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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Na 2 Mn 3 Se 4 : Strongly Frustrated Antiferromagnetic Semiconductor with Complex Magnetic Structure

A new ternary selenide, Na 2 Mn 3 Se 4 , was prepared by a stoichiometric reaction between Na 2 Se 4 and metallic Mn at 923 K. Crystal structure determination revealed a new structure type, built of alternating layers of Na + ions and [Mn 3 Se 4 ] 2– anionic slabs. Band structure calculations indicate that Na 2 Mn 3 Se 4 is an indirect band gap semiconductor with E g = 1.59 eV, although a direct band gap is only marginally larger, at 1.64 eV. The material shows antiferromagnetic (AFM) ordering at 27 K, while the Weiss constant of ~–400 K suggests much stronger nearest-neighbor AFM exchange between the Mn sites. This discrepancy is attributed to the strong spin frustration caused by a triangulated arrangement of the Mn sites in the [Mn 3 Se 4 ] 2– layer. In conclusion, the magnetic frustration leads to the stabilization of a complex AFM ordered structure with non-collinear arrangement of the Mn magnetic moments, as established from neutron diffraction data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Simultaneous suppression of lignin, tricin and wall‐bound phenolic biosynthesis via the expression of monolignol 4‐ O ‐methyltransferases in rice

Summary Grass lignocelluloses feature complex compositions and structures. In addition to the presence of conventional lignin units from monolignols, acylated monolignols and flavonoid tricin also incorporate into lignin polymer; moreover, hydroxycinnamates, particularly ferulate, cross‐link arabinoxylan chains with each other and/or with lignin polymers. These structural complexities make grass lignocellulosics difficult to optimize for effective agro‐industrial applications. In the present study, we assess the applications of two engineered monolignol 4‐ O ‐methyltransferases (MOMTs) in modifying rice lignocellulosic properties. Two MOMTs confer regiospecific para ‐methylation of monolignols but with different catalytic preferences. The expression of MOMTs in rice resulted in differential but drastic suppression of lignin deposition, showing more than 50% decrease in guaiacyl lignin and up to an 90% reduction in syringyl lignin in transgenic lines. Moreover, the levels of arabinoxylan‐bound ferulate were reduced by up to 50%, and the levels of tricin in lignin fraction were also substantially reduced. Concomitantly, up to 11 μmol/g of the methanol‐extractable 4‐ O ‐methylated ferulic acid and 5–7 μmol/g 4‐ O ‐methylated sinapic acid were accumulated in MOMT transgenic lines. Both MOMTs in vitro displayed discernible substrate promiscuity towards a range of phenolics in addition to the dominant substrate monolignols, which partially explains their broad effects on grass phenolic biosynthesis. The cell wall structural and compositional changes resulted in up to 30% increase in saccharification yield of the de‐starched rice straw biomass after diluted acid‐pretreatment. These results demonstrate an effective strategy to tailor complex grass cell walls to generate improved cellulosic feedstocks for the fermentable sugar‐based production of biofuel and bio‐chemicals.

4-O-methylated↗
DOE OSTI2023

Data for Simultaneous Suppression of Lignin, Tricin and Wall-Bound Phenolic Biosynthesis via the Expression of Monolignol 4- O -Methyltransferases in Rice

Grass lignocelluloses feature complex compositions and structures. In addition to the presence of conventional lignin units from monolignols, acylated monolignols and flavonoid tricin also incorporate into lignin polymer; moreover, hydroxycinnamates, particularly ferulate, cross-link arabinoxylan chains with each other and/or with lignin polymers. These structural complexities make grass lignocellulosics difficult to optimize for effective agro-industrial applications. In the present study, we assess the applications of two engineered monolignol 4- O -methyltransferases (MOMTs) in modifying rice lignocellulosic properties. Two MOMTs confer regiospecific para-methylation of monolignols but with different catalytic preferences. The expression of MOMTs in rice resulted in differential but drastic suppression of lignin deposition, showing more than 50% decrease in guaiacyl lignin and up to an 90% reduction in syringyl lignin in transgenic lines. Moreover, the levels of arabinoxylan-bound ferulate were reduced by up to 50%, and the levels of tricin in lignin fraction were also substantially reduced. Concomitantly, up to 11 μmol/g of the methanol-extractable 4- O -methylated ferulic acid and 5–7 μmol/g 4- O -methylated sinapic acid were accumulated in MOMT transgenic lines. Both MOMTs in vitro displayed discernible substrate promiscuity towards a range of phenolics in addition to the dominant substrate monolignols, which partially explains their broad effects on grass phenolic biosynthesis. The cell wall structural and compositional changes resulted in up to 30% increase in saccharification yield of the de-starched rice straw biomass after diluted acid-pretreatment. These results demonstrate an effective strategy to tailor complex grass cell walls to generate improved cellulosic feedstocks for the fermentable sugar-based production of biofuel and bio-chemicals.

Biomass Analytics↗
DOE OSTI2021

Disturbance-accelerated succession increases the production of a temperate forest

Many secondary deciduous forests of eastern North America are approaching a transition in which maturing early successional tree species are declining, resulting in an uncertain future for these forests’ century-long carbon (C) sink. We initiated the Forest Accelerated Succession Experiment (FASET) at the University of Michigan Biological Station to examine the patterns and mechanisms underlying forest C cycling following the stem-girdling induced mortality of >6,700 early successional Populus spp. (aspen) and Betula papyrifera (paper birch). Since 2008, meteorological flux tower-based C cycling observations from the 33-ha treatment forest have been paired with those from a nearby unmanipulated forest. Following over a decade of observations, herein we revisit our core hypothesis: that net ecosystem production (NEP) would increase following the transition to mid-late successional species dominance due to increased canopy structural complexity. Supporting our hypothesis, NEP was stable, briefly declined, and then increased relative to the control in the decade following disturbance; however, increasing NEP was not associated with rising structural complexity but rather the rapid 1-year recovery of total LAI as mid-late successional Acer, Quercus, and Pinus assumed canopy dominance. The transition to mid-late successional species dominance improved carbon-use efficiency (CUE = NEP/gross primary production) as ecosystem respiration declined. Similar soil respiration rates in control and treatment forests, along with species differences in leaf physiology and the rising relative growth rates of mid-late successional species in the treatment forest, suggest changes in aboveground plant respiration and growth, respectively, were primarily responsible for increases in NEP. We conclude that deciduous forests transitioning from early to middle succession are capable of sustained or increased NEP, even when experiencing extensive tree mortality. This adds to mounting evidence that aging deciduous forests in the region will function as C sinks for decades to come.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantifying rupture characteristics of microearthquakes in the Parkfield Area using a high-resolution borehole network

It is well known that large earthquakes often exhibit significant rupture complexity such as well separated subevents. With improved recording and data processing techniques, small earthquakes have been found to exhibit rupture complexity as well. Studying these small earthquakes offers the opportunity to better understand the possible causes of rupture complexities. Specifically, if they are random or are related to fault properties. We examine microearthquakes (M < 3) in the Parkfield, California, area that are recorded by a high-resolution borehole network. We quantify earthquake complexity by the deviation of source time functions and source spectra from simple circular (omega-square) source models. We establish thresholds to declare complexity, and find that it can be detected in earthquakes larger than magnitude 2, with the best resolution above M2.5. Comparison between the two approaches reveals good agreement (>90 per cent), implying both methods are characterizing the same source complexity. For the two methods, 60–80 per cent (M 2.6–3) of the resolved events are complex depending on the method. The complex events we observe tend to cluster in areas of previously identified structural complexity; a larger fraction of the earthquakes exhibit complexity in the days following the M w 6 2004 Parkfield earthquake. Ignoring the complexity of these small events can introduce artefacts or add uncertainty to stress drop measurements. Focusing only on simple events however could lead to systematic bias, scaling artefacts and the lack of measurements of stress in structurally complex regions.

58 GEOSCIENCES↗
DOE OSTI2018

Anisotropic modeling and joint-MAP stitching for improved ultrasound model-based iterative reconstruction of large and thick specimens

One-sided non-destructive evaluation (NDE) is widely used to inspect materials, such as concrete structures in nuclear power plants (NPP). A widely used method for one-sided NDE is the synthetic aperture focusing technique (SAFT). The SAFT algorithm produces reasonable results when inspecting simple structures. However, for complex structures, such as heavily reinforced thick concrete structures, SAFT results in artifacts and hence there is a need for a more sophisticated inversion technique. Model-based iterative reconstruction (MBIR) algorithms, which are typically equivalent to regularized inversion techniques, offer a powerful framework to incorporate complex models for the physics, detector miscalibrations and the materials being imaged to obtain high quality reconstructions. Previously, we have proposed an ultrasonic MBIR method that signifcantly improves reconstruction quality compared to SAFT. However, the method made some simplifying assumptions on the propagation model and did not disucss ways to handle data that is obtained by raster scanning a system over a surface to inspect large regions. In this paper, we propose a novel MBIR algorithm that incorporates an anisotropic forward model and allows for the joint processing of data obtained from a system that raster scans a large surface. We demonstrate that the new MBIR method can produce dramatic improvements in reconstruction quality compared to SAFT and suppresses articfacts compared to the perviously presented MBIR approach.

Almansouri, Hani↗
DOE OSTI2015

The contribution of Diamond Light Source to the study of strongly correlated electron systems and complex magnetic structures

We review some of the significant contributions to the field of strongly correlated materials and complex magnets, arising from experiments performed at the Diamond Light Source (Harwell Science and Innovation Campus, Didcot, UK) during the first few years of operation (2007–2014). We provide a comprehensive overview of Diamond research on topological insulators, multiferroics, complex oxides and magnetic nanostructures. Several experiments on ultrafast dynamics, magnetic imaging, photoemission electron microscopy, soft X-ray holography and resonant magnetic hard and soft X-ray scattering are described.

Radaelli, P. G.↗
DOE OSTI2016

3D printing of large, complex metallic glass structures

Metallic glasses (MGs) or amorphous alloys although have superior mechanical properties their products are limited to simple geometries such as foils/plates or rods with thin section-thickness due to the requirement of high cooling rates. In this study, 3D, large dimensions of amorphous structures with complex geometry are manufactured by our newly developed Laser Foil Printing (LFP) technology. Zr-based (LM105, provided by Liquidmetal Technologies, Inc.) amorphous foils of 100 μm thickness are used as feedstock, and they are laser welded, layer-by-layer, to become 3D amorphous structures. Test results by X-Ray diffraction (XRD), differential scanning calorimetry (DSC), and micro-hardness confirm that the printed structures at selected process parameters achieve the same or better degree of amorphization as the raw foils. A mathematical model was developed to calculate the heating and cooling rates during structure manufacturing which helps the selection of process parameters. Here this study expands MG products to 3D arbitrary geometries with large dimensions due to the inherited advantages of the LFP technology which would open many potential applications.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Genomic Functionalization: The Next Revolution In Biology

We have implemented a ligand-alignment algorithm into our developed computational pipeline for identifying specificity-determining features (SDFs) in protein-ligand complexes. Given a set of protein-ligand complex structures, the algorithm aligns the complexes by ligand rather than by the C -RMSD or standard approach, providing a single reference frame for extracting SDFs. We anticipate that this ligand-alignment capability will be highly useful for protein function prediction. We already have a database containing > 20 K ligand-protein complex crystal structures taken from the Protein Data Bank. By aligning these proteins to single reference frames using ligand alignment, we can submit the complexes to our pipeline for SDF extraction. The SDFs derived from this training procedure can be used as thumbprints that are hallmarks of individual enzyme classes. These SDF thumbprints may then serve as guides to the prediction of function of new unknown proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Photodissociation of (SO{sub 2}⋯XH) Van der Waals complexes and clusters (XH = C{sub 2}H{sub 2}, C{sub 2}H{sub 4}, C{sub 2}H{sub 6}) excited at 32 040–32 090 cm{sup −1} with formation of HSO{sub 2} and X

We studied photodecomposition dynamics of (SO{sub 2}⋯XH) Van der Waals’ (VdW) complexes and clusters in gas phase, with X = C{sub 2}H, C{sub 2}H{sub 3}, and C{sub 2}H{sub 5}. SO{sub 2} was excited by frequency-doubled radiation of a tunable dye laser and resonance-enhanced multiphoton ionization was used to detect the C{sub 2}H (m/z 25), C{sub 2}H{sub 3} (m/z 27), and C{sub 2}H{sub 5} (m/z 29) ions by time-of-flight mass spectroscopy. Spectra obtained at higher nozzle pressures (P{sub 0} > 2.5 atm) indicate formation of clusters. Detailed studies of the VdW complex structure were carried out by analyzing the rotational structure of the respective action spectra. We also performed ab initio theoretical analysis of structures of the VdW complexes and transitional states leading to photodecomposition. We find that the structure of the transition state is significantly different as compared to the equilibrium ground-state structure of the respective complex. The photodecomposition mechanism depends on the hydrocarbon molecule bound to SO{sub 2}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Four-coordinate six-membered ketiminate and diketiminate boron complexes. Synthesis, structure, reactivity, and application in the design of nitrogen heterocycles

The data on ketiminate and diketiminate boron complexes are first reviewed. The present review is focused on the synthesis and chemical transformations of these chelates. The special attention is paid to the application of these boron chelates in the synthesis of nitrogen heterocycles including CF{sub 3}-substituted derivatives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Uncovering the lipidic basis for the preparation of functional nicotinic acetylcholine receptor detergent complexes for structural studies

This study compares the lipid composition, including individual phospholipid molecular species of solubilized nAChR detergent complexes (nAChR-DCs) with those of the bulk lipids from their source, Torpedo californica (Tc) electric tissue. This lipidomic analysis revealed seventy-seven (77) phospholipid species in the Tc tissue. Analysis of affinity-purified nAChR-DCs prepared with C-12 to C-16 phospholipid analog detergents alkylphosphocholine (FC) and lysofoscholine (LFC) demonstrated that nAChR-DCs prepared with FC12, LFC14, and LFC16 contained >60 phospholipids/nAChR, which was more than twice of those prepared with FC14, FC16, and LFC12. Significantly, all the nAChR-DCs lacked ethanolamine and anionic phospholipids, contained only four cholesterol molecules, and a limited number of phospholipid molecular species per nAChR. Upon incorporation into oocytes, FC12 produce significant functionality, whereas LFC14 and LFC16 nAChR-DCs displayed an increased functionality as compared to the crude Tc membrane. All three nAChR-DCs displayed different degrees of alterations in macroscopic activation and desensitization kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Structures of glycolate oxidase from Nicotiana benthamiana reveal a conserved pH sensor affecting the binding of FMN

Highlights: • We solved the structures of apo- and FMN-bound GOX from Nicotiana benthamiana. • We reported the first crystal structure of GOX without FMN among all species. • We found that the binding of FMN induces a pronounced conformational change of GOX. • We found a conserved pH sensor that might directly regulate the binding of FMN. • We provided a feasible method to regulate the activity of GOX in patients and crops. Glycolate oxidase (GOX), a flavin mononucleotide (FMN)-dependent enzyme, modulates reactive oxygen species-mediated signal transduction in green plants. It has been a target protein for crop improvement because of performing a key step in photorespiration that causes the energy losses. In human, GOX is involved in the production of oxalate, which is a key metabolite in the formation of kidney stone. Here, we report the first apo-GOX structure and its complex structure with cofactor FMN from Nicotiana benthamiana by X-ray crystallography. The binding of FMN induces a pronounced conformational change of GOX tetramer. Interestingly, a conserved pH sensor found among different species might directly regulate the binding of FMN and the enzyme activity. Combined with enzymatic experiments and biophysical analyses, we provide new insights in the molecular mechanism of regulating GOX biological activity reversibly and new methods of agricultural production and clinical application.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Constrained GAN-Generated X-Ray CT Data For Self-Supervised And Foundation-Model Segmentation Of Concrete Microstructures

Three-dimensional characterization of materials using X-ray computed tomography (XCT) is challenging due to the complexity of internal structures, noise, and variations in resolution. Traditional computer vision models often struggle to accurately segment these images, particularly in domain-specific applications like materials science. While supervised deep learning approaches have been developed to address the limitations of conventional algorithms, they typically require large amounts of labeled training data and often fail to generalize across different datasets. Self-supervised, few-and zero-shot learning methods have gained prominence in natural image processing and segmentation tasks, but their application to scientific imaging remains limited due to the unique structural complexity, noise, and textural artifacts present in materials science data. In this work, we investigate how domain adaptation, leveraging physics-based and GAN-generated synthetic data, impacts segmentation performance. We introduce a modified Contrastive Unpaired Translation (CUT) model designed to generate realistic labeled data, which can be used for training, pre-training, and fine-tuning segmentation models for real XCT microstructure data. We evaluate the performance of two segmentation approaches: a self-supervised network (SSL-ALPNet) and a foundation model (Segment Anything Model), assessing their improvements when pre-trained and/or fine-tuned on the synthesized data. Our results demonstrate that leveraging synthetic data significantly enhances segmentation performance, particularly in challenging materials science applications.

Ziabari, Amir [ORNL] (ORCID:000000034776457X)↗
DOE OSTI2022

End-to-end optimization for battery materials and molecules by combining graph neural networks and reinforcement learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to design new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗
DOE OSTI2022

End-to-End Optimization for Battery Materials and Molecules by Combining Graph Neural Networks and Reinforcement Learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to the design of new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗
DOE OSTI2024

Simple Scattering: Lipid nanoparticle structural data repository

Lipid nanoparticles (LNPs) are being intensively researched and developed to leverage their ability to safely and effectively deliver therapeutics. To achieve optimal therapeutic delivery, a comprehensive understanding of the relationship between formulation, structure, and efficacy is critical. However, the vast chemical space involved in the production of LNPs and the resulting structural complexity make the structure to function relationship challenging to assess and predict. New components and formulation procedures, which provide new opportunities for the use of LNPs, would be best identified and optimized using high-throughput characterization methods. Recently, a high-throughput workflow, consisting of automated mixing, small-angle X-ray scattering (SAXS), and cellular assays, demonstrated a link between formulation, internal structure, and efficacy for a library of LNPs. As SAXS data can be rapidly collected, the stage is set for the collection of thousands of SAXS profiles from a myriad of LNP formulations. In addition, correlated LNP small-angle neutron scattering (SANS) datasets, where components are systematically deuterated for additional contrast inside, provide complementary structural information. The centralization of SAXS and SANS datasets from LNPs, with appropriate, standardized metadata describing formulation parameters, into a data repository will provide valuable guidance for the formulation of LNPs with desired properties. To this end, we introduce Simple Scattering, an easy-to-use, open data repository for storing and sharing groups of correlated scattering profiles obtained from LNP screening experiments. Here, we discuss the current state of the repository, including limitations and upcoming changes, and our vision towards future usage in developing our collective knowledge base of LNPs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Synthesis of 2-deoxy-2,2-difluoro-α-maltosyl fluoride and its X-ray structure in complex with Streptomyces coelicolor GlgEI-V279S

Streptomyces coelicolor (Sco) GlgEI is a glycoside hydrolase involved in α-glucan biosynthesis and can be used as a model enzyme for structure-based inhibitor design targeting Mycobacterium tuberculosis (Mtb) GlgE. The latter is a genetically validated drug target for the development of anti-Tuberculosis (TB) treatments. Inhibition of Mtb GlgE results in a lethal buildup of the GlgE substrate maltose-1-phosphate (M1P). However, Mtb GlgE is difficult to crystallize and affords lower resolution X-ray structures. Sco GlgEI-V279S on the other hand crystallizes readily, produces high resolution X-ray data, and has active site topology identical to Mtb GlgE. In this article, we report the X-ray structure of Sco GlgEI-V279S in complex with 2-deoxy-2,2-difluoro-α-maltosyl fluoride (α-MTF, 5) at 2.3 Å resolution. α-MTF was designed as a non-hydrolysable mimic of M1P to probe the active site of GlgE1 prior to covalent bond formation without disruption of catalytic residues. The α-MTF complex revealed hydrogen bonding between Glu423 and the C1F which provides evidence that Glu423 functions as proton donor during catalysis. Further, hydrogen bonding between Arg392 and the axial C2 difluoromethylene moiety of α-MTF was observed suggesting that the C2 position tolerates substitution with hydrogen bond acceptors. The key step in the synthesis of α-MDF was transformation of peracetylated 2-fluoro-maltal 1 into peracetylated 2,2-difluoro-α-maltosyl fluoride 2 in a single step via the use of Selectfluor ® .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗