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NASA NTRS1984

Systematic data interpretation of remote sensing in the reception of hydrocarbons, volume 1

The utilization of MSS-LANDSAT and RADAR imagery in the definition of morphostructural anomalies, which are indicative of hydrocarbon entrapment sites in the limit of the Middle and Lower Amazons basins was systemized. The identification and classification of the morphostructural anomalies were accomplished by means of the drainage network interpretation, based on the criteria previously proposed. Thirty anomalies were recognized, being subdivided into twenty domes, two fault controlled domes, six structural depressions, one fault controlled structural depression and one structure developed on a tilted fault block. Many anomalies are not randomly located. Rather, they seem to be aligned according to directions ENE and NNW, suggesting the presence of morphstructural trends in this part of the Amazons Basin. Significant orientations of lineaments were determined through statistical analysis, which defined many regional trends. The directions coincide with morphostructural trends orientations and with the directions of important structures in the Precambrian basement.

Demiranda, F. P.↗

DOE OSTI2021

Real-Time Alignment and Reorientation of Polymer Chains in Liquid Crystal Elastomers

Liquid crystal elastomers (LCEs) exhibit soft elasticity due to the alignment and reorientation of mesogens upon mechanical loading, which provides additional mechanisms to absorb and dissipate energy. This enhanced response makes LCEs potentially transformative materials for biomedical devices, tissue replacements, and protective equipment. However, there is a critical knowledge gap in understanding the highly rate-dependent dissipative behaviors of LCEs due to the lack of real-time characterization techniques that probe the microscale network structure and link it to the mechanical deformation of LCEs. In this work, we employ in situ optical measurements to evaluate the alignment and reorientation degree of mesogens in LCEs. The data are correlated to the quantitative physical analysis using polarized Fourier-transform infrared spectroscopy. The time scale of mesogen alignment is determined at different strain levels and loading rates. The mesogen reorientation kinetics is characterized to establish its relationship with the macroscale tensile strain, and compared to theoretical predictions. Overall, this work provides the first detailed study on the time-dependent evolution of mesogen alignment and reorientation in deformed LCEs. It also provides an effective and more accessible approach for other researchers to investigate the structural-property relationships of different types of polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Structural dynamics of the renewable energy economy: A longitudinal input-output insights for a resilient transition

As countries accelerate their energy transitions, understanding how renewable energy (RE) systems structurally integrate into national economies is essential. This study presents a longitudinal economic input-output (EIO) analysis of the renewable energy sector in South Korea from 2016 to 2022. We develop a novel EIO-based framework that disaggregates the RE sector both by energy source (thermal, hydro, nuclear and renewable) and by industrial function (manufacturing, generation, and services), allowing for a detailed assessment of production dynamics, value-added creation, and import dependency. By quantifying backward and forward linkages and induced economic effects, the analysis reveals persistent structural vulnerabilities in renewable manufacturing and increasing sectoral interdependencies. Results reveal that while the renewable energy sector's production and value-added shares have increased, critical segments remain highly import-dependent, particularly in equipment manufacturing. The analysis highlights systemic gaps in domestic supply chain resilience and offers sector-specific insights for reducing vulnerability and enhancing energy security. Although applied to South Korea as a case study, the proposed framework is designed to be transferable to other national contexts where renewable energy planning requires economic structural insights. The findings offer policy-relevant guidance for enhancing domestic energy resilience and aligning industrial strategy with long-term decarbonization goals.

Economic linkage↗

NASA NTRS1986

High dynamic range VLBI observations of NGC 6251

The large radio galaxy NGC 6251 has been observed with an 11-telescope VLBI array, including the full VLA, at 18 cm. High-dynamic-range maps of both the VLBI-scale and VLA-scale radio structure from these observations, as well as hybrid maps from earlier VLBI experiments at 6 and 13 cm, are presented. The 18-cm VLBI hybrid map has an unusually high dynamic range of about 300 to 1 (ratio of the peak brightness to five times the rms noise level) and is limited by thermal noise rather than calibration errors. A lower limit of 80 to 1 for the ratio of jet/counterjet brightness at parsec scales can be set. This is the strongest such limit produced by VLBI observations of any source to date. If the absence of a detectable counterjet is caused by relativistic beaming, then the jet must be aligned within 45 deg of the line of sight. The VLA map shows a complex structure along the previously detected kiloparsec-scale counterjet. The physical conditions in the inner few parsecs of the NGC 6251 jet and their relation to the conditions in the extraordinarily long and well collimated kiloparsec-scale jets are discussed, and it is shown that both small-scale and large-scale morphology can be explained in terms of a simple model and relativistic beaming.

Jones, D. L.↗

DOE OSTI2023

Structure and electronic tunability of acene alkylamine based layered hybrid organic-inorganic perovskites from first principles

Twelve layered hybrid organic-inorganic perovskites combining oligoacene derivatives [phenylmethylammonium (PMA), naphthylmethylammonium (NMA), anthrylmethylammonium (AMA), and tetrylmethylammonium (TMA)] and lead halides (Cl - , Br - , and I - anions) are investigated by first-principles density functional theory (DFT), showing broad, rational tunability of band gap, quantum well type, and spin-dependent energy band properties. Six compounds are known from previous syntheses and are used to devise a computational search space for likely low-energy structures. Among the six known compounds, a refined structure is identified for (NMA) 2 ⁢ PbCl 4 and a new, lower-energy structure is suggested for (AMA) 2 ⁢PbCl 4 . The DFT based search methodology is next applied to predict the likely structures for the six unknown compounds. Computationally predicted energy levels for all 12 compounds from spin-orbit coupled hybrid DFT reveal tunable type I quantum well alignments, with frontier orbitals located on the inorganic component, on the organic component, or on both, as controlled by cation and anion selection. In conclusion, several structures spontaneously break local and global inversion symmetry, causing strong spin splitting of the conduction bands [up to 0.12 eV for (PMA) 2 ⁢PbCl 4 ] and showing potential for spin-dependent transport properties and future spintronic and tunable chiroptical applications.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Mineralized sclerites in the gorgonian coral Leptogorgia chilensis as a natural jamming system

The soft corals (Cnidaria, Octocorallia), a diverse group of colonial marine invertebrates, can reversibly tune their body stiffness in response to external stimuli. This capability is attributed to their dynamic skeletal systems, which consist of thousands of mineralized skeletal elements, called sclerites, embedded within a gel-like matrix that swells/deswells and unjams/jams the sclerites, thus modulating skeletal stiffness. While sclerite morphology is widely used for species identification, its role in the mechanical performance of a soft coral’s skeletal system is largely unknown. Here, we investigated structure-jamming relationships in sclerite-based skeletal architectures using the red gorgonian octocoral Leptogorgia chilensis as a model system. The sclerites of L. chilensis exhibit a shaft-like geometry with two axial branches and two sets of triradiate side branches, which are aligned with the crystallographic symmetry of the constituent magnesium-containing calcite. By combining multiscale three-dimensional (3D) structural characterization, parametric geometrical modeling, 3D printing, mechanical testing, and discrete element simulations, we demonstrate how sclerite geometry achieves a balanced jamming performance in terms of stiffness, weight, strength, and fracture resistance in comparison to alternative geometries parametrically modified from the native sclerites (e.g., changes in the length and number of side branches). Here, we also found that these performance metrics are achieved through the effective interlocking among side and axial branches, which is further enhanced by the fractal-like microscopic spikes on the branch tips. The findings in this natural jamming system offer insights for designing synthetic mechanotunable material architectures for a wide range of applications, from soft robotics to mechanical dampeners.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Hund's coupling assisted orbital-selective superconductivity in Ba1-xKxFe2As2

While the superconducting transition temperature of hole-doped Ba_{1-x}K_{x}Fe_{2}As_{2} decreases past optimal doping, superconductivity does not completely disappear even for the fully doped KFe_{2}As_{2} compound. In fact, superconductivity is robust through a Lifshitz transition where electron bands become hole-like around the zone corner at around x=0.7, thus challenging the conventional understanding of superconductivity in iron-based systems. High-resolution angle-resolved photoemission spectroscopy is used to investigate the superconducting gap structure, as well as the normal state electronic structure, around optimal doping and across the Lifshitz transition. Our findings reveal a largely orbital-dependent superconducting gap structure, where the more strongly correlated d_{xy} band has a vanishing superconducting gap at higher doping, aligning with the Hund's metal behavior observed in the normal state. Notably, the superconducting gap on the d_{xy} band disappears before the Lifshitz transition, suggesting that the Fermi surface topology may play a secondary role. We discuss how these results point to orbital-selective superconducting pairing and how strong correlations via Hund's coupling may shape superconducting gap structures in iron-based and other multiorbital superconductors.

FOS: Physical sciences↗

NASA NTRS2007

Increased Alignment in Carbon Nanotube Growth

Method and system for fabricating an array of two or more carbon nanotube (CNT) structures on a coated substrate surface, the structures having substantially the same orientation with respect to a substrate surface. A single electrode, having an associated voltage source with a selected voltage, is connected to a substrate surface after the substrate is coated and before growth of the CNT structures, for a selected voltage application time interval. The CNT structures are then grown on a coated substrate surface with the desired orientation. Optionally, the electrode can be disconnected before the CNT structures are grown.

Delzeit, Lance D.↗

NASA NTRS1985

Shock associated noise of inverted-profile coannular jets. II - Condition for minimum noise. III - Shock structure and noise characteristic

The generation of noise by the shock-turbulence interaction with shock cells in an inverted-profile coannular jet with nozzle exit velocity aligned with the jet axis is investigated analytically, interpreting the optical measurements of Tanna et al. (1985). The noise-intensity minimum at slightly supersonic primary-flow velocities is related to the weakness of the primary-stream shock-cell structure and the lack of such a pattern in the outer fan stream. The discrepancies between this finding and those of Dosanjh et al. (1977 and 1978) are attributed to nozzle design, the definition of minimum noise, and different interpretative approaches. A first-order shock-cell model is then developed to derive formulas for the peak frequencies and the scaling of noise intensity. The results of computations using these formulas are presented in graphs and found to be in good agreement with the experimental data.

Tam, C. K. W.↗

DOE OSTI2024

Machine Learning meets Algebraic Combinatorics: A Suite of Benchmark Datasets to Accelerate AI for Mathematics Research

The use of benchmark datasets has become an important engine of progress in machine learning (ML) over the past 15 years. Recently there has been growing interest in utilizing machine learning to drive advances in research-level mathematics. However, off-the-shelf solutions often fail to deliver the types of insights required by mathematicians. This suggests the need for new ML methods specifically designed with mathematics in mind. The question then is: what benchmarks should the community use to evaluate these? On the one hand, toy problems such as learning the multiplicative structure of small finite groups have become popular in the mechanistic interpretability community whose perspective on explainability aligns well with the needs of mathematicians. While toy datasets are a useful benchmark for initial work, they lack the scale, complexity, and sophistication of many of the principal objects of study in modern mathematics. To address this, we introduce a new collection of benchmark datasets, Algebraic Combinatorics Benchmarks (ACBench), representing either classic or open problems in algebraic combinatorics, a subfield of mathematics that studies discrete structures arising from abstract algebra. After describing the datasets, we discuss the challenges involved in constructing “good” mathematics benchmarks, describe baseline model performance, and discuss some of the insights these datasets can provide that may be of interest even to those who are not interested in mathematics research itself.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

d -Electron Heavy Fermion Behavior in a Near-Room-Temperature Polar Metallic Ferrimagnet: A Case of Mn 5 SiC

Polycrystalline Mn 5 SiC was synthesized by using a high-temperature solid-state method. Mn 5 SiC adopts a polar space group (Cmc2 1 ) with six crystallographic Mn sites confirmed by X-ray and neutron diffraction, transmission electron microscopy, and second harmonic generation experiments. The complex crystal structure features edge-sharing trigonal prisms and icosahedra, as well as face/edge-sharing pentagonal prisms. Magnetic measurements indicate ferrimagnetic ordering with a transition temperature of 284 K. The ferrimagnetic structure (magnetic space group Cm’c’2 1 ) was further identified by powder neutron diffraction, where collinear Mn spins align along the crystallographic c-axis. The refined magnetic moment for each crystallographic Mn site at 4 K is 1.8(2), −2.42(9), −1.72(8), 0.51(6), 0.50(4), and 1.7(2) μ B . Density functional theory calculations confirm both the metallic behavior and the ferrimagnetic structure observed experimentally and further provide insight into the observed Mn moment dependence across crystallographic sites. The resistivity and specific heat measurements and density functional theory calculations reveal a substantially large Kadowaki–Woods ratio of 5 × 10 –5 μΩ·cm/(mJ/mol) 2 and a many-body renormalization factor of 5.5, indicating the unusual heavy Fermion behavior in such an itinerant magnetic metal.

Messegee, Zachary T. [George Mason University, Fai↗

DOE OSTI2025

Nine Canyon Long-Duration Energy Storage: A Feasibility Study

The Nine Canyon Long Duration Energy Storage (LDES) Feasibility Study explores the technical and economic viability of deploying advanced energy storage technologies at Energy Northwest's (EN) Nine Canyon (9C) Wind Project site in Benton County, Washington. Supported by the Washington State Department of Commerce and the U.S. Department of Energy’s Office of Electricity under its LDES Voucher Program, the study represents a collaborative effort between EN, Pacific Northwest National Laboratory (PNNL), and ARES North America. At the core of this effort is the development of a generalized techno-economic modeling framework and evaluation tool designed to assess the value proposition of LDES projects across a variety of contexts. The modeling tool is technology-agnostic and accommodates user-defined parameters such as rated power, energy duration, round-trip efficiency, capital and operational costs, and dispatch constraints. It also integrates economic inputs, including market prices, energy revenue structures, and financing parameters to evaluate performance through key metrics. The tool provides utilities with a transparent, adaptable platform to support decision-making, investment prioritization, and portfolio planning for various storage technologies. To guide scenario design and interpretation, the study first surveyed the LDES technology landscape, including lithium-ion batteries, flow batteries, non-hydro gravity storage, and thermo-mechanical systems, comparing cost trajectories, technical performance, safety and hazards, materials sourcing and recyclability, and spatial/siting considerations. This literature-grounded review highlights technology trade-offs and reinforces the need to align technology choice with site characteristics, use cases, and project objectives. A companion chapter examines ownership structures (EN ownership, third-party ownership, shared models) and offtake options (energy marketing, capacity/energy PPAs, time-of-use PPAs, block-delivery PPAs, and tolling), where PPAs (power purchase agreements) represent contractual arrangements for buying and selling electricity. The chapter also highlights implications for risk allocation, capital access, operational control, and revenue certainty. The study also evaluates supervisory control and data acquisition (SCADA) and transmission interconnection pathways, options include upgrading the existing SCADA or deploying a dedicated LDES controller, with attention to protection schemes, data telemetry, cybersecurity, and regulatory coordination with BPA. In addition, an ARES-specific geotechnical and hydrology assessment presented in the appendix screens multiple corridors for slope stability, bearing capacity, cut-and-fill magnitude, and stormwater behavior.

25 ENERGY STORAGE↗

DOE OSTI2021

Electronic Structure and Stacking Arrangement of Tungsten Disulfide at the Gold Contact

There is an intensive effort to control the nature of attractive interactions between ultrathin semiconductors and metals and to understand its impact on the electronic properties at the junction. In this work, we present a photoelectron spectroscopy study on the interface between WS 2 films and gold, with a focus on the occupied electronic states near the Brillouin zone center (i.e., the Γ point). To delineate the spectra of WS 2 supported on crystalline Au from the suspended WS 2 , we employ a microscopy approach and a tailored sample structure, in which the WS 2 /Au junction forms a semi-epitaxial relationship and is adjacent to suspended WS 2 regions. The photoelectron spectra, as a function of WS 2 thickness, display the expected splitting of the highest occupied states at the Γ point. In multilayer WS 2 , we discovered variations in the electronic states that spatially align with the crystalline grains of underlying Au. Corroborated by density functional theory calculations, we attribute the electronic structure variations to stacking variations within the WS 2 films. We propose that strong interactions exerted by Au grains cause slippage of the interfacing WS 2 layer with respect to the rest of the WS 2 film. Our findings illustrate that the electronic properties of transition metal dichalcogenides, and more generally 2D layered materials, are physically altered by the interactions with the interfacing materials, in addition to the electron screening and defects that have been widely considered.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

MOSAIC-CONUS: A Multimodal, Multi-Temporally Paired Dataset for Earth Sciences

Earth embeddings—vector representations of geographic locations indexed in space and time—are emerging as a unifying interface for geospatial AI. However, their quality depends not only on model design, but on how multimodal Earth observation (EO) data are spatially indexed, temporally aligned, and cross-modally associated during pretraining. We introduce MOSAIC-CONUS (Multimodal Observations with Spatially Aligned Imagery, Urban Points of Interest, In-Situ Measurements and Text Captions), a large-scale EO dataset over the contiguous United States, organized around 250,000 stratified point indices that serve as stable spatial keys across seven modalities: active radar, passive optical imagery, lidar-derived elevation, land cover, functional context, hydrometeorological measurements, and textual summaries. Unlike existing EO datasets, MOSAIC-CONUS introduces four contributions not jointly addressed in prior work: 1. an open-source, large-scale multimodal EO corpus structured around point-indexed data designed to support Earth embedding learning; 2. explicit radar-optical pairing tables spanning twelve temporal alignment regimes, formalizing cross-sensor alignment as a controllable variable for analyzing how temporal mismatch across modalities influences learned embeddings quality; 3. a benchmark suite spanning cross-modal retrieval, annual nightlights regression, and basin-held-out streamflow prediction, positioning MOSAIC-CONUS as a benchmark-ready resource for multimodal AI systems; and 4. a language-based embedding layer through co-registered textual summaries, enabling Earth embeddings to function as a queryable interface for agentic AI systems. The dataset and pairing protocols are publicly released.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Pseudospin versus magnetic dipole moment ordering in the isosceles triangular lattice material K 3 Er(VO 4 ) 2

Spin- 1 / 2 antiferromagnetic triangular lattice models are paradigms of geometrical frustration, revealing very different ground states and quantum effects depending on the nature of anisotropies in the model. Due to strong spin orbit coupling and crystal field effects, rare-earth ions can form pseudospin- 1 / 2 magnetic moments with anisotropic single-ion and exchange properties. Thus, rare-earth-based triangular lattices enable the exploration of this interplay between frustration and anisotropy. Here we study one such case, the rare-earth double vanadate glaserite material K 3 Er ( VO 4 ) 2 , which is a quasi-two-dimensional (2D) isosceles triangular antiferromagnet. Our specific heat and neutron powder diffraction data from K 3 Er ( VO 4 ) 2 reveal a transition to long range magnetic order at T N = 155 ± 5 mK which accounts for all R ln 2 entropy. Furthermore, we observe what appears to be a coexistence of three-dimensional (3D) and quasi-2D order below T N . The quasi-2D order leads to an anisotropic Warren-like peak profile for ( h k 0 ) reflections, while the 3D order is best-described by layers of antiferromagnetic b -aligned moments alternating with layers of zero moment. Our magnetic susceptibility data reveal that Er 3 + takes on a strong X Y single-ion anisotropy in K 3 Er ( VO 4 ) 2 , leading to vanishing moments when pseudospins are oriented along c . Thus, the magnetic structure, when considered from the pseudospin point of view could comprise of alternating layers of b -axis and c -axis aligned antiferromagnetism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Automation of Laser Plasma Focused Ion Beam Microscopy for Next-Gen Energy Materials

Automation can revolutionize the use of ultrafast laser ablation and plasma-focused ion beam (PFIB) techniques for high-throughput, reproducible cross-sectioning and various sample preparation in materials characterization. As these methods become essential for analyzing complex energy materials and next-generation devices, efficient, standardized workflows are needed to minimize variability and enhance precision. This work highlights our advancements in developing automated processes for sample preparation that integrates machine learning, workflow optimization, and large-scale data acquisition to improve efficiency and scalability in applications such as electrolyzers, photovoltaic cells, and microelectronics. To streamline cross-sectioning and lamella fabrication, we have implemented fully automated workflows that standardize laser ablation and PFIB milling sequences. These workflows incorporate pre-programmed protocols for material removal, alignment, and thinning, reducing user intervention and ensuring consistency across different sample types. Machine learning algorithms further enhance automation by predicting optimal milling strategies and adapting parameters based on material properties and sectioning requirements. This approach significantly improves throughput while maintaining the structural integrity of prepared samples for high-resolution imaging and analysis, including transmission electron microscopy. Beyond sample preparation, our automation platform enables the acquisition of large, high-resolution datasets through serial sectioning, image alignment, and 3D reconstruction. These automated routines facilitate multi-scale characterization, capturing structural and compositional details from the nanoscale to the device level. By reducing variability and increasing efficiency, our automated approach enhances defect analysis, failure diagnostics, and process optimization, accelerating advancements in materials research and device engineering.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Cylindrical C 96 Fullertubes: A Highly Active Metal‐Free O 2 ‐Reduction Electrocatalyst

Abstract A new isolation protocol was recently reported for highly purified metallic Fullertubes D 5h ‐C 90 , D 3d ‐C 96 , and D 5d ‐C 100, which exhibit unique electronic features. Here, we report the oxygen reduction electrocatalytic behavior of C 60 , C 70 (spheroidal fullerenes), and C 90 , C 96 , and C 100 (tubular fullerenes) using a combination of experimental and theoretical approaches. C 96 (a metal‐free catalyst) displayed remarkable oxygen reduction reaction (ORR) activity, with an onset potential of 0.85 V and a halfway potential of 0.75 V, which are close to the state‐of‐the‐art Pt/C benchmark catalyst values. We achieved an excellent power density of 0.75 W cm −2 using C 96 as a modified cathode in a proton‐exchange membrane fuel cell, comparable to other recently reported efficient metal‐free catalysts. Combined band structure (experimentally calculated) and free‐energy (DFT) investigations show that both favorable energy‐level alignment active catalytic sites on the carbon cage are responsible for the superior activity of C 96 .

Sanad, Mohamed Fathi↗

DOE OSTI2025

Impact of SO 2 on NiFe Nanoparticle Exsolution and Dissolution from LaFe 0.9 Ni 0.1 O 3 Perovskite Oxides

Ni-doped LaFeO 3 perovskite oxide is a promising cathode material for solid oxide electrolysis cells (SOECs) designed for CO 2 /H 2 O coelectrolysis. Here, the performance of LaFe 0.9 Ni 0.1 O 3 is being investigated under real-world conditions that include exposure to acid gases, such as SO 2 , relevant to SOEC operation. Experiments show that LaFe 0.9 Ni 0.1 O 3 exsolves NiFe nanoparticles, along with the formation of surface SO 4 2– and SO 3 2– after being exposed to 200 ppm of SO 2 . This suggests that the ionic diffusion of Ni 3+ and Fe 3+ between the bulk and the surface remains unaffected throughout the exsolution–dissolution–exsolution cycle. Thermochemical water splitting has been employed as a probe reaction to evaluate the catalytic properties of the exsolved NiFe nanoparticles. These nanoparticles demonstrated improved hydrogen production compared to bare perovskite oxide substrates. However, after exposure to SO 2 , the formation of Fe-rich NiFe nanoparticles led to poor thermocatalytic performance and rapid deactivation of the perovskite at elevated temperatures. Density functional theory (DFT) analysis was utilized to validate the experimental findings, indicating a significantly negative reaction energy for water splitting over exsolved Fe, as well as stronger binding of SO 2 to Fe than to Ni. Computational analysis further suggests that the presence of surface sulfate promotes the formation of Fe-rich NiFe nanoparticles, aligning with the experimental results. Overall, this study clarifies how SO 2 affects the structure of SOEC perovskite oxide candidate materials. Future engineering efforts should focus on enhancing nanoparticle exsolution and sulfur resistance, which is crucial for improving the hydrogen production capacity of La-based perovskite oxides for electro- and thermocatalytic water splitting in real environments containing acid gases.

Najimu, Musa [Univ. of Southern California, Los An↗