI2026

Experimental protocol for phase 1 of the APARC QUOCA (QUasibiennial oscillation and Ozone Chemistry interactions in the Atmosphere) working group

The quasi-biennial oscillation (QBO) is the main mode of variability in the tropical stratosphere, influencing the predictability of other regions in the atmosphere through its teleconnections to the stratospheric polar vortices and coupling to surface tropical and extratropical variability. However, climate and forecasting models consistently underestimate QBO amplitudes in the lower stratosphere, likely contributing to their failure to simulate these teleconnections. One underexplored contributor to model biases is missing representation of ozone-radiative feedbacks, which enhance temperature variability in the lower stratosphere, particularly at periods at and greater than the QBO (>28 months). While previous studies suggest that ozone-radiative feedbacks can impact QBO periods, amplitudes and the associated secondary circulation in the lower stratosphere, the reported impacts differ widely among models and are hard to interpret due to differences in methodology. To this end, here we propose a coordinated experimental protocol – held joint between the Atmospheric Processes and their Role in Climate (APARC) Quasi-Biennial Oscillation Initiative (QBOi) and Chemistry Climate Modeling Initiative (CCMI) activities – which is aimed at assessing the coupling between stratospheric ozone, temperature and the circulation. We use the proposed experiments to define the ozone feedback on the QBO in both present-day and idealized (abrupt quadrupling of carbon dioxide) climates. While primary focus is on the QBO, the proposed protocol also enables analysis of other aspects of ozone-radiative-dynamical coupling in the atmosphere, including impacts on the Brewer-Dobson Circulation and tropospheric eddy-driven jet responses to future climate change. Here we document the scientific rationale and design of the QUOCA Phase 1 experiments, summarize the data request, and give a brief overview of participating models. Preliminary results using the NASA Goddard Institute for Space Studies E2-2 climate model are used to illustrate sensitivities to certain methodological choices.

Environmental sciences↗
DOE OSTI2026

Systematic Benchmarking of Climate Models: Methodologies, Applications, and New Directions

As climate models become increasingly complex, there is a growing need to comprehensively and systematically assess model performance with respect to observations. Given the increasing number and diversity of climate model simulations in use, the community has moved beyond simple model intercomparison and toward developing methods capable of benchmarking a large number of simulations against a suite of climate metrics. Here, we present a detailed review of evaluation and benchmarking methods and approaches developed in the last decade, focusing primarily on scientific implications for Coupled Model Intercomparison Project (CMIP) simulations and CMIP6 results that contributed to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Based on this review, we explain the resulting contemporary philosophy of model benchmarking, and provide clear distinctions and definitions of the terms model verification, process validation, evaluation, and benchmarking. While significant progress has been made in model development based on systematic evaluation and benchmarking efforts, some climate system biases still remain. The development of open‐source community software packages has played a fundamental role in identifying areas of significant model improvement and bias reduction. We review the key features of several software packages that have been commonly used over the past decade to evaluate and benchmark global and regional climate models. Additionally, we discuss best practices for the selection of evaluation and benchmarking metrics and for interpreting the obtained results, the importance of selecting suitable sources of reference data and accurate uncertainty quantification.

Environmental sciences↗
DOE OSTI2025

Water Mass Transformation Budgets in Finite‐Volume Generalized Vertical Coordinate Ocean Models

Water Mass Transformation (WMT) theory provides conceptual tools that in principle enable innovative analyses of numerical ocean models; in practice, however, these methods can be challenging to implement and interpret, and therefore remain under-utilized. Our aim is to demonstrate the feasibility of diagnosing all terms in the water mass budget and to exemplify their usefulness for scientific inquiry and model development by quantitatively relating water mass changes, overturning circulations, boundary fluxes, and interior mixing. We begin with a pedagogical derivation of key results of classical WMT theory. We then describe best practices for diagnosing each of the water mass budget terms from the output of Finite-Volume Generalized Vertical Coordinate (FV-GVC) ocean models, including the identification of a non-negligible remainder term as the spurious numerical mixing due to advection scheme discretization errors. We illustrate key aspects of the methodology through the analysis of a polygonal region of the Greater Baltic Sea in a regional demonstration simulation using the Modular Ocean Model v6 (MOM6). We verify the convergence of our WMT diagnostics by brute-force, comparing time-averaged (“offline”) diagnostics on various vertical grids to timestep-averaged (“online”) diagnostics on the native model grid. Finally, we briefly describe a stack of xarray-enabled Python packages for evaluating WMT budgets in FV-GVC models (culminating in the new xwmb package), which is intended to be model-agnostic and available for community use and development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Emergent constraints on future methane emissions from global wetlands

Future methane (CH 4 ) emissions from natural wetlands are predicted to increase due to global warming, leading to positive feedback on climate change. However, the magnitude of this increase remains highly uncertain. Here we present novel ensemble simulations of seven state-of-the-art terrestrial biosphere models to estimate wetland CH 4 emissions (eCH 4 ) during the twenty-first century. Our estimates suggest that for every 1 °C increase in global land surface temperature, there is a 24 ± 10 Tg CH 4 yr −1 increase in eCH 4 . We also identify an emergent relationship between contemporary temperature dependence and projected eCH 4 . When constrained by 163 site-year eddy-covariance measurements of eCH 4 , we show that wetland emissions can increase by 50–60% by the 2090s relative to the 2010s under a high-warming scenario. The projected decadal increase in eCH 4 from the 2010–2019 baseline to the 2030s would very likely (90% probability) offset an amount equivalent in scale to 8–10% of anthropogenic eCH 4 at the 2020 level, comparable to the reductions committed under the Global Methane Pledge. However, the constraint is dominated by mid- and high-latitude observations, with limited tropical coverage, and uncertainties in projected wetland inundation contribute substantially to uncertainty in eCH 4 . Our findings reduce the uncertainty in projected wetland methane–climate feedback and highlight its potential impacts on methane mitigation efforts to slow global warming.

Zhang, Zhen [Chinese Academy of Sciences (CAS), Be↗
NASA NTRS1982

The effects of moisture on trapped mountain lee waves

The effects of latent heat release on the dynamics of mountain lee waves are examined with the aid of two-dimensional numerical simulations, for several situations in which the Scorer parameter has a nearly two-layer vertical structure. Changes in the moisture in the lowest layer are found to produce three fundamentally different behaviors: (1) resonant waves in an absolutely stable environment are distorted and untrapped by an increase in moisture; (2) resonant waves in a conditionally unstable layer are destroyed by an increase in moisture; and (3) resonant waves in a moist environment are detuned by a decrease in moisture. Changes in the humidity in the upper layer are found to amplify or damp the wave response, depending on the depth of the lower layer. In most situations, the wave response is significantly more complicated than that predicted by simply replacing the dry stability with an equivalent moist stability in the saturated layer.

Durran, D. R.↗
DOE OSTI2026

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗
NASA NTRS2019

Overexpression of Catalase in Mitochondria Mitigates the Effects of Simulated Microgravity and Social Isolation on Cytokine Expression in Mouse Hippocampus

Space flight missions are becoming longer and more common and evidence points to the physiological toll the missions have on the human body. Aging, sedentary lifestyle, and spaceflight have similar degenerative effects on almost every part of our body; both exposure to the space environment and aging result in cardiovascular deconditioning, bone loss, muscle atrophy, brain changes, and immune response impairment. We hypothesize that exposure to the space environment generates excessive Reactive Oxygen Species (ROS), which results in neuroinflammation and aging-like degenerative symptoms in the brain. We used the hindlimb unloading (HU) model to mimic microgravity with either paired or single housed animals (social isolation). Responses to 30d (30 days) of HU were compared in wildtype or transgenic MCAT (Mitochondrial-targeted CATalase) mice, in which mitochondrial ROS is quenched by over-expression of human catalase. Expression of 4-Hydroxynonenal (4HNE) and Park7 (redox-sensitive chaperone and sensor of oxidative stress) were measured by ELISA (Enzyme-Linked ImmunoSorbent Assay), a protein array quantified from the hippocampal cytokines and 8-hydroxy-2'-deoxyguanosine in serum was measured by ELISA to assess oxidative DNA damage. Preliminary analysis of cage behavior patterns from video collected at the end of the study showed that MCAT HU mice (socially housed) were more active and conducted more exploratory activities compared to NL (Normally Loaded). Our biochemical results showed simulated microgravity and/or social isolation caused changes in levels of cytokines related to immune responses. Two-way ANOVA (Analysis of Variance) revealed significant interaction effects of HU and genotype in expression levels of five cytokines (out of 35) in socially-housed animals. Elevation of these generally pro-inflammatory cytokines by HU in WT (Wild Type) mice was mitigated in MCAT mice, suggesting a role for mitochondrial ROS signaling in inflammatory CNS (Central Nervous System) responses to microgravity. Interestingly, some of these cytokines in the hippocampus displayed strong correlations to the 4HNE levels. We also found substantive cytokine responses to social isolation in the hippocampus; housing and genotype interaction effects were significant (by 2-Factor ANOVA) for 15 cytokines, most of which were mitigated in MCAT mice.Taken together, our results showed that both simulated microgravity and social isolation influenced cytokine levels in the hippocampus and MCAT mice were at least partially protected from these changes. These findings implicate a potentially important role for mitochondrial ROS in CNS responses to the challenges posed by long duration spaceflight.

MCAT↗
NASA NTRS2017

Lunar Exploration Missions Since 2006

The announcement of the Vision for Space Exploration in 2004 sparked a resurgence in lunar missions worldwide. Since the publication of the first "New Views of the Moon" volume, as of 2017 there have been 11 science-focused missions to the Moon. Each of these missions explored different aspects of the Moon's geology, environment, and resource potential. The results from this flotilla of missions have revolutionized lunar science, and resulted in a profoundly new emerging understanding of the Moon. The New Views of the Moon II initiative itself, which is designed to engage the large and vibrant lunar science community to integrate the results of these missions into new consensus viewpoints, is a direct outcome of this impressive array of missions. The "Lunar Exploration Missions Since 2006" chapter will "set the stage" for the rest of the volume, introducing the planetary community at large to the diverse array of missions that have explored the Moon in the last decade. Content: This chapter will encompass the following missions: Kaguya; ARTEMIS (Acceleration, Reconnection, Turbulence, and Electrodynamics of the Moon’s Interaction with the Sun); Chang’e-1; Chandrayaan-1; Moon Impact Probe; Lunar Reconnaissance Orbiter (LRO); Lunar Crater Observation Sensing Satellite (LCROSS); Chang’e-2; Gravity Recovery and Interior Laboratory (GRAIL); Lunar Atmosphere and Dust Environment Explorer (LADEE); Chang’e-3.

LUNAR EXPLORATION MISSIONS 200↗
NASA NTRS1994

Locomotion in a rotating space station: a synthesis of new data with established concepts

Despite technical problems associated with designing a rotating space station it is still thought that such a device may provide a more tolerable work environment and prevent some of the physiological changes that currently pose a threat to long-duration space missions. In the present analysis four case studies are presented and the results show that centrifugal and Coriolis effects could hinder one's ability to walk or run in a natural way in such an environment. In a rotating station that has a nominal 'G-level' equal to that on earth it can be shown that a person running at 3.8 m s -1 could experience foot 'heaviness' effects that range from 1 to 3 g and fore-aft foot 'forces' that range fom -0.5 to +0.5 g. In contrast the hip region could sense a relatively constant 'force' equal to 2 g. With regard to the body as a whole there would be 'weight changes' that depended on the direction of gait. While these conditions imply that locomotion in a rotating space station would be different from normal gait, it is likely that given sufficient training, astronauts could learn optimal strategies to account for centrifugal and Coriolis effects on individual body segments. The learning process would also entail developing strategies on which route to take when moving from one location to another, since in many cases the shortest route would not be the least energy consuming. Such training would be justified if it were shown that artificial gravity was an effective countermeasure to the problems of muscle atrophy and bone loss.

NASA Discipline Musculoskeletal↗
DOE OSTI2025

Hunga Tonga–Hunga Ha′apai Volcano Impact Model Observation Comparison (HTHH-MOC) project: experiment protocol and model descriptions

The 2022 Hunga volcanic eruption injected a significant amount of water vapor and a moderate amount of sulfur dioxide into the stratosphere, causing observable responses in the climate system. We have developed a model–observation comparison project to investigate the evolution of volcanic water and aerosols and their impacts on atmospheric dynamics, chemistry, and climate, using several state-of-the-art chemistry climate models. The project goals are (1) to evaluate the current chemistry–climate models to quantify their performance in comparison to observations and (2) to understand atmospheric responses in the Earth system after this exceptional event and investigate the potential impacts in the projected future. To achieve these goals, we designed specific experiments for direct comparisons to observations, for example from balloons and the Microwave Limb Sounder satellite instrument. Experiment 1 consists of two sets of free-running ensemble experiments from 2022 to 2031: one with fixed sea-surface temperatures and sea ice and one with coupled ocean. These experiments will help to understand the long-term evolution of water vapor and aerosols; quantify HTHH effects on stratospheric and mesospheric temperatures, dynamics, and transport; understand the impact of dynamic changes on ozone chemistry; quantify the net radiative forcings; and evaluate any surface climate impact. Experiment 2 is a nudged-run experiment from 2022 to 2023 using observed meteorology. To allow participation of more climate models with varying complexities of aerosol simulation, we include two sets of simulations in Experiment 2: Experiment 2a is designed for models with internally generated aerosol, while Experiment 2b is designed for models using prescribed aerosol surface area density. This experiment will help to analyze H 2 O and aerosol evolution, quantify the net radiative forcings, understand the impacts on mid-latitude and polar O 3 chemistry, and allow close comparisons with observations.

Zhu, Yunqian [Univ. of Colorado, Boulder, CO (Unit↗
DOE OSTI2021

Active Compensation of Radiation Effects on Optical Fibers for Sensing Applications

Neutron and gamma irradiation is known to compact silica, resulting in macroscopic changes in refractive index (RI) and geometric structure. The change in RI and linear compaction in a radiation environment is caused by three well-known mechanisms: (i) radiation-induced attenuation (RIA), (ii) radiation-induced compaction (RIC), and (iii) radiation-induced emission (RIE). These macroscopic changes induce errors in monitoring physical parameters such as temperature, pressure, and strain in optical fiber-based sensors, which limit their application in radiation environments. We present a cascaded Fabry–Perot interferometer (FPI) technique to measure macroscopic properties, such as radiation-induced change in RI and length compaction in real time to actively account for sensor drift. The proposed cascaded FPI consists of two cavities: the first cavity is an air cavity, and the second is a silica cavity. The length compaction from the air cavity is used to deduce the RI change within the silica cavity. We utilize fast Fourier transform (FFT) algorithm and two bandpass filters for the signal extraction of each cavity. Inclusion of such a simple cascaded FPI structure will enable accurate determination of physical parameters under the test.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

One Beam, Dual Insights: Simultaneous Chemical and Structural Changes in Nanopatterned Ceria under Reaction Conditions

Ceria’s interaction with hydrogen can proceed through multiple chemical forms (hydride, hydroxyl, and oxyhydroxide-like), with consequences for the oxidation state, density, and morphology that are rarely tracked in the same evolving state. Here, in this work, we show that under mild H 2 (and H 2 and CO 2 ) environments nanopatterned ceria undergoes oxidation-state changes accompanied by hydrogen incorporation that increases the effective electron density, establishing the following order: CeO 2 Hy > CeO 2 > CeO 2–x Hy > CeO 2–x . In parallel, the surface roughens in a chemically specific manner, with the largest changes coinciding with conditions where incorporated hydrogen is driven to react with oxygen supplied either by air exposure between experiments or by added CO 2 . We obtained these insights by using a single X-ray beam to simultaneously perform ambient-pressure X-ray photoelectron spectroscopy and grazing-incidence X-ray scattering on the same sample spot. Single-mode measurements can miss key ceria–H 2 transformations relevant to optimizing ceria-based hydrogenation catalysts and supports.

anions↗
DOE OSTI2026

Applied genomics for industrially relevant microalgal strain development & optimization: characterizing genotype-phenotype relationships towards scalable environment-enhancing energy systems

Multiple planetary boundaries considered a safe operating space for humanity have been exceeded in recent years, with twice as many boundaries transgressed in 2023 as in 2009. Bioenergy systems are unique in that they can interact with and improve many of the transgressed boundaries directly, including multiple geochemical cycles, water and land use, and climate change. Among bioenergy systems, microalgae-based environment enhancing energy (E 2 -energy) are promising bioenergy systems for drop-in biofuels, valuable materials, chemicals and therapeutics, while making deep emission cuts and remediating wastewater, all without competing for agricultural resources.

09 BIOMASS FUELS↗