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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Observing Chemical and Morphological Changes in a Cu@TiO x Core@Shell Catalyst: Impact of Reversible Metal-Oxide Interactions on CO 2 Activation and Hydrogenation

A combination of several in-situ techniques (XRD, XAS, AP-XPS, E-TEM) was used to explore links between the structural and chemical properties of a Cu@TiO x catalyst under CO 2 hydrogenation conditions. The active phase of the catalyst involved an inverse oxide/metal configuration, but the initial core@shell motif was disrupted during the pre-treatment in H 2 . As a consequence of strong metal-support interactions, the titania shell cracked and Cu particles migrated from the core to on top of the oxide with the simultaneous formation of a Cu-Ti-O x phase. The generated Cu particles had a diameter of 20-40 nm and were decorated by small clusters of TiO x (< 5 nm in size). Results of in-situ XAS and XRD and images of E-TEM showed a very dynamic system, where the inverse oxide/metal configuration promoted the reactivity of the system towards CO 2 and H 2 . At room temperature, CO 2 oxidized the Cu nanoparticles (CO 2,gas → CO gas + O oxide ) inducing a redistribution of the TiO x clusters and big modifications in catalyst surface morphology. The generated oxide overlayer disappeared at elevated temperatures (> 180 °C) upon exposure to H 2 , producing a transient surface that was very active for the reverse water-gas shift reaction (CO 2 + H 2 → CO + H 2 O) but was not stable at 250 °C. When oxidation and reduction occurred at the same time, under a mixture of CO 2 and H 2 , the surface structure evolved toward a dynamic equilibrium that strongly depended on the temperature. Neither CO 2 nor H 2 can be considered as passive reactants. In the Cu@TiO x system, morphological changes were linked to variations in the composition of metal-oxide interfaces which were reversible with temperature or chemical environment and affected the catalytic activity of the system. Finally, the present study illustrates the dynamic nature of phenomena associated with the trapping and conversion of CO 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Rate of Canopy Development Modulates the Link Between the Timing of Spring Leaf Emergence and Summer Moisture

Shifts in phenological timing have important implications for ecosystem processes, with spring leaf emergence as a dominant control of carbon, water, and energy cycling. Phenological events are predominantly determined by weather and climate, therefore dynamic in time and sensitive to climate feedbacks. Improving our understanding of how ecosystems respond to changes in phenological timing will enhance our ability to assess summer soil water availability, since the timing of spring leaf emergence may lead to soil moisture deficits later in the growing season. We leveraged data from five AmeriFlux towers in central and eastern United States to investigate the extent spring leaf emergence (i.e., start of spring, SoS ) influences rates at which forest canopies develop and how this impacts summer soil moisture ( θ JJA ) variability. Our results indicate that ecosystem processes, specifically gross primary production ( GPP ) and evapotranspiration ( ET ), exhibit compensatory responses to varying leaf emergence; with delayed spring-onset, the canopy developed more quickly, resulting in rapid GPP and ET increases, consistent across sites. Nonetheless, early SoS is a relatively good indicator for potential summer soil water deficits, particularly when it occurs together with meteorological conditions (i.e., lower-than-average precipitation, hot summer temperatures) that contribute to soil water deficits. When these meteorological conditions coincide with early SoS , θ JJA deficits are exacerbated. To the extent that these extreme conditions occur more frequently under future climate scenarios, the dynamics of spring phenology and hydroclimate may play an increasingly important role in portending the likelihood of summer water deficits, which are projected to become more severe.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Thermogravimetric Temperature-Programmed Thermal Redox Protocol for Rapid Screening of Metal Oxides for Solar Thermochemical Hydrogen Production

As combinatorial and computational methods accelerate the identification of potentially suitable thermochemically-active oxides for use in solar thermochemical hydrogen production (STCH), the onus shifts to quickly evaluating predicted performance. Traditionally, this has required an experimental setup capable of directly carrying out a two-stage thermochemical water-splitting process. But this can be a difficult endeavor, as most off-the-shelf equipment cannot adequately deal simultaneously with the high temperatures, varying oxygen partial pressures, and high H 2 O partial pressures required; achieving sufficient temporal sensitivity to accurately quantify the kinetics is also a major challenge. However, as proposed here, a less complicated experiment can be used as a first screening for thermochemical water splitting potential. Temperature-Programmed Thermal Redox (TPTR) using thermogravimetry evaluates the thermal reduction behavior of materials. This technique does not require water splitting or CO 2 -splitting analogs but can nonetheless predict water-splitting performance. Three figures of merit are obtained from the TPTR experiment: reduction onset temperature, extent of reduction, and extent of recovery upon reoxidation. These metrics can collectively be used to determine if a material is capable of thermochemical water-splitting, and, to good approximation, predict whether the thermodynamics are favorable for use under more challenging high-conversion conditions. This paper discusses the pros and cons of using TPTR and proposes a protocol for use within the STCH community.

08 HYDROGEN↗
DOE OSTI2020

The older plant gets the sun: Age-related changes in Miscanthus × giganteus phenology

Age-related changes are usually overlooked in perennial grass research; when they are considered it is usually as a change in plant size (e.g., biomass). Whether other physiological or developmental aspects change as stands age, and how those aspects may impact long-term stand dynamics, remains unclear. Conventional experimental designs study a single stand over multiple growing seasons and thereby confound age-related changes with growing season conditions. Here we used a staggered-start experimental design with three repeated planting years over two growing seasons to isolate growing season effects. We studied changes in Miscanthus × giganteus phenology during its yield-building stage (first 3 years) and estimated age, growing season and nitrogen (N) effects on development using nonlinear regression parameters. Stand age clearly changed plant growth; faster developmental rates were usually seen in 1-year-old stands (young), but because 2- and 3-year-old stands (mature) emerged 3 months earlier than newly planted stands they produced ~30% more stems with 30%–60% more leaves. Nitrogen fertilization modulated some age-related phenological changes. Fertilized 2-year-old stands reached similar stem densities as unfertilized 3-year-old stands and had fewer number of senesced leaves like 1-year-old stands. In addition, N fertilization had no effect on young M. × giganteus , but extended mature stands’ growing season more than 2 weeks by hastening emergence and delaying senescence. It also delayed flowering regardless of stand age. Our results suggest that, along with changes in size, M. × giganteus stands showed shifts in developmental strategies: young stands emerged later and developed faster, while mature stands grew for longer but more slowly. In temperate regions, where hard frost events are likely to interrupt development in late autumn, rapid early development is critical to plant survival. Nonlinear regression parameter differences proved effective in identifying phenological shifts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A high-temperature mixed potential CO gas sensor for in situ combustion control

An in situ, accurate and robust sensor that can sustain a high temperature of above 1000 °C is needed for on-site combustion monitoring because it can give real-time and local data to the control system to adjust the overall combustion efficiency. In this work, we find that nickel oxide (NiO) is a promising sensing material for CO which is a direct indicator of the status of the combustion process of a power plant. Under the conditions of 0.5–3% O 2 and 1000 °C, the fabricated yttrium-stabilized zirconia (YSZ)-based mixed potential sensor using porous NiO demonstrates good sensitivity to CO, showing a signal as high as 36 mV to 1000 ppm CO. The effects of gas transport, structure and geometry of the NiO electrode on the sensing performance are studied. Results show that fast gas transport is much beneficial to improved sensitivity. NiO having a porous structure is much more sensitive to CO than that having a dense structure. But the t90 (time to achieve 90% final signal magnitude) of the former is much longer due to slower gas diffusion inside the pores. It's worth noting that the NiO sensor exhibits a positive relationship with the CO content, opposite to other reported results of mixed potential sensors to detect CO. We find that this might be due to the electrochemical reduction, instead of oxidation of CO during the interaction with NiO at 1000 °C. Selectivity tests on how CO 2 , CH 4 and steam affect CO sensing are also demonstrated. NiO is insensitive to even 10% CO 2 . CH 4 does not shift the average value of the CO sensing response. However, it makes the sensing signal fluctuate more intensively. 2% steam exerts a great influence on NiO sensitivity to CO: it magnifies the sensitivity of the porous NiO electrode to a low CO range of 0–100 ppm, but inhibits its sensitivity to a CO range of 100 ppm to 1000 ppm. Lastly, an 11 day stability test demonstrates the promising stability property of the proposed NiO-based YSZ sensor.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Impact of Oxygen Storage Components in Prototype Pd-Based Three-Way Catalysts under Exhaust Conditions Relevant to Propane Engines

With increasing concerns about global warming, the push for sustainable and eco-friendly fuels is accelerating. Propane, recognized as liquefied petroleum gas or LPG, has garnered research interest as an alternative fuel due to its notable advantages, including a high-octane rating, reduced greenhouse gas emissions, and potential cost-effectiveness. However, to realize its full potential as an alternative fuel it is essential to develop catalysts that efficiently handle emissions at low temperatures. In our research, we investigated three distinct palladium (Pd)-based three-way catalyst (TWC) formulations (PdRh, Pd-only, and Pd-OSC) to investigate the influence of typical TWC components rhodium (Rh) and oxygen storage components (OSC) in exhaust scenarios relevant to propane-fueled engines. Among these, the formulation containing oxygen storage components (Pd-OSC) showed the highest reactivity for both NO and C 3 H 8 while minimizing performance degradation from hydrothermal aging (HTA). Notably, the temperature of 50% conversion (T50) for propane in the Pd-OSC fresh and HTA sample was lower by 30 °C and 13 °C, respectively, compared to the Pd-only sample, highlighting the role of oxygen storage materials in enhancing catalyst performance, even without dithering. Additionally, N 2 physisorption showed that the PdOSC sample has a higher surface area and increased pore volume. This underscores the idea that OSC materials not only augment the catalyst’s porosity but also optimize reactant accessibility to active sites, thus elevating catalytic efficiency. In addition to evaluating performance, we further explored the performance and characteristics of the catalysts using catalytic probe reactions, such as water–gas shift and steam reforming reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Phosphate-modulated transformation of Sb(V)-bearing ferrihydrite under microbial iron- and sulfate-reducing conditions

Antimony (Sb) is a toxic metalloid that poses environmental risks in terrestrial and aquatic systems. The fate of the Sb(V) oxyanion, Sb(OH) 6 − , is governed by complex biogeochemical processes, including immobilization by ferric (Fe(III)) oxides, reduction by sulfide, and the less-explored competitive adsorption with other anions such as phosphate (PO 4 3− ). Here, this study investigates the interplay between such mechanisms in controlling the behavior of Sb(V) associated with ferrihydrite (Fh) under Fe(III)- and sulfate-reducing conditions, with a particular emphasis on the role of phosphate in influencing Sb(V) mobility and transformation. Anoxic reactors that contained Sb(V)-coprecipitated Fh, varying PO 4 3− concentrations (0, 0.2, and 2 mM), and sulfate, were inoculated with a microbial community sourced from Sb-contaminated soil. Additionally, abiotic reactors with either Sb(V)-adsorbed or Sb(V)-coprecipitated Fh and different PO 4 3− loadings (0–100 mM) were created to investigate the competitive adsorption mechanisms in the absence of microbial activity. Results from the abiotic reactors suggest that Sb(V) is likely incorporated into the Fh structure, with only minor amounts remaining surface-bound and extractable by PO 4 3− . In the biotic reactors, microbial Fe(III) and sulfate reduction were more extensive in the presence of PO 4 3− . At 0.2 mM PO 4 3− , microbial activity transformed Fh into siderite and led to the complete reduction of Sb(V) to Sb(III) as stibnite (Sb 2 S 3 ). At 2 mM PO 4 3− , the greater coverage by PO 4 3− stabilized Fh and decreased the extent of both Fe(III) and Sb(V) reduction, and shifted the reduced products to mackinawite and Sb(III) adsorbed onto Fh, in addition to stibnite formation. This study demonstrates that while PO 4 3− may not directly compete with Sb(V) for sorption sites, it can influence Sb mobility in Fe(III)- and sulfate-reducing environments by enhancing microbial activity and altering the mineralization pathways.

Microbial Fe(III) and sulfate reduction↗
DOE OSTI2021

Nonlinear X-ray Optics

Novel X-ray free-electron lasers (XFELs) are capable of producing radiation with unprecedented properties. Specifically, their ultrashort coherent X-ray pulses can generate extreme peak intensities where ordinary rules of light-matter interaction may no longer apply, and nonlinear processes start to become important. XFELs have made it possible to observe some of the most important coherent non-sequential nonlinearities, including X-ray-optical sum frequency generation (SFG), X-ray second harmonic generation (XSHG), two-photon absorption (TPA) and nonlinear two-photon Compton scattering (2PCS). In particular, the 2PCS experiment has led to unexpected results, namely the observation of a substantial anomalous red shift in the energy of photons generated by nonlinear two-photon X-ray Compton scattering in beryllium. The energy shift is in addition to the predicted nonlinear Compton shift and was neither expected from extrapolations from linear X-ray interactions nor from nonlinear effects at optical wavelengths. Our results suggest a novel nonlinear scattering mechanism that can only be observed at high fields at X-ray wavelengths, where the photon energy is a significant fraction of the electron rest mass (and thus a significant momentum transfer to the electron occurs during the scattering) and where the interaction is not dominated by the quiver motion of the electron in the field (ponderomotive potential) as is usually the case at longer (optical) wavelengths. The goal of this research project was the investigation of fundamental nonlinear X-ray-matter interactions. As these processes are typically weak, part of this research is the exploration of more efficient nonlinear X-ray processes by studying novel mechanisms including solid-state effects, the assistance of optical radiation and novel phase-matching techniques. These experiments require extremely large X-ray field strengths, such as produced by XFELs. Nonlinear X-ray effects can lead to important applications in many research fields. For example, it could lead to instantaneous plasma diagnostics for materials in extreme conditions, as a method for combining atomic-scale structural sensitivity with chemical specificity, or as a probe of electron dynamics in solids on the attosecond (1 as = 10 -18 s) time- and Ångstrom (10 -10 m) length scales. In addition, a detailed understanding of nonlinear X-ray matter interactions is crucial for understanding and extending the limits of structural determination at high intensity such as in serial femto-crystallography. The results could have a profound impact on advanced XFEL light sources such as the LCLS-II.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

STOCHASTIC OPTIMAL POWER FLOW FOR REAL-TIME MANAGEMENT OF DISTRIBUTED RENEWABLE GENERATION AND DEMAND RESPONSE (Final Report)

To meet the grand challenge of a sustainable energy future, there has been a surge of interest in renewable energy. Today, the uncertainty associated with renewable resources is handled by using operating reserves. The high penetration of renewable resources, however, introduces difficult-to-control dynamics and challenges for power system operation. Decision support tools are necessary at the bulk system operational level to recognize and efficiently utilize renewable resources and distributed demand response products in concert with traditional grid resources. It is envisaged that responsive load can potentially have very significant cost advantages over either spinning or non-spinning ramping reserve. Critical decisions are made during hour(s)-ahead and real-time power system operation regarding the commitment and dispatch of generators to ensure power delivery is both reliable and economic. These decisions are typically made by a security constrained optimal flow, which determines future generator commitments, dispatches, and ensures adequate reserves are available in the event of a contingency (unexpected outage) or if future system conditions deviate from forecasts. However, security has been always based on a pre-specified subset of contingency constraints whose enforcement does not guarantee security under all possible future possibilities while also giving little or no weight to the likelihood of each contingent event or the severity of its consequences. Existing tools, which are based exclusively on deterministic optimization models, do not yield optimal operational decisions to address these new challenges, in terms of both reliability and cost-effectiveness. This project has focused on developing a stochastic optimal power flow (SOPF) framework, which integrates renewable resource uncertainty, load uncertainty, distributed storage (DS), demand response (DR) products, in a holistic manner to address the uncertainty associated with ever-increasing renewable resources, along with the inclusion of distributed demand response products in future power systems. A proof-of-concept problem was created using the Pennsylvania-Jersey-Maryland (PJM) power system network. Synthetic wind generation was added to the system to simulate 50% wind penetration. A 1-hour test of SOPF operation indicated more than 6% operational cost savings. The project continued by adding the Midwestern Independent System Operator (MISO) as a partner, with focus shifting from SOPF to Stochastic Look-Ahead Unit Commitment (SLAC). Unlike PJM, MISO is faced with significant renewable energy resources within its footprint and is challenged with substantial uncertainty in its operations. The SLAC distinguishes itself from existing tools that operators use. At best, today’s tools solve two to three cases independently, where one or two system parameters, such as forecasted load level (e.g., a low, base, and high forecast), are varied and the resulting scenarios are analyzed independently. The stochastic-based optimization of SLAC leverages statistical information from an ensemble of potential operational scenarios and their respective likelihood. The SLAC output can be translated into valuable information to the operator such as suggested commitments, optimal scheduling and dispatch of resources, reserve requirements at both locational and zonal resolutions, ramping availability and requirements, availability of demand response including operational guidance concerning the near-term and real-time coordination between distributed energy resources, and utilization of distributed storage resources. The developed SOPF/SLAC tool, a stand-alone tool compatible with existing EMSs, will provide system operators with unprecedented visibility, flexibility and predictability to these resources and operational guidance concerning the real-time coordination between DERs and DR/DS products. The game changing and practical impact of this disruptive technology will be dramatic and will usher in a new era in the electric power industry, wherein green energy concepts are fully embraced, and electric power costs are lowered throughout the nation.

42 ENGINEERING↗
DOE OSTI2026

Development of Advanced, Radiation Resistant, Optical-based Detector Technology for Future Experiments.

The primary objective of this project has been to advance the design of high-performance electromagnetic (EM) calorimeters for future particle physics experiments, to identify and measure the timing, position and energy of electrons, positrons and gamma rays, particularly in high-luminosity environments with intense radiation and pileup conditions. To meet such challenges, the proposed research has focused on the development of ultra-compact, radiation-hard calorimeter modules, to provide excellent timing, spatial, and energy resolution. The work aligns with the DOE’s Basic Research Needs (BRN) for High Energy Physics (HEP) Instrumentation and the research team contributes actively to the Coordinating Panel on Advanced Detectors (CPAD) RDC9 calorimetry collaboration in the USA and the European Committee on Future Accelerators (ECFA) DRD-CALO calorimetry collaboration at CERN, the European Laboratory for Particle Physics located in Geneva, Switzerland. The research builds on the RADiCAL (radiation-hard, ultra-compact) modular sampling calorimeter approach, developed by the research team, which employs dense and very bright optical materials such as LYSO:Ce scintillator plates that are interleaved with very dense tungsten plates to minimize detector size while optimizing performance. The modules are comparable in size to a human index finger, dimensionally 14 mm x 14 mm in cross section and 135 mm in length. And despite the small size, the structure is capable of providing excellent timing and energy resolution. This is facilitated through the use of specialized quartz capillaries filled with wavelength-shifting filaments, positioned at various depths along the length of a module, to collect and guide light signals to silicon photomultipliers (SiPMs) which detect and convert the optical signals to electronic signals for analysis. The primary goals of this project have been: (1) Achieve a timing resolution to σ t ≤ 30 ps for high-energy electrons and photons, important for their association with specific events produced in colliding-beam experiments and for the detection of decays-in-flight of long-lived particles. The project has achieved this goal in beam tests of a single RADiCAL module at CERN, during which a timing resolution of σ t = 27 ps was measured for electrons of energy E = 150 GeV. Based upon a mathematical fit to the data measured over a broad energy range from low energy to high energy, a resolution of σ t ≤ 18 ps has been estimated for electrons of very high (TeV) energy. From these measurements and with further expected technical improvements, the timing resolution should reach σ t ≤ 10 ps, important for searches for discovery physics in upcoming and future experiments. (2) Achieve an energy resolution of σ E / E ≤ 10% / $\sqrt{E}$. The project has yet to achieve this goal, but is close to it, having measured a value of σ E / E ≤ 15.9% / $\sqrt{E}$ using a modular array. Ultimately, the resolution goal is expected to be reached by adjustments to material thicknesses within the modules, which will improve the sampling fraction to measure more precisely the shower energy for lower energy particles. The versatility of the modular RADiCAL approach enables the testing of advanced materials, photosensors and electronics, developed in collaboration with CPAD RDC and ECFA DRD-CALO groups. The structure can distinguish electrons, positrons and gamma rays from hadrons and muons and beam-induced backgrounds, making it a valuable tool in a variety of detector environments, including future circular colliders (FCC-ee, FCC-hh) proposed for the European Laboratory for Particle Physics (CERN), the muon-collider proposed for Fermi National Accelerator Laboratory (Fermilab), and searches for new physics in beam-dump, fixed target and forward-physics experiments. And, while designed with particle physics applications in mind, the technologies developed in this project have the potential for application more broadly in particle and nuclear physics, materials science, and medical physics, underscoring the far-reaching potential of this line of instrumentation research and development.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Deeper snow increases the net soil organic carbon accrual rate in moist acidic tussock tundra: 210Pb evidence from Arctic Alaska

The net change in the carbon inventory of arctic tundra remains uncertain as global warming leads to shifts in arctic water and carbon cycles. To better understand the response of arctic tundra carbon to changes in winter precipitation amount, we investigated soil depth profiles of carbon concentration and radionuclide activities ( 7 Be, 137 Cs, 210 Pb, and 241 Am) in the active layer of a twenty-two-year winter snow depth manipulation experiment in moist acidic tussock tundra at Toolik Lake, Alaska. Depth correlations of cumulative carbon dry mass (g cm -2 ) vs. unsupported 210 Pb activity (mBq g -1 ) were examined using a modified constant rate of supply (CRS) model. Results were best fit by two-slope CRS models indicating an apparent step temporal increase in the accumulation rate of soil organic carbon. Most of the best-fit model chronologies indicated that the increase in carbon accumulation rate apparently began and persisted after snow fence construction in 1994. The inhomogeneous nature of permafrost soils and their relatively low net carbon accumulation rates make it challenging to establish robust chronologic records. Nonetheless, the data obtained in this study support a decadal-scale increase in net soil organic carbon accumulation rate in the active layer of arctic moist acidic tussock tundra under conditions of increased winter precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Distortions of the Rain Distribution With Warming, With and Without Self-Aggregation

We investigate how mesoscale circulations associated with convective aggregation can modulate the sensitivity of the hydrologic cycle to warming. We quantify changes in the full distribution of rain across radiative-convective equilibrium states in a cloud-resolving model. For a given Sea Surface Temperature (SST), the shift in mean rainfall between disorganized and organized states is associated with a shift in atmospheric radiative cooling, and is roughly analogous to the effect of a 4K SST increase. With rising temperatures, the increase in mean rain rate is insensitive to the presence of organization, while extremes can intensify faster in the aggregated state, leading to a faster amplification in the sporadic nature of rain. When convection aggregates, heavy rain is enhanced by 20%–30% and nonlinear behaviors are observed as a function of SST and strength of aggregation feedbacks. First, radiative- and surface-flux aggregation feedbacks have multiplicative effects on extremes, illustrating a non-trivial sensitivity to the degree of organization. Second, alternating Clausius-Clapeyron and super-Clausius-Clapeyron regimes in extreme rainfall are found as a function of SST, corresponding to varying thermodynamic and dynamic contributions, and a large sensitivity to precipitation efficiency variations in some SST ranges. The potential for mesoscale circulations in amplifying the hydrologic cycle is established. However, these nonlinear distortions question the quantitative relevance of idealized self-aggregation. This calls for a deeper investigation of relationships which capture the coupling between global energetics, aggregation feedbacks and local convection, and for systematic tests of their sensitivity to domain configurations, surface boundary conditions, microphysics, and turbulence schemes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Water availability modulates maximum canopy heights of low-elevation Amazonian second-growth forests

Tropical second-growth forests of the Amazon sequester large amounts of carbon and are important carbon sinks, contributing substantially to climate change mitigation, biodiversity conservation, and providing crucial ecosystem services. Deforestation due to selective logging and shifting cultivation is expanding second-growth forest areas in tropical forest regions, which if well managed, regenerate rapidly over time. Maximum forest canopy height is an important metric of biomass and carbon accumulation in second-growth forests and is strongly influenced by water availability. The water limitation hypothesis explains the positive influence of water availability on maximum tree heights and has been examined and demonstrated at a small-scale using field data, and at a global scale, with limited accuracy, using remote sensing data in tropical ecosystems. However, this hypothesis concerning maximum canopy height has not been much studied at regional and national scales for tropical second-growth forests. In this study, we leveraged NASA GEDI spaceborne lidar data across the Brazilian Amazon and derived second-growth forest relative height metrics for delineating the influence of water availability, second-growth forest age, and topographic elevation on maximum canopy height. Water availability was found to significantly influence the maximum canopy height of second-growth forest trees, of age range from 30 to 35 years, at elevations less than 500 m and maximum precipitation thresholds of 1500 mm. Our results indicate that changing precipitation patterns or increased drought conditions under different climate change regimes could impact forest structure, plant communities, ecosystem functioning, and carbon sequestration capabilities of tropical second-growth forests in the Amazon.

Carbon sequestration↗
DOE OSTI2023

Feasibility Analysis for the Use of Retrofitted Air-Conditioners Using Thermal Energy Storage (TES) for High Ambient Temperature (HAT) Countries

In high ambient temperature (HAT) countries, summer temperatures exceed 35℃, degrading the performance of air-conditioning systems and straining power grids. In this paper, a feasibility analysis was conducted to investigate potential savings during the peak using latent Thermal Energy Storage (TES) at near room phase-change temperatures, replacing condensers, thus, minimizing temperature lifts. Weather data, building loads, and baseline air-conditioning systems data were gathered for Dubai. A transient vapor-compression model in Modelica was used to compare the COP, total power input and cooling capacity of the air-conditioner at peak hours when ambient temperatures range between 35 – 45 ⁰C versus the TES-Phase-Change Material (PCM) melting temperatures from 22 – 28⁰C. The results indicate that the TES-PCM can enhance the system COP at the peak by a factor 1.4 and 2 for during for outdoor temperatures of 35 – 40⁰C, and 40 – 45⁰C, respectively. Lower melting temperature PCMs were able to reduce the required power input by 30-50%, with more savings occurring at higher temperature days. On the other hand, higher temperature PCMs enhancements were minimal especially at outdoor ambient temperatures ranging between 35 – 40⁰C. Improvements to the cooling capacity range from 8 – 18 % for the outdoor temperature range of 35 – 45 ⁰C. An economic analysis was conducted to find the potential saving in utility costs for 30%, 60%, and 90% of the space cooling demands of Dubai, and find the trade-off points between utility savings and cost of PCM-TES implementation. If the peak loads are to be shifted by 6 hours daily, the percentage utility savings for the city is 18%. Using estimated costs of the PCM-TES, ranging from $200-500/kWh, the daily load shifting hours were estimated to range from 4 hours at the lowest cost systems to 2.5 hours at the highest costs.

25 ENERGY STORAGE↗
DOE OSTI2026

Characterization of Electronic Stress-Induced Changes in Multilayer MoS 2

Transition metal dichalcogenides like molybdenum disulfide (MoS 2 ) are compelling for next-generation electronic devices. In this work, we investigate the impact of electronic stress on MoS 2 to illustrate that observational and phenomenological information on multiple devices can be useful to describe changes in the device, and caution against the rationalization of paltry results as representative or correlative to device behavior. Here, we stress MoS 2 by applying a sustained 20 V DC bias to study the material’s response. Post-stress electronic characterization revealed nonuniform shifts in current–voltage (I–V) behavior alongside microscale changes. Complementary mechanical, spectroscopic, and scanning microwave impedance measurements showed that stress-induced features locally modulate stiffness, surface potential, Raman intensity, and charge carrier density. We correlated I–V behavior with morphological features (wrinkles, tears, folds, height) and device-level geometry (MoS 2 overlap with electrodes, channel area, contact length) on 50 test structures across five chips to move beyond anecdotal conclusions. We found no universal correlations before DC stress. However, device-level geometry was correlated with I–V behavior after DC stress, suggesting that electrode contacts play a more dominant role than morphology in determining performance. Delamination and thinning induced by DC stress led to localized reductions in charge carrier density within the affected regions. Further, delamination and thinning appear to map to I–V device performance in a few samples, but the correlation is lost when a larger sample size is considered. This suggests significant sample-to-sample variability in surface electronic states of the test structures. We also discuss how environmental factors introduced during fabrication may contribute to the observed heterogeneous device response. Progress will require high-resolution, multimodal analysis across many samples constructed under controlled, clean conditions. By building data sets that capture variability, we can better identify the true drivers of performance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

How Water Attacks MXene

Two-dimensional (2D) transition metal carbides and nitrides (MXenes) have shown outstanding performances in electrochemical energy storage and many other applications. However, the stability of MXene remains a concern, especially its quick degradation in aqueous solutions under ambient conditions. Here, we report on the water/Ti 3 C 2 O 2 -MXene interfacial chemistry from first-principles molecular dynamics simulations at room temperature. Surprisingly, we find that the water molecules can attack the basal plane of Ti 3 C 2 O 2 and pull the surface Ti atoms out, thereby reconstructing the surface. Further, by tracking close encounters of water molecules and surface Ti atoms on the basal plane of Ti 3 C 2 O 2 , we show that the attack is initiated by the chemisorption of a water molecule on a surface Ti atom, followed by the breaking of Ti–C bonds and deprotonation of the water molecule, leading to the formation of Ti–OH on the Ti 3 C 2 O 2 surface and a hydronium ion in the aqueous phase. Our finding highlights the susceptibility of Ti 3 C 2 O 2 MXene to water attack, supporting recent experimental observations. Furthermore, we demonstrate that preventing close encounters of water molecules and the surface Ti atoms is key to the stability of the basal plane and can be realized by negatively charging the surface (thereby reorienting the O atoms of water away from the surface) or converting the surface O to -OH groups (thereby shifting the water layer further away from the surface). Our insights and approach highlight the importance of the reactivity of water when interfacing with 2D materials such as MXenes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Regime Characterization of Offshore Wind Resource Using Unsupervised Learning

Predictability of wind resource conditions is critical for offshore wind design and operations. While many studies of extreme wind conditions focus on specific events such as low-level jets or ramps, these rely on threshold definitions that limit generality. Here we present a data-driven framework that combines principal component analysis (PCA), self-organizing maps (SOM), and k-means clustering to classify wind resource conditions as typical and anomalous from climatological data. Anomalies are defined not by fixed thresholds but by flagging samples located far from SOM node centers inside the baseline SOM structure. This reframes extremes as rare ebents and hence, likely difficult to anticipate by numerical weather prediction models. We applied this approach to 23 years (2000–2022) of hourly profiles from the NOW-23 hindcast model at the Humboldt Wind Energy Area. Classification is conducted on a feature space consisting of 10 m wind speed and direction, bulk shear and veer across 30–270 m, and a low-level jet index. Dimensionality reduction is achieved through PC. A 2 × 3 OM lattice trained on the PCA vectors identified six baseline regimes spanning weak to strong flow states. High quantization-error profiles are identified and re-clustered into four anomalous regimes. The baseline regimes exhibited clear seasonal and diurnal cycles. Meanwhile, the anomalous regimes represented <10 % of all hours but showed distinct combinations of speed, shear, and veer, when compared to the baseline regimes. Anomalous regimes are typically short-lived (~few hours), yet their transitions can lead to hub-height wind changes of −18 to +9 m s -1 . For a representative 15 MW turbine, these shifts imply rapid swings in capacity factor from near-full output to negligible generation. Validation with lidar buoy data showed 51% agreement in SOM labels across ~6,000 overlapping hours, with most mismatches confined to adjacent speed classes. HRRR comparisons further revealed that anomalous regimes were disproportionately associated with forecast biases exceeding 5 m s -1 . Together, these results reframe extremes in offshore wind from absolute maxima or minima to weather states that are difficult to anticipate from models.

17 WIND ENERGY↗
DOE OSTI2022

Data Curation for Machine Learning Applied to Geothermal Power Plant Operational Data for GOOML: Geothermal Operational Optimization with Machine Learning: Preprint

Geothermal Operational Optimization with Machine Learning (GOOML) is a transferable and extensible component-based geothermal asset modeling framework that considers complex steamfield relationships and identifies optimization prospects using a data-driven approach to physics-guided, data-centric machine learning. This framework has been used to develop digital twins that provide steamfield operators with operational environments to analyze and understand historical and forecasted power production, explore new steamfield configuration possibilities, and seek optimal asset management in real world applications. To create, test, and apply the GOOML framework, diverse time-series datasets spanning multiple years were sourced from various geothermal power plant components within several complex real-world geothermal operations. These operations are based in the United States and New Zealand and include a variety of technologies, end-uses and configurations, collectively covering nearly all relevant operating conditions for modern geothermal fields. Datasets were acquired from multiple sources to ensure that machine learning experiments generalized properly to various operating conditions. It was found that the data varied in quality, format, and completeness. To ensure consistency between the various datasets, a standardized data curation process was developed to reliably streamline data preparation. This paper will discuss best practices as learned from the GOOML data curation process which takes the following steps: 1) acquisition of large quantities of data from power plant operators, 2) digestion of data to gain an initial understanding of what is included, 3) data transformation, which includes converting the data into a standardized machine-readable format so that they can be visualized, quality checked, and cleaned, 4) quality assurance and quality control, involving identification of significant data gaps and apparent anomalies through mapping of data features to real world componentry via the GOOML historical model, followed by discussion with modelers and power plant operators to identify additional data needs and to resolve issues, 5) use in machine learning algorithms, and 6) repetition of steps one through five until all data needs are met and data are deemed suitable for producing trustworthy modeling results which may be disseminated, ideally along with the curated dataset. This iterative process is focused on improving the quality of the data rather than tuning machine learning model parameters and supports a shift towards data-centric AI as a means to improving real-world applicability of geothermal machine learning projects.

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