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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A FAIR-compliant parts catalogue for genome engineering and expression control in Saccharomyces cerevisiae

The synthetic biology toolkit for baker's yeast, Saccharomyces cerevisiae, includes extensive genome engineering toolkits and parts repositories. However, with the increasing complexity of engineering tasks and versatile applications of this model eukaryote, there is a continued interest to expand and diversify the rational engineering capabilities in this chassis by FAIR (findable, accessible, interoperable, and reproducible) compliance. In this study, we designed and characterised 41 synthetic guide RNA sequences to expand the CRISPR-based genome engineering capabilities for easy and efficient replacement of genomically encoded elements. Moreover, we characterize in high temporal resolution 20 native promoters and 18 terminators using fluorescein and LUDOX CL-X as references for GFP expression and OD600 measurements, respectively. Additionally, all data and reported analysis is provided in a publicly accessible jupyter notebook providing a tool for researchers with low-coding skills to further explore the generated data as well as a template for researchers to write their own scripts. We expect the data, parts, and databases associated with this study to support a FAIR-compliant resource for further advancing the engineering of yeasts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Compositional and temporal division of labor modulates mixed sugar fermentation by an engineered yeast consortium

Abstract Synthetic microbial communities have emerged as an attractive route for chemical bioprocessing. They are argued to be superior to single strains through microbial division of labor (DOL), but the exact mechanism by which DOL confers advantages remains unclear. Here, we utilize a synthetic Saccharomyces cerevisiae consortium along with mathematical modeling to achieve tunable mixed sugar fermentation to overcome the limitations of single-strain fermentation. The consortium involves two strains with each specializing in glucose or xylose utilization for ethanol production. By controlling initial community composition, DOL allows fine tuning of fermentation dynamics and product generation. By altering inoculation delay, DOL provides additional programmability to parallelly regulate fermentation characteristics and product yield. Mathematical models capture observed experimental findings and further offer guidance for subsequent fermentation optimization. This study demonstrates the functional potential of DOL in bioprocessing and provides insight into the rational design of engineered ecosystems for various applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Subseasonal Tropical Cyclone Prediction and Modulations by MJO and ENSO in CESM2

Subseasonal tropical cyclone (TC) reforecasts from the Community Earth System Model version 2 (CAM6) subseasonal prediction system are examined in this study. Here, we evaluate the modeled TC climatology and the probabilistic forecast skill of basin-wide TC genesis at weekly temporal resolution. Prediction skill is calculated using the Brier skill score relative to a constant annual mean climatology and to a monthly varying seasonal climatology during TC season. The model captures the observed basin-wide climatological TC seasonality and spatial distributions at weeks 1–6, but TC genesis is largely underestimated from Week 2 onward. For some basins and lead times, the predicted TC genesis is primarily controlled by the number of TC “seeds” and the mean-state climate condition. The model has good prediction skill relative to the constant climatology across all the basins and lead times, but is only skillful in the eastern Pacific, North Indian Ocean, and Southern Hemisphere at Week 1 when compared to the seasonal climatology, indicating limited skill in predicting deviations from the seasonal cycle. We find strong modulations of the predicted TC genesis at up to 3 weeks of forecast lead time by the Madden-Julian Oscillation. The interannual variability of predicted TC genesis and accumulated cyclone energy are skillfully predicted in the North Atlantic and the Northwestern Pacific, with a strong modulation by the El Nino-Southern Oscillation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Capturing O2 Desorption Through Isoconversional Kinetics for CFD Application

The present work examines desorption mechanisms and kinetics of the calcium-doped strontium perovskite at 25% calcium content (i.e., Sr_0.75 Ca_0.25 FeO_(3-δ)). Laboratory-scale, low inventory, fixed bed redox cycle experiments were developed and conducted in both dry and steam-based environments for three isothermal temperatures, 450, 500 and 550C. The temporal evolution of the conversion extent of the material sample over the redox cycles were obtained through the analysis of the gaseous products of the redox reactions. Using subsequently isoconversional differential methods, it was found that the activation energy exhibits a strong dependence on the extent of conversion during the desorption of this perovskite. In addition, the reconstruction of the reaction model showed that the desorption kinetics are controlled by a three-step mechanism. A successful a priori verification of the isoconversional desorption kinetics against the dry and steam-based environment desorption experimental data are shown.

Konan, Ndri A.↗
DOE OSTI2025

Greenhouse gas flux response in biochar- and compost-amended urban soils under simulated soil hydrologic dynamics

Understanding greenhouse gas emission dynamics in lawn soils is essential for improving climate change mitigation strategies in urban and suburban environments. This project measured fluxes of carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) fluxes from turfgrass soil columns amended with biochar, compost, biochar-compost blend, control (no amendment) in a controlled greenhouse mesocosm experiment. This project simulated contrasting water saturation regimes consisting of normal irrigation with sprinkler, transient half or full saturation by water table manipulation, and subsequent drying phase under both sod or seeded grass conditions. Compost-amended columns (compost or biochar-compost blend) exhibited higher average CO 2 fluxes (6 µmol m-2 s-1) compared to biochar or control columns (4.5 – 5.0 µmol m-2 s-1) across all saturation levels under sod conditions. Seeded grass conditions generally resulted in less CO 2 emissions. The CO 2 fluxes were positively correlated with air temperature and negatively correlated with soil moisture. Biochar-amended columns retained high soil moisture (~95 %) throughout experiments, demonstrating superior moisture retention compared to compost. CH 4 and N 2 O fluxes exhibited temporal increases (5-8 nmol m-2 s-1) during saturation and drainage phases, indicating their sensitivity to hydrologic conditions. These findings suggest that temperature and amendment types are primary driver of CO 2 emissions, while CH 4 and N 2 O fluxes are more responsive to water saturation dynamics in lawn soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Large spatiotemporal variability in aerosol properties over central Argentina during the CACTI field campaign

Abstract. Few field campaigns with extensive aerosol measurements have been conducted over continental areas in the Southern Hemisphere. To address this data gap and better understand the interactions of convective clouds and the surrounding environment, extensive in situ and remote sensing measurements were collected during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign conducted between October 2018 and April 2019 over the Sierras de Córdoba range of central Argentina. This study describes measurements of aerosol number, size, composition, mixing state, and cloud condensation nuclei (CCN) collected on the ground and from a research aircraft during 7 weeks of the campaign. Large spatial and multiday variations in aerosol number, size, composition, and CCN were observed due to transport from upwind sources controlled by mesoscale to synoptic-scale meteorological conditions. Large vertical wind shears, back trajectories, single-particle measurements, and chemical transport model predictions indicate that different types of emissions and source regions, including biogenic emissions and biomass burning from the Amazon and anthropogenic emissions from Chile and eastern Argentina, contribute to aerosols observed during CACTI. Repeated aircraft measurements near the boundary layer top reveal strong spatial and temporal variations in CCN and demonstrate that understanding the complex co-variability of aerosol properties and clouds is critical to quantify the impact of aerosol–cloud interactions. In addition to quantifying aerosol properties in this data-sparse region, these measurements will be valuable to evaluate predictions over the midlatitudes of South America and improve parameterized aerosol processes in local, regional, and global models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Temporal contrast degradation from mid-spatial-frequency surface error on stretcher mirrors

Temporal contrast degradation due to mid-spatial-frequency error in chirped-pulse amplification stretcher optics is studied. Third-order cross-correlation measurements reveal a temporal peak that appears when using two different mirrors processed by magnetorheological finishing, despite an improvement in rms roughness compared to a third unprocessed mirror. Simulations based on measured power spectral density show how the actual impact on contrast is different from measurements using a typical bandwidth-limited third-order cross correlator. Furthermore, strategies are proposed to avoid this type of contrast degradation while exploiting computer numerically controlled polishing techniques for enhancement of surface figure and roughness.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Metaoptics Enabled Multifunctional Imaging

Despite the fact that most microorganisms occupy two- and three-dimensional space in heterogeneous arrangements and in proximity to other microorganisms of different species, much of our current knowledge about their metabolic processes is derived from homogenizing, then analyzing, the chemical content of cultures containing a single microbial species. This project addressed this fundamental dichotomy by developing a set of optical imaging principles combining multiple new technologies. The imaging strategies developed in this project combine metaoptics structures with active in situ nanoscale control of the chemical environment and applied them to a microbial system, Myxococcus xanthus, with particular relevance to the DoE mission. The combination of metaoptical architectures and nanoscale control over the molecular environment enables: (a) precise control over the electromagnetic (EM) field at length scales smaller than the wavelength of light; (b) control of the interaction of the EM field with critical molecular systems in DOE relevant microbes; (c) control over the chemical environment – especially the presence and quantity of reactive oxygen species (ROS) that can affect redox homeostasis; and (d) the ability to ask new kinds of questions not accessible to ‘omics’ approaches or standard methods of biological imaging. These capabilities are applicable to detailed studies of metabolic pathways in microbes and to lignocellulosic biomass deconstruction. To accomplish these objectives, we pursued two over-arching technical goals: (1) the development of new metaoptics-enabled approaches to imaging and spectroscopic characterization; and (2) the development of tools to control the chemical environment of a microbial sample with nanometer-scale precision. Goal 1 was addressed through the design, fabrication, and characterization of new metasurfaces capable of super-resolution imaging through extreme confinement of the optical field. Goal 2 was addressed by controlling the redox potential on the nanoscale in microbial communities and characterizing their effect on intrinsic bacterial fluorophores which act as molecular sentinels and through characterization of soluble factors secreted by Myxococcus xanthus by confocal Raman imaging. The optical imaging/sensing approaches developed here make it possible to use these powerful new imaging and sensing modalities in metabolic studies by making it possible to visualize and track the spatial and temporal expression patterns of natural or engineered pathways in microorganisms.

09 BIOMASS FUELS↗
DOE OSTI2026

An Integrated Framework for Memory-Centric Analysis: From Trace Collection to Co-Design

The memory wall phenomenon—where advances in processor performance significantly outpace those in memory subsystems—poses a fundamental challenge for contemporary computing systems. In memory-bound applications, memory subsystem behavior dominates performance, yet existing analysis approaches present significant limitations: detailed microarchitectural simulators require days to weeks to simulate modest workloads; hardware performance counters provide only aggregate statistics that obscure temporal and spatial access patterns; and scaled simulation approaches face challenges in capturing certain behaviors that emerge at larger scales. These limitations reflect a processor-centric design philosophy increasingly misaligned with memory-bound workloads where detailed understanding of memory access patterns, cache hierarchy interactions, and contention is critical for effective optimization. This paper presents an integrated framework for memory-centric analysis that enables effective hardware-software co-design. We describe practical trace collection techniques, including hardware-assisted processor tracing with minimal overhead and portable software-based instrumentation with statistical sampling. We present multi-perspective analysis methods that examine memory behavior from temporal, sequential, spatial, and relational viewpoints, revealing distinct optimization opportunities invisible in aggregate metrics. We detail an architectural modeling framework that uses sampled traces with temporal interpolation and confidence-based filtering to evaluate cache and memory configurations. Evaluation on representative benchmarks demonstrates that this framework achieves practical accuracy (L2 cache errors of 2.64\%, confidence-filtered L3 errors of 9.92\%, bandwidth errors of 7.33\%) while providing substantial speedup (26.8×) over cycle-accurate simulation, enabling rapid design space exploration. We demonstrate how this integrated framework enables systematic identification of both hardware optimizations (memory controller tuning, bank partitioning, NUMA configuration) and software optimizations (data layout restructuring, prefetching strategies, memory-aware scheduling). Through this comprehensive treatment of the memory-centric analysis pipeline—from trace collection through architectural modeling to co-design application—we provide researchers and practitioners with practical techniques for addressing memory bottlenecks in contemporary computing systems.

Gajaria, Dhruv Mayur↗
DOE OSTI2024

Event-Based Energy Impact Tracking and Forecasting with Limited Measurements for Rooftop Units

Packaged air conditioning units and heat pumps, also known as rooftop units (RTUs), are responsible for almost 133 billion kWh of electricity usage annually on site for space cooling U.S. commercial buildings. In addition, the use of heat pumps is a trend we expect to accelerate as buildings transition from fossil fuel-based heating to electricity as a key step for decarbonizing the U.S. commercial buildings sector. However, the operation conditions and energy use of RTUs and heat pumps are usually not well monitored as they are not commonly integrated with building automation systems and lack exposed sensing and control points. To fill this gap, this paper proposes a framework for tracking and forecasting energy impacts resulting from degradation of performance and improved performance for unit servicing using limited data. The proposed framework makes use of a constrained dataset, specifically measurements of the outdoor air temperature and the power demand of individual RTUs, to track and forecast changes in energy use associated with changes in performance over various temporal horizons ranging from days to weeks. Following the detection of an RTU fault, performance degradation, or performance improvement, the framework employs a prediction model to assess the cumulative energy impact. We demonstrate the effectiveness of the method with field-collected data for servicing and degradation examples and compare the predicting accuracy of Gradient Boosting Decision Tree (GBDT) Regression models to Support Vector Regression and Linear Regression models. The results show that GBDT achieved the best accuracy for time-series validation datasets for the servicing and degradation cases, and the prediction model was able to track the cumulative energy impacts of events. The proposed framework can inform building owners of the cumulative change in energy usage of RTUs associated with performance degradation, performance improvement, or a fault.

packaged air conditioners, packaged heat pumps, ro↗
DOE OSTI2024

PPI DataHub Project Data Package: S. elongatus PCC 7942 Circadian Control Bioproduction Metabolomics (PB-DP5)

The purpose of this experiment was to evaluate how circadian clock regulation impacts carbon partitioning between storage, growth, and product synthesis in Synechococcus elongatus PCC 7942 in providing insights to strategies for enhanced bioproduction. Culture samples were collected at 0, 0.5, 1, 2, 4, 6, and 8 hours for extracellular sucrose analysis. Circadian metabolomics data was acquired using a Agilent single quadrupole gas chromatography-mass spectrometer and processed using Agilent Mass Hunter for targeted sucrose quantification. Metabolomic analysis of PCC 7942 light-dark cycle cultures transitioned to constant light revealed distinct temporal patterns in sucrose production. Processed metabolomic datasets are openly accessible from the PNNL DataHub project dataset download page and contain secondary processed GC-MS results files and supporting metadata materials linked to relevant source code information supporting data transparency and reuse.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

T3CO (Transportation Technology Total Cost of Ownership) Open Source [SWR-21-54]

T3CO (Transportation Technology Total Cost of Ownership), is open source software for modeling total cost of ownership for commercial vehicles with advanced powertrains. T3CO is a modeling framework for determining geospatially and temporally optimized total cost of ownership (TCO) for vehicle powertrain technologies. T3CO runs NREL's FASTSim™ software for a representative set of operating conditions to minimize TCO based on vehicle parameters that affect purchase and operating costs (e.g., fuel/electricity consumption, asset depreciation, opportunity costs associated with charging time) while simultaneously ensuring that firm performance constraints (e.g. zero-to-sixty time, gradeability) are satisfied. T3CO will enable the user to control which powertrain parameters are used in optimizing TCO, and these parameters will be modified by a multi-objective optimization (MOO) algorithm to identify a Pareto-optimal solution set. The optimization algorithm will be modular so that users can choose from many different MOO options or insert their own user-defined optimization tool. NREL T3CO Homepage: https://www.nrel.gov/transportation/t3co.html PyPI package: https://pypi.org/project/t3co/

Lustbader, Jason↗
DOE OSTI2021

Physics Goals of DWA Experiments at FACET-II

The dielectric wakefield acceleration (DWA) program at FACET produced a multitude of new physics results that range from GeV/m acceleration to the discovery of high field-induced conductivity in THz waves, and beyond, to a demonstration of positron-driven wakes. Here we review the rich program now developing in the DWA experiments at FACET-II. With increases in beam quality, a key feature of this program is extended interaction lengths, near 0.5 m, permitting GeV-class acceleration. Detailed physics studies in this context include beam breakup and its control through the exploitation of DWA structure symmetry. The next step in understanding DWA limits requires the exploration of new materials with low loss tangent, large bandgap, and improved thermal characteristics. Advanced structures with photonic features for mode confinement and exclusion of the field from the dielectric, as well as quasi-optical handling of coherent Cerenkov signals is discussed. Use of DWA for laser-based injection and advanced temporal diagnostics is examined.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

A phase transition model and temporal logic specifications for smart energy systems - revisited

In this paper, we revisit the method of a phase transition model for representing hybrid systems and temporal logic specifications (TLSs) for specifying desired behaviors of systems, and discuss their usefulness for smart energy systems. On the one hand, the phase transition model incorporates the continuous model of the relay device action with a particular structural form that allows for the construction of a single, global differential-algebraic equation for hybrid systems (thus smoothed hybrid systems). On the other hand, the TLS allows sophisticated descriptions of control specifications addressing both magnitude and time simultaneously, which has recently been applied to the control strategy of several types of continuous and hybrid systems. We provide high-level descriptions of each of the two techniques and present simulation results in the context of smart energy systems.

Park, Byungkwon↗
DOE OSTI2023

A Graph Dynamical neural network approach for decoding dynamical states in ferroelectrics.

Ferroelectric materials such as BaTiO 3 show tremendous potential for emerging advances in memory devices, particular neuromorphic type devices. High density of memory can be obtained by stabilising polar domain walls at the nanoscale, regions of discontinuity between the well-defined polarization order parameter, but little is known about what controls their structure and dynamics in real nanoscale materials. Indeed, chiral polar domain walls have been observed in heterogeneous ferroelectrics, such as oxygen-deficient BaTiO 3 , but very little is known about how such polar-domains walls interact with defects. Indeed, a critical understanding of how dynamics of domain-walls depend on point-defects is crucial to create engineered ferroelectric memory devices. For this work, we perform large-scale simulations of nansocale domain-wall dynamics in pristine and defective BaTiO 3 using reactive force-field developed by us earlier (Phys. Chem. Chem. Phys., 2019, 21, 18240–18249), and capture their dynamical dependence on point defects using a graph dynamical neural-network approach, which we adapted to interrogate solids with well-defined order-parameters, and implemented using Pytorch based libraries. Our machine learning (ML) approach goes beyond the traditional post-processing methods to capture both spatial and temporal heterogeneities of large-scale molecular dynamics simulations of complex defective ferroelectric oxide materials. We crucially find that isolated oxygen vacancies introduce very localized spatial regions (~1–2 unit-cell in length) that show slow dipole relaxation due to formation of defect-dipoles, and that these defect-dipoles in turn slow the intrinsic dynamics of domain walls. Further, the roughness of domain walls, also influenced by vacancies, introduce dynamic heterogeneity along the domain-wall. As such we find a novel mechanism by which quenched disorder due to defects introduce dynamic heterogeneity thereby influencing response to external fields (particularly time varying fields) in a ferroelectric. Our study also emphasizes the need for creating digital twins of dynamical quantities to achieve autonomous in operando control of nanoscale switching.

42 ENGINEERING↗
DOE OSTI2024

Endophyte mediated Populus trichocarpa water use efficiency is dependent on time of day and plant water status

Endophytes are potential partners for improving the resource use efficiency of bioenergy feedstock systems such as short rotation coppiced Populus. Endophytes isolated from members of the Salicaceae family have broad host compatibility and can improve water use efficiency (WUE) through decreases in stomatal conductance. However, the literature is inconsistent with regards to the environmental conditions and temporal patterns of these benefits. This study investigates how endophyte mediated changes in Populus trichocarpa (Torr. and Gray) ‘Nisqually-1’ stomatal conductance and WUE shift with time and scale in response to water-deficit stress. Leaf gas exchange and above-ground productivity were used to evaluate the carbon and water balances of glasshouse grown plants in response to endophyte inoculation and water-deficit. Differences in stomatal conductance between control and inoculated plants were more pronounced (39.7 % decrease, Welch’s two-sample t(14.34 dfadj) = -2.358, p-value = 0.033) under water-deficit conditions in the late morning during a period of higher light intensity. The decrease in stomatal conductance accompanied a substantial increase in intrinsic WUE (iWUE) for water-deficit inoculated plants. However, increases in iWUE did not result in improvements in aboveground productivity or shoot biomass WUE (WUEsb) for water-deficit inoculated plants. This decoupling between iWUE and aboveground productivity may be an indicator of assimilate allocation to microbial metabolism as an additional carbon sink or a shift in carbon allocation towards belowground biomass. Future work should take a whole-plant approach that accounts for diurnal patterns in incident irradiance to evaluate the impact of endophyte inoculation on host WUE and stress tolerance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Pressure-Driven Fiber-Optic Sensor for Online Corrosion Monitoring

For many industrial applications, corrosion is a life-limiting phenomenon and therefore requires careful consideration and rigorous experimental testing before structural materials can be reliably deployed, particularly in harsh chemical environments. The traditional approach to measuring corrosion requires exposing many samples to the intended environment and then extracting them individually at discrete intervals for postexposure characterization. This approach does not provide a high degree of temporal resolution, nor does it provide any real-time information regarding dynamic changes in corrosion rates. Additionally, developing an online corrosion monitor capable of surviving harsh chemical environments could provide valuable information regarding the structural health of components and changing process conditions that could accelerate corrosion. To this end, a corrosion sensor was developed based on a pressure-driven Fabry-Pérot cavity (FPC). This sensor uses a pressure control system to internally pressurize the FPC formed between the sensor’s housing and a metal-embedded singlemode optical fiber. Simultaneous measurement of the change in FPC length using low-coherence interferometry and the applied pressure enables the calculation of the relative changes in the sensor’s diaphragm thickness due to corrosion on its outer surface. Measurements were made in situ while actively corroding the sensor and were validated against surveillance specimens that were corroded simultaneously. The uncertainties in the measured corrosion were analyzed using error propagation of the uncertainties in the measured pressures and displacements and were found to be <1% of the initial diaphragm thickness.

42 ENGINEERING↗