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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

2023 Annual Report of Available Drawdowns for Each Oil Storage Cavern in the Strategic Petroleum Reserve

DOE maintains an up-to-date documentation of the number of available full drawdowns of each of the caverns at the U.S. Strategic Petroleum Reserve (SPR). This information is important for assessing the SPR’s ability to deliver oil to domestic oil companies expeditiously if national or world events dictate a rapid sale and deployment of the oil reserves. Sandia was directed to develop and implement a process to continuously assess and report the evolution of drawdown capacity, the subject of this report. This report covers impacts on drawdown availability due to SPR operations during Calendar Year 2022. A cavern has an available drawdown if, after that drawdown, the long-term stability of the cavern, the cavern field, or the oil quality are not compromised. Thus, determining the number of available drawdowns requires the consideration of several factors regarding cavern and wellbore integrity and stability, including stress states caused by cavern geometry and operations, salt damage caused by dilatant and tensile stresses, the effect of enhanced creep on wellbore integrity, and the sympathetic stress effect of operations on neighboring caverns. Finite-element geomechanical models have been used to determine the stress states in the pillars following successive drawdowns. By computing the tensile and dilatant stresses in the salt, areas of potential structural instability can be identified that may represent red flags for additional drawdowns. These analyses have found that many caverns will maintain structural integrity even when grown via drawdowns to dimensions resulting in a pillar-to-diameter ratio of less than 1.0. The analyses have also confirmed that certain caverns should only be completely drawn down one time. As the SPR caverns are utilized and partial drawdowns are performed to remove oil from the caverns (e.g., for oil sales, purchases, or exchanges authorized by the Congress or the President), the changes to the cavern caused by these procedures must be tracked and accounted for so that an ongoing assessment of the cavern’s drawdown capacity may be continued. A methodology for assessing and tracking the available drawdowns for each cavern is reiterated. This report is the latest in a series of annual reports, and it includes the baseline available drawdowns for each cavern, and the most recent assessment of the evolution of drawdown expenditures. A total of 222 million barrels of oil were released in calendar-year 2022. A nearly-equal amount of raw water was injected, resulting in an estimated 34 million barrels of cavern leaching. Twenty caverns have now expended a full drawdown. Cavern BC 18 has expended all its baseline available drawdowns, and has no drawdowns remaining. Cavern BM 103 has expended one of its two baseline drawdowns, and is now a single-drawdown cavern. All other caverns with an expenditure went from at-least-5 to at-least-4 remaining drawdowns.

02 PETROLEUM↗
DOE OSTI2023

Simulating organic aerosol in Delhi with WRF-Chem using the volatility-basis-set approach: exploring model uncertainty with a Gaussian process emulator

The nature and origin of organic aerosol in the atmosphere remain unclear. The gas–particle partitioning of semi-volatile organic compounds (SVOCs) that constitute primary organic aerosols (POAs) and the multigenerational chemical aging of SVOCs are particularly poorly understood. The volatility basis set (VBS) approach, implemented in air quality models such as WRF-Chem (Weather Research and Forecasting model with Chemistry), can be a useful tool to describe emissions of POA and its chemical evolution. However, the evaluation of model uncertainty and the optimal model parameterization may be expensive to probe using only WRF-Chem simulations. Gaussian process emulators, trained on simulations from relatively few WRF-Chem simulations, are capable of reproducing model results and estimating the sources of model uncertainty within a defined range of model parameters. In this study, a WRF-Chem VBS parameterization is proposed; we then generate a perturbed parameter ensemble of 111 model runs, perturbing 10 parameters of the WRF-Chem model relating to organic aerosol emissions and the VBS oxidation reactions. This allowed us to cover the model's uncertainty space and to compare outputs from each run to aerosol mass spectrometer observations of organic aerosol concentrations and O:C ratios measured in New Delhi, India. The simulations spanned the organic aerosol concentrations measured with the aerosol mass spectrometer (AMS). However, they also highlighted potential structural errors in the model that may be related to unsuitable diurnal cycles in the emissions and/or failure to adequately represent the dynamics of the planetary boundary layer. While the structural errors prevented us from clearly identifying an optimized VBS approach in WRF-Chem, we were able to apply the emulator in the following two periods: the full period (1–29 May) and a subperiod period of 14:00–16:00 h LT (local time) on 1–29 May. The combination of emulator analysis and model evaluation metrics allowed us to identify plausible parameter combinations for the analyzed periods. We demonstrate that the methodology presented in this study can be used to determine the model uncertainty and to identify the appropriate parameter combination for the VBS approach and hence to provide valuable information to improve our understanding of OA production.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Full circle mechanical dynamic characterization including experimental modal analysis and finite element analysis

During operation, it was observed that a specific mechanical system experienced undesirable vibration and it became necessary to understand and mitigate this phenomenon. This document investigates the tools, methodology, and results of the dynamic characterization of the system. The characterization makes use of the experimental modal analysis (EMA) methods of single input multiple output (SIMO) and single input single output (SISO). The validity of the theory of reciprocity is confirmed to minimize measurement error, cost, and time of repeat testing. Finite element analysis (FEA) is used in choosing transducer and modal impact locations to adequately characterize the system. Single degree of freedom (SDOF) and multiple degree of freedom (MDOF) curve fitting is used to fully characterize the system’s mode shapes and natural frequencies. The EMA characterization results are used to modify and validate the FEA model so that FEA can be used to model potential structural modifications to the system to mitigate the undesirable vibration. Structural modifications are chosen, implemented, and their effectiveness is quantified using EMA. Finally, a qualitative evaluation of the methodology of FEA validation by EMA and tuning of the model to match the experimental results is discussed.

42 ENGINEERING↗
DOE OSTI2021

Correlating Li-Ion Solvation Structures and Electrode Potential Temperature Coefficients

Temperature coefficients (TCs) for either electrochemical cell voltages or potentials of individual electrodes have been widely utilized to study the thermal safety and cathode/anode phase changes of lithium (Li)-ion batteries. However, the fundamental significance of single electrode potential TCs is little known. Here, we discover that the Li-ion desolvation process during Li deposition/intercalation is accompanied by considerable entropy change, which significantly contributes to the measured Li/Li + electrode potential TCs. To explore this phenomenon, we compare the Li/Li + electrode potential TCs in a series of electrolyte formulations, where the interaction between Li-ion and solvent molecules occurs at varying strength as a function of both solvent and anion species as well as salt concentrations. As a result, we establish correlations between electrode potential TCs and Li-ion solvation structures and further verify them by ab initio molecular dynamics simulations. We show that measurements of Li/Li + electrode potential TCs provide valuable knowledge regarding the Li-ion solvation environments and could serve as a screening tool when designing future electrolytes for Li-ion/Li metal batteries.

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

Structural Characterization of Potential Carbon Dioxide Reservoirs and Adjacent Strata within the Llandovery Silurian to Middle Devonian Strata of Ohio

The Midwest Regional Carbon Sequestration Partnership (MRCSP) has incorporated the work of geologic research teams (Geoteams) in its regional characterization, project planning and carbon dioxide (CO 2 ) injection implementation work since the partnership was established by the U.S. Department of Energy (DOE) in 2003. Over this 16-year period, the cohort of Geoteams has grown from five to ten states and has contributed to the characterization of geologic sequestration opportunities, refinement of reservoir and seal data, and supported injection efforts through both predictive and post-injection assessments. This report details the work led by the Ohio Department of Natural Resources, Division of Geological Survey to evaluate the structure of nine formations in the Appalachian Basin of Ohio to assess seal integrity and whether carbon dioxide (CO 2 ) migration pathways could pose a potential risk. As part of Phase II MRCSP work, the Pennsylvania Geological Survey led the characterization of the Llandovery Silurian (“middle Silurian”) to Middle Devonian regional geologic characterization CO 2 utilization and storage. This preliminary assessment included generalized, regional-scale mapping, as well as the development of relatively coarse structure and isochore maps of stratigraphic intervals of interest for the Appalachian Basin. Because this stratigraphic interval offers several enhanced oil recovery targets and secondary targets for CO 2 storage, the Ohio Geological Survey undertook efforts in Phase III to characterize the Ohio’s portion of the Appalachian Basin more precisely and to resolve inconsistencies within Ohio’s formation tops. This study refined the subsurface correlations of the Silurian-through-Devonian stratigraphic section in Ohio. Higher-resolution isochore mapping of the CO 2 storage reservoirs and seals provides greater detail of potential high-porosity zones and potential structural influence on the interval.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Crystal Structure Prediction of Binary Alloys via Deep Potential

Predicting crystal structure has been a challenging problem in physics and materials science for a long time. A reliable energy calculation engine combined with an efficient global search algorithm, such as particle swarm optimization algorithm or genetic algorithm, is needed to conduct crystal structure prediction. In recent years, machine learning-based interatomic potential energy surface models have been proposed, potentially allowing us to perform crystal structure prediction for systems with the accuracy of density functional theory (DFT) and the speed of empirical force fields. In this paper, we employ a previously developed Deep Potential model to predict the intermetallic compound of the aluminum–magnesium system, and find six meta-stable phases with negative or nearly zero formation energy. In particular, Mg 12 Al 8 shows excellent ductility and Mg 5 Al 27 has a high Young's modulus. Based on our benchmark results, we propose a relatively robust structure screening criterion that selects potentially stable structures from the Deep Potential-based convex hull and performs DFT refinement. By using this criterion, the computational cost needed to construct the convex hull with ab initio accuracy can be dramatically reduced.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Flexible machine-learning interatomic potential for simulating structural disordering behavior of Li 7 La 3 Zr 2 O 12 solid electrolytes

Batteries based on solid-state electrolytes, including Li 7 La 3 Zr 2 O 12 (LLZO), promise improved safety and increased energy density; however, atomic disorder at grain boundaries and phase boundaries can severely deteriorate their performance. Machine-learning (ML) interatomic potentials offer a uniquely compelling solution for simulating chemical processes, rare events, and phase transitions associated with these complex interfaces by mixing high scalability with quantum-level accuracy, provided that they can be trained to properly address atomic disorder. To this end, we report the construction and validation of an ML potential that is specifically designed to simulate crystalline, disordered, and amorphous LLZO systems across a wide range of conditions. The ML model is based on a neural network algorithm and is trained using ab initio data. Performance tests prove that the developed ML potential can predict accurate structural and vibrational characteristics, elastic properties, and Li diffusivity of LLZO comparable to ab initio simulations. As a demonstration of its applicability to larger systems, we show that the potential can correctly capture grain boundary effects on diffusivity, as well as the thermal transition behavior of LLZO. Here these examples show that the ML potential enables simulations of transitions between well-defined and disordered structures with quantum-level accuracy at speeds thousands of times faster than ab initio methods.

25 ENERGY STORAGE↗
DOE OSTI2026

Development of Machine-Learned Interatomic Potentials to Predict Structure, Transport, and Reactivity in Platinum-Based Fuel Cells

Machine-learned interatomic potentials (MLIPs) have rapidly progressed in accuracy, speed, and data efficiency in recent years. However, training robust MLIPs in multicomponent systems remains a challenge. In this work, we train an MLIP to describe hydrated Nafion ionomers and platinum catalysts, which are important components of fuel cells, by constructing a diverse training set to describe the bulk polymer and interfacial catalyst–polymer interactions well. We use our trained MLIP to study the properties of the platinum–Nafion system, including polymer structure, proton mobility in a bulk Nafion polymer and near a platinum-Nafion interface, and reactions near and far from the interface, finding excellent results for structure and reactions contained within our training set. Transport seems to be well described, with both vehicular transport and Grotthuss hopping captured, although converged calculations of diffusivities were not computed because they require calculations of tens of nanoseconds that are challenging with current state-of-the-art MLIPs. The combined insights that this model provides can be leveraged to optimize fuel cell performance, and the approach can be applied to other chemical processes and devices where structure, transport, and reactivity all contribute to the overall observed performance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Correlation between Redox Potential and Solvation Structure in Biphasic Electrolytes for Li Metal Batteries

The activity of lithium ions in electrolytes depends on their solvation structures. However, the understanding of changes in Li + activity is still elusive in terms of interactions between lithium ions and solvent molecules. Herein, the chelating effect of lithium ion by forming [Li(15C5)] + gives rise to a decrease in Li + activity, leading to the negative potential shift of Li metal anode. Moreover, weakly solvating lithium ions in ionic liquids, such as [Li(TFSI) 2 ] - (TFSI = bis(trifluoromethanesulfonyl)imide), increase in Li + activity, resulting in the positive potential shift of LiFePO 4 cathode. This allows the development of innovative high energy density Li metal batteries, such as 3.8 V class Li | LiFePO 4 cells, along with introducing stable biphasic electrolytes. In addition, correlation between Li + activity, cell potential shift, and Li + solvation structure is investigated by comparing solvated Li + ions with carbonate solvents, chelated Li + ions with cyclic and linear ethers, and weakly solvating Li + ions in ionic liquids. These findings elucidate a broader understanding of the complex origin of Li + activity and provide an opportunity to achieve high energy density lithium metal batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Moving beyond the constraints of chemistry via crystal structure discovery with isotropic multiwell pair potentials

The rigid constraints of chemistry-dictated by quantum mechanics and the discrete nature of the atom-limit the set of observable atomic crystal structures. What structures are possible in the absence of these constraints? Here, we systematically crystallize one-component systems of particles interacting with isotropic multiwell pair potentials. We investigate two tunable families of pairwise interaction potentials. Our simulations self-assemble a multitude of crystal structures ranging from basic lattices to complex networks. Sixteen of the structures have natural analogs spanning all coordination numbers found in inorganic chemistry. Fifteen more are hitherto unknown and occupy the space between covalent and metallic coordination environments. The discovered crystal structures constitute targets for self-assembly and expand our understanding of what a crystal structure can look like.

crystal structures↗
DOE OSTI2025

Crystal structure prediction with host-guided inpainting generation and foundation potentials

Unconditional crystal structure generation with diffusion models faces challenges in identifying symmetric crystals as the unit cell size increases. Here, we present the crystal host-guided generation (CHGGen) framework to address this challenge through conditional generation using an inpainting method, which optimizes a fraction of atomic positions within a predefined and symmetrized host structure to improve the success rate for symmetric structure generation. By integrating inpainting structure generation with a foundation potential for structure optimization, we demonstrate the method on the ZnS–P 2 S 5 and Li–Si chemical systems, where the inpainting method generates a higher fraction of symmetric structures than unconditional generation. The practical significance of CHGGen extends to enabling the structural modification of crystal structures, particularly for systems with partial occupancy or intercalation chemistry. The inpainting method also allows for seamless integration with other generative models, providing a versatile framework for accelerating materials discovery.

Zhong, Peichen [University of California, Berkeley↗
DOE OSTI2020

Quantitative investigation of surface structure and interatomic potential with impact-collision ion scattering spectroscopy

Helium ion beam interactions with materials have important implications for magnetic confinement fusion, material modification, and helium ion microscopy. These interactions depend on the precise physics of how helium ions channel into the materials, which can vary greatly based on the local crystalline orientation. Here, we performed a dedicated experiment to investigate helium ion channeling in a well-characterized tungsten single crystal. Time-of-flight impact-collision ion scattering spectroscopy was used to obtain multi-angle maps of the backscattering intensity for 3 keV He + → W(111). We found that the backscattering intensity profile arising from helium ion channeling could be well described by a shadow cone analysis. This analysis revealed that subsurface W atoms as deep as the ninth monolayer contributed to the backscattering intensity profile. Binary collision approximation simulations were performed with MARLOWE to model the experimental maps with sufficient accuracy to allow for quantitative comparisons using reliability factors. These quantitative comparisons were applied to investigate how the W lattice structure and He–W interatomic potential affect the multi-angle maps.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Structural Characterization of Potential Carbon Dioxide Reservoirs and Adjacent Strata within the Llandovery Silurian to Middle Devonian Strata of Ohio

As part of the Midwest Regional Carbon Sequestration Partnership (MRCSP)’s regional characterization project, the Ohio Department of Natural Resources, Division of Geological Survey evaluated the structure of nine formations in the Appalachian Basin of Ohio to assess seal integrity and whether carbon dioxide (CO 2 ) migration pathways could pose a potential risk.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Deep-Learning Interatomic Potential Connects Molecular Structural Ordering to the Macroscale Properties of Polyacrylonitrile

Polyacrylonitrile (PAN) is an important commercial polymer, bearing atactic stereochemistry resulting from nonselective radical polymerization. As such, an accurate, fundamental understanding of governing interactions among PAN molecular units is indispensable for advancing the design principles of final products at reduced processability costs. While ab initio molecular dynamics (AIMD) simulations can provide the necessary accuracy for treating key interactions in polar polymers, such as dipole–dipole interactions and hydrogen bonding, and analyzing their influence on the molecular orientation, their implementation is limited to small molecules only. Herein, we show that the neural network interatomic potentials (NNIPs) that are trained on the small-scale AIMD data (acquired for oligomers) can be efficiently employed to examine the structures and properties at large scales (polymers). NNIP provides critical insight into intra- and interchain hydrogen-bonding and dipolar correlations and accurately predicts the amorphous bulk PAN structure validated by modeling the experimental X-ray structure factor. Furthermore, the NNIP-predicted PAN properties, such as density and elastic modulus, are in good agreement with their experimental values. Overall, the trend in the elastic modulus is found to correlate strongly with the PAN structural orientations encoded in the Hermans orientation factor. In conclusion, this study enables the ability to predict the structure–property relations for PAN and analogues with sustainable ab initio accuracy across scales.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Relationship between atomic and electronic structure in Ln-bearing oxides

Metastable states of matter are of great interest as they offer the promise of novel functionality. They are often a natural consequence of exposure to nonequilibrium environments. In oxides, metastability can take the form of new polymorphs, chemical disorder, and even amorphization. While significant attention has been given to the impact those changes have on the atomic properties of the material, the corresponding changes in the electronic structure have received less attention. Here, using density functional theory, we consider how the electronic structure varies with potential metastable structures in two classes of lanthanide-bearing oxides—pyrochlores and interlanthanide sesquioxides. We find that the changes depend strongly on both the crystal structure and crystal chemistry of the compound with, for example, disordering and amorphization either increasing or decreasing the bandgap depending on the chemistry. For the 𝐴 2 ⁢𝐵 2 ⁢O 7 pyrochlores, we find different dependencies of the bandgap on the 𝐴 = 𝐿⁢𝑛 cations as the 𝐵 cation is changed, which we relate to the nature of the density of states at the conduction band minimum for different 𝐵 chemistries. Our calculations are validated by electron energy loss spectroscopy measurements for two pyrochlore compounds in which amorphization does reduce the bandgap, consistent with our calculations on these two compounds. In conclusion, our results highlight the relationship between atomic and electronic structure and how radiation can be used to modify and potentially control the electronic properties of oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2021

On the Equilibrium Electrostatic Potential and Light-Induced Charge Redistribution in Halide Perovskite Structures

Lead halide perovskites are semiconductor materials which are employed as nonintentionally doped absorbers inserted between two selective carrier transport layers (SCTL), realizing a p-i-n or n-i-p heterojunction. In our study, we have developed and investigated a lateral device, based on methylammonium lead iodide (MAPbI3) in which the p-i-n heterojunction develops in the horizontal direction. Our research suggests that the effective doping level in the MAPbI3 film should be very low, below 1012 cm-3. Along the vertical direction, this doping level is not enough to screen the electric field of the buried heterojunction with the SCTL. The perovskite work function is therefore affected by the work function of the SCTL underneath. From drift-diffusion simulations, we show that intrinsic perovskite-SCTL structures develop mV range surface photovoltages (SPVs) under continuous illumination. However, perovskite-SCTL structures can develop SPVs of hundreds of mV, as confirmed by our measurements. We therefore analyzed the compatibility between low doping and low defect densities in the perovskite layer and such high SPV values using numerical modeling. It is shown that these high SPV values could originate from electronic processes due to large band offsets in the buried perovskite-SCTL heterojunctions, or at the SCTL-transparent conductive oxide (TCO) buried heterojunction. However, such electronic processes can hardly explain the long SPV persistence after switching off the illumination.

defects↗
DOE OSTI2022

Structures of Vanadium-Containing Silicate and Borosilicate Glasses: Vanadium Potential Development and MD Simulations

Vanadium-containing multi-component glasses have been found with widely interests in various applications. However, the complex compositions, thus structures, lead to the challenges in experiments to understand the structural origin of the property change of these glasses. In this work, we developed compatible vanadium-related parameters for a widely used pair wise potential set to enable the simulations of the vanadium-containing multi-component glasses. Various crystal structures and glass compositions (with vanadium in different oxidation states) have been tested using the newly developed parameters, and structural information of cell parameters, pair distribution function, estimated bond distance, and coordination number have been obtained. The results are in good agreement with available experimental data, which indicates the new vanadium parameters can be used to simulate the vanadium-containing multi-component glasses and thus help study those applications with wide interests.

Deng, Lu↗