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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhanced Weathering May Benefit From Co‐Application With Organic Amendments

Abstract Enhanced weathering has emerged as a promising natural climate solution that has the potential to remove billions of tons of carbon from the atmosphere if widely adopted in agricultural settings. Despite this potential, few field trials have been published that verify the carbon dioxide removal (CDR) potential of enhanced weathering in croplands and, until now, none had been published in grazing lands. Anthony et al. (2025, https://doi.org/10.1029/2024AV001480 ) conducted the first trial of enhanced weathering in a California rangeland and showed weathering of ground silicate rocks despite drought conditions in an already dry climate. Co‐application of inorganic (silicate rocks) with organic (biochar and compost) amendments revealed not just additive, but synergistic effects whereby organic amendments increased rates of weathering. This is important because field CDR rates were <10% of the theoretical maximum (i.e., the rate if basalt was completely weathered); thus, methods to improve weathering rates will be necessary for this practice to scale in a meaningful way. Multi‐carbon pool measurements revealed not only how co‐application of soil amendments heightened net carbon benefits, but also how soil amendments complemented each other to produce net benefits for soil carbon, biomass growth, and greenhouse gas emission reductions. Anthony et al. (2025, https://doi.org/10.1029/2024AV001480 ) produce new insights toward our understanding of enhanced weathering as well as introduce paths for future research concerning combined amendment applications, synergistic mechanisms for carbon storage, and deployment in various agricultural contexts. While questions remain about the fate of weathering products in arid regions, Anthony et al. (2025, https://doi.org/10.1029/2024AV001480 ) present novel findings on the potential for significant weathering to occur even under suboptimal conditions.

Almaraz, Maya [Yale Center for Natural Carbon Capt↗
DOE OSTI2025

Remote Influence of Andean Convection on Amazonian Rainfall and Its Mechanisms

Models from Coupled Model Intercomparison Project Phase 6 produce too much precipitation over the Andes but too little over the Amazon or the Wet Andes-Dry Amazon (WADA) bias pattern. Unlike the conventional view that convection parameterization and land model deficiencies can contribute to Amazonian rainfall biases, we approach this long-standing biased model behavior through the lens of Andean convection. Using Community Earth System Model v1.1 and focusing on the wet season, our mechanism-denial experiments demonstrate that Andean convection notably reduces precipitation over the Amazon during austral summer. The Andean forced Amazonian response operates on weather timescale. Furthermore, the reduction of Amazonian rainfall is detectable within a few hours after initial Andean forcing. The precipitation response is primarily driven by variations in the moisture budget and is moderated by changes in convective available potential energy over the Amazon. Changes in the total advection of moisture over the Amazon are dominated by the vertical advection term and can be attributed to discrepancies in the dynamic omega field. In the experiments, the Andean east flank region is scrutinized where the vertical velocity and moisture fields play an intermediary role for the Andean driven WADA connection. The Andean forcing induces descending anomalies on the Andean east flank. The disturbances of wind and geopotential fields over the Andean east flank propagate eastward via Kelvin waves. Over the Amazon, descending anomalies and advective drying lead to reduction of mid-to-high level cloud, increase of shortwave cloud forcing and surface net radiation, and enhancement of themodynamic stability and rainfall reduction.

58 GEOSCIENCES↗
DOE OSTI2025

Rising infrastructure inequalities accompany urbanization and economic development

Impending global urban population growth is expected to occur with considerable infrastructure expansion. However, our understanding of attendant infrastructure inequalities is limited, highlighting a critical knowledge gap in the sustainable development implications of urbanization. Using satellite data from 2000 to 2019, we examine country-level population-adjusted biases in infrastructure distribution within and between regions of varying urbanization levels and derive four key findings. First, we find long-run positive associations between infrastructure inequalities and both urbanization and economic development. Second, our estimates highlight increasing infrastructure inequalities across most of the countries examined. Third, we find greater future infrastructure inequality increases in the global south, where inequalities will rise more in countries with substantial urban primacy. Fourth, we find that infrastructure inequality may evolve differently than economic inequalities. Overall, advancing sustainable development vis-à-vis urbanization and economic development will require intentional infrastructure planning for spatial equity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

One-shot learning for solution operators of partial differential equations

Learning and solving governing equations of a physical system, represented by partial differential equations (PDEs), from data is a central challenge in many areas of science and engineering. Traditional numerical methods can be computationally expensive for complex systems and require complete governing equations. Existing data-driven machine learning methods require large datasets to learn a surrogate solution operator, which could be impractical. Here, we propose a solution operator learning method that requires only one PDE solution, i.e., one-shot learning, along with suitable initial and boundary conditions. Leveraging the locality of derivatives, we define a local solution operator in small local domains, train it using a neural network, and use it to predict solutions of new input functions via mesh-based fixed-point iteration or meshfree neural-network based approaches. We test our method on various PDEs, complex geometries, and a practical spatial infection spread application, demonstrating its effectiveness and generalization capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Single-photon emission from two-dimensional perovskites channeled through low-energy edge states

Two-dimensional perovskites, an emerging family of van der Waals materials with an innate quantum-well structure, exhibit remarkable optical characteristics and compositional tunability. However, their potential as a source for quantum emitters remains unexplored. Here, we investigate low-energy edge states unique to two-dimensional perovskites using comprehensive photoluminescence imaging and spectroscopy, to further leverage them towards uncovering quantum emitters. In contrast to above-bandgap excitation, spatially localized single-photon emitters are realized through sub-bandgap energy excitation at the edges in exfoliated single crystals. Specifically, the sub-bandgap excitation facilitates efficient access to deeply confined states within the bandgap, as charge carriers can channel through low-energy edge states while inhibiting competing processes. Furthermore, we demonstrate single-photon emitters from artificially created edges via strain as well as from two-dimensional perovskites with different quantum-well thicknesses. Our findings provide promising opportunities in the development of two-dimensional quantum emitters, where two-dimensional perovskites may provide added functionalities with versatility in material design, fabrication, and scalability.

Materials for optics↗
DOE OSTI2026

Hierarchical Multi-agent Large Language Model Reasoning for Autonomous Heterogeneous Catalyst Discovery

Artificial intelligence is reshaping scientific exploration, but most methods automate procedural tasks without engaging in scientific reasoning, limiting autonomy in discovery. We demonstrate that hierarchical agentic large language model reasoning can efficiently drive simulation and scientific exploration. Across two chemical applications, CO adsorption on Cu surface transition metal adatoms and on M–N–C catalysts, reasoning-guided exploration reduces required atomistic simulations by up to 90% relative to heuristic or random selection. Comparisons across single-agent, multi-agent, and stochastic baselines show that hierarchical strategies yield more coherent and information-efficient search trajectories. Reasoning traces reveal chemically grounded decisions that cannot be explained by semantic bias or stochastic sampling. We realize these agentic reasoning strategies in Materials Agents for Simulation and Theory in Electronic-structure Reasoning (MASTER), a multimodal system that translates natural language into density functional theory workflows. Altogether, multi-agent collaboration accelerates heterogeneous catalyst discovery and marks a step toward more autonomous, reasoning-guided scientific exploration.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Cracking in polymer substrates for flexible electronic devices and its mitigation

Mechanical reliability plays a critical role in determining the durability of flexible electronic devices because of the significant mechanical stresses they experience during manufacturing and operation. Many such devices are built on sheets comprising stiff transparent-conducting oxide (TCO) electrode films on compliant polymer substrates, and it is generally assumed that the high-toughness polymer substrates do not crack. Contrary to this assumption, here we show extensive cracking in the polymer substrates during bending of a variety of TCO/polymer sheets, and a device example — flexible perovskite solar cells. Such substrate cracking, which compromises the overall mechanical integrity of the entire device, is driven by the amplified stress-intensity factor caused by the elastic mismatch at the film/substrate interface. To mitigate this substrate cracking, an interlayer-engineering approach is designed and experimentally demonstrated. This approach is potentially applicable to myriad flexible electronic devices, with stiff films on compliant substrates, for improving their durability and reliability.

42 ENGINEERING↗
DOE OSTI2026

Achieving high tensile strength and ductility in refractory alloys by tuning electronic structure

The energy efficiency of heat engines (gas and steam turbines) for electricity production and propulsion is determined by the Carnot cycle and scales with operating temperature. Commercial nickel- and cobalt-based superalloys melt near 1,500 °C and rapidly lose mechanical strength beyond 1,000 °C. Refractory metals melt well above 2,000 °C but have inherent manufacturability challenges that are barriers to adoption, such as high ductile-to-brittle transition temperatures. Using density functional theory-guided design, we demonstrate tailored local lattice distortions that promote phase-stable, non-equiatomic refractory concentrated solid solutions with both high ductility and strength. Here, we exemplify this for single-phase, body-centred cubic Nb 4 Ta 4 V 3 Ti that exhibits castability, excellent room-temperature tensile yield strength (∼1 GPa) and ductility (approaching 20% uniform strain), and exceptional high-temperature tensile strength (500 MPa at 1,000 °C). These findings illustrate a path for designing materials that hold great potential for advancing next-generation technologies such as Generation IV fission reactors, first-generation fusion-plasma reactors, and more efficient gas turbines for electricity generation and propulsion.

DFT↗
DOE OSTI2025

Nanoscopic cross-grain cation homogenization in perovskite solar cells

Multiscale cation inhomogeneity has been a major hurdle in state-of-the-art formamidinium–caesium (FA–Cs) mixed-cation perovskites for achieving perovskite solar cells with optimal power conversion efficiencies and durability. Although the field has attempted to homogenize the overall distributions of FA–Cs in perovskite films from both plan and cross-sectional views, our understanding of grain-to-grain cation inhomogeneity and ability to tailor it—that is, spatially resolving the FA–Cs compositional difference between individual grains down to the nanoscale—are lacking. Here we reveal that as fundamental building blocks of a perovskite film, individual grains exhibit cationic compositions deviating from the prescribed ideal composition, severely limiting the interfacial optoelectronic properties and perovskite layer durability. This performance-limiting nanoscopic factor is linked to thermodynamic-driven morphological grooving, leading to a segmented surface landscape. At the grain triple junctions, grooves form nanoscale groove traps that hinder the mixing of solid-state cations across grains and thus retard inter-grain FA–Cs mixing. By rationally modulating the heterointerfacial energies, we reduced the depth of these nanoscale groove traps by a factor of three, significantly improving cation homogeneity. Perovskite solar cells with shallower nanoscale groove traps demonstrate enhanced power conversion efficiencies (25.62%) and improved stability under various standardized international protocols. In conclusion, our work highlights the significance of resolving surface nano-morphologies for homogeneous properties of perovskites.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Nuclear shell structure governs short-range nucleon pairing

Atomic nuclei are intricate quantum systems in which nucleons (protons and neutrons) are held together by the strong nuclear force. At very short distances, nucleons can momentarily form high-momentum pairs—known as short-range-correlated pairs—that shape the high-momentum structure of nuclear matter. Studying how nucleons form short-range-correlated pairs provides a rare experimental window into the short-distance behaviour of the strong interaction. Here, in this study, we use the scattering of high-energy electrons from 40 Ca, 48 Ca and 54 Fe, chosen for their distinct shell structures, to probe the formation of short-range-correlated pairs. Unexpectedly, we find that short-range-correlated pairing depends far more on the specific quantum orbitals occupied by protons and neutrons than on the nuclear mass or neutron–proton imbalance. This dependence is much stronger than that predicted by theoretical models. Our results point to a need for new angular-momentum quantum selection rules governing short-range nucleon pairing and reveal a deep connection between long-range nuclear shell structure and short-range interactions.

Nguyen, D. [Thomas Jefferson National Accelerator ↗
DOE OSTI2024

The High-resolution Urban Meteorology for Impacts Dataset (HUMID) daily for the Conterminous United States

Many current gridded surface meteorological datasets are inadequate for quantifying near surface spatiotemporal variability because they do not fully represent the impacts of land surface heterogeneity. Of note, explicit representation of the spatial structure and magnitude of local urban warming are usually lacking. Here we enhance the representation of spatial meteorological variability over urban areas in the conterminous United States (CONUS) by employing the High-Resolution Land Data Assimilation System (HRLDAS), which accounts for the fine-scale impacts of spatiotemporally varying land surfaces on weather. We also synthesize in situ meteorological data including local mesonets to create a 1 km grid spacing model-observation fusion product spanning 1981-2018 over the CONUS. Daily maximum, minimum, and mean values for a variety of temperature estimates, humidity, and surface energy budget terms, among others, are included. This High-resolution Urban Meteorology for Impacts Dataset (HUMID) will be useful for studies examining spatial variability of near surface meteorology and the impacts of urban heat islands across many disciplines including epidemiology, ecology, and climatology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Advanced pathways for hydrogen production: a collective view from a technical experts meeting

Hydrogen is an essential fuel and feedstock that can be produced in multiple ways to meet requirements for technological sectors that include energy storage, transportation, petroleum refining, and ammonia synthesis. To consider the future state of hydrogen manufacturing, a team of experts has assembled and examined three emerging hydrogen production technologies – photoelectrochemical, biological, and thermochemical. Each of these emerging technologies holds significant long-term potential for cost reduction while lowering industrial emissions associated with conventional methods of hydrogen manufacture (e.g., steam methane reforming) by using sunlight and renewable resources as primary sources of energy and feedstock, respectively. All three are currently at low technology readiness levels, however their applications, cost reduction opportunities and performance improvement pathways are under active development. In this work, opportunities and outlook for research that can directly advance the technologies are discussed.

08 HYDROGEN↗
DOE OSTI2025

Illuminating the mechanistic impacts of an Fe-quaterpyridine functionalized crystalline poly(triazine imide) semiconductor for photocatalytic CO 2 reduction

The strategy of incorporating earth-abundant catalytic centers into light-absorbing architectures is desirable from the viewpoint of low cost, low toxicity, and versatility for activating small molecules to produce solar-based fuels. Herein, we show that an Fe-quaterpyridine molecular catalyst can be anchored to a light-absorbing, crystalline, carbon nitride (PTI), to yield a molecular-catalyst/material hybrid, Fe-qpy-PTI, capable of facilitating CO 2 reduction to CO selectively (up to ∼97–98%) in aqueous solution under low-intensity light irradiation. This hybrid material leverages the ability of the Fe-qpy catalyst to bind CO 2 upon a one-electron reduction, as achieved by transfer of excited electrons from the carbon-nitride semiconductor. At a low incident power density of only 50 mW cm −2 , the catalytic activity of the hybrid material was measured across a range of catalyst loadings from 0.1–3.8 wt%, yielding CO rates of up to 596 μmol g −1 h −1 for a 3.8 wt% loading during a 3 h experiment. Over the course of 8 h, the hybrid material attained a CO evolution rate of 608 μmol g −1 h −1 and 305 turnovers for a TOF of ∼38 h −1 and an apparent quantum yield of 2.6%. Higher light intensities provided an initial increase in activity but negatively impacted photocatalytic rates with time, with an AQY of 0.6% at 150 mW cm −2 and 0.4% at 250 mW cm −2 . Transient absorption spectroscopy results showed electron survival probabilities consistent with the trends in observed product rates. Computational modeling was also used to evaluate and understand the mechanistic pathway of the high product selectivity for CO versus H 2 . These results thus help unveil key factors for leveraging the mechanistic understanding of molecular catalysts for CO 2 reduction for pairing with light absorbing semiconductors and establishing optimal conditions to attain maximal rates in aqueous solution.

McGuigan, Scott [Baylor University, Waco, TX (Unit↗
DOE OSTI2025

Structure of the D1-Val185Asn mutated photosystem II complex with slow O–O bond formation reveals changes in the Cl1 water channel

During photosynthesis, the photosystem II (PSII) enzyme catalyzes the light-driven oxidation of water, fueling life on Earth by storing light energy and releasing O 2 as a byproduct. Determining the molecular mechanism for this water oxidation reaction has been of significant interest for the development of synthetic catalysts, but many details remain elusive. One of the open questions is how protons are strategically removed from the active site, a Mn 4 CaO 5 cluster called the oxygen-evolving complex (OEC), during the reaction cycle via conserved water channels, and how proton transfer contributes to O–O bond formation energetics. Site-directed mutagenesis studies have investigated the role of conserved amino acid side chains in facilitating proton transfer. One of the most influential mutations is the Val185Asn substitution on the D1 subunit, which substantially slows O 2 release kinetics without abolishing catalytic activity. Forming a molecular understanding of how this mutation affects the active site will provide insight into the water oxidation reaction mechanism. Here, we investigated the structural basis of the Val185Asn substitution by determining a 1.99 Å-resolution cryo-EM structure. We observed that Asn185 orients away from the OEC and donates a H-bond to Cl1, a conserved chloride ion. We furthermore observed an alternative D2-Glu312-facing conformation of the D2-Lys317 side chain in the Cl1 water channel, a conformation that is consistent with recent models for proton transfer. These changes also produce perturbations to the hydrogen-bonding network. Overall, these finding provide insight into proton transfer in the Cl1 channel and its effect on the water oxidation reaction mechanism.

cryo-EM↗
DOE OSTI2025

Leveraging Hamiltonian simulation techniques to compile operations on bosonic devices

Circuit quantum electrodynamics enables the combined use of qubits and oscillator modes. Despite a variety of available gate sets, many hybrid qubit-boson (i.e. qubit-oscillator) operations are realizable only through optimal control theory, which is oftentimes intractable and uninterpretable. We introduce an analytic approach with rigorously proven error bounds for realizing specific classes of operations via two matrix product formulas commonly used in Hamiltonian simulation, the Lie–Trotter–Suzuki and Baker–Campbell–Hausdorff product formulas. We show how this technique can be used to realize a number of operations of interest, including polynomials of annihilation and creation operators, namely (a) p (a † ) q for integer p, q. We show examples of this paradigm including obtaining universal control within a subspace of the entire Fock space of an oscillator, state preparation of a fixed photon number in the cavity, simulation of the Jaynes–Cummings Hamiltonian, and simulation of the Hong-Ou-Mandel effect. This work demonstrates how techniques from Hamiltonian simulation can be applied to better control hybrid qubit-boson devices.

bosonic qubits↗
DOE OSTI2025

Mondo: integrating disease terminology across communities

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities⁠—including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology—a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene–disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.

biomedical informatics↗
DOE OSTI2026

Integrative analysis of CAM photosynthesis reveals its impact on primary metabolism in Yucca

Crassulacean Acid Metabolism (CAM) is an adaptation that temporally separates carbon uptake at night from photosynthesis during the day. CAM has evolved repeatedly across vascular plants, as its emergence may depend on simple regulatory changes to deeply conserved metabolic pathways. Modern CAM research relies heavily on interpretation of transcriptomic data, though regulation occurs at multiple levels following transcription. Additionally, while most research to date has focused on a handful of genes and metabolites in the core CAM pathway, the co-option of conserved regulatory and functional genes is bound to have wide-ranging effects on other aspects of primary metabolism. In this study, we integrate transcriptomic, proteomic, and metabolomic data to compare primary metabolism between the CAM species Yucca aloifolia and closely related C 3 species, Y. filamentosa. We observe minimal correlation between protein abundance and mRNA expression, suggesting significant post-transcriptional regulation in CAM species. We also find evidence of shifts in gene expression and metabolite accumulation outside of the central CAM pathway, suggesting that the shift to CAM has cascading effects across primary metabolism, especially nitrogen metabolism. Our findings provide insights into the metabolic shifts associated with CAM evolution, and highlight the complexity of its regulation at multiple biological levels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Correlation-driven topological band inversion in VSe 2

Recent spectroscopic studies have uncovered topological surface states and band inversion in 1⁢T−VSe 2 , positioning this material at the intersection of correlated electron physics and nontrivial band topology. While previous interpretations attribute these features to surface strain, the microscopic origin of the topological band structure remains unresolved. Here, we present an alternative explanation based on electronic correlations, showing that a negative effective Hubbard interaction (𝑈 eff < 0) applied to the Se 4p orbitals can reproduce the experimentally observed band inversion at both the Γ and 𝑀 points. Using density functional theory (DFT) calculations with orbital-selective interactions, we demonstrate that this approach naturally gives rise to topological surface states without invoking structural distortions. In conclusion, our results highlight the crucial role of ligand orbital correlations in shaping band topology and provide a novel framework for understanding and engineering topological phases in chalcogenide-based quantum materials.

36 MATERIALS SCIENCE↗