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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Combined speckle- and propagation-based single shot two-dimensional phase retrieval method

Single-shot two-dimensional (2D) phase retrieval (PR) can recover the phase shift distribution within an object from a single 2D x-ray phase contrast image (XPCI). Two competing XPCI imaging modalities often used for single-shot 2D PR to recover material properties critical for predictive performance capabilities are: speckle-based (SP-XPCI) and propagation-based (PB-XPCI) XPCI imaging. However, PR from SP-XPCI and PB-XPCI images are, respectively, limited to reconstructing accurately slowly and rapidly varying features due to noise and differences in their contrast mechanisms. Herein, we consider a combined speckle- and propagation-based XPCI (SPB-XPCI) image by introducing a mask to generate a reference pattern and imaging in the near-to-holographic regime to induce intensity modulations in the image. We develop a single-shot 2D PR method for SPB-XPCI images of pure phase objects without imposing restrictions such as object support constraints. It is compared against PR methods inspired by those developed for SP-XPCI and PB-XPCI on simulated and experimental images of a thin glass shell before and during shockwave compression. Reconstructed phase maps show improvements in quantitative scores of root-mean-square error and structural similarity index measure using our proposed method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Climate Change Feedbacks from Interactions Between New and Old Carbon

Priming effects, or responses of SOM decomposition rates to inputs of new, labile carbon (C), have the potential to dramatically alter projections of ecosystem C storage. Priming effects occur in most ecosystems, are significant in magnitude, and are highly sensitive to global changes. Nevertheless, our mechanistic understanding of priming effects remains poor, and this has prevented the inclusion of these dynamics into current Earth system models (ESMs). We conducted two manipulative experiments in the field to quantify how priming effects influence SOM dynamics. Specifically, we asked: To what extent do inputs of “new” root-derived carbon (C) influence “older” C in SOM, and are the magnitude and direction of these effects sensitive to climate? We addressed these questions within the Boston-Area Climate Experiment - an old-field ecosystem that has been subjected to three precipitation treatments (ambient, -50%, and +50% of each precipitation event during the growing season) and four warming treatments (from ambient to +4°C) since 2008. In the first experiment, we installed root and fungal ingrowth cores into the plots. Each core was filled with SOM that had an isotopic signature (of its C compounds) that differed from the vegetation in the plots such that inputs of “new” C from roots/fungi could be quantified using the change in isotopic signatures of C in the cores. Further, we used cores with different mesh sizes to isolate root vs. mycorrhizal fungal inputs. We found that belowground C fluxes were dominated by root inputs (as opposed to mycorrhizal inputs), and that root-derived inputs were greatest in the plots subjected to experimental warming. Given that that the warming-induced increase in belowground C flux did not result in a net increase in soil C, we conclude that the warming treatment likely enhanced priming effects in these soils. In the second experiment, we experimentally dripped dissolved organic C compounds into soils in the BACE plots to simulate root-derived C fluxes. Specifically, we constructed artificial roots attached to an automated peristaltic pump to deliver the compounds to soil semi-continuously during the peak of the growing season. We found that changes in exudate quality had small but significant effects on microbial activities, often interacting with N availability and temperature-induced changes. These results further underscore the importance of priming effects, especially under warming conditions. Collectively, our results provide some of the first field-based estimates of how soil moisture and temperature can directly and indirectly alter root-induced changes in SOM dynamics. This exploratory project lays the groundwork for further research on priming that incorporates effects of plant species and microbial communities to global changes. Such information should enable the development of more mechanistic and better predictive models of SOM decomposition under increased greenhouse gas levels, with the ultimate goal of reducing the level of uncertainty in projections of future climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Using Systems Approaches to Improve Photosynthesis and Water Use Efficiency in Sorghum

Throughout the 5 years of this project, 8 labs coordinated to make significant progress on our understanding of how C4 grasses, which include some of our most important crops, can use water more efficiently. We took an integrated approach, using physiology to study how to improve photosynthesis, how to manipulate the pores that move water and CO2 in and out of leaves and the formation and structure of roots. We coupled that with genetic and computational approaches to identify the genes controlling these traits and then used modeling to understand how the genomic system integrates the functions of the genes. We then developed synthetic biology approaches to manipulate the genes and gene editing and plant transformation approaches to insert those traits into a model C4 grass and the bioenergy crop Sorghum bicolor. Through the course of the project, we developed new software tools and genetic resources, filed 5 patents and published 46 papers. We made significant contributions to the bioeconomy through the training of undergraduates, graduate students and postdoctoral researchers. In addition to addressing the specific objectives, our work on this project led to several new and exciting outcomes. We were also to use our expertise and efforts to contribute to many community efforts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Using discrete Bayesian networks for diagnosing and isolating cross-level faults in HVAC systems

Fault detection and diagnosis (FDD) technologies are critical to ensure satisfactory building performance, such as reducing energy wastes and negative impacts on occupant comfort and productivity. Existing FDD technologies mainly focus on component-level FDD solutions, which could lead to mis-diagnosis of cross-level faults in heating, ventilating, and air-conditioning (HVAC) systems. Cross-level faults are those faults that occur in one component or subsystem, but cause operational abnormalities in other components or subsystems, and result in a building level performance degradation. How to effectively diagnose the root cause of a cross-level fault is the focus of this study. Here, this paper presents a novel discrete Bayesian Network (DisBN)-based method for diagnosing cross-level faults in an HVAC system commonly used in commercial buildings. A two-level DisBN structure model is developed in this study. The parameters used in the DisBN model are obtained either from expert knowledge or through machine-learning strategies from normal system operation data. Meanwhile, the probability parameters are discretized to incorporate the uncertainties associated with typical expert knowledge. Thus, the developed DisBN method addresses the challenges many other BN based FDD methods face, i.e., the lack of fault data for BN parameter training. The developed DisBN represents causal relationships between a fault and its cross-level system impacts (i.e., fault symptoms or fault indicators) by considering how fault impacts propagate across different levels in an HVAC system. A weather and schedule information-based Pattern Matching (WPM) method is employed to automatically create WPM baseline data sets for each incoming real time snapshot data from the building systems. Consequently, BN inference and real-time diagnostics are achieved by comparing incoming snapshot data and the WPM baseline data set. The proposed method is evaluated using experimental fault data collected in a campus building. Fault diagnosis results demonstrate that the WPM-DisBN method is effective at locating the root causes of cross-level faults in an HVAC system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Vegetation Warming Experiment: 15N Uptake Experiment Arctagrostis latifolia Root Traits, Utqiagvik (Barrow), Alaska, 2018

This dataset consists of measured A. latifolia root traits (specific root length (SRL), mass, length, C and N content) from vegetation warming experiment enclosures and paired control plots located on the BEO, Utqiagvik, Alaska. Vegetation warming chambers (Zero Power) were deployed on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. These chambers (Figure 1) consistently elevated air temperatures by approximately 4°C using a self-venting system described by Lewin et al (2017). Five chambers were deployed from June 17, 2018 to September 24, 2018 on the BEO within a 1 km2 area centered on 71.275N, -156.641W. Each chamber was co-located with an ambient plot where temperatures were not manipulated on patches of tundra containing the target species Arctagrostis latifolia. An intensive field campaign in late July investigated the impact of warming had on A. latifolia biomass, chemistry, and uptake of 15N labeled ammonia that was injected into the surface soils for one week. Initial measurements were taken on July 21, 2018. Harvest occurred on July 27, 2018. Water-extractable nutrients in soils were measured in July following harvests of A. latifolia plants and underlying soils. Availability of ammonia, nitrate, and phosphate throughout the growing season was measured by extracting nutrients bound to anion and cation binding resins deployed from July through September. Environmental variables (thaw depth, surface soil temperatures, surface soil moisture) were measured. Leaf traits and root traits of A. latifolia were also measured. Files include one *.csv data file and one *.pdf user guide. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

SU-G-BRA-12: Development of An Intra-Fractional Motion Tracking and Dose Reconstruction System for Adaptive Stereotactic Body Radiation Therapy in High-Risk Prostate Cancer

Purpose: A clinical trial on stereotactic body radiation therapy (SBRT) for high-risk prostate cancer is undergoing at our institution. In addition to escalating dose to the prostate, we have increased dose to intra-prostatic lesions. Intra-fractional prostate motion deteriorates well planned radiation dose, especially for the small intra-prostatic lesions. To solve this problem, we have developed a motion tracking and 4D dose-reconstruction system to facilitate adaptive re-planning. Methods: Patients in the clinical trial were treated with VMAT using four arcs and 10 FFF beam. KV triggered x-ray projections were taken every 3 sec during delivery to acquire 2D projections of 3D anatomy at the direction orthogonal to the therapeutic beam. Each patient had three implanted prostate markers. Our developed system first determined 2D projection locations of these markers and then 3D prostate translation and rotation via 2D/3D registration of the markers. Using delivery log files, our GPU-based Monte Carlo tool (goMC) reconstructed dose corresponding to each triggered image. The calculated 4D dose distributions were further aggregated to yield the delivered dose. Results: We first tested each module in our system. MC dose engine were commissioned to our treatment planning system with dose difference of <0.5%. For motion tracking, 1789 kV projections from 7 patients were acquired. The 2D marker location error was <1 mm. For 3D motion tracking, root mean square (RMS) errors along LR, AP, and CC directions were 0.26mm, 0.36mm, and 0.01mm respectively in simulation studies and 1.99mm, 1.37mm, and 0.22mm in phantom studies. We also tested the entire system workflow. Our system was able to reconstruct delivered dose. Conclusion: We have developed a functional intra-fractional motion tracking and 4D dose re-construction system to support our clinical trial on adaptive high-risk prostate cancer SBRT. Comprehensive evaluations have shown the capability and accuracy of our system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Holography from lattice $\mathcal{N}$ = 4 super Yang-Mills

In this paper we use lattice simulation to study four dimensional $\mathcal{N}$ = 4 super Yang-Mills (SYM) theory. We have focused on the three color theory on lattices of size 12 4 and for ’t Hooft couplings up to λ = 40.0. Our lattice action is based on a discretization of the Marcus or GL twist of $\mathcal{N}$ = 4 SYM and retains one exact supersymmetry for non-zero lattice spacing. We show that lattice theory exists in a single non-Abelian Coulomb phase for all ’t Hooft couplings. Furthermore the static potential we obtain from correlators of Polyakov lines is in good agreement with that obtained from holography — specifically the potential has a Coulombic form with a coefficent that varies as the square root of the ’t Hooft coupling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Proteomics Coupled with Metabolite and Cell Wall Profiling Reveal Metabolic Processes of a Developing Rice Stem Internode

Internodes of grass stems function in mechanical support, transport, and, in some species, are a major sink organ for carbon in the form of cell wall polymers. This study reports cell wall composition, proteomic and metabolite analyses of the rice elongating internode. Along eight segments of the second rice internode (internode II) at booting stage, cellulose, lignin, and xylose increase as a percentage of cell wall material from the younger to the older internode segments, indicating active cell wall synthesis. Liquid-chromatography tandem mass spectrometry (LC-MS/MS) of trypsin-digested peptides of size-fractionated proteins extracted from this internode at booting reveals 2547proteins with at least two unique peptides. The dataset includes many glycosyltransferases, acyltransferases, glycosyl hydrolases, cell wall-localized proteins, and protein kinases that have or may have functions in cell wall biosynthesis or remodeling. Phospho-enrichment of the internode II peptides identified 21 unique phosphopeptides belonging to 20 phosphoproteins including an LRR-III family receptor like kinase. GO over-representation and KEGG pathway analyses highlight the abundances of internode proteins involved in biosynthetic processes, especially the synthesis of secondary metabolites such as phenylpropanoids and flavonoids. LC-MS of hot methanol-extracted secondary metabolites from internode II at four stages (elongation, early mature, mature and post mature) indicates that secondary metabolites in stems are distinct from those of roots and leaves, and differ during stem maturation. This work fills a void of knowledge of proteomics and metabolomics data for grass stems, specifically for rice, and provides baseline knowledge for more detailed studies of cell wall synthesis and other biological processes during internode development, toward improving grass agronomic properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

ACOUSTIC PRESSURE FIELDS GENERATED WITH A HIGH FREQUENCY ACOUSTIC LEVITATOR

Acoustic levitation is an advantageous particle positioning mechanism currently employed for applications of x-ray spectroscopy and micro-material manufacturing[1], [2]. By levitating a particle using only acoustic pressure waves, one eliminates the need for a container or other physical structure which may contaminate the specimen. Unfortunately, the pressure field generated by a standing acoustic wave is susceptible to periodic instabilities, and a particle that is levitated in this field tends to vibrate. The amplitude of the vibration is largest in the directions that are orthogonal to the axis in which the acoustic wave is generated. Therefore, by generating additional acoustic waves in each orthogonal axis, the vibration amplitude of the levitated particle is significantly reduced. The authors have shown this phenomenon to be true in a previous study[3]. In this paper, the authors explore the details of the pressure field that is generated with the device. A single degree-of freedom relationship is developed between the acoustic field pressure, the location of the levitated particle, and the mechanical vibration needed to produce levitation. In order to levitate a 100 micrometer diameter water droplet at 55 kilohertz, the calculations suggest that the transducer must achieve an average surface vibration amplitude of at least 6.43 micrometers. This mechanical vibration must produce a root means-squared pressure amplitude of 933 Pascal. Under these conditions, the particle will levitate approximately 0.4 millimeters below a zero pressure node. To validate the use of the single degree of freedom relationships and to explore the acoustic field for one, two, and three-axis levitation, the authors designed and prototyped an acoustic levitator capable of generating standing waves in three orthogonal directions. Using a simple electrical control circuit, the acoustic wave transducers of each axis can be turned on individually or simultaneously. An experiment was developed to measure the pressure of the acoustic field using a microphone. Preliminary pressure magnitude results were measured for one axis levitation along the center of the vertical axis of the levitator. The measurements suggest that the theoretical development provides a valid first approximation for the pressure magnitude and required mechanical vibration amplitude.

acoustic levitator↗
DOE OSTI2020

Mass production of high-performance single atomic FeNC electrocatalysts via sequenced ultrasonic atomization and pyrolysis process

Mass production of highly efficient, durable, and inexpensive single atomic catalysts is currently the major challenge associated with the oxygen reduction reaction (ORR) for fuel cells. In this study, we develop a general strategy that uses a simple ultrasonic atomization coupling with pyrolysis and calcination process to synthesize single atomic FeNC catalysts (FeNC SACs) at large scale. The microstructure characterizations confirm that the active centers root in the single atomic Fe sites chelating to the four-fold pyridinic N atoms. The identified specific Fe active sites with the variable valence states facilitate the transfer of electrons, endowing the FeNC SACs with excellent electrochemical ORR activity. The FeNC SACs were used as cathode catalysts in a homemade Zn-air battery, giving an open-circuit voltage (OCV) of 1.43 V, which is substantially higher than that of commercial Pt/C catalysts. This study provides a simple approach to the synthesis of single atomic catalysts at large scale.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Bottom-up responses to environmental and social impact assessments: A case study from Guatemala

In this article we take a closer look at resistance to the practice of Environmental Impact Assessment (EIA) in mining and energy projects in Guatemala. Collectivities resisting mining and hydropower projects in Guatemala are increasingly using the evaluations of EIAs conducted by international independent professionals. Reaching out to international experts is facilitated by local communities' engagements in transnational networks bringing together activists, NGOs, scientists, journalists and others. We argue that resistance movements resort to international professionals to challenge the limits imposed on them by the national legislation and institutional arrangements as well as by the way in which EIAs are performed in the country. Further, the engagements in networks that facilitate access to knowledge contribute to strengthen the legitimacy of communities' claims. Challenges to and complaints about EIAs are ways in which affected communities try to reclaim their right to participate in decision-making related to their local environment and the development of their communities. Both complaints about EIAs and the use of transnational networks to attain better participation in decision making processes at local levels, illustrated in this study for Guatemala, are common responses to the advancement of extractive industries and hydropower development across Latin America. The widespread of initiatives to challenge EIAs involving international experts in the region show that EIAs have become a sort of a transnational battleground. - Highlights: • Communities’ opposition to extractive projects is rooted in lack of participation in decision-making, including EIAs • Experts’ evaluations of approved EIAs confirm communities’ claims of poor practices in the public sector • Research presented here shows that local communities linked to transnational networks are able to scale up their demands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning

Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. Furthermore, these findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.

Adsorption↗
DOE OSTI2020

EXAFS investigation of the local structure in URu 2-x Fe x Si 2 : Evidence for distortions below 100 K

X-ray absorption measurements at the U L III , Ru K , and Fe K edges are reported for the hidden order (HO) material URu 2 - x Fe x Si 2 ( x = 0 , 0.05, 0.08, 0.10, 0.12, 0.15, and 0.20) as a function of x and temperature T . Furthermore, when Fe is substituted for Ru, the local structure about Fe shrinks slightly and the first neighbor Fe-Si bond length decreases by ≈ 0.05 Å . More importantly excess disorder is observed below 80–100 K (the coherence temperature T * ) in plots of the Debye-Waller factor σ 2 ( σ is the width of the pair distribution function); at low T the data deviate from the usual Einstein or correlated-Debye model plots. This excess disorder is most prominent for the Ru-Si bond, and σ 2 actually increases below 80 K. These results suggest a local orthorhombic distortion with B 1 g -like symmetry that develops below 80–100 K. A model that describes these local distortions is presented, and discussed in terms of other measurements that indicate a breaking of fourfold symmetry at low T . In addition, the square root of the difference between σ 2 ( T ) for the Ru-Si pair and a Debye fit to these data serves as an order parameter for this orthorhombic distortion, in the temperature range below 100 K. This quantity is a length related to a - b , the difference between the a and b lattice constants in the orthorhombic phase, and provides a connection between this distortion and T * . X-ray absorption near edge structure (XANES) measurements also show that there are no changes in the edge positions down to 0.1 eV for any edge as a function of x , for T in the HO regime.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

SO(3)-invariant PCA with application to molecular data

Principal component analysis (PCA) is a fundamental technique for dimensionality reduction and denoising; however, its application to three-dimensional data with arbitrary orientations -- common in structural biology -- presents significant challenges. A naive approach requires augmenting the dataset with many rotated copies of each sample, incurring prohibitive computational costs. In this paper, we extend PCA to 3D volumetric datasets with unknown orientations by developing an efficient and principled framework for SO(3)-invariant PCA that implicitly accounts for all rotations without explicit data augmentation. By exploiting underlying algebraic structure, we demonstrate that the computation involves only the square root of the total number of covariance entries, resulting in a substantial reduction in complexity. We validate the method on real-world molecular datasets, demonstrating its effectiveness and opening up new possibilities for large-scale, high-dimensional reconstruction problems.

Fraiman, Michael [Tel Aviv Univ., Tel Aviv (Israel↗
DOE OSTI2016

Multi-threaded Geant4 on the Xeon-Phi with complex high-energy physics geometry

To study the performance of multi-threaded Geant4 for high-energy physics experiments, an application has been developed which generalizes and extends previous work. Here, a highly-complex detector geometry is used for benchmarking on an Intel Xeon Phi coprocessor. Additonally, an implementation of parallel I/O based on Intel SCIF and ROOT technologies is incorporated and studied.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A stable 15-member bacterial SynCom promotes Brachypodium growth under drought stress

Introduction: Rhizosphere microbiomes are known to drive soil nutrient cycling and influence plant fitness during adverse environmental conditions. Field-derived robust Synthetic Communities (SynComs) of microbes mimicking the diversity of rhizosphere microbiomes can greatly advance a deeper understanding of such processes. However, assembling stable, genetically tractable, reproducible, and scalable SynComs remains challenging. Methods: Here, we present a systematic approach using a combination of network analysis and cultivation-guided methods to construct a 15-member SynCom from the rhizobiome of Brachypodium distachyon. This SynCom incorporates diverse strains from five bacterial phyla. Genomic analysis of the individual strains was performed to reveal encoded plant growth-promoting traits, including genes for the synthesis of osmoprotectants (trehalose and betaine) and Na+/K+ transporters, and some predicted traits were validated by laboratory phenotypic assays. Results: The SynCom demonstrates strong stability both in vitro and in planta. Most strains encoded multiple plant growth-promoting functions, and several of these were confirmed experimentally. The presence of osmoprotectant and ion transporter genes likely contributed to the observed resilience of Brachypodium to drought stress, where plants amended with the SynCom recovered better than those without. We further observed preferential colonization of SynCom strains around root tips under stress, likely due to active interactions between plant root metabolites and bacteria. Discussion: Our results demonstrate that trait-informed construction of synthetic communities can yield stable, functionally diverse consortia that enhance plant resilience under drought. Preferential colonization near root tips points to active, localized plant-microbe signaling as a component of stress-responsive recruitment. This stable SynCom provides a scalable platform for probing mechanisms of plant-microbe interaction and for developing microbiome-based strategies to improve soil and crop performance in variable environments.

Yadav, Archana↗
DOE OSTI2023

CRISPR/Cas9 mutants delineate roles of Populus FT and TFL1/CEN/BFT family members in growth, dormancy release and flowering

Abstract Vegetative and reproductive phase change and phenology are economically and ecologically important traits. Trees typically require several years of growth before flowering and, once mature, seasonal control of the transition to flowering and flower development is necessary to maintain vegetative meristems and for reproductive success. Members of two related gene subfamilies, FLOWERING LOCUST (FT) and TERMINAL FLOWER1 (TFL1)/CENTRORADIALIS (CEN)/BROTHER OF FT AND TFL1 (BFT), have antagonistic roles in flowering in diverse species and roles in vegetative phenology in trees, but many details of their functions in trees have yet to be resolved. Here, we used CRISPR/Cas9 to generate single and double mutants involving the five Populus FT and TFL1/CEN/BFT genes. The ft1 mutants exhibited wild-type-like phenotypes in long days and short days, but after chilling, to release dormancy, they showed delayed bud flush and GA3 could compensate for the ft1 mutation. After rooting and generating some phytomers in tissue culture, both cen1 and cen1ft1 mutants produced terminal as well as axillary flowers, indicating that the cen1 flowering phenotype is independent of FT1. The CEN1 showed distinct circannual expression patterns in vegetative and reproductive tissues and comparison with the expression patterns of FT1 and FT2 suggests that the relative levels of CEN1 compared with FT1 and FT2 regulate multiple phases of vegetative and reproductive seasonal development.

Forestry↗
DOE OSTI2026

Resolving root causes of experiment discrepancies guided by machine learning

Abstract Scientists rely on accurate experimental data to explain nature and then harness this knowledge for applications addressing human needs. However, discrepancies between experiments of the same observable can impede scientific progress if one does not understand the underlying causes. Here, we developed a process that unravels data discrepancies by first using Bayesian machine learning to relate discrepancies to few of many, potentially biasing metadata features that encode experiment procedures. This machine learning output guides human experts to study discrepancy causes by simulating suspicious aspects of historical experiments or designing modern ones to address open questions. The study findings then lead to rejecting or correcting historical data on firm scientific bases. This process is demonstrated for the energy spectrum of neutrons emitted promptly (<1 ns) after fission of 252 Cf, a trusted nuclear physics Standard. It reduces the spread in experimental 252 Cf spectra by up to a factor of 6.

Neudecker, D. (ORCID:0000000339200627)↗