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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Coupling of high-resolution mass spectrometer and photosynthesis system for comprehensive leaf volatile metabolite profiling

Background Leaf-level biogenic volatile organic compounds (BVOCs) emissions represent a major source of organic gases in the atmosphere, influencing both climate and air quality. These emissions are strongly driven by environmental perturbations, which affect individual plant- to ecosystem-level processes. Uncovering all the BVOCs and understanding how their emissions respond to altered environmental conditions provide critical insights into vegetation-driven changes in atmospheric chemistry. We developed a tandem instrumentation setup that integrates a proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) with parts-per-trillion detection limits and a photosynthetic infrared gas exchange system for the untargeted survey of all the BVOCs. This novel system enables simultaneous, real-time monitoring of BVOC emissions and photosynthetic parameters at the leaf level, offering new opportunities to disentangle the physiological and environmental drivers of VOC release. Furthermore, we established the VOC Analysis and Processing Optimization Resource (VAPOR), an open-access software tool designed for rapid data post-processing and the analysis of the variability of hundreds of BVOCs. We assessed the performance of the tandem system under varying background conditions, using standard gas mixtures and a range of environmental factors. Results Blank emissions were substantially lower for major BVOCs (e.g., isoprene) compared to those observed in plant emissions. Despite this, the observation of background-level VOCs highlights the importance of routinely acquiring and accounting for blank measurements in analyses using the coupled instrumentation. Introduction of known VOC concentrations to the system demonstrated a linear response across different compounds with varying molecular compositions, indicating minimal gas loss regardless of chemical moieties within the coupled instrumentation. We applied the optimized system to investigate the physiological mechanisms driving BVOC emissions across different genotypes of poplar and pennycress. The high mass resolution capabilities of the PTR-ToF-MS, coupled with comprehensive VAPOR-driven data analysis, enabled the identification of several important BVOCs, including methanol and methanethiol; these BVOCs displayed substantial variation across pennycress genotypes and showed concentrations ~ 100–350% higher than the blank. Moreover, isoprene emissions varied significantly among poplar genotypes grown in different potting media. Conclusions Tandem instrumentation offers a powerful tool for profiling volatile molecular markers and elucidating their genetic and environmental underpinnings. This approach enhances our ability to predict BVOC emissions in response to genotype by environmental interactions and contributes to a deeper understanding of vegetation responses to environmental changes.

Biogenic volatile organic compounds↗
DOE OSTI2020

Hydrogen and Solid Carbon Products from Natural Gas: A Review of Process Requirements, Current Technologies, Market Analysis, and Preliminary Techno Economic Assessment

In this paper, we review relevant technologies—primarily thermochemical and plasma conversion processes—that use natural gas to produce solid carbon and hydrogen, and recent research progress and commercial activities. Technical challenges include the high energetic requirements necessary for methane activation and, for some catalytic processes, the separation of solid carbon product from the spent catalyst. We assess current and new carbon product markets that could be served given technological advances, and we discuss technical barriers and potential areas of research to address these needs. We provide preliminary economic analysis where it was concluded that the cost of pyrolytically produced CO2-free hydrogen can be potentially reduced to <$4/kg target levels with the co-production and sale of sufficiently high-value carbon products.

Dagle, Robert A.↗
DOE OSTI2020

Process Failure Detection via Recurrence Quantification Analysis in a Slot-Rectangular Spouted Bed

A study was conducted to explore the applicability of recurrence and recurrence quantification analysis (RQA) to the detection of process failures in spouted bed reactor systems. Here, three different potential failure modes were examined in a transparent, cold flow slot-rectangular spouted bed. These being, a simulated air leak from a side wall of the reactor, a simulated gas leak from the top wall of the reactor, and simulated agglomeration of solids via introduction of larger “klinker” particles. Bed pressure drop time history data were collected and analyzed via generation of recurrence plots (RPs) and RQA parameters. In general, the simulated agglomeration case was quite easily detected via ever RQA Parameter examined, whereas the simulated air leaks were detected by only a single RQA parameter.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

CO 2 conversion to syngas via electrification of endothermal reactors: Process design and environmental impact analysis

CO 2 utilization via reverse water gas shift (rWGS) reaction has been proposed as a path to the sustainable utilization. Here this work presents a detailed process modelling study where steam methane reforming (SMR) generated hydrogen was combined with rWGS to produce syngas (CO + H 2 ) with various hydrogen-to-carbon oxide ratios. To further decrease CO 2 emissions that may offset the benefits of CO 2 converted in rWGS, electrification of endothermal reactors, both SMR and rWGS was considered where CO 2 emitting fuel burning in the furnace was replaced by the emerging ohmic (resistive) heating. Material and energy inventory obtained from process design calculations was used to perform Life Cycle Analysis (LCA) to calculate environmental impacts of CO 2 consumption and reactor electrification. The results showed that greenhouse gas emissions, in CO 2 kg equivalent, were the lowest when both SMR and rWGS were heated using wind-generated electricity, decreasing from 25 to 10 kg CO 2 equivalent for H 2 :CO = 2:1 while the conventional electricity mix used for furnace electrical heating across the board of scenarios generated highest environmental impacts, much higher than those that used natural gas as fuel. Process economics calculations suggested that, when both SMR and rWGS were electrically heated, the process only showed product syngas cost parity with the conventional fuel heated design when electricity cost was ~$0.008/kWh. This suggests that CO 2 utilization scenarios involving process electrification need to be carefully considered from the total design perspective so they do not produce more greenhouse gases than in conventional non-electrified scenarios.

42 ENGINEERING↗
DOE OSTI2021

Comparative Assessment of Data-driven Process Models in Health Information Technology

Process mining for conformance analysis consists of comparing a reference process model against a data-driven process model generated via log files from information technology systems. However, in the absence of a complete reference process model, we found no suggested approaches in the literature to address the need for evaluating process conformance among different healthcare facilities to assess standardization of care. Our goal is to find similarities and dissimilarities in data-driven process models among US Veterans Health Administration (VHA) facilities that can be indicative of patient safety issues. Our hypothesis was that the analysis would not produce statistically significant differences in outcome. We present a unique implementation of conformance analysis in process mining that consists of combining process mining, process mapping and statistical metrics. We illustrate our approach by applying it to the analysis of two clinical radiology order process models generated from healthcare data provided by two similar facilities in the VHA. The comparative assessment showed that about 70% of the orders completed successfully and 30% were not completed due to policy and duplications. Our analysis found a good statistical correlation between both facilities, as the Spearman’s correlation coefficient between facilities for the frequency of cases per total hours was 0.87879, for the frequency of cases by state transition was 0.79702 and for the throughput time per state transition was 0.63582. Additional statistical analyses using the Mann-Whitney U test and the root mean square error both produced values that were not significant. The foregoing approach validated our hypothesis by demonstrating a good statistical correlation of data describing the flow of clinical radiology orders absent a credible reference model. Finding good agreement between both facilities was important in confirming that the clinical orders flow in a similar manner, suggesting standardization of care.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Small Hydropower Interconnections: Small Hydropower in the United States

Small hydropower projects, which we define as generators below 20 MW in capacity have been the predominant source of hydropower growth over the past decade and create the most cost-effective and environmentally permissible avenues for new hydropower installation in the United States (DOE 2016; Johnson et al. 2018). Small hydropower developers across the United States have found that interconnecting these projects with the grid can be challenging due to unexpected costs and schedule overruns. Understanding the interconnection challenges and improving the process may allow more small hydropower projects to be successful. Noting these challenges, the U.S. Department of Energy Water Power Technologies Office enlisted Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory (ORNL) to investigate the small hydropower interconnection landscape across the United States. To begin to analyze the existing interconnection processes and challenges facing small hydropower, the state of small hydropower development in the U.S. must first be described to understand the characteristics of the industry. The first in a series, this paper presents the state of small hydropower projects in the U.S. to describe their type, location, and size based on data extracted from the HydroSource database (ORNL 2020). The following papers in the series will detail the variety of state interconnection processes to connect power generators with the grid (“Small Hydropower Interconnections: State Interconnection Processes”), analyze these interconnection processes (“Small Hydropower Interconnections: Analysis of Interconnection Processes”), and present best practices in interconnection processes (“Small Hydropower Interconnections: Best Practices”) that will help overcome barriers to future small hydropower development.

13 HYDRO ENERGY↗
DOE OSTI2022

Small Hydropower Interconnections: State Interconnection Processes

Small hydropower projects with rated power output between 0 to 20 MW have been the predominant source of hydropower growth over the past decade in the United States (DOE 2016; Johnson et al. 2018). However, interconnection to electricity distribution and transmission grids is a persistent barrier. Interconnection of an electricity generating unit is overseen by the distribution or transmission owner, who use interconnection standards and requirements that vary by state. The differences between standards in standards may affect the final cost, timeline, and success of a small hydropower project. Small hydropower project developers across the United States have found interconnection procedures to be fraught with cost surprises and schedule overruns. System operators have struggled to understand impacts to overburdened or rapidly evolving transmission and distribution grids. The results of these shortcomings have been stranded costs and unrealized small hydropower potential. Though regulatory actions and policy recommendations at the state level have increased the situational awareness of interconnection challenges, the remote locations of small hydropower resources and the relatively small revenues associated with energy production through small hydropower facilities continue to make interconnection processes and requirements confusing and costly. Noting these challenges, the U.S. Department of Energy Water Power Technologies Office enlisted Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory (ORNL) to investigate the small hydropower interconnection landscape across the United States. The second in a series, this paper investigates the interconnection process in each state in the U.S. to compare their attributes. Subsequent papers in the series will analyze these interconnection processes (“Small Hydropower Interconnections: Analysis of Interconnection Processes”) and present best practices (“Small Hydropower Interconnections: Best Practices”) that will help overcome barriers to future small hydropower development. The first paper in the series examined the state of small hydropower projects in the United States (“Small Hydropower Interconnections: Small Hydropower in the United States”) to understand the industry characteristics.

13 HYDRO ENERGY↗
DOE OSTI2022

Marine Shallow Cloud Adjustments to the Presence of Shortwave-Absorbing Aerosols: Advancing Understanding Through a Combined Analysis of Lasic Datasets and Process Modeling (Final Report)

This is a final report for this award, whose purpose was to support the analysis of data emanating from the LASIC (Layered Atlantic Smoke Interaction with Clouds) campaign. (Layered Atlantic Smoke Interactions with Clouds) is a strategy to improve our understanding of aged carbonaceous aerosol, its seasonal evolution, and the mechanisms by which clouds adjust to the presence of the aerosol. The observational strategy centers on deploying the AMF1 cloud, aerosol, and atmospheric profiling instrumentation to Ascension Island, located within the trade-wind shallow cumulus regime (14.50W, 80S) 3000 km offshore of continental Africa. The location is within the latitude zone of the maximum outflow of aerosol, with the deepening boundary layer known to entrain free-tropospheric smoke. The primary activities for LASIC are: 1) to improve current knowledge on aged biomass burning aerosol and its radiative properties as a function of the seasonal cycle; 2) to use surface-based remote sensing to sensitively interrogate the atmosphere for the relative vertical location of aerosol and clouds; 3) to improve our understanding of the cloud adjustments to the presence of shortwave-absorbing aerosol within the vertical column, both through aerosol-radiation and through aerosol-cloud interactions; 4) to aid low cloud parameterization efforts for climate models. This award serves to further these activities and includes a sub-award to Dr. Pablo Saide at UCLA for activities 3) and 4).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Facile One-Pot Nanoproteomics for Label-Free Proteome Profiling of 50–1000 Mammalian Cells

Recent advances in sample preparation enable label-free MS-based proteome profiling of small numbers of mammalian cells. However, specific devices are often required to downscale sample processing volume from the standard 50-200 µL to sub-µL for effective nanoproteomics, which greatly impedes the implementation of current nanoproteomics methods by broad proteomics research community. Here we report a facile one-pot nanoproteomics method termed SOPs-MS (Surfactant-assisted One-Pot sample processing at the standard volume coupled with MS) for convenient proteome profiling of 50-1000 mammalian cells. Building upon our recent development of SOP-MS for label-free single-cell proteomics at low µL volume (Commun Bio 2021, 4, 265), we have systematically evaluated its processing volume at 10-200 µL using 100 human cells for robust reproducible nanoproteomic analysis. The processing volume of 50 µL which is in the range of volume for standard proteomics sample preparation, has been selected for easy sample handling with benchtop micropipette. Using the commonly accessible LC-MS platform, SOPs-MS allows for reliable label-free quantification of ~1200-2700 protein groups from 50-1000 MCF10A cells. When applied to small subpopulations of mouse colon crypt cells, SOPs-MS can reveal distinct protein signatures between any two subpopulation cells with identification of ~1500-2500 protein groups for each subpopulation. SOPs-MS may pave the way for routine deep proteome profiling of small numbers of cells as well as low-input samples.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Utility-Scale Operational Consequences for Solar Grid Services

This report delves into the critical aspects of grid services provided by solar inverter-based resources (IBRs), with an emphasis on the evolving landscape of microgrids, virtual power plants (VPPs), aggregators, and distributed energy resource management systems (DERMS). As the energy sector undergoes a transformative shift towards more decentralized and resilient grid architectures, understanding the multifaceted risks associated with these technologies becomes paramount. The report categorizes these risks into organizational, technical, and procedural domains, providing a thorough risk assessment framework that stakeholders can utilize to anticipate and mitigate potential issues. In addressing the increasing complexity of grid interconnections, the report highlights the importance of Cyber-Informed Engineering (CIE). By embedding engineering controls and cybersecurity measures into the early stages of system design, this approach aims to fortify grid infrastructure against emerging cyber threats. The analysis includes an exploration of best practices and strategies for integrating CIE principles to enhance grid security and resilience. To provide practical insights, the report conducts a detailed consequence analysis of various grid services and cyber mitigations that can be applied through the interconnection process. This analysis evaluates the potential impacts of different failure modes and vulnerabilities, offering a clear understanding of the consequences that could arise from disruptions within the energy grid. The findings are further enriched by a series of case studies that illustrate real-world scenarios and lessons learned from past incidents. Through this comprehensive examination of grid services and their criticality, the report aims to prepare industry professionals with the knowledge and tools necessary to navigate the complexities of modern energy systems. By providing a comprehensive approach that includes risk assessment, cybersecurity, and consequence analysis, solar stakeholders can more effectively guarantee the reliability, efficiency, and security of the energy grid.

14 SOLAR ENERGY↗
DOE OSTI2021

Techno-Economic Analysis and Life Cycle Assessment of Waste Lignin Fractionation and Valorization Using the ALPHA Process

Techno-Economic Analysis (TEA) and Life Cycle Assessment (LCA) were performed on the Aqueous Lignin Purification with Hot Agents (ALPHA) process, which is being investigated for the fractionation and purification of raw, bulk lignins recovered from cellulosic ethanol biorefineries or Kraft pulp mills. Here, ALPHA is proposed for the isolation of lignin from a corn stover-to-ethanol plant into purified low, medium, and high molecular weight (MW) fractions for producing polyurethane foam, activated carbon, and carbon fiber, respectively. A scenario analysis was conducted to determine the effect of ALPHA solvent choice on process economics and environmental performance. Solvent choice was found to have a significant impact on ALPHA, with a minimum selling price of 838/tonne with use of acetic acid vs 463/tonne with ethanol. Conversion of the lignin, processed with ethanol solvent, to high-value products yields 151 million/year in profit, which over 30 years results in a total net present value of 533 million. A life cycle assessment was conducted to determine the “gate-to-gate” greenhouse gas emissions and energy consumption of the lignin-based products compared to fossil-based equivalents. In conclusion, a value allocation scenario was conducted and it was determined that products generated using the ALPHA process with ethanol have similar or lower greenhouse gas emissions than the same products from fossil feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2023

The γ -process nucleosynthesis in core-collapse supernovae

The γ-process nucleosynthesis in core-collapse supernovae is generally accepted as a feasible process for the synthesis of neutron-deficient isotopes beyond iron. However, crucial discrepancies between theory and observations still exist: the average yields of γ-process nucleosynthesis from massive stars are still insufficient to reproduce the solar distribution in galactic chemical evolution calculations, and the yields of the Mo and Ru isotopes are a factor of ten lower than the yields of the other γ-process nuclei. We investigate the γ-process in five sets of core-collapse supernova models published in the literature with initial masses of 15, 20, and 25 M ⊙ at solar metallicity. We compared the γ-process overproduction factors from the different models. To highlight the possible effect of nuclear physics input, we also considered 23 ratios of two isotopes close to each other in mass relative to their solar values. Further, we investigated the contribution of C–O shell mergers in the supernova progenitors as an additional site of the γ-process. Our analysis shows that a large scatter among the different models exists for both the γ-process integrated yields and the isotopic ratios. We find only ten ratios that agree with their solar values, all the others differ by at least a factor of three from the solar values in all the considered sets of models. The γ-process within C–O shell mergers mostly influences the isotopic ratios that involve intermediate and heavy proton-rich isotopes with A > 100. We conclude that there are large discrepancies both among the different data sets and between the model predictions and the solar abundance distribution. More calculations are needed; particularly updating the nuclear network, because the majority of the models considered in this work do not use the latest reaction rates for the γ-process nucleosynthesis. Moreover, the role of C–O shell mergers requires further investigation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Embedded Error Bayesian Calibration of Thermal Decomposition of Organic Materials

Organic materials are an attractive choice for structural components due to their light weight and versatility. However, because they decompose at low temperatures relative to tradiational materials they pose a safety risk due to fire and loss of structural integrity. To quantify this risk, analysts use chemical kinetics models to describe the material pyrolysis and oxidation using thermogravimetric analysis. This process requires the calibration of many model parameters to closely match experimental data. Previous efforts in this field have largely been limited to finding a single best-fit set of parameters even though the experimental data may be very noisy. Furthermore the chemical kinetics models are often simplified representations of the true de- composition process. The simplification induces model-form errors that the fitting process cannot capture. In this work we propose a methodology for calibrating decomposition models to thermogravimetric analysis data that accounts for uncertainty in the model-form and experimental data simultaneously. The methodology is applied to the decomposition of a carbon fiber epoxy composite with a three-stage reaction network and Arrhenius kinetics. The results show a good overlap between the model predictions and thermogravimetric analysis data. Uncertainty bounds capture devia- tions of the model from the data. The calibrated parameter distributions are also presented. In conclusion, the distributions may be used in forward propagation of uncertainty in models that leverage this material.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Slycat Enables Synchronized 3D Comparison of Surface Mesh Ensembles [Brief]

In support of analyst requests for Mobile Guardian Transport studies, researchers at Sandia National Laboratories have expanded data types for the Slycat ensemble-analysis and visualization tool to include 3D surface meshes. This new capability represents a significant advance in our ability to perform detailed comparative analysis of simulation results. Analyzing mesh data rather than images provides greater flexibility for post-processing exploratory analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Irradiation-Driven Restructuring of UO 2 Thin Films: Amorphization and Crystallization

Combustion synthesis in uranyl nitrate–acetylacetone–2-methoxyethanol solutions was used to deposit thin UO 2 films on aluminum substrates to investigate the irradiation-induced restructuring processes. Thermal analysis revealed that the combustion reactions in these solutions are initiated at ~160 °C. The heat released during the process and the subsequent brief annealing at 400 °C allow the deposition of polycrystalline films with 5–10 nm UO 2 grains. The use of multiple deposition cycles enables tuning of the film thicknesses in the 35–260 nm range. Irradiation with Ar 2+ ions (1.7 MeV energy and a fluence of up to 1 × 10 17 ions/cm 2 ) is utilized to generate a uniform distribution of atomic displacements within the films. X-ray fluorescence (XRF) and alpha-particle emission spectroscopy showed that the films were stable under irradiation and did not undergo sputtering degradation. X-ray photoelectron spectroscopy (XPS) showed that the stoichiometry and uranium ionic concentrations remain stable during irradiation. The high-resolution electron microscopy imaging and electron diffraction analysis demonstrated that at the early stages of irradiation (below 1 × 10 16 ion/cm 2 ) UO 2 films show complete amorphization and beam-induced densification (sintering), resulting in a pore-free disordered film. Prolonged irradiation (5 × 10 16 ion/cm 2 ) is shown to trigger a crystallization process at the surface of the films that moves toward the UO 2 /Al interface, converting the entire amorphous material into a highly crystalline film. This work reports on an entirely different radiation-induced restructuring of the nanoscale UO 2 compared to the coarse-grained counterpart. The preparation of thin UO 2 films deposited on Al substrates fills an area of national need within the stockpile stewardship program of the National Nuclear Security Administration and fundamental research with actinides. Here, the method reported in this work produces pure, robust, and uniform thin-film actinide targets for nuclear science measurements

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Investigating Influential Parameters for High-Purity Germanium Crystal Growth

This paper focuses on the research and development of high-purity germanium (HPGe) crystals for detector fabrication, specifically targeting applications in rare-event physics searches. The primary objective was to produce large-scale germanium crystals weighing >1 kg with a controlled diameter of ∼10 cm and an impurity range of approximately 1010/cm 3. Ensuring structural integrity and excellent crystalline quality requires a thorough assessment of dislocation density, a critical aspect of the crystal development process. Dislocation density measurements play a crucial role in maximizing the sensitivity of HPGe detectors, and our findings confirmed that the dislocation density fell within acceptable ranges for detector fabrication. Additionally, this paper examines the segregation coefficient of various contaminants during the crystal development process. Comprehensive analysis of impurity segregation is essential for reducing contaminant quantities in the crystal lattice and customizing purification processes. This, in turn, minimizes undesired background noise, enhancing signal-to-noise ratios for rare-event physics searches and overall detector performance. The investigation included the segregation coefficients of three major acceptors and one donor in crystals grown at the University of South Dakota, providing valuable insights for optimizing crystal purity and detector efficiency.

Bhattarai, Sanjay↗
DOE OSTI2024

RTDP: Streaming Readout Real-Time Development and Testing Platform

The Thomas Jefferson National Accelerator Facility (JLab) has created and is currently working on various tools to facilitate streaming readout (SRO) for upcoming experiments. These include reconstruction frameworks with support for Artificial Intelligence/Machine Learning, distributed High Throughput Computing (HTC), and heterogeneous computing which all contribute significantly to swift data processing and analysis. Designing SRO systems that combine such components for new experiments would benefit from a platform that would combine both simulation and execution components for simulation, testing, and validation before large investments are made. The Real-Time Development Platform (RTDP) is being developed as part of an LDRD funded project at JLab. RTDP aims to establish a seamless connection between algorithms, facilitating the seamless processing of data from SRO to analysis, as well as enabling the execution of these algorithms in various configurations on compute and data centers. Individual software components simulating specific hardware can be replaced with actual hardware when it is available.

Gyurjyan, Vardan↗
DOE OSTI2022

Database-wide hazard modelling of the onset of DIII-D tearing modes with field features

The rate of onset (hazard) of tearing modes is modelled probabilistically using statistical learning algorithms. Axisymmetric energy-density equilibrium fields are taken as raw high-dimensional input features which are reduced with principal component analysis. Signal processing of non-axisymmetric magnetics fluctuation array data provides the target information from which to learn. Model selection, visualization and calibration assessment procedures are detailed. Here, the analysis is deployed at large scale across the DIII-D tokamak database. Standard model selection criteria suggest that the energy-density post-processed feature is a better choice for modelling the onset rate compared to the non-processed equilibrium reconstruction solution. Two example applications of the learned rate function are demonstrated: (i) proximity-to-onset discharge monitoring and (ii) database analysis showing an (expected) observational global trend that the general hazard increases as a plasma performance metric increases. An important connection between the hazard function and its use as a conditional probability generator is reviewed in the Appendix.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗