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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Adapting C 4 photosynthesis to atmospheric change and increasing productivity by elevating Rubisco content in sorghum and sugarcane

Meta-analyses and theory show that with rising atmospheric [CO 2 ], Rubisco has become the greatest limitation to light-saturated leaf CO 2 assimilation rates (A sat ) in C 4 crops. So would transgenically increasing Rubisco increase A sat and result in increased productivity in the field? Here, we successfully overexpressed the Rubisco small subunit (RbcS) with Rubisco accumulation factor 1 (Raf1) in both sorghum and sugarcane, resulting in significant increases in Rubisco content of 13 to 25% and up to 90% respectively. A sat increased 12 to 15% and Rubisco enzyme activity ~40% in three independent transgenic events of both species. Sorghum plants also showed increased speeds of photosynthetic induction and decreased bundle sheath leakiness. These improvements translated into average increases of 15.5% in biomass in field-grown sorghum and a 37 to 81% increase in greenhouse-grown sugarcane. This suggests a potential opportunity to achieve substantial increases in productivity of this key economically important clade of C 4 crops, future proofing their value under global atmospheric change.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Thermal modulation of nonlinear ultrasonic waves for nondestructive evaluation of elastic materials

Temperature variation is often considered an undesirable factor in ultrasonic testing, as wave velocity is highly sensitive to thermal fluctuations. However, completely eliminating the temperature effect is difficult, particularly in tests requiring precise velocity measurements. Recently, a method called Thermal Modulation of Nonlinear Ultrasonics (TMNL) has been developed. Instead of eliminating the thermal effect, the TMNL method leverages the temperature variation as a driving force to stimulate the nonlinear response of the medium and modulate the ultrasonic waves propagating in it. These modulated waves can then be used to evaluate the nonlinear behaviours of the test medium. This paper presents a focused review of the TMNL technique, including its theoretical foundations, particularly the conceptual challenges in integrating thermal effects into classical acoustoelastic theory, and recent applications in non-destructive evaluation (NDE). Three case studies are presented to demonstrate TMNL’s application in detecting microcracking in concrete, assessing ageing in polymer materials, and enabling temperature compensation in acoustoelastic tests. In conclusion, the review also summarises related studies, including photothermal crack modulation, and discusses current limitations and future directions of TMNL in elastic media.

NDE↗
DOE OSTI2026

A comprehensive framework to assess elemental mercury in the Department of Energy: A time series analysis

Objective: This study investigated whether seasonal categories affect airborne mercury concentrations in the U.S. Department of Energy operations. Methods: We conducted an initial assessment of the general variability of airborne elemental mercury time-weighted average (TWA) samples. Then, we performed a two-component time series analysis to determine whether long-term, cyclical temperature change patterns affect mercury concentrations. Results: Both ARIMA time series models demonstrated stationary, non-random means (χ² = 83.8, p < 0.001) and standard deviation (χ² = 55.8, p < 0.001) of mercury concentrations. Here, our results indicate that the seasonal factors did not influence mercury concentration. Conclusions: Our results demonstrate that mercury concentrations primarily emanate from operational activities, work practices, and/or transient environmental conditions rather than seasonal fluctuations.

Cannady, Ryan T. [Oak Ridge National Laboratory (O↗
DOE OSTI2025

Direct structural retrieval from gas-phase ultrafast diffraction data using a genetic algorithm

Ultrafast scattering techniques such as ultrafast electron diffraction and ultrafast x-ray diffraction have been utilized to elucidate the structural dynamics, reaction intermediates, and final products in molecular reactions following photoexcitation. The time-dependent structures are typically not directly retrieved from the experimental data, but they rely on comparison with calculations. The genetic algorithm (GA), a global optimization strategy, can be used to retrieve the molecular structures directly from diffraction patterns without any theoretical input. However, the robustness of the GA with respect to real experimental conditions such as a limited momentum transfer range, noise, and artifacts has not been studied in detail. In this work, we characterize the performance of the GA with simulated data that mimic realistic experimental conditions. We have developed and implemented a variant of the GA specific to diffraction measurements which performs better in the presence of imperfect data compared to the standard implementation of the GA. We demonstrate this method with both synthetic data and experimental ultrafast electron diffraction data on the UV-induced photodissociation of trifluoroiodomethane (C⁢F 3⁡ I) molecules.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Direct and indirect spin current generation and spin-orbit torques in ferromagnet/nonmagnet/ferromagnet trilayers

Spin-orbit torques in ferromagnet/nonmagnet/ferromagnet trilayers are studied using a combination of symmetry analysis, circuit theory, semiclassical simulations, and first-principles calculations using the nonequilibrium Green's function method with supercell disorder averaging. Here, we focus on unconventional processes involving the interplay between the two ferromagnetic layers, which are classified into direct and indirect mechanisms. The direct mechanism involves spin current generation by one ferromagnetic layer and its subsequent absorption by the other. In the indirect mechanism, the in-plane spin-polarized current from one ferromagnetic layer “leaks” into the other layer, where it is converted into an out-of-plane spin current and reabsorbed by the original layer. The direct mechanism results in a predominantly dampinglike torque, which damps the magnetization towards a certain direction 𝐬 𝑑 . The indirect mechanism results in a predominantly fieldlike torque with respect to a generally different direction 𝐬 𝑓 . Similarly to the current-in-plane giant magnetoresistance, the indirect mechanism is only active if the thickness of the nonmagnetic spacer is smaller than or comparable to the mean free path. Numerical calculations for a semiclassical model based on the Boltzmann equation confirm the presence of both direct and indirect mechanisms of spin current generation. First-principles calculations reveal sizable unconventional spin-orbit torques in Co/Cu/Co, Py/Cu/Py, and Co/Pt/Co trilayers and provide strong evidence of indirect spin current generation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Spin-Transfer Torque in Altermagnets with Magnetic Textures

We predict the existence of anisotropic spin-transfer torque effect in textured altermagnets. To this end, we generalize the Zhang-Li torque to incorporate the symmetry associated with prototypical 𝑑-wave altermagnets and identify the spin-splitter adiabatic and nonadiabatic torques. Applying our results to domain wall dynamics induced by spin-transfer torque, we find that, in certain regimes, the spin-splitter adiabatic torque can induce domain wall precession, significantly slowing down domain wall motion. The response of the domain wall also becomes anisotropic, reflecting the 𝑑-wave symmetry of the altermagnet. Furthermore, we observe that the spin-splitter adiabatic torque modifies skyrmion dynamics, inducing anisotropic skyrmion Hall effect. Furthermore, the above phenomena can serve as a hallmark of altermagnetism in textured magnets, distinguishing it from the behavior of ordinary antiferromagnets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Multi-strain analysis of Pseudomonas putida reveals the metabolic and genetic diversity of the species

Pseudomonas putida is a gram-negative bacterial species increasingly utilized in biotechnology due to its robust growth, ability to degrade aromatic compounds, solvent tolerance, and genetic tractability. In this study, we report a comprehensive multi-strain analysis of 164 P. putida strains based on the reconstruction of a pan-putida metabolic network and the formulation of strain-specific genome-scale metabolic models (GEMs). We performed whole-genome sequencing and hybrid assembly for 40 strains, contributing a ~8% increase to the available genomic data for P. putida . Furthermore, high-throughput phenotypic profiling using the Biolog phenotype microarray system for 24 strains on 190 unique carbon sources, along with 15 aromatic compounds not present on Biolog plates, yielded 4,920 unique strain-phenotype measurements. These data were leveraged to curate GEMs for 24 representative strains, including a refined model for strain KT2440, which comprised 1,480 genes and 2,191 metabolites, achieving a prediction accuracy of 91.2% in carbon utilization. Systematic comparison of genomes and GEMs revealed both conserved core pathways and significant allelic and functional divergence across strains, highlighting strain-specific variation in aromatic degradation. While pathways for protocatechuate and phenylacetate degradation were widely conserved, metabolic capabilities for compounds such as ferulate, phenol, and cresols varied markedly, suggesting adaptation to distinct ecological niches. Alleleome analysis of enzymes, such as PcaI and PcaJ, revealed distinct, functionally similar clades, indicating possible convergent evolution or horizontal gene transfer. These results provide computable resources and informative models for selecting P. putida strains with desired traits for biomanufacturing and bioremediation and offer insights into the evolution and phylogeny of the P. putida species.

aromatics utilization↗
DOE OSTI2025

TGCM: (T)rait, (G)ene, and (C)rop Growth (M)odel Directed Targeted Gene Characterization in Sorghum (Final Technical Report)

Understanding which genes control important crop traits could help scientists develop better bioenergy and food crops more efficiently. However, plant genomes contain tens of thousands of genes, and testing each one individually is expensive and time-consuming. This project developed computational tools to predict which genes are most likely to matter, allowing researchers to focus their efforts where they will have the greatest impact. This project developed and validated integrated approaches combining machine learning, quantitative genetics, and crop growth modeling to improve the efficiency of functional gene characterization in sorghum (Sorghum bicolor), a critical bioenergy and food security crop. The research addressed a fundamental challenge in plant biology: the majority of genes in plant genomes lack experimentally validated functions, making it difficult to prioritize which genes to study using resource-intensive reverse genetics approaches.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Heterogeneous Multi-Domain Dataset Synthesis to Facilitate Privacy and Risk Assessments in Smart City IoT

The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and context-aware services. However, this same proliferation intensifies privacy risks, particularly those arising from cross-modal data linkage across heterogeneous sensing platforms. To address these challenges, this paper introduces a comprehensive, statistically grounded framework for generating synthetic, multimodal IoT datasets tailored to Smart City research. The framework produces behaviorally plausible synthetic data suitable for preliminary privacy risk assessment and as a benchmark for future re-identification studies, as well as for evaluating algorithms in mobility modeling, urban informatics, and privacy-enhancing technologies. As part of our approach, we formalize probabilistic methods for synthesizing three heterogeneous and operationally relevant data streams—cellular mobility traces, payment terminal transaction logs, and Smart Retail nutrition records—capturing the behaviors of a large number of synthetically generated urban residents over a 12-week period. The framework integrates spatially explicit merchant selection using K-Dimensional (KD)-tree nearest-neighbor algorithms, temporally correlated anchor-based mobility simulation reflective of daily urban rhythms, and dietary-constraint filtering to preserve ecological validity in consumption patterns. In total, the system generates approximately 116 million mobility pings, 5.4 million transactions, and 1.9 million itemized purchases, yielding a reproducible benchmark for evaluating multimodal analytics, privacy-preserving computation, and secure IoT data-sharing protocols. To show the validity of this dataset, the underlying distributions of these residents were successfully validated against reported distributions in published research. We present preliminary uniqueness and cross-modal linkage indicators; comprehensive re-identification benchmarking against specific attack algorithms is planned as future work. This framework can be easily adapted to various scenarios of interest in Smart Cities and other IoT applications. By aligning methodological rigor with the operational needs of Smart City ecosystems, this work fills critical gaps in synthetic data generation for privacy-sensitive domains, including intelligent transportation systems, urban health informatics, and next-generation digital commerce infrastructures.

IoT↗
DOE OSTI2025

Turn‐On of Current‐Induced Spin Torque Upon Non‐collinear Antiferromagnetic Ordering in Delafossite PdCrO 2

We report measurements of the current-induced spin torque produced by the delafossite antiferromagnet PdCrO 2 and acting on an adjacent ferromagnetic permalloy layer. The spin torque increases strongly as the temperature is reduced through the Néel temperature, when the PdCrO 2 transitions from a paramagnetic phase to a noncollinear antiferromagnetic state. This result is qualitatively consistent with density functional theory calculations regarding how spin-current generation changes upon antiferromagnetic ordering in PdCrO 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multi-site Milling Strategy Reveals Significant Variation in Biomass Composition of Switchgrass ( Panicum virgatum ) Grown at Ten Locations

Cell wall composition influences biomass use as a forage and as a feedstock for biofuel and chemical conversion. To examine the influence of environment on composition of switchgrass (Panicum virgatum L.), we utilized a multi-environment experiment consisting of clones of switchgrass genotypes grown at up to ten locations in the continental US. We tested the influence of different milling treatments on biomass composition trait predictions via near-infrared reflectance spectroscopy (NIRS). We found that most compositional trait predictions (29/34) were significantly different (P < 0.05) when a single lot of biomass was subjected to disparate milling treatments, i.e., knife milling vs. knife milling with an additional cyclone milling. Further, depending on the plant material tested, three to eight compositional trait predictions vary (P < 0.05) when identical biomass was knife milled at different sites followed by cyclone milling at a single site, including for traits such as Klason lignin, nitrogen, and carbon. In some cases, variation due to milling site exceeded environmentally induced compositional variation of a single switchgrass genotype grown at different sites. From these observations, we recommend a protocol with two sequential millings that decouples growth environment from a particular mill. Utilizing this approach, we found that 46/46 biomass composition traits from the warm season herbaceous forage and switchgrass bioethanol NIRS equations vary significantly (P < 0.001) in clones of a switchgrass genotype (WBC) grown at ten sites, with the growth site representing the largest average source of variation (41%). This multi-site milling approach can be used to examine environmental and gene-by-environment influences on composition with the goal of optimizing cell wall composition in different environments for biomass utilization.

09 BIOMASS FUELS↗
DOE OSTI2024

Systematic discovery of new nano-scale metastable intermetallic eutectic phases in laser rapid solidified Aluminum-Germanium alloy

Laser surface remelting of as-cast Al-Ge eutectic alloy is shown to produce ultrafine lamellar eutectic morphology with interlamellar spacing refined up to ∼60 nm and composed of FCC Al solid solution and unusual Al x Ge y intermetallic phases that do not form during near-equilibrium solidification. The microstructures are characterized and analyzed using a combination of selected area electron diffraction, high-resolution scanning transmission electron microscopy, energy dispersive X-ray spectroscopy to obtain high-resolution elemental maps, and atomistic modeling using density functional theory followed by atomic-scale image simulation. Depending on the local solidification conditions, the crystallography of the Al x Ge y intermetallic phases in the eutectic microstructure is either monoclinic (C 2/c) or monoclinic (P 2 1 ), with high densities of defects in both cases. This is in sharp contrast to the as-cast alloys that showed nominally pure Al and Ge phases with significant solute partitioning and equilibrium FCC and diamond cubic crystal structures, respectively. Corresponding kinetic phase diagrams are proposed to interpret the evolution of nano-lamellar eutectic morphologies with equilibrium Al and metastable Al x Ge y phases, and to explain increased solid solubility in the Al phases manifested by precipitation of ultrafine clusters of Ge. Furthermore, the reasons for the formation of these metastable eutectics under laser rapid solidification are discussed from the perspective of the competitive growth criterion.

Al-Ge eutectic↗
DOE OSTI2025

Resonance ultrasound prediction of residual stress within a hybrid layer for additively manufactured samples

Hybrid additive manufacturing (AM) involves secondary processes or energy sources to alter specified locations within the build volume. Each hybrid step can refine the grain size, increase dislocation density, or modify residual stresses. Typically, the changes in mechanical properties are not confined within a single layer but have a compounding effect on preceding layers. Existing methods of measuring AM residual stress are limited in terms of their sensitivity, or they are destructive measurements. We propose using resonant ultrasound spectroscopy (RUS) to measure the residual stress in hybrid-AM components noninvasively, based on changes to the resonances, compared to a stress-free component. In this paper, we use finite element models to simulate residual stress in hybrid-AM components and to examine the sensitivity of RUS measurements in terms of frequency shifts and mode shapes with respect to single hybrid layers. Then, the RUS results are used to predict stress for a layer at a known location with unknown stress. Here, the approach highlights the capabilities of RUS to address an AM characterization challenge.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Charge Disproportionation at Twisted SrTiO 3 Bilayer Interface Driven by Local Atomic Registry

The interplay of lattice, orbital, and charge degrees of freedom in complex oxide materials has hosted a plethora of exotic quantum phases and physical properties. Recent advances in the synthesis of freestanding complex oxide membranes and twisted heterostructures assembled from membranes provide diverse opportunities for discovery using moiré design with local lattice control. To this end, we designed moiré crystals at the coincidence site lattice condition, providing commensurate structure within the moiré supercell arising from the multiatom complex oxide unit cell. We fabricated such twisted bilayers from freestanding SrTiO 3 membranes and used depth-sectioning-based electron microscopic methods to investigate ordered charge states at the moiré interface. By selectively imaging SrTiO 3 atomic planes at different depths through the bilayer, we clearly resolved the moiré periodic structure at the twisted interface and found that it exhibits lattice-dependent charge disproportionation in the local atomic registry within the moiré supercell. Density functional modeling of the twisted oxide interface predicts that these moiré phenomena are accompanied by a two-dimensional flat band that can drive exceptional electronic phases. Our work provides a robust strategy for controlling moiré periodicity in twisted oxides and paves pathways to exploit the extraordinary functionalities via moiré lattice-driven charge-orbital correlation.

charge disproportionation↗
DOE OSTI2026

Rethinking Suicide Thi4 Thiazole Synthases: Comparative Genomic Insights and Pilot Functional Evidence

Suicide thiazole synthases (Thi4) are mononuclear metal enzymes that form the thiazole moiety of thiamin from NAD + , glycine, and a sulfur atom that is stripped from an active-site cysteine residue, causing enzyme inactivation. Comparative genomic analysis shows that prokaryotic Thi4 genes often cluster on the chromosomal regions encoding ThiS, ThiF, and other proteins that can produce, relay, or use persulfide or thiocarboxylate sulfur. These recurring genomic associations raise the possibility that, in some microorganisms, suicide Thi4s may interact with sulfur-relay systems, i.e., they can possibly operate in a nonsuicide mode. This proof-of-concept study explores this possibility via complementation assays using Escherichia coli as a heterologous platform. A representative bacterial Thi4 that clustered with thiS and thiF complemented an E. coli ΔthiG (thiazole auxotroph) single mutant better than a ΔthiG ΔthiF ΔthiS triple mutant. Although (in)direct sulfur transfer could not be assessed in the scope of our investigation, the initial results suggest a dependence on host sulfur relay components, consistent with predicted interactions with the host sulfide transfer chain. Collectively, this new perspective provides a useful guide for future biochemical studies on alternative modes of action for “suicide Thi4s” and accessory proteins.

Bacteria↗
DOE OSTI2025

Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching

Integrating genome-scale metabolic networks with reactive transport models (RTMs) provides a detailed description of the dynamic changes in microbial growth and metabolism. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated application of linear programming (LP) to obtain flux balance analysis (FBA) solutions in every time step and spatial grid. To address this challenge, we propose a new simulation method where we train and validate artificial neural networks (ANNs) using randomly sampled FBA solutions and incorporate the resulting surrogate FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study of Shewanella oneidensis MR-1. During aerobic growth on lactate, S. oneidensis produces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred nutrients are depleted. To effectively simulate these complex dynamics, we used a cybernetic approach that models metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based surrogate models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Moreover, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Enhanced magnetic and optical properties of Y 3 Fe 5 O 12 (YIG) films with Au nanoinclusions

Y 3 Fe 5 O 12 (YIG) thin films are well known for their ferrimagnetic insulating property and low Gilbert damping coefficient (α), allowing them to be used for various spintronic applications and as magneto-optical isolators for photonic devices. Instead of doping, incorporation of plasmonic metals as nanoinclusions could be a promising route for improved magneto-optical coupling properties. In this work, YIG–Au nanocomposites have been deposited with ferrimagnetic insulating YIG as the matrix and Au nanoinclusions which introduce plasmonic absorption, optical anisotropy, and hyperbolic properties. Films with varying Au nanoinclusion densities have been processed and annealed to compare with the as-deposited ones. The films that had low Au nanoinclusion density and were annealed presented a lower magnetic damping coefficient of 2.84 × 10 −4 than the pure YIG film (9.66 × 10 −4 ). The as-deposited film with the highest Au density shows the strongest hyperbolic properties among all samples. These results demonstrate that both magnetic damping and optical properties can be tuned through deposition conditions in YIG–Au nanocomposite thin films, allowing for a balance of both properties. This YIG–Au nanocomposite system presents promising potential in next-generation opto-spintronic devices.

Quigley, Lizabeth [Purdue Univ., West Lafayette, I↗
DOE OSTI2025

Imaging the photochemistry of cyclobutanone using ultrafast electron diffraction: Experimental results

We investigated the ultrafast structural dynamics of cyclobutanone following photoexcitation at λ = 200 nm using gas-phase megaelectronvolt ultrafast electron diffraction. Our investigation complements the simulation studies of the same process within this special issue. It provides information about both electronic state population and structural dynamics through well-separable inelastic and elastic electron scattering signatures. We observe the depopulation of the photoexcited S 2 state of cyclobutanone with n3s Rydberg character through its inelastic electron scattering signature with a time constant of (0.29 ± 0.2) ps toward the S 1 state. The S 1 state population undergoes ring-opening via a Norrish Type-I reaction, likely while passing through a conical intersection with S 0 . The corresponding structural changes can be tracked by elastic electron scattering signatures. These changes appear with a delay of (0.14 ± 0.05) ps with respect to the initial photoexcitation, which is less than the S 2 depopulation time constant. This behavior provides evidence for the ballistic nature of the ring-opening once the S 1 state is reached. The resulting biradical species react further within (1.2 ± 0.2) ps via two rival fragmentation channels yielding ketene and ethylene, or propene and carbon monoxide. Furthermore, our study showcases the value of both gas-phase ultrafast diffraction studies as an experimental benchmark for nonadiabatic dynamics simulation methods and the limits in the interpretation of such experimental data without comparison with such simulations.

Carbon monoxide↗