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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

UDP-glucuronic acid decarboxylase in alfalfa: a target to improve ruminal digestibility of stems

Alfalfa (Medicago sativa) has a high nutritional value, but poor digestibility of the stems limits its value as an energy source in ruminant diets. Xylan and lignin negatively affect cell wall digestibility, whereas pectins have high digestibility in the rumen. In plants, UDP-xylose synthase (UXS) catalyses the decarboxylation of UDP-glucuronic acid to form UDP-xylose in an irreversible step that is key for xylan synthesis. Here, we functionally characterized two UXS genes in alfalfa, namely MsaUXS2 and MsaUXS4, and investigated their impact on ruminal digestibility. Both genes are more highly expressed in stems than leaves, and the enzymes have UDP-glucuronic acid decarboxylase activity in vitro. Silencing of MsaUXS2 and MsaUXS4 via RNAi altered plant growth and resulted in a 40% decrease in xylose, a 115% increase in arabinose, and a 60% increase in galacturonic acid in the polysaccharide matrix as well as a 20% decrease in lignin in the cell wall. Together, our results show a major role for UXS2 and UXS4 in xylan synthesis and secondary cell wall deposition in alfalfa. Additionally, in vitro rumen digestibility assays for the silenced lines had on average 30% increased gas production at 24 h, demonstrating the potential of targeting UXS genes to increase stem digestibility.

UDP-xylose synthase↗
DOE OSTI2025

Multi-angle Precession Electron Diffraction (MAPED): A Versatile Approach to 4D-STEM Precession

Precession of a converged beam during acquisition of a 4D-STEM dataset improves strain, orientation, and phase mapping accuracy by averaging over continuous angles of illumination. Precession experiments usually rely on integrated systems, where automatic alignments lead to fast, high-quality results. The dependence of these experiments on specific hardware and software is evident even when switching to nonintegrated detectors on a precession tool, as experimental set-up becomes challenging and time-consuming. Here, we introduce multi-angle precession electron diffraction (MAPED): a method to perform electron diffraction by collecting sequential 4D-STEM scans at different incident beam tilts. The multiple diffraction datasets are averaged together postacquisition, resulting in a single dataset that minimizes the impact of the curvature and orientation of the Ewald sphere relative to the crystal under study. Our results demonstrate that even four additional tilts improved measurement of material properties, namely strain and orientation, as compared to single-tilt 4D-STEM experiments. We show the versatility and flexibility of our MAPED approach with data collected on a number of microscopes with different hardware configurations and a variety of detectors.

4D-STEM↗
DOE OSTI2024

Experiments and Project-Based Enhancements for STEM Learning

Motivating K-12 students to pursue careers in science, technology, engineering, and mathematics (STEM) is an effort that requires consistent engagement. Throughout the K-12 student timeline, STEM educators need to continuously pivot their teaching and update their educational materials to motivate the next generation of students. Once students begin their undergraduate education, university professors need to encourage them to consider pursuing graduate studies to ensure that a qualified future workforce can be developed for research and teaching. In this paper, we present our work on developing STEM materials for K-12 student engagement. Our K-12 materials target the grid integration of hydrogen assets that are suitable to engage students in the classroom. Our undergraduate materials target hands-on projects and collaboration with industry to connect classroom learning with real-world applications and needs in renewable energy. Our work leverages available open-source models and tools to create projects for undergraduate students and motivate their interest in pursuing research topics in graduate-level education.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Real-Time Interactive 4D-STEM Phase-Contrast Imaging From Electron Event Representation Data: Less computation with the right representation

The arrival of direct electron detectors (DED) with high frame-rates in the field of scanning transmission electron microscopy has enabled many experimental techniques that require collection of a full diffraction pattern at each scan position, a field which is subsumed under the name four dimensional-scanning transmission electron microscopy (4D-STEM). DED frame rates approaching 100 kHz require data transmission rates and data storage capabilities that exceed commonly available computing infrastructure. Current commercial DEDs allow the user to make compromises in pixel bit depth, detector binning or windowing to reduce the per-frame file size and allow higher frame rates. This change in detector specifications requires decisions to be made before data acquisition that may reduce or lose information that could have been advantageous during data analysis. The 4D Camera, a DED with 87 kHz frame-rate developed at Lawrence Berkeley National Laboratory, reduces the raw data to a linear-index encoded electron event representation (EER). Here we show with experimental data from the 4D Camera that linear-index encoded EER and its direct use in 4D-STEM phase contrast imaging methods enables real-time, interactive phase-contrast from large-area 4D-STEM datasets. Furthermore, we detail the computational complexity advantages of the EER and the necessary computational steps to achieve real-time interactive ptychography and center-of-mass differential phase contrast using commonly available hardware accelerators.

4D-STEM↗
DOE OSTI2024

The stem cell-type transcriptome of bioenergy sorghum reveals the spatial regulation of secondary cell wall networks

Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about stem cell-type gene expression and regulation was available to enable engineering. To obtain this information, Laser Capture Microdissection (LCM) was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type.

cell specificity↗
NASA NTRS2018

Stem Cell-Based Regenerative Health in Microgravity

The research of Dr. Almeida's Lab at NASA Ames focuses on the effects of microgravity mechanical unloading on stem-cell-based tissue regeneration. The research focuses on testing the broad hypothesis that mechanical load from gravity at 1 g is required for normal adult stem cell proliferation and differentiation during tissue regeneration. Research from the lab has provides evidence supporting the hypothesis in various biological models, including newt tail regeneration, mouse bone and bone marrow in whole animals, and mouse embryonic stem cells all exposed to microgravity during spaceflight. Using these models, the lab has identified overexpression of the cell cycle inhibitor p21/CDKN1a as a candidate molecular mediator mechanism of bone marrow mesenchymal and hematopoietic lineage tissue regenerative arrest in microgravity. The labis currently focused on using p21/CDKN1a null mouse and cell culture approaches in microgravity to test the gravity tissue regeneration hypothesis.

stem cells microgravity regeneration↗
DOE OSTI2021

Increasing Diversity in Energy Efficiency Professions: JUMP into STEM

A long-term approach to achieving equity in the energy efficiency industry is to increase the overall diversity of the professionals who work in the field. Building science professionals have a direct impact on energy efficiency policy and programs, as many become leaders within the industry. Buildings are used every day by almost all members of U.S. society, so diversity in building science professionals is critical to better understanding the behaviors and needs of the full spectrum of building occupants. Many groups of people, including minorities and women, are underrepresented in the industry. The industry needs to attract a wide range of current college and university students to careers in building science, so that many perspectives are included in the clean energy transition. The JUMP into STEM student competition addresses this need by inspiring students from diverse backgrounds to use creative ideation to solve real-world building science problems. Student teams - comprising an interdisciplinary mix of majors and underrepresented groups in science, technology, engineering, and math (STEM) - respond to one of three buildings-related challenges. Diversity is encouraged through challenge design, competition guidelines, and evaluation criteria for the submission. Winners of the competition are awarded paid building science internships, a gateway to a career in this field. The competition has an advisory panel of diversity experts and a professor team that includes representation from minority-serving institutions. This paper presents the JUMP into STEM approach to fostering diversity and creative ideation on technical challenges and discusses outcomes from the 2019 and 2020 competitions.

buildings↗
DOE OSTI2021

Sub-Sampled Imaging for STEM: Maximising Image Speed, Resolution and Precision Through Reconstruction Parameter Refinement

Sub-sampling during image acquisition in scanning transmission electron microscopy (STEM) has been shown to provide a means to increase the overall speed of acquisition while at the same time providing an efficient means to control the dose, dose rate and dose overlap delivered to the sample. In this paper, we discuss specifically the parameters used to reconstruct sub-sampled images and highlight their effect on inpainting using the beta-process factor analysis (BPFA) methodology. The selection of the main control parameters can have a significant effect on the resolution, precision and sensitivity of the final inpainted images, and here we demonstrate a method by which these parameters can be optimised for any image in STEM. As part of this paper, we also provide a link to open source code and a tutorial on its use, whereby these parameters can be tested for any datasets. When coupled with the hardware necessary to rapidly sub-sample images in STEM, this approach can have significant implications for imaging beam sensitive materials and dynamic processes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Accessing Atomic-scale Phosphorus Dopant Distribution in Precise Silicon Devices by Advanced STEM Imaging and Spectroscopy

The structural and chemical characterization at the atomic-scale plays a critical role in understanding the structure-property relationship in precise electrical devices such as those produced by atomic-precision advanced manufacturing (APAM). APAM, utilizing hydrogen lithography in a scanning tunneling microscope, offers a potential pathway to ultra-efficient transistors, and has been developed to produce phosphorus (P)-based donor devices integrated into bare Si substrates. Structural characterization of the buried, Si with P dopant (Si:P) delta-layer in the devices by scanning transmission electron microscopy (STEM), however, is a challenge due to similar atomic number and low concentration of the P dopants. In this paper, we describe several efforts of utilizing advanced STEM imagining and spectroscopic techniques to quantify the Si:P deltalayers. STEM imaging combining low-angle and high-angle annular dark-field (LAADF, HAADF) detectors as well as atomic-scale elemental mapping using energy-dispersive X-ray spectroscopy (EDS) are used to reveal the P and defect distribution across the delta-layer processed under various thermal conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
DOE OSTI2021

Improving the Academic Climate of an R1 STEM Department: Quantified Positive Shifts in Perception

Ongoing efforts to improve diversity in science, technology, engineering, and mathematics (STEM) primarily manifest as attempts to recruit more women and individuals from historically marginalized groups. Yet, these efforts fail to repair the specific, systemic issues within academic communities that hinder diverse individuals from persisting and thriving in STEM. Here, we present the results of a quantitative, multiyear effort to make the academic climate of an R1 STEM department more inclusive. We use a student-led, department-specific, faculty-supported initiative to assess and improve the climate of the Department of Chemistry at the University of California, Berkeley, as a case study. Our results provide quantitative evidence that community discussions grounded in our own data, alongside cooperative community efforts to address the issues present in those data, are effective methods for driving positive change. Longitudinal assessment of our academic climate from 2018 to 2020 via annual department-wide surveys indicates that these interventions have succeeded in shifting the perception of our academic climate. This study confirms the positive outcomes of having a practical, sustainable, and data-driven framework for affecting change within a graduate community.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Theory and application of the vector pair correlation function for real-space crystallographic analysis of order/disorder correlations from STEM images

Deviations of local structure and chemistry from the average crystalline unit cell are increasingly recognized to have a significant influence on the properties of many technologically important materials. Here, we present the vector pair correlation function (vPCF) as a new real-space crystallographic analysis method, which can be applied to atomic-resolution scanning transmission electron microscopy (STEM) images to quantify and analyze structural order/disorder correlations. Our STEM-based vPCFs have several advantages over radial PCFs and/or 3D pair distribution functions from x-ray total scattering: vPCFs explicitly retain crystallographic orientation information, are spatially resolved, can be applied directly on a sublattice basis, and are suitable for any material that can be imaged with STEM. To show the utility of our approach, we measure partial vPCFs in Ba 5 SmSn 3 Nb 7 O 30 (BSSN), a tetragonal tungsten bronze (TTB) structured complex oxide. Many TTBs are known to be classical or relaxor ferroelectrics, and these properties have been correlated with the presence of superlattice ordering. BSSN, specifically, exhibits relaxor behavior and an incommensurate structural modulation. From the vPCF data, we observe that, of the cation sites, only the Ba (A2) sublattice is structurally modulated. We then infer the local modulation vector and reveal a marked anisotropy in its correlation length. Finally, short-range correlated polar displacements on the B2 cation sites are observed. This work introduces the vPCF as a powerful real-space crystallography technique, which enables direct, robust quantification of short-to-long range order on a sublattice-specific basis and is applicable to a wide range of complex material types.

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

Automating STEM Aberration Correction via Bayesian Optimization

Multipole aberration correctors have given scanning transmission electron microscopes (STEM) the ability to produce high-quality, atomic-resolution images, enabling STEM to be a key tool in material sciences for characterizing the structure and composition of materials. However, the process of correcting these aberrations typically requires human input and is accomplished using scanned STEM or Ronchigram images at different focii and beam tilts. In this work, we demonstrate an automated on-sample aberration correction system using Bayesian Optimization. We have developed a Python-based server able to communicate with the CEOS DCOR aberration corrector and the Thermo Fischer microscope scripting interface. This server allows us to change aberrations, acquire images and perform basic image analysis.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Mutation-driven RRE stem-loop II conformational change induces HIV-1 nuclear export dysfunction

Abstract The Rev response element (RRE) forms an oligomeric complex with the viral protein Rev to facilitate the nuclear export of intron-retaining viral RNAs during the late phase of HIV-1 (human immunodeficiency virus type 1) infection. However, the structures and mechanisms underlying this process remain largely unknown. Here, we determined the crystal structure of the HIV-1 RRE stem-loop II (SLII), revealing a unique three-way junction architecture in which the base stem (IIa) bifurcates into the stem-loops (IIb and IIc) to compose Rev binding sites. The crystal structures of various SLII mutants demonstrated that while some mutants retain the same “compact” fold as the wild type, other single-nucleotide mutants induce drastic conformational changes, forming an “extended” SLII structure. Through in vitro Rev binding assays and Rev activity measurements in HIV-1-infected cells using structure-guided SLII mutants designed to favor specific conformers, we showed that while the compact fold represents a functional SLII, the alternative extended conformation inhibits Rev binding and oligomerization and consequently stimulates HIV-1 RNA nuclear export dysfunction. The propensity of SLII to adopt multiple conformations as captured in crystal structures and their influence on Rev oligomerization illuminate emerging perspectives on RRE structural plasticity-based regulation of HIV-1 nuclear export and provide opportunities for developing anti-HIV drugs targeting specific RRE conformations.

Biochemistry & Molecular Biology↗
DOE OSTI2020

Divergences in hydraulic conductance and anatomical traits of stems and leaves in three temperate tree species coping with drought, N addition and their interactions

Drought and N addition have been shown to affect tree hydraulic traits, but few studies have been made on their interactions across species with different wood types or leaf forms. We examined the responses of hydraulic conductance and xylem anatomical traits of Quercus mongolica (ring-porous with simple-leaves), Fraxinus mandshurica (ring-porous with compound-leaves), and Tilia amurensis (diffuse-porous with simple-leaves) to drought, N addition and their interactions. Drought stress decreased current-year xylem-specific conductivity in stems (Ksx) and leaf hydraulic conductance (Kleaf), but N addition affected Ksx and Kleaf differently among species and watering regimes. These divergent effects were associated with different responses of anatomical traits and leaf forms. Higher mean vessel diameter in stems (Dstem) and lower vessel density in leaves (VDvein) were observed with N addition. The three-way interactive effects of drought, N addition and tree species were significant for most values of anatomical traits. These results were also reflected in large differences in vessel diameter and density among species with different wood types or leaf forms. The two-way interactive effects of drought and N addition were significant on Kleaf and predawn water potential (?pd), but not Ksx, indicating that leaves were more sensitive than stems to a combination of drought stress and N addition. Our results provide mechanistic insight into the variable responses of xylem water transport to the interactions of drought and N availability.

Hydraulic conductance, hydraulic architecture, N f↗
DOE OSTI2020

Towards oilcane: Engineering hyperaccumulation of triacylglycerol into sugarcane stems

Abstract Metabolic engineering to divert carbon flux from sucrose to oil in high biomass crop like sugarcane is an emerging strategy to boost lipid yields per hectare for biodiesel production. Sugarcane stems comprise more than 70% of the crops' biomass and can accumulate sucrose in excess of 20% of their extracted juice. The energy content of oils in the form of triacylglycerol (TAG) is more than twofold that of carbohydrates. Here, we report a step change in TAG accumulation in sugarcane stem tissues achieving an average of 4.3% of their dry weight (DW) in replicated greenhouse experiments by multigene engineering. The metabolic engineering included constitutive co‐expression of wrinkled1; diacylglycerol acyltransferase1‐2; cysteine‐oleosin; and ribonucleic acid interference‐suppression of sugar‐dependent1. The TAG content in leaf tissue was also elevated by more than 400‐fold compared to non‐engineered sugarcane to an average of 8.0% of the DW and the amount of total fatty acids reached about 13% of the DW. With increasing TAG accumulation an increase of 18:1 unsaturated fatty acids was observed at the expense of 16:0 and 18:0 saturated fatty acids. Total biomass accumulation, soluble lignin, Brix and juice content were significantly reduced in the TAG hyperaccumulating sugarcane lines. Overcoming this yield drag by engineering lipid accumulation into late stem development will be critical to exceed lipid yields of current oilseed crops.

09 BIOMASS FUELS↗
DOE OSTI2022

Egr1 is a 3D matrix–specific mediator of mechanosensitive stem cell lineage commitment

While extracellular matrix (ECM) mechanics strongly regulate stem cell commitment, the field’s mechanistic understanding of this phenomenon largely derives from simplified two-dimensional (2D) culture substrates. Here, we found a 3D matrix–specific mechanoresponsive mechanism for neural stem cell (NSC) differentiation. NSC lineage commitment in 3D is maximally stiffness sensitive in the range of 0.1 to 1.2 kPa, a narrower and more brain-mimetic range than we had previously identified in 2D (0.75 to 75 kPa). Transcriptomics revealed stiffness-dependent up-regulation of early growth response 1 (Egr1) in 3D but not in 2D. Egr1 knockdown enhanced neurogenesis in stiff ECMs by driving β-catenin nuclear localization and activity in 3D, but not in 2D. Mechanical modeling and experimental studies under osmotic pressure indicate that stiff 3D ECMs are likely to stimulate Egr1 via increases in confining stress during cell volumetric growth. To our knowledge, Egr1 represents the first 3D-specific stem cell mechanoregulatory factor.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Directed evolution of a stem-helix–targeting antibody enables MERS-CoV cross-neutralization through enhanced binding affinity

Broadly neutralizing antibodies (bnAbs) targeting conserved regions of the betacoronavirus spike are important for pan-betacoronavirus protection and pandemic preparedness. Here, we report the isolation of a human monoclonal antibody, CC65.1, from a SARS-CoV-2 convalescent donor that targets the conserved S2 stem helix region. CC65.1 neutralizes various sarbecoviruses, including SARS-CoV-2, and binds to the MERS-CoV spike but lacks MERS-CoV-neutralizing activity due to insufficient binding affinity. We utilized directed evolution to enhance the binding affinity of CC65.1 for the MERS-CoV S2 stem helix, yielding engineered antibody variants with newly acquired MERS-CoV-neutralizing activity. High-resolution structural analysis reveals key paratope mutations that enhance binding and stabilize epitope engagement. Our findings demonstrate the potential of in vitro affinity maturation to expand the neutralization breadth of stem-helix-targeting antibodies across divergent betacoronaviruses. This work supports the development of engineered bnAbs for broadly protective betacoronavirus countermeasures and provides a strategy for achieving cross-lineage neutralization.

Zhou, Panpan↗