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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Shared governance in the plant holobiont and implications for one health

Abstract The holobiont Holobiont theory is more than 80 years old, while the importance of microbial communities for plant holobionts was already identified by Lorenz Hiltner more than a century ago. Both concepts are strongly supported by results from the new field of microbiome research. Here, we present ecological and genetic features of the plant holobiont that underpin principles of a shared governance between hosts and microbes and summarize the relevance of plant holobionts in the context of global change. Moreover, we uncover knowledge gaps that arise when integrating plant holobionts in the broader perspective of the holobiome as well as one and planetary health concepts. Action is needed to consider interacting holobionts at the holobiome scale, for prediction and control of microbiome function to improve human and environmental health outcomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Differentially Private Synthesis and Sharing of Network Data Via Bayesian Exponential Random Graph Models

Abstract Network data often contain sensitive relational information. One approach to protecting sensitive information while offering flexibility for network analysis is to share synthesized networks based on the information in originally observed networks. We employ differential privacy (DP) and exponential random graph models (ERGMs) and propose the DP-ERGM method to synthesize network data. We apply DP-ERGM to two real-world networks. We then compare the utility of synthesized networks generated by DP-ERGM, the DyadWise Randomized Response (DWRR) approach, and the Synthesis through Conditional distribution of Edge given nodal Attribute (SCEA) approach. In general, the results suggest that DP-ERGM preserves the original information significantly better than two other approaches in network structural statistics and inference for ERGMs and latent space models. Furthermore, DP-ERGM satisfies node DP through modeling the global network structure with ERGM, a stronger notion of privacy than the edge DP under which DWRR and SCEA operate.

graph synthesis↗
DOE OSTI2025

BioPortal: an open community resource for sharing, searching, and utilizing biomedical ontologies

Abstract BioPortal (https://bioportal.bioontology.org) is the world’s most comprehensive repository of biomedical ontologies. It provides infrastructure for finding, sharing, searching, and utilizing biomedical ontologies. Launched in 2005, BioPortal now includes 1549 ontologies (1182 of them public). Its open, freely accessible website enables anyone (i) to browse the ontology library, (ii) to search for terms across ontologies, (iii) to browse mappings between terms, (iv) to see popularity ratings and recommendations on which ontologies are most relevant to their use cases, (v) to annotate text with ontology terms, (vi) to submit an ontology, and (vii) to request ontology changes. The library of ontologies can be accessed programmatically via a REST application programming interface (API). Recent enhancements include a BioPortal knowledge graph that integrates knowledge from multiple ontologies; a unified data model for interoperability with other knowledge sources; ontology popularity ratings and recommendations for relevant ontologies; and the ability to request ontology changes via a simple user interface that automatically converts user change requests to GitHub Pull Requests that specify the edits that will be made to the ontology upon approval.

Vendetti, Jennifer↗
DOE OSTI2024

Phylometagenomics of cycad coralloid roots reveals shared symbiotic signals

Cycads are known to host symbiotic cyanobacteria, includingNostocalesspecies, as well as other sympatric bacterial taxa within their specialized coralloid roots. Yet, it is unknown if these bacteria share a phylogenetic origin and/or common genomic functions that allow them to engage in facultative symbiosis with cycad roots. To address this, we obtained metagenomic sequences from 39 coralloid roots sampled from diverse cycad species and origins in Australia and Mexico. Culture-independent shotgun metagenomic sequencing was used to validate sub-community co-cultures as an efficient approach for functional and taxonomic analysis. Our metanalysis shows a host-independent microbiome core consisting of seven bacterial orders with high species diversity within the identified taxa. Moreover, we recovered 43 cyanobacterial metagenome-assembled genomes, and in addition toNostocspp., symbiotic cyanobacteria of the genusAulosirawere identified for the first time. Using this robust dataset, we used phylometagenomic analysis to reveal three monophyletic cyanobiont clades, two host-generalist and one cycad-specific that includesAulosiraspp. Although the symbiotic clades have independently arisen, they are enriched in certain functional genes, such as those related to secondary metabolism. Furthermore, the taxonomic composition of associated sympatric bacterial taxa remained constant. Our research quadruples the number of cycad cyanobiont genomes and provides a robust framework to decipher cyanobacterial symbioses, with the potential of improving our understanding of symbiotic communities. This study lays a solid foundation to harness cyanobionts for agriculture and bioprospection, and assist in conservation of critically endangered cycads.

Genetics & Heredity↗
DOE OSTI2026

Canted antiferromagnetism and spin reorientation in corner-shared single chain quasi-one-dimensional Ba 2 ⁢FeSe 3

Here, we report the canted antiferromagnetic (AFM) structure together with a spin reorientation in a single chain quasi-one-dimensional (Q-1D) iron chalcogenide Ba 2⁢ FeSe 3 . Ba 2 ⁢FeSe 3 crystallizes in Pnma (No. 62) orthorhombic structure with linear single iron chains consisting of corner-shared distorted FeSe 4 tetrahedra along the 𝑏 axis. Ba 2 ⁢FeSe 3 is a narrow-gap semiconductor and orders AFM below 60 K. Modeling of neutron powder diffraction data reveals a canted AFM ground state of magnetic space group 𝑃⁢𝑎⁢21/𝑐 (BNS No. 14.80) with commensurate propagation vector 𝐤 =(0, $\frac{1}{2}$, 0), where the Fe ion spins are AFM aligned with up-down-up-down (↑−↓−↑−↓) sequence along the Q-1D chain direction of the 𝑏 axis. In the magnetically ordered state, the canting of magnetic moments reorients from the 𝑎⁢𝑐 plane to the 𝑎⁢𝑏 plane below 30 K, with a 10° tilting angle toward the 𝑎 axis, and the magnetic moment does not induce a net moment in either orientation. The density functional theory results indicate that an ↑−↓−↑−↓ AFM state is stabilized along the chain direction. In this work, we elucidate the unique canted AFM of the iron chalcogenide and pave the way for searching exotic physics in Q-1D Ba 2⁢ FeSe 3 .

Gao, Fei [Univ. of Texas at Dallas, Richardson, TX↗
DOE OSTI2021

Symmetry analysis of tensors in the honeycomb lattice of edge-sharing octahedra

In this work, we obtain the most general forms of rank-2 and rank-3 tensors allowed by the crystal symmetries of the honeycomb lattice of edge-sharing octahedra for crystals belonging to different crystallographic point groups, including the monoclinic point group 2/$\textit{m}$ and the trigonal (or rhombohedral) point group $\bar{3}$. Our results are relevant for two-dimensional materials, such as α-RuCl 3 , CrI 3 , and the honeycomb iridates. We focus on the magnetic-field-dependent thermal conductivity tensor $κ_{ij}$ (H), which describes a system’s longitudinal and thermal Hall responses, for the cases when the magnetic field is applied along high-symmetry directions, perpendicular to the plane and in the plane. We highlight some unexpected results, such as the equality of fully longitudinal components to partially transverse components in rank-3 tensors for

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Fission-fragment excitation energy sharing beyond scission

A simplified, though realistic, model describing two receding and accelerating fission fragments, due to their mutual Coulomb repulsion, shows that fission fragments share excitation energy well after they ceased to exchange nucleons. Here, this mechanism leads to a lower total kinetic energy of the fission fragments, particularly if the pygmy resonances in the fission fragments are excited. Even though the emphasis here is on fission, similar arguments apply to fragments in heavy-ion reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Evaluating Impacts of Sustainable Aviation Fuel Production with CO2-to-Fuels Technologies on High Renewable Share Power Grid

This paper investigates the impact of Sustainable Aviation Fuel (SAF) production using CO 2 -to-Fuels technologies on a future power grid with a high share of renewable energy. We focus on understanding the implications of the 2050 SAF production goal on the U.S. power system's long-term planning, encompassing generation, transmission, and cost analysis. Via the Regional Energy Deployment System (ReEDS) model, we developed a detailed SAF electricity demand model based on a low-temperature electrolysis-syngas fermentation-ethanol pathway. Four SAF target scenarios which aim to meet 10%, 15%, 20%, and 27% of SAF demand by 2050. These scenarios are exhaustively simulated to assess their impact on the power grid. Our results reveal that increasing SAF demand will result in higher electricity requirements, as well as expanded generator and transmission capacities, leading to an overall rise in system costs. However, these impacts are manageable within the broader context of U.S. capacity expansion plans. This study provides valuable insights into incorporating the CO 2 -to-Fuels electricity demand model and other carbon capture technologies into power system planning, emphasizing their significance in shaping a sustainable energy future.

capacity expansion model↗
DOE OSTI2024

Utility-Scale Shared Energy Storage Deployment: Challenges, Research Gaps, and Opportunities

Although community energy storage (CES) and behind-the-meter (BTM) energy storage systems have been widely used to offer homeowners and communities a variety of localized benefits, their scalability and grid support functionalities are limited. On the other hand, utility-scale shared energy storage (USES) systems may offer a number of benefits for grid integration, scalability, and economic viability. When compared to BTM and CES alternatives, these large-scale systems provide more storage capacity, more efficient operations, and more economically viable options. The deployment of USES presents opportunities for optimizing grid performance, integrating renewable energy resources, and improving energy security at the community level. However, significant research gaps exist in optimizing the integration and operation of these systems, especially to allocate energy for consumer use, grid services, and enhancing energy resilience. This paper reviews the literature in this regard, focusing on the opportunities, research gaps, and challenges associated with USES deployment. Firstly, the paper provides an overview of USES systems and emphasizes their benefits. Secondly, the key challenges are identified, and research gaps associated with the operation and integration of these systems are highlighted. Lastly, some potential solutions and opportunities that can be adopted to facilitate the rapid deployment and management of USES are presented. Technological, economic, regulatory, and environmental aspects are also discussed in this paper, providing an overview of the current state and future prospects of this technology.

Gautam, Mukesh [BATTELLE (PACIFIC NW LAB)] (ORCID:↗
DOE OSTI2025

Day-Ahead Forecasting with Federated LSTM to Plan Energy Sharing in a Community Microgrid

Energy balancing in microgrids is a key enabler of resilience. Community microgrids located close to each other have the added benefit of networking and sharing surplus energy, if available. Such complex decision-making runs on optimization that requires reliable short-term (up to very-short-term) forecasts of energy generation and consumption for scheduling or trading. Each microgrid may also opt to not expose their sensitive data such as consumption patterns of individual businesses or residences. This paper investigates a federated approach to dayahead forecasting that trains naive long short-term memory (LSTM) at each business in a microgrid and aggregates weights at the microgrid controller using proximal regularization. This approach ensures that the controller has access only to energy surplus/deficit and not the actual generation or consumption values, avoiding unwanted exposure of sensitive data. A community microgrid in Adjuntas, Puerto Rico with 3 businesses is selected as a case study with a laboratory-scale computing setup. A central LSTM forecaster, where sensitive data from businesses are aggregated at the controller, is implemented as a baseline for qualifying the results. This work serves as a proof-of-concept for scaling the approach to networked and nested microgrids with more complex control options.

Sundararajan, Aditya [ORNL] (ORCID:000000033577854↗
DOE OSTI2023

Dynamics of Current-Sharing Within a REBCO Tape-Stack Cable

Current redistribution in a non-insulating REBCO tape-stack cable may enable the use of such a cable in a high field dipole without provision for transposition of the constituent tapes. As current is increased in the REBCO cable a dynamic resistance arises in the superconducting layer near operation at critical current. The critical current of each tape in the stack is determined by the local magnetic field variation within the cable. The superconducting-normal transition in REBCO occurs over a working range of current and, within that range, the longitudinal Ohmic electric field produces a transverse electric field between adjacent tapes with different critical currents. Circuit models indicate that, as a given tape approaches critical operation, current will naturally redistribute to neighboring tapes with higher current carrying capacity due to the dynamic rise in resistivity thus preventing premature quench. Here, a multi-scale model is being developed to study the dynamics of current-sharing, the limits of stability, and the impact of fluctuations in critical-current density along each tape.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Sequential multidimensional heteroepitaxy of chalcogen-sharing 3D ZnSe and 2D MoSe 2 with quasi van der Waals interface engineering

Two-dimensional (2D) materials are emerging as a promising platform for epitaxial growth, largely free from the constraints of lattice constant and thermal expansion coefficient mismatches. Among them, transition metal dichalcogenides (TMDs), known for their superior electrical properties, are ideal for ultrathin semiconductor applications. Their unique epitaxial characteristics enable seamless integration with 3D materials, facilitating the development of gate stacks and heterojunction devices. In this regard, developing a process for growing high-quality 3D epitaxial materials before and after the growth of 2D TMDs and understanding the 2D/3D interface are crucial. This study demonstrates the sequential growth of fully epitaxial ZnSe/MoSe 2 /ZnSe heterostructures using metal-organic chemical vapor deposition. ZnSe and MoSe 2 , sharing chalcogen elements, enable large-area quasi van der Waals epitaxy with sharp interfaces without intermediate phase. Multiscale analysis involving transmission electron microscopy and density functional theory calculation reveals lattice commensurability, van der Waals gaps, termination, and interfacial reconstruction. Understanding these interactions is crucial for advancing multidimensional integration of 2D and 3D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

RAP: Resource-aware Automated GPU Sharing for Multi-GPU Recommendation Model Training and Input Preprocessing

Ensuring high-quality recommendations for newly onboarded users requires the continuous retraining of Deep Learning Recommendation Models (DLRMs) with freshly generated data. To serve the online DLRM retraining, existing solutions use hundreds of CPU computing nodes designated for input preprocessing, causing significant power consumption that surpasses even the power usage of GPU trainers. To this end, we propose RAP, an end-to-end DLRM training framework that supports Resource-aware Automated GPU sharing for DLRM input Preprocessing and Training. The core idea of RAP is to accurately capture the remaining GPU computing resources during DLRM training for input preprocessing, achieving superior training efficiency without requiring additional resources. Specifically, RAP utilizes a co-running cost model to efficiently assess the costs of various input preprocessing operations, and it implements a resource-aware horizontal fusion technique that adaptively merges smaller kernels according to GPU availability, circumventing any interference with DLRM training. In addition, RAP leverages a heuristic searching algorithm that jointly optimizes both the input preprocessing graph mapping and the co-running schedule to maximize the end-to-end DLRM training throughput. The comprehensive evaluation shows that RAP achieves 78.3× speedup on average over CPU-based DLRM input preprocessing frameworks. In addition, the end-to-end training throughput of RAP is only 2.04% lower than the ideal case, which has no input preprocessing overhead.

Wang, Zheng↗
DOE OSTI2023

Elephants Sharing the Highway: Studying TCP Fairness in Large Transfers over High Throughput Links

Escalating bandwidth demand strains high-performance data networks, posing potential performance risks. TCP congestion control algorithms enhance reliability and optimize bandwidth usage. Network performance is influenced by factors such as AQM algorithms and router buffer size. In the context of constrained network resources, understanding how TCP flows share networks and the resulting performance impact is essential. This paper introduces insights into TCP fairness and performance involving a comparison of TCP CUBIC, Reno, Hamilton, and BBR versions 1 and 2 across real-world networks supporting high bandwidths of up to 25 Gbps. The research explores TCP behaviors with AQM algorithms like FIFO, FQ_CODEL, and RED, alongside diverse buffer sizes. Notably, findings reveal that manipulating buffers and queuing methods yields contrasting outcomes based on bandwidth. BBRv2 emerges as a superior fair algorithm, pivotal for swift transfers, particularly in scientific data scenarios. These results provide crucial guidance for future network design, ensuring equitable performance optimization.

Kiran, Mariam↗
DOE OSTI2025

Minimizing CGYRO HPC Communication Costs in Ensembles with XGYRO by Sharing the Collisional Constant Tensor Structure

First-principles fusion plasma simulations are both compute and memory intensive, and CGYRO is no exception. The use of many HPC nodes to fit the problem in the available memory thus results in significant communication overhead, which is hard to avoid for any single simulation. That said, most fusion studies are composed of ensembles of simulations, so we developed a new tool, named XGYRO, that executes a whole ensemble of CGYRO simulations as a single HPC job. By treating the ensemble as a unit, XGYRO can alter the global buffer distribution logic and apply optimizations that are not feasible on any single simulation, but only on the ensemble as a whole. The main saving comes from the sharing of the collisional constant tensor structure, since its values are typically identical between parameter-sweep simulations. This data structure dominates the memory consumption of CGYRO simulations, so distributing it among the whole ensemble results in drastic memory savings for each simulation, which in turn results in overall lower communication overhead.

CGYRO↗
DOE OSTI2025

Revenue-Maximizing Shared Parking and Electric Vehicle Charging Management in Multi-Unit Dwellings

In urban areas, searching for parking and electric vehicle (EV) charging can result in cruising, congestion, and environmental externalities. Recognizing the business opportunity of offering private parking and charging infrastructure access within multi-unit dwellings (MUDs) during daytime, we model a shared parking and EV charging management system. We maximize the revenue of MUD charging hubs in mixed land use, catering to public demand. Our approach accounts for the objectives of the two stakeholders involved: a demand model is fitted on the choices of EV charging users, and the supply model optimizes the allocation of parking and charging requests in an MUD parking lot. A binary integer linear programming model for the allocation of parking and charging spaces with a rolling horizon is integrated with matching rules that handle both parking and charging requests. In our numerical experiments in a neighborhood of Chicago, Illinois, we estimate the performance of the MUD parking and charging system with metrics that include revenue, number of matchings, and utilization rates. At any given time, MUDs with lower prices attract more charging requests, particularly those of longer duration, resulting in higher revenue and greater charging utilization. Dynamic pricing facilitates a more equitable distribution of requests; as MUD parking lots reach capacity and their fees increase, other MUDs become more competitive, attracting additional requests. Comparing our method against first-come-first-served and optimal-solution benchmarks, we demonstrate our model’s effectiveness in dynamically managing mixed parking and charging demand in MUD charging hubs.

electric vehicle, multi-unit dwelling, charging in↗
DOE OSTI2026

Substitution or Shared Utilization? Intrahousehold Vehicle Use in Mixed-Powertrain Households

While previous research has focused heavily on understanding the factors deriving alternative fuel vehicle adoption rates, there remains a significant gap in understanding how households distribute mileage across different powertrains. This study utilizes data from the 2022 Next Generation National Household Travel Survey to investigate vehicle miles traveled within a sample of 150 plug-in electric vehicle (PEV)-owning households (in which at least one battery electric vehicle is present), characterizing how different powertrains are integrated into daily mobility. Leveraging a Seemingly Unrelated Regression (SUR) framework the study jointly models the utilization of PEVs, hybrid electric vehicles (HEV), and internal combustion engine vehicles (ICEVs) while accounting for household-level substitution effects. The results provide evidence of an asymmetric substitution effect. In households with mixed-powertrain configurations, the ICEV captures a substantially higher share of household miles (compared with the PEV), acting as a utility sponge. Conversely, the model identifies specific socioeconomic and geographic cohorts that prioritize PEV as the primary household workhorse, indicating a systematic sorting effect. Although the sample size limits broader generalizability, these findings suggest that PEVs are used for frequent, specific routine-intensive roles, whereas the ICEV remains a specialized utility vehicle. These insights highlight distinct intrahousehold vehicle use behaviors that are often obscured by aggregate fleetwide statistics.

25 ENERGY STORAGE↗