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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Uncovering the Size-dependent Thermal Solid Transformation of Akaganéite

Investigating the structural evolution and phase transformation of iron oxides is crucial for gaining a deeper understanding of geological changes on diverse planets and preparing oxide materials suitable for industrial applications. In this study, we employed in-situ heating techniques in conjunction with transmission electron microscopy (TEM) observations and ex-situ characterization to thoroughly analyze the thermal solid-phase transformation of akaganéite one-dimensional (1D) nanostructures with varying diameters. Our findings offer compelling evidence for a size-dependent morphology evolution in akaganéite 1D nanostructures, which can be attributed to the transformation from akaganéite to maghemite (?-Fe2O3) and subsequent crystal growth. Specifically, we observed that akaganéite nanorods with a diameter of around 50 nm transformed into hollow polycrystalline maghemite nanorods, which demonstrated remarkable stability without arresting crystal growth under continuous heating. In contrast, smaller akaganéite nanoneedles or nanowires with a diameter ranging from 20 to 8 nm displayed a propensity for forming single-crystal nanoneedles or nanowires through phase transformation and densification. By manipulating the size of the precursors, we have developed a straightforward method for the synthesis of single-crystal and polycrystalline maghemite nanowires through solid-phase transformation. These significant findings provide new insights into the size-dependent structural evolution and phase transformation of iron oxides at the nanoscale.

Wang, Xiang↗
DOE OSTI2024

Provable Repair of Vision Transformers

Vision Transformers have emerged as state-of-the-art image recognition tools, but may still exhibit incorrect behavior. Incorrect image recognition can have disastrous consequences in safety-critical real-world applications such as self-driving automobiles. In this paper, we present Provable Repair of Vision Transformers (PRoViT), a provable repair approach that guarantees the correct classification of images in a repair set for a given Vision Transformer without modifying its architecture. PRoViT avoids negatively affecting correctly classified images (drawdown) by minimizing the changes made to the Vision Transformer’s parameters and original output. Here, we observe that for Vision Transformers, unlike for other architectures such as ResNet or VGG, editing just the parameters in the last layer achieves correctness guarantees and very low drawdown. We introduce a novel method for editing these last-layer parameters that enables PRoViT to efficiently repair state-of-the-art Vision Transformers for thousands of images, far exceeding the capabilities of prior provable repair approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Miscanthus giganteus Biolistic Transformation Using the Visible RUBY Red Marker Gene to Monitor Transformation Efficiency

Miscanthus × giganteus ( M × g ) is a high-yielding perennial C4 bioenergy crop, but genetic improvement by breeding is constrained by triploid sterility and clonal propagation. Improving genetic transformation methods for M × g would provide opportunities for advantageous trait introgression. Use of an easy to phenotype reporter gene is a promising strategy to improve transformation processes and efficiency. This study presents an efficient novel method for biolistic transformation of inflorescence-derived callus in M × g and demonstrates its efficacy using RUBY, a betalain-based noninvasive reporter that is visible throughout the transformation process. RUBY expression ( Zea mays codon optimized) was visible from callus stage through plantlet development into maturity. RUBY expressing independently transformed plants were confirmed by hygromycin phosphotransferase ELISA and by genomic PCR demonstrating that the RUBY phenotype is sufficient for screening transformants. The Zea mays codon optimized hygromycin selection marker was driven by previously established promoters for Miscanthus, ZmUBI and 2×35S, while the RUBY gene expression was controlled by a known Zea mays C4 promoter, Brachypodium UBI10, newly employed in Miscanthus. The construct containing the 2×35S promoter for hygromycin had a 15.1% transformation efficiency while the ZmUBI promoter had a 20.5% transformation efficiency. This study provides a novel, highly efficient protocol for successful biolistic transformation of M × g for stable expression. This study also demonstrates that RUBY expression can be used as a convenient and powerful monitor of transformation in ongoing and future work to engineer M × g into an improved bioproduct feedstock.

RUBY↗
DOE OSTI2026

Data for Miscanthus giganteus Biolistic Transformation Using the Visible RUBY Red Marker Gene to Monitor Transformation Efficiency

Miscanthus × giganteus ( M × g ) is a high- yielding perennial C4 bioenergy crop, but genetic improvement by breeding is constrained by triploid sterility and clonal propagation. Improving genetic transformation methods for M × g would provide opportunities for advantageous trait introgression. Use of an easy to phenotype reporter gene is a promising strategy to improve transformation processes and efficiency. This study presents an efficient novel method for biolistic transformation of inflorescence- derived callus in M × g and demonstrates its efficacy using RUBY, a betalain-based noninvasive reporter that is visible throughout the transformation process. RUBY expression ( Zea mays codon optimized) was visible from callus stage through plantlet development into maturity. RUBY expressing independently transformed plants were confirmed by hygromycin phosphotransferase ELISA and by genomic PCR demonstrating that the RUBY phenotype is sufficient for screening transformants. The Zea mays codon optimized hygromycin selection marker was driven by previously established promoters for Miscanthus, ZmUBI and 2×35S, while the RUBY gene expression was controlled by a known Zea mays C4 promoter, Brachypodium UBI10, newly employed in Miscanthus. The construct containing the 2×35S promoter for hygromycin had a 15.1% transformation efficiency while the ZmUBI promoter had a 20.5% transformation efficiency. This study provides a novel, highly efficient protocol for successful biolistic transformation of M × g for stable expression. This study also demonstrates that RUBY expression can be used as a convenient and powerful monitor of transformation in ongoing and future work to engineer M × g into an improved bioproduct feedstock. **NOTE: in "TableS2_ProtocolComparison.csv", the data from row 665 to 971 should be removed.

Gene Editing↗
DOE OSTI2026

Laplace Transform–Based Quantum Eigenvalue Transformation via Linear Combination of Hamiltonian Simulation

Eigenvalue transformations, which include solving time-dependent differential equations as a special case, have a wide range of applications in scientific and engineering computation. While quantum algorithms for singular value transformations are well studied, eigenvalue transformations are distinct, especially for nonnormal matrices. Here, we propose an efficient quantum algorithm for performing a class of eigenvalue transformations that can be expressed as a certain type of matrix Laplace transformation. This allows us to significantly extend the recently developed linear combination of Hamiltonian simulation method [D. An, J.-P. Liu, and L. Lin, Phys. Rev. Lett., 131 (2023), 150603; D. An, A. M. Childs, and L. Lin, Commun. Math. Phys. 407, 19 (2026)] to represent a wider class of eigenvalue transformations, such as powers of the matrix inverse, 𝐴 −𝑘 , and the exponential of the matrix inverse, 𝑒 −𝐴 −1 . The latter can be interpreted as the solution of a mass-matrix differential equation of the form form 𝐴⁢𝑢′⁡⁡(𝑡) =−𝑢⁡(𝑡). We demonstrate that our eigenvalue transformation approach can solve this problem without explicitly inverting 𝐴, thereby reducing the computational complexity.

Laplace transform↗
DOE OSTI2024

Understanding Line Losses and Transformer Losses in Rural Isolated Distribution Systems

Rural, isolated power systems in the mainland U.S. and in states like Alaska and Hawaii are powered by assets like diesel generators. These rural, isolated power systems also cannot operate at the higher band of medium voltage (like 69kV). They are primarily in the 12 to 14 kV range to keep the cost of the distribution investments lower. Because of this mid-band medium voltage range, the line losses and distribution transformers losses consume significant diesel consumption (almost 10 percent of the peak load). This work considers one such power system powering an isolated system and presents key findings online losses, and transformer losses. Understanding and documenting the impacts is critical for these communities operating their power systems and take actions to reduce expensive diesel consumption. In this paper, we will present one such typical grid and model it in electromagnetic transients (EMT) domain. We used the tower structure, under ground cabling installation to develop high fidelity models of lines. We also used high fidelity models of distribution transformers to present the no-load losses and full load loses. We will also present technical solutions available commercially off-the-shelf to reduce these losses and reduce diesel consumption. This work will be a primer for communities to understand the technical challenges and to understand the possible solution available to solve such challenges for rural, isolated power system operators.

blackstart↗
DOE OSTI2025

Topotactic Phase Transformation of Lithiated Spinel to Layered LiMn0.5Ni0.5O2: The Interaction of 3-D and 2-D Li-ion Diffusion

This study investigates the structural evolution of LiMn0.5Ni0.5O2 cathode materials for Li-ion batteries as a function of synthesis temperature and its effect on electrochemical performance. It is demonstrated that, as the synthesis temperature increases from 400 to 900 ?C, a gradual topotactic transformation occurs between a lithiated spinel structure, denoted herein as “lithium-excess spinel” LxS-LiMn0.5Ni0.5O2 (or LxS-LMNO), and the well-known layered LiMn0.5Ni0.5O2 structure prepared at high temperature, HT-LiMn0.5Ni0.5O2 (HT-LMNO). The electrochemical capacity of the LiMn0.5Ni0.5O2 electrodes follows a parabolic trend with increasing synthesis temperature, which is attributed primarily to the gradual transformation of 3-dimensional (3-D) to 2-dimensional (2-D) diffusion pathways for the Li ions. When synthesized at 400 °C, LxS-LiMn0.5Ni0.5O2 electrodes perform well, benefitting from the 3-D network of channels within the LxS structure. By contrast, when prepared at 500-700 °C, LiMn0.5Ni0.5O2 electrodes operate poorly, which is attributed to the formation of locally disordered structural arrangements that impede Li-ion diffusion. Such an increase in local disorder in the mid-temperature synthesis range is attributed to the structural frustration between the lithium-excess spinal and layered end-members. The transformation from the locally disordered to more ordered layered components between 700 °C and 900 °C enhances electrochemical performance. The study opens new avenues for designing next-generation Mn-rich cathode materials by fine-tuning the synthesis conditions as well as the composition and structure of LxS-LMNO electrodes.

energy storage↗
DOE OSTI2026

Extended continuous cooling transformation diagram for 410 stainless steel encompassing δ → γ and γ → αʹ transformations determined by dilatometry

In this study, we use dilatometry to construct an extended Continuous Cooling Transformation (CCT) diagram for 410 stainless steel, capturing both δ → γ and γ → αʹ transformations specifically for directed energy deposition (DED) additive manufacturing (AM) applications. To ensure that the findings are representative of AM specific microstructures and compositions, dilatometry coupons were extracted from a wire arc DED wall, thereby preserving the inherent microstructural and compositional variability within the material. The on-heating phase transformations, including A c1 , A c3 , and γ → δ, were found to be essentially location independent, despite the typical heterogeneity associated with AM. Conversely, increasing cooling rates were observed to shift the start and finish temperatures of both δ → γ and γ → αʹ transformations to lower values. The resulting extended CCT diagram offers a more complete depiction of phase transformation behavior in the system, enabling accurate microstructure evolution modeling and residual stress predictions specifically for directed energy deposition additive manufacturing applications.

Additive manufacturing↗
DOE OSTI2026

Transforming the $v$ World: A New Multivariate Transformer Energy Estimator for NOvA

The NOvA Transformer Energy Estimator (Transformer_EE) is a universal machine learning tool currently used to infer the incoming beam neutrino energy and the outgoing lepton energy in both near andfar detectors. It uses a unique, highly flexible framework for simultaneous multivariate prediction that supports many possible loss functions. A spectral reweighting and flattening scheme lessens training bias. A feature noising subroutine enables adversarial-like training, mitigating sensitivities to certain systematic effects at marginal resolution loss at inference time. The state of the Transformer_EE will be reviewed, and its robustness with respect to several NOvA Near and Far Detector systematics highlighted.

Tong, Leon [Minnesota U.] (ORCID:0000000231625965)↗
DOE OSTI2024

Transforming the bootstrap: using Transformers to compute scattering amplitudes in planar N = 4 Super Yang-Mills theory

Abstract We pursue the use of deep learning methods to improve state-of-the-art computations in theoretical high-energy physics. Planar N = 4 Super Yang-Mills theory is a close cousin to the theory that describes Higgs boson production at the Large Hadron Collider; its scattering amplitudes are large mathematical expressions containing integer coefficients. In this paper, we apply Transformers to predict these coefficients. The problem can be formulated in a language-like representation amenable to standard cross-entropy training objectives. We design two related experiments and show that the model achieves high accuracy (> 98%) on both tasks. Our work shows that Transformers can be applied successfully to problems in theoretical physics that require exact solutions.

Cai, Tianji (ORCID:0000000232359486)↗
DOE OSTI2025

Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. II. cosmological results

Here, we present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years of the Dark Energy Survey. We implement the following: (1) second and third moments; (2) wavelet phase harmonics; (3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven 𝑤 Cold Dark Matter (𝑤⁢ CDM) cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the figure of merit (𝑆 8 , Ω m ) is improved by 70% (Λ ⁢CDM) and 90% (𝑤 ⁢CDM). When all the summary statistics are combined, we achieve a 2% constraint on the amplitude of fluctuations parameter 𝑆 8 ≡ 𝜎 8 ⁢(Ω m /0.3) 0.5 , obtaining 𝑆 8 = 0.794 ±0.017 (Λ⁢ CDM) and 𝑆 8 = 0.817 ±0.021 (𝑤 ⁢CDM), and a ∼10% constraint on Ω m , obtaining Ω m =0.259 ±0.025 (Λ ⁢CDM) and Ω m = 0.273 ±0.029 (𝑤⁢ CDM). In the context of the 𝑤⁢ CDM scenario, these statistics also strengthen the constraints on the parameter 𝑤, obtaining 𝑤 <−0.72. The constraints from different statistics are shown to be internally consistent (with a 𝑝-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the first three years of the Dark Energy Survey data, finding good consistency; we also compare with results from external datasets, such as planck constraints from the cosmic microwave background, finding statistical agreement, with discrepancies no greater than <2.2⁢𝜎.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Supramolecular Motion Enables Chondrogenic Bioactivity of a Cyclic Peptide Mimetic of Transforming Growth Factor-β1

Transforming growth factor (TGF)-β1 is a multifunctional protein that is essential in many cellular processes that include fibrosis, inflammation, chondrogenesis, and cartilage repair. In particular, cartilage repair is important to avoid physical disability since this tissue does not have the inherent capacity to regenerate beyond full development. We report here on supramolecular coassemblies of two peptide amphiphile molecules, one containing a TGF-β1 mimetic peptide, and another which is one of two constitutional isomers lacking bioactivity. Using human articular chondrocytes, we investigated the bioactivity of the supramolecular copolymers of each isomer displaying either the previously reported linear form of the mimetic peptide or a novel cyclic analogue. Based on fluorescence depolarization and 1 H NMR spin–lattice relaxation times, we found that coassemblies containing the cyclic compound and the most dynamic isomer exhibited the highest intracellular TGF-β1 signaling and gene expression of cartilage extracellular matrix components. Here, we conclude that control of supramolecular motion is emerging as an important factor in the binding of synthetic molecules to receptors that can be tuned through chemical structure.

Antigens↗
DOE OSTI2025

Transforming the Process Industries through Electrification: Challenges and Opportunities

For the more than 70 years, the process industries have provided essential fuels and materials for global growth. Increased manufacturing production comes with substantial environmental impact. Reducing environmental impact through process electrification, carbon capture, and other emerging technologies would require large changes throughout the process industries. We review opportunities and challenges related to electrification, focusing on technical, operational, and economic considerations. Here, we conclude that electrification could completely eliminate scope 1 CO 2 emissions, increase product quality, and reduce the equipment size and cost. On the other hand, it calls for a significant expansion of power generation capacity, as well as new paradigms for process design and operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Mn(II)-induced phase transformation of Mn(IV) oxide in seawater

Manganese (Mn) oxides are key components of oceanic and lacustrine Mn nodules and influence metal cycling through oxidation and adsorption processes. Layered Mn oxides (LMOs) are the most common minerals in these nodules and the immediate products of microbially mediated Mn(II) oxidation by O 2 . LMOs can transform into tunneled Mn oxides (TMOs), Mn oxyhydroxides (MnOOH), or Mn(II,III) phase (Mn 3 O 4 ). LMOs often concur with Mn(II) in the environment and the adsorption and oxidation of Mn(II) by LMOs can greatly promote the transformation of LMOs to those phases. However, the Mn(II)-promoted transformation of LMOs in seawater—rich in various cations (300 mM Na + , 10 mM K + , 50 mM Ca 2+ , and 10 mM Mg 2+ ) remains poorly understood. We examined the transformation of δ-MnO 2 in artificial seawater (pH 8.2) under anoxic conditions with the Mn(II)/MnO 2 ratio (r) ranging from 0.08 to 3.83. To assess the effect of ionic strength (IS), parallel experiments were conducted in a mixed 530 mM NaCl and 10 mM KCl solution (having seawater ionic strength but without Ca 2+ and Mg 2+ ) and in 100 mM NaCl solution as a control. At low r (0.08), δ-MnO 2 transformed into triclinic birnessite and a 4 × 4 TMO in 100 mM NaCl solution, which, however, was suppressed in seawater due to strong interactions of Ca 2+ /Mg 2+ with δ-MnO 2 . In the mixed 530 mM NaCl and 10 mM KCl solution (the same ionic strength as of seawater), the transformation occurred extensively but the products had lower crystallinity compared to in 100 mM NaCl solution. At the high Mn(II)/MnO 2 ratios (0.5 ≤ r ≤ 3.83), δ-MnO 2 transformed extensively into MnOOH phases and hausmannite (Mn 3 O 4 ) in 100 mM NaCl solution. The seawater suppressed the transformation, but the suppression became weaker with increasing Mn(II)/MnO 2 ratio. For example, the transformation was completely suppressed at r = 0.5 but essentially negligible at r = 3.83. The suppression at these high Mn(II)/MnO 2 ratios was mainly ascribed to the influence of Ca 2+ and Mg 2+ rather than of the high IS, and the weaker suppression at the higher Mn(II)/MnO 2 ratio suggests stronger competition of Mn(II) with Ca 2+ /Mg 2+ for interacting with δ-MnO 2 . Moreover, the composition and crystallinity of the transformation products (i.e., the relative abundance of MnOOH (α, β, and γ) and Mn 3 O 4 ) were influenced by both the high ionic strength and the presence of Ca 2+ and Mg 2+ . Therefore, even though Ca 2+ and Mg 2+ concentrations are much lower than Na + in seawater, their impacts on the transformation are dominant. Our study explains why MnOOH phases, hausmannite, and TMOs are less common than LMOs in oceanic environments, partially because seawater chemistry suppresses their formation. LMOs are the most reactive for metal adsorption and oxidation among all Mn oxides. Thus, the high stability of LMOs in an oceanic environment confers the high impacts of Mn oxides on metal cycling in the ocean.

Divalent manganese↗
DOE OSTI2025

A Novel Gene Stacking Method in Plant Transformation Utilizing Split Selectable Markers

Gene stacking, the process of introducing multiple genes into a single plant to enhance desired traits, is essential for plant genetic improvement through both conventional breeding and genetic transformation. In general, transformation-based gene stacking can be achieved through either co-transformation to simultaneously introduce multiple genes or sequential multi-round transformation. While co-transformation is generally faster and more efficient than sequential multi-round transformation, it often requires two selectable marker genes, which confer resistance to antibiotics, for selecting transgenic events. However, in most cases, there is only one best selectable marker gene for a specific plant species or genotype. Also, it is harder to optimize the concentrations of two antibiotics for co-transformation than using one antibiotic for selecting transgenic events. To overcome this challenge, we recently developed an innovative split selectable marker system for plant co-transformation, allowing the use of one selectable marker gene to select transgenic events. This method involves constructing two binary vectors, each carrying a subset of genes of interest and a partial fragment of the selectable marker gene, which is connected to a partial intein fragment. Following Agrobacterium -mediated co-transformation, plants harboring both binary vectors are selected using a single antibiotic, such as kanamycin. This split-marker system can be used to co-transform multiple genes into both herbaceous and woody plants, accelerating genetic improvement of polygenic traits or integrative improvement of multiple traits to simultaneously increase crop yield and quality.

59 BASIC BIOLOGICAL SCIENCES↗