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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 OSTI2022

When physics-informed data analytics outperforms black-box machine learning: A case study in thickness control for additive manufacturing

Aerosol jet printing (AJP) has emerged as a promising noncontact additive manufacturing method for high-resolution printing for a wide range of material systems. A key challenge limiting the broader adoption of AJP in the material science community is the lack of methods to precisely control thickness. Herein, we develop a model-based design of experiment (MBDoE) framework that integrates physics-informed models, nonlinear regression, and information criteria to postulate, select and calibrate the best model to describe and optimize the AJP manufacturing process. Starting with already available data from system commissioning (e.g., prior single variable sensitivity analysis), four candidate physics-informed models are postulated and trained. MBDoE identifies a single additional optimal experiment to validate these predictive models with quantified uncertainties, which are then used to determine the best experimental conditions to control printed film thickness. As a comparative benchmark, the analysis is repeated using the same dataset with nonparametric Gaussian process regression (GPR) model that does not incorporate physical information. Using MBDoE principles, we find that only five experiments are necessary to calibrate the nonlinear physics-informed parametric model, and with said limited data, this model outperforms the black-box machine learning GPR model. This key result underscores an emerging trend in the data science community: incorporating physical information into predictive models often drastically reduces the data requirements. Leveraging MBDoE further increased the data efficiency. By design, the proposed data science framework is general in nature and can be easily extended to other experimental and additive manufacturing systems beyond AJP.

Aerosol jet printing↗
DOE OSTI2023

Experimental determinations of carbon and hydrogen isotope fractionations and methane clumped isotope compositions associated with ethane pyrolysis from 550 to 600°C

Methane clumped isotope compositions signify the relative natural abundances of rare, doubly substituted isotopic species of methane ( 13 CH 3 D and 12 CH 2 D 2 ) and have emerged as a new isotopic tool to trace the sources, sinks, and lifecycles of methane in the environment. Such measurements can identify equilibration (or reequilibration) temperatures if found to be in isotopic equilibrium or non-equilibrium processes (e.g., kinetically controlled reactions or mixing) if not in isotopic equilibrium. Naturally occurring thermogenic methane—formed by the thermally activated breakdown of larger organic molecules—has been found to have clumped isotope compositions consistent with equilibrium at reasonable gas formation temperatures in some settings and non-equilibrium processes occurring during either formation, migration, storage, or extraction in others. To explore the potential controls on the isotopic composition of thermogenic methane, we conducted isothermal time-series ethane pyrolysis experiments at 550 and 600 °C to measure methane and ethane 13 C/ 12 C and D/H fractionations and methane clumped isotope compositions (resolved 13 CH 3 D and 12 CH 2 D 2 ). We explore the effects of modifying the initial clumped isotope composition of ethane and the addition of water vapor to pyrolysis experiments. We observe that ethane and methane 13 C/ 12 C are controlled by kinetic isotope effects and Rayleigh distillation processes. In contrast, ethane and methane D/H and methane clumped isotope compositions appear to be controlled by a combination of these processes and hydrogen isotope exchange. The hydrogen isotope exchange processes lead to isotopic equilibrium as reaction completion is approached for both D/H (ethane/methane) and methane clumped isotope compositions. Here, we develop a chemical model based on a mass balance approach that accounts for inheritance vs. hydrogen-abstraction formation pathways for singly and doubly substituted isotopologues of ethane and methane that is compared to the experimental data. The model allows the determination of carbon and hydrogen kinetic isotope effects associated with ethane cracking and hydrogen abstraction reactions that, where applicable, we compare to prior theoretical constraints. From the comparison of the model to the experimental data, we infer that the kinetically controlled ethane and methane bulk isotope compositions and methane clumped isotope compositions are controlled by kinetic isotope effects (both primary and secondary) associated with both C–C bond and C–H bond cleavage reactions. Specifically, the methane clumped isotope compositions likely result from a combination of clumped isotope effects associated with ethane breakdown and/or assembly of methane isotopologues (expressed in terms of γ-factor parameters ≠ 1) and combinatorial effects that arise probabilistically. We discuss our experimental results in the context of recent pyrolysis experiments and observations of naturally occurring thermogenic methane. We consider a proposal consistent with observations from nature that the hydrogen isotope exchange reactions that promote equilibration of methane isotopic molecules at or near formation temperature may be facilitated by free radicals generated by pyrolysis reactions. In this framework, isotope exchange effectively ceases when pyrolysis effectively ceases locking in compositions that can be consistent with peak formation temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Theoretical investigation of the decarboxylation and decarbonylation mechanism of propanoic acid over a Ru(0 0 0 1) model surface

The hydrodeoxygenation of organic acids is often found to be a rate-controlling process during upgrading of biomass feedstocks into fuels. We developed a microkinetic model based on data obtained from density functional theory calculations for the decarboxylation and decarbonylation mechanisms of propanoic acid (CH 3 CH 2 COOH) over a Ru(0 0 0 1) model surface. The model predicts that the decarbonylation mechanism is two orders of magnitude faster than the decarboxylation mechanism. The most favorable decarbonylation pathway proceeds via removal of the acid –OH group to produce propanoyl (CH 3 CH 2 CO) followed by C–CO bond scission of propanoyl to produce CH 3 CH 2 and CO. Finally, CH 3 CH 2 is hydrogenated to CH 3 CH 3 . Dehydrogenation reactions that have been observed to be important over Pd catalysts play no role over Ru(0 0 0 1), and a sensitivity analysis indicates that removal of the acid –OH group is the rate-controlling step in the deoxygenation. Altogether, our results suggest that to improve the Ru catalyst performance for the decarbonylation of organic acids, the free site coverage needs to be increased by, for example, adding a catalyst promoter that decreases the hydrogen and CO adsorption strength (without significantly affecting the C–OH bond scission rate), or by raising the reaction temperature and operating at relatively low CO and H 2 partial pressures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Comparative analysis for various redox flow batteries chemistries using a cost performance model

A robust performance-based cost model is developed for all-vanadium, iron-vanadium and iron chromium redox flow batteries. Systems aspects such as shunt current losses, pumping losses and thermal management are accounted for. The objective function, set to minimize system cost, allows determination of stack design and operating parameters such as current density, flow rate and depth of discharge (DOD). Component costs obtained from vendors are used to calculate system costs for various time frames. A 2 kW stack data was used to estimate unit energy costs and compared with model estimates for the same size electrodes. The tool has been shared with the redox flow battery community to both validate their stack data and guide future direction.

electrolyte↗
DOE OSTI2022

Machine-learning-assisted high-temperature reservoir thermal energy storage optimization

High-temperature reservoir thermal energy storage (HT-RTES) has the potential to become an indispensable component in achieving the goal of the net-zero carbon economy, given its capability to balance the intermittent nature of renewable energy generation. In this study, a machine-learning-assisted computational framework is presented to co-optimize the performance metrics of HT-RTES by combining physics-based simulation with stochastic hydrogeologic formation and thermal energy storage operation parameters, artificial neural network regression of the simulation data, and genetic algorithm-enabled multi-objective optimization. A doublet well configuration with a layered (aquitard-aquifer-aquitard) generic reservoir is simulated for cases of continuous operation and seasonal-cycle operation scenarios. Further, neural network-based surrogate models are developed for the two scenarios and applied to generate the Pareto fronts of the HT-RTES performance for four potential HT-RTES sites. The developed Pareto optimal solutions indicate the performance of HT-RTES is operation-scenario (i.e., fluid cycle) and reservoir-site dependent, and the performance metrics have competing effects for a given site and a given fluid cycle. The developed neural network models can be applied to identify suitable sites for HT-RTES, and the proposed framework sheds light on the design of resilient HT-RTES systems.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Plant roots alter microbial functional genes supporting root litter decomposition

Decomposition of soil organic carbon is central to the global carbon cycle and profoundly affected by plant roots. While root “priming” of decomposition has been extensively investigated, it is not known how plants alter the molecular ecology of soil microbial decomposers. We disentangled the effects of Avena fatua, a common annual grass, on 13 C-labeled root litter decomposition and quantified multiple genetic characteristics of soil bacterial and fungal communities. In our study, plants consistently suppressed rates of root litter decomposition. Microbes from planted soils had relatively more genes coding for low molecular weight compound degradation enzymes, while those from unplanted had more macromolecule degradation genes. Higher abundances of “water stress” genes in planted soils suggested that microbes experienced plant-induced water stress. We developed a conceptual model based on Mantel analyses of our extensive data set. This model indicates that plant root effects on the multiple soil environmental and microbial mechanisms involved in root litter decomposition act through changing the functional gene profiles of microbial decomposers living near plant roots.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Estimation of placental and lactational transfer and tissue distribution of atrazine and its main metabolites in rodent dams, fetuses, and neonates with physiologically based pharmacokinetic modeling

Atrazine (ATR) is a widely used chlorotriazine herbicide, a ubiquitous environmental contaminant, and a potential developmental toxicant. To quantitatively evaluate placental/lactational transfer and fetal/neonatal tissue dosimetry of ATR and its major metabolites, physiologically based pharmacokinetic models were developed for rat dams, fetuses and neonates. These models were calibrated using pharmacokinetic data from rat dams repeatedly exposed (oral gavage; 5 mg/kg) to ATR followed by model evaluation against other available rat data. Model simulations corresponded well to the majority of available experimental data and suggest that: (1) the fetus is exposed to both ATR and its major metabolite didealkylatrazine (DACT) at levels similar to maternal plasma levels, (2) the neonate is exposed mostly to DACT at levels two-thirds lower than maternal plasma or fetal levels, while lactational exposure to ATR is minimal, and (3) gestational carryover of DACT greatly affects its neonatal dosimetry up until mid-lactation. To test the model's cross-species extrapolation capability, a pharmacokinetic study was conducted with pregnant C57BL/6 mice exposed (oral gavage; 5 mg/kg) to ATR from gestational day 12 to 18. By using mouse-specific parameters, the model predictions fitted well with the measured data, including placental ATR/DACT levels. However, fetal concentrations of DACT were overestimated by the model (10-fold). This overestimation suggests that only around 10% of the DACT that reaches the fetus is tissue-bound. These rodent models could be used in fetal/neonatal tissue dosimetry predictions to help design/interpret early life toxicity/pharmacokinetic studies with ATR and as a foundation for scaling to humans. - Highlights: • We developed PBPK models for atrazine in rat dams, fetuses, and neonates. • We conducted pharmacokinetic (PK) study with atrazine in pregnant mice. • Model predictions were in good agreement with experimental rat and mouse PK data. • The fetus is exposed to atrazine/its main metabolite at levels similar to the dam. • The nursing neonate is exposed primarily to atrazine's main metabolite DACT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Estimating Cost and Energy Demand in Producing Lithium Hexafluorophosphate for Li-Ion Battery Electrolyte

In this work, the production of Lithium hexafluorophosphate (LiPF 6 ) for Lithium-ion battery application is studied. Spreadsheet-based process models are developed to simulate three different production processes. These process models are then used to estimate and analyze the factors affecting cost of manufacturing, energy demand, and environmental impact due to greenhouse gas (GHG) emissions. Moreover, the results indicate that in a facility with a capacity of making 10,000 metric tons per year of LiPF 6 the cost of production is around $20 per kg of LiPF 6 , energy consumption is around 30 GWh per year, and the emission of greenhouse gases in CO 2- equivalent gases is around 80 metric tons per day. The impact of change in process and economic parameters on the cost of production, energy demand, and emissions is studied. In addition, a few insights on reducing the cost of production are presented. Lastly, the impact of varying LiPF 6 costs on the overall cost of a Li-ion battery ($ kWh -1 ) is presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Polarizable Water Potential Derived from a Model Electron Density

A new empirical potential for efficient, large scale molecular dynamics simulation of water is presented. The HIPPO (Hydrogen-like Intermolecular Polarizable POtential) force field is based upon the model electron density of a hydrogen-like atom. This framework is used to derive and parametrize individual terms describing charge penetration damped permanent electrostatics, damped polarization, charge transfer, anisotropic Pauli repulsion, and damped dispersion interactions. Initial parameter values were fit to Symmetry Adapted Perturbation Theory (SAPT) energy components for ten water dimer configurations, as well as the radial and angular dependence of the canonical dimer. The SAPT-based parameters were then systematically refined to extend the treatment to water bulk phases. The final HIPPO water model provides a balanced representation of a wide variety of properties of gas phase clusters, liquid water, and ice polymorphs, across a range of temperatures and pressures. This water potential yields a rationalization of water structure, dynamics, and thermodynamics explicitly correlated with an ab initio energy decomposition, while providing a level of accuracy comparable or superior to previous polarizable atomic multipole force fields. The HIPPO water model serves as a cornerstone around which similarly detailed physics-based models can be developed for additional molecular species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Unraveling Exciton Trap Dynamics and Nonradiative Loss Pathways in Quantum Dots via Atomistic Simulations

Surface defects in colloidal quantum dots are a major source of nonradiative losses, yet the microscopic mechanisms underlying exciton trapping and recombination remain elusive. Here, we develop a model Hamiltonian based on atomistic electronic calculations to investigate exciton dynamics in CdSe/CdS core/shell QDs containing a single hole trap introduced by an unpassivated sulfur atom. By systematically varying the defect depth and reorganization energy, we uncover how defect-induced excitonic states mediate energy relaxation pathways. Our simulations reveal that a single localized defect can induce a rich spectrum of excitonic states, leading to multiple dynamical regimes, from slow, energetically off-resonant trapping to fast, cascaded relaxation through in-gap defect states. Crucially, we quantify how defect-induced polaron shifts and exciton-phonon couplings govern the balance between efficient radiative emission and rapid nonradiative decay. These insights clarify the microscopic origin of defect-assisted loss channels and suggest pathways for tailoring QD optoelectronic properties via surface and defect engineering.

Defects↗
DOE OSTI2015

Direct comparisons of X-ray scattering and atomistic molecular dynamics simulations for precise acid copolymers and ionomers

Designing acid- and ion-containing polymers for optimal proton, ion, or water transport would benefit profoundly from predictive models or theories that relate polymer structures with ionomer morphologies. Recently, atomistic molecular dynamics (MD) simulations were performed to study the morphologies of precise poly(ethylene-co-acrylic acid) copolymer and ionomer melts. Here, we present the first direct comparisons between scattering profiles, I(q), calculated from these atomistic MD simulations and experimental X-ray data for 11 materials. This set of precise polymers has spacers of exactly 9, 15, or 21 carbons between acid groups and has been partially neutralized with Li, Na, Cs, or Zn. In these polymers, the simulations at 120 °C reveal ionic aggregates with a range of morphologies, from compact, isolated aggregates (type 1) to branched, stringy aggregates (type 2) to branched, stringy aggregates that percolate through the simulation box (type 3). Excellent agreement is found between the simulated and experimental scattering peak positions across all polymer types and aggregate morphologies. The shape of the amorphous halo in the simulated I(q) profile is in excellent agreement with experimental I(q). We found that the modified hard-sphere scattering model fits both the simulation and experimental I(q) data for type 1 aggregate morphologies, and the aggregate sizes and separations are in agreement. Given the stringy structure in types 2 and 3, we develop a scattering model based on cylindrical aggregates. Both the spherical and cylindrical scattering models fit I(q) data from the polymers with type 2 and 3 aggregates equally well, and the extracted aggregate radii and inter- and intra-aggregate spacings are in agreement between simulation and experiment. Furthermore, these dimensions are consistent with real-space analyses of the atomistic MD simulations. By combining simulations and experiments, the ionomer scattering peak can be associated with the average distance between branches of type 2 or 3 aggregates. Furthermore, this direct comparison of X-ray scattering data to the atomistic MD simulations is a substantive step toward providing a comprehensive, predictive model for ionomer morphology, gives substantial support for this atomistic MD model, and provides new credibility to the presence of stringy, branched, and percolated ionic aggregates in precise ionomer melts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Feedbacks Between Surface Deformation and Permafrost Degradation in Ice Wedge Polygons, Arctic Coastal Plain, Alaska

In the past three decades, an abrupt, pan-Arctic acceleration of ice wedge melting has transformed tundra landscapes, spurring the formation of hummock-like features known as high-centered polygons (HCPs). This rapid geomorphic transition profoundly alters regional hydrology and influences surface emissions of CO 2 and CH 4 . In Arctic Alaska, most recent instances of ice wedge degradation have arrested within 15–20 years of inception, stabilizing HCP microtopography. However, feedbacks between ground surface deformation and permafrost stability are incompletely understood, limiting our capacity to predict trajectories of landscape evolution in a still warmer future. In this work, we use field data from a site near Prudhoe Bay, Alaska, to develop a modeling-based framework for assessing the strength of positive (i.e., exacerbating) feedbacks on ice wedge degradation, focusing on the importance of heterogeneity in surface drainage and microtopographic conditions. Our simulations suggest that, when troughs are narrow, positive feedbacks on ice wedge melting (associated with thermokarst pool formation) are relatively weak. Positive feedbacks are markedly stronger beneath wide troughs, such as those that form above older, larger ice wedges. Seasonal thaw abruptly accelerates once a talik begins to form beneath wide and deep thermokarst pools. Once a talik initiates, winter severity and snowpack thickness increase in importance as predictors of thaw intensity in summer. Our results indicate that meter-scale heterogeneity in polygonal microtopography potentially exerts strong, nonlinear controls on thermokarst trajectories. These findings are useful for predicting future thermokarst dynamics and for interpreting the results from coarser-resolution land surface models operating at greater spatial and temporal scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Adaptation Strategies Strongly Reduce the Future Impacts of Climate Change on Simulated Crop Yields

Abstract Simulations of crop yield due to climate change vary widely between models, locations, species, management strategies, and Representative Concentration Pathways (RCPs). To understand how climate and adaptation affects yield change, we developed a meta‐model based on 8703 site‐level process‐model simulations of yield with different future adaptation strategies and climate scenarios for maize, rice, wheat and soybean. We tested 10 statistical models, including some machine learning models, to predict the percentage change in projected future yield relative to the baseline period (2000–2010) as a function of explanatory variables related to adaptation strategy and climate change. We used the best model to produce global maps of yield change for the RCP4.5 scenario and identify the most influential variables affecting yield change using Shapley additive explanations. For most locations, adaptation was the most influential factor determining the projected yield change for maize, rice and wheat. Without adaptation under RCP4.5, all crops are expected to experience average global yield losses of 6%–21%. Adaptation alleviates this average projected loss by 1–13 percentage points. Maize was most responsive to adaptive practices with a projected mean yield loss of −21% [range across locations: −63%, +3.7%] without adaptation and −7.5% [range: −46%, +13%] with adaptation. For maize and rice, irrigation method and cultivar choice were the adaptation types predicted to most prevent large yield losses, respectively. When adaptation practices are applied, some areas are predicted to experience yield gains, especially at northern high latitudes. These results reveal the critical importance of implementing adequate adaptation strategies to mitigate the impact of climate change on crop yields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Influence of Vertical Hydrologic Exchange Flow, Channel Flow, and Biogeochemical Kinetics on CH 4 Emissions From Rivers

Abstract CH 4 emissions from inland water are highly uncertain in the current global CH 4 budget, especially for rivers and streams due to sparse measurements and the uncertainty of measurements caused by turbulent water flow. A previous study has revealed that vertical hydrologic exchange flow (VHEF) is the main regulator of CH 4 emissions from riverbed sediments. However, to what extent the understanding obtained from the plot‐scale can be extended to the reach scale and basin scale remains unknown. To address this challenge, we developed a process‐based model to estimate CH 4 flux at the air‐water interface using the attributes available in the national hydrography data set. It calculates the annual mean flux of VHEF, CH 4 production in sediments, and CH 4 transport in the river channel in a sequential manner. Model performance is evaluated by CH 4 efflux observed at the Hanford reach of the Columbia River. We show that reach‐wise sediment hydrologic and biogeochemical conditions estimated from the national hydrography data set could serve as a good indicator of CH 4 emissions from rivers. Aerobic methane oxidation and export to the downstream are the dominant ways of total CH 4 loss for the large lowland river. The hotspots of CH 4 emissions are likely to be at the reaches with fine sediments and slow channel velocity. This study demonstrates the possibility of quantifying CH 4 emissions at the reach scale and the modeling framework has the potential to be extended to the basin scale to improve estimates of CH 4 emissions from lotic inland water.

58 GEOSCIENCES↗
DOE OSTI2025

Advances in geophysical forensic event monitoring

Forensic analysis of man-made, non-nuclear events (such as industrial accidents, explosion experiments and mine collapses) has become more frequent and detailed owing to advancements in geophysical monitoring. Here, in this Technical Review, we demonstrate how geophysical forensic monitoring using seismic, infrasound and hydroacoustic recordings provides insights on events in the solid earth, atmosphere and underwater. Advanced techniques, including machine-learning-based models, have been developed to detect, identify and investigate these events, providing information on location, subevents, sources and explosive yield. The increase in data availability, application of advanced methods and computation and the growth of multitechnology approaches have increased the accuracy of forensic event analysis and enabled more realistic characterization of uncertainties. For example, the 2020 Beirut explosion in Lebanon demonstrated that various seismic, acoustic and other methods could be used to estimate explosive yield (and yield uncertainties) of about 1 ktonne, providing confidence in the application of these methods to smaller events where data are available. However, forensic investigations remain largely limited to known events with identified sources. Increased access to data, sophisticated analysis methods and high-resolution earth models will improve forensic event analysis further, enabling civil and scientific applications, such as localization in the search for the lost ARA San Juan submarine.

geophysics↗
DOE OSTI2015

A thermodynamic tank model for studying the effect of higher hydrocarbons on natural gas storage in metal-organic frameworks

Metal-organic frameworks (MOFs) are promising materials for storing natural gas in vehicular applications. Evaluation of these materials has focused on adsorption of pure methane, although commercial natural gas also contains small amounts of higher hydrocarbons such as ethane and propane, which adsorb more strongly than methane. There is, thus, a possibility that these higher hydrocarbons will accumulate in the MOF after multiple operating (adsorption/desorption) cycles, and reduce the storage capacity. To study the net effect of ethane and propane on the performance of an adsorbed natural gas (ANG) tank, we developed a mathematical model based on thermodynamics and mass balance equations that describes the state of the tank at any instant. The required inputs are the pure-component isotherms, and mixture adsorption data are calculated using the Ideal Adsorbed Solution Theory (IAST). We focused on how the "deliverable energy'' provided by the ANG tank to the engine changed over 200 operating cycles for a sample of 120 MOF structures. We found that, with any MOF, the ANG tank performance monotonically declines during early operating cycles until a "cyclic steady state'' is reached. We determined that the best materials when the fuel is 100% methane are not necessarily the best when the fuel includes ethane and propane. Among the materials tested, some top MOFs are MOF-143 > NU-800 > IRMOF-14 > IRMOF-20 > MIL-100 > NU-125 > IRMOF-1 > NU-111. MOF-143 is predicted to deliver 5.43 MJ L-1 of tank to the engine once the cyclic steady state is reached. The model also provided insights that can assist in future work to discover more promising adsorbent materials for natural gas storage.

Zhang, HD↗
DOE OSTI2011

Strange particle production at low and intermediate energies

The weak kaon production off the nucleon induced by neutrinos and antineutrinos is studied at low and intermediate energies of interest for some ongoing and future neutrino oscillation experiments. We develop a microscopical model based on the SU(3) chiral Lagrangians. The studied mechanisms are the main source of kaon production for neutrino energies up to 2 GeV for the various channels and the cross sections are large enough to be amenable to be measured by experiments such as Minerva, T2K and NOvA.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗