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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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A facile, scalable, wastewater-free synthesis of high energy density LiMn0.5Fe0.5PO4 (LMFP) cathodes with high electrode press density is achieved by employing the spinel LiMnFeO4 (LMFO) as a precursor.
Key insights in materials at extreme temperatures and pressures can be gained by accurate measurements that determine the electrical conductivity. Free-electron laser pulses can ionize and excite matter out of equilibrium on femtosecond time scales, modifying the electronic and ionic structures and enhancing electronic scattering properties. The transient evolution of the conductivity manifests the energy coupling from high temperature electrons to low temperature ions. Here we combine accelerator-based, high-brightness multi-cycle terahertz radiation with a single-shot electro-optic sampling technique to probe the evolution of DC electrical conductivity using terahertz transmission measurements on sub-picosecond time scales with a multi-undulator free electron laser. Our results allow the direct determination of the electron-electron and electron-ion scattering frequencies that are the major contributors of the electrical resistivity.
In 2015, the Lawrence Livermore National Laboratory started development of next-generation multiphysics simulation capabilities for the National Nuclear Security Administration under the Advanced Technologies Development and Mitigation (ATDM) element of the Advanced Simulation and Computing program in collaboration with the Exascale Computing Project (ECP). A key driver for this effort across the NNSA tri-lab was the emergence of advanced high performance computing (HPC) architectures based on heterogeneous compute capabilities, including GPU based systems, as part of the national drive toward exascale computing platforms at multiple Department of Energy (DOE) facilities. Developing a multiphysics code capable of meeting the various simulation needs of the NNSA as defined by the current generation of integrated codes (or ICs), initially developed as part of the Accelerated Strategic Computing Initiative (ASCI) program beginning in 1996, and able to scale to the current 100 petaflop class pre-exascale systems, as well the forthcoming exaflop class computers, is a daunting challenge. To accomplish this ambitious goal, LLNL has embraced two key themes: use of high-order numerical methods and a modular approach to code development. The LLNL next generation effort is organized under the Multi-Physics on Advanced Platforms Project (MAPP). A foundational component of MAPP is the Axom computer science (CS) toolkit which provides infrastructure for the development of modular, performance portable, multi-physics application codes. MARBL is a next-generation application code built on the Axom base to address the modeling needs of the high energy density physics (HEDP) community for simulating high-explosive, magnetic or laser driven experiments such as inertial confinement fusion (ICF), pulsed-power magneto-hydrodynamics (MHD), equation of state (EOS) and material strength studies as part of the NNSA’s stockpile stewardship program (SSP).
Metal-cluster surfaces present a wide variety of unique coordination environments. This complexity makes it difficult to manually probe the surface reactivity of such clusters. Here, we present a simple and automated method to systematically discover reaction pathways on cluster surfaces, based on the automated cluster surface scanning (ACSS) technique for mapping out potential energy surfaces. We showcase our method on 55-atom icosahedral Cu and Ag clusters, where we determine the activation energies of four elementary steps common in heterogeneous catalysis – hydrogen recombination (H* + H* → H 2 * + *), oxygen recombination (O* + O* → O 2 * + *), water formation (OH* + H* → H 2 O* + *), and CO oxidation (CO* + O* → CO 2 * + *) – with density functional theory calculations (DFT-PBE + D3). We show that the ACSS method requires significantly less human effort than the established manually performed climbing-image nudged elastic band (MP + CI-NEB) technique and locates transition states with comparable accuracy (root-mean-squared error of 0.10 eV) and similar computational cost. Rigorous sampling of the potential energy surface with the ACSS method allows one to locate all lowest-energy reaction pathways obtained via the MP+CI-NEB approach, as well as alternative pathways that one may have missed with the MP+CI-NEB approach due to the many possible pathways available on these clusters. The accuracy and efficiency afforded by the ACSS method could enable high-throughput exploration of the diverse reactivity of metal clusters.
The fluid mixing caused by variable-density instabilities is important in a wide variety of scenarios from ocean mixing and astrophysical phenomena to nuclear fusion techniques and atomic weapons. This thesis explores the mixing resulting from a specific instability known as the Blast Driven Instability (BDI). This work investigates the variable density mixing in an explosively driven environment due to the fluid instabilities at the material interfaces. Specifically, diverging Richtmyer-Meshkov (impulsive-acceleration environment) and Rayleigh-Taylor (variable-acceleration environment) instabilities (present in supernova and inertial confinement fusion) are studied using advanced high-speed diagnostics in carefully designed laboratory experiments. The BDI morphology is presented through a time development of Mie scattering images, and steps through the parameter space (varying density ratio and driver speed), highlighting the development of the structures that form during mixing. A scaling criterion is used to relate the two systems of vastly different spatiotemporal scales. Velocity fields in the BDI have been captured for the first time using the high temporal resolution PIV technique. Subsequent analysis of the dynamics of the instability from the velocity fields illustrates the distribution of kinetic energy, the transition to turbulence, and the characteristic growth of the instability are discussed. This study furthers understanding of how blast-driven instability pertains to supernova and inertial confinement fusion science. The morphology of the BDI has been characterized for the first time. This work steps through the parameter space covered in Mie scattering experiments, and how the different parameters contribute to development of structures and mixing. It also examines a scaling of the Atwood number for expanding predictive capabilities to other experimental conditions and simulations. The first collection of velocity fields acquired for the BDI are recorded, and subsequent analysis evaluating the distribution of kinetic energy throughout space and time for two density ratios from the overall parameter space, as well as the transition to turbulence, estimated from a Reynolds number calculated based on momentum mixing are all presented. This information is useful in advancing the development of models to predict physics of high energy density applications where experiments are not always readily available. This research has successfully demonstrated understanding for the time criteria defining regimes where the shock driven (Richtmyer-Meshkov instability) and the buoyancy driven (Rayleigh-Taylor instability) dominates through a parametric study of density variation (Atwood number) and driver speed (Mach number). All this furthers understanding of how the BDI pertains to SN and ICF.
Spacecraft historically have had sub-1kW(sub e), electrical requirements for GN&C, science, and communications: Galileo at 600W(sub e), and Cassini at 900W(sub e), for example. Because most missions have had the same order of magnitude power requirements, the Power Distribution Systems (PDS) use existing, space-qualified technology and are DC. As science payload and mission duration requirements increase, however, the required electrical power increases. Subsequently, this requires a change from a passive energy conversion (solar arrays and batteries) to dynamic (alternator, solar dynamic, etc.), because dynamic conversion has higher thermal and conversion efficiencies, has higher power densities, and scales more readily to higher power levels. Furthermore, increased power requirements and physical distribution lengths are best served with high-voltage, multi-phase AC to maintain distribution efficiency and minimize voltage drops. The generated AC-voltage must be stepped-up (or down) to interface with various subsystems or electrical hardware. Part of the trade-space design for AC distribution systems is volume and mass estimation of high-power transformers. The volume and mass are functions of the power rating, operating frequency, the ambient and allowable temperature rise, the types and amount of heat transfer available, the core material and shape, the required flux density in a core, the maximum current density, etc. McLyman has tabulated the performance of a number of transformers cores and derived a "cookbook" methodology to determine the volume of transformers, whereas Schawrze had derived an empirical method to estimate the mass of single-phase transformers. Based on the work of McLyman and Schwarze, it is the intent herein to derive an empirical solution to the volume and mass estimation of three-phase, laminated EI-core power transformers, having radiated and conducted heat transfer mechanisms available. Estimation of the mounting hardware, connectors, etc. is not included.
Chemical looping with oxygen uncoupling (CLOU) materials is actively sought for combustion of carbonaceous materials to achieve complete conversion and capture of carbon dioxide. These materials may play a vital role in reducing atmospheric carbon via negative carbon output. However, there is no one‐size‐fits‐all approach as different operating conditions and feedstocks may require different CLOU materials. As a result, the exploration and discovery of high‐performance CLOU materials can be a slow process. To address this challenge, a high‐throughput inverse machine learning workflow that identifies optimum materials from perovskite oxides for a given set of targets is developed—temperature and Gibbs free energy of oxygen formation. The model is trained on high‐throughput density functional theory calculations of CLOU materials and inverts the materials design process using a genetic algorithm to produce realistic substituted SrFeO 3‐δ compositions as output. Using the inverse model, it is able to identify several interesting new families of CLOU materials: Sr 1‐ x A x Fe 1‐ y B y O 3‐δ (e.g., A = Ca or K; B = Mg, Bi, Mn, Ni, Co, Cu, or Zn). These materials have shown promising properties, and some of them even outperform the benchmark material in terms of oxygen release kinetics under relevant CLOU operating conditions.
Global measurement of terrestrial snow cover is critical to two of the NASA Earth Science focus areas: (1) climate variability and change and (2) water and energy cycle. For radar backscatter measurements, Ku-band frequencies, scattered mainly within the volume of the snowpack, are most suitable for the SWE (snow-water equivalent) measurements. To isolate the complex effects of different snowpack (density and snowgrain size), and underlying soil properties and to distinctly determine SWE, the space-based synthetic aperture radar (SAR) system will require a dual-frequency (13.4 and 17.2 GHz) and dual polarization approach. A transmit/receive (T/R) module was developed operating at Ku-band frequencies to enable the use of active electronic scanning phased-array antenna for wide-swath, high-resolution SAR imaging of terrestrial snow cover. The T/R module has an integrated calibrator, which compensates for all environmental- and time-related changes, and results in very stable power and amplitude characteristics. The module was designed to operate over the full frequency range of 13 to 18 GHz, although only the two frequencies, 13.4 GHz and 17.2 GHz, will be used in this SAR radar application. Each channel of the transmit module produces > 4 W (35 dbm) over the operating bandwidth of 20 MHz. The stability requirements of <0.1 dB receive gain accuracy and <0.1 dB transmit power accuracy over a wide temperature range are achieved using a self-correction scheme, which does real-time amplitude calibration so that the module characteristics are continually corrected. All the calibration circuits are within the T/R module. The timing and calibration sequence is stored in a control FPGA (field-programmable gate array) while an internal 128K 8bit high-speed RAM (random access memory) stores all the calibration values. The module was designed using advanced components and packaging techniques to achieve integration of the electronics in a 2 x6.5x1-in. (5x17x2.5-cm) package. The module size allows 4 T/R modules to feed the 16 16-element subarray on an antenna panel. The T/R module contains four transmit channels and eight receive channels (horizontal and vertical polarizations).
Physical vapor deposition of organic explosives enables growth of polycrystalline films with a unique microstructure and morphology compared to the bulk material. This study demonstrates the ability to control crystal orientation and porosity in pentaerythritol tetranitrate films by varying the interfacial energy between the substrate and the vapor-deposited explosive. Additionally, variation in density, porosity, surface roughness, and optical properties is achieved in the explosive film, with significant implications for initiation sensitivity and detonation performance of the explosive material. Various surface science techniques, including angle-resolved X-ray photoelectron spectroscopy and multiliquid contact angle analysis, are utilized to characterize interfacial characteristics between the substrate and explosive film. Optical microscopy and scanning electron microscopy of pentaerythritol tetranitrate surfaces and fracture cross sections illustrate the difference in morphology evolution and the microstructure achieved through surface energy modification. X-ray diffraction studies with the Tilt-A-Whirl three-dimensional pole figure rendering and texture analysis software suite reveal that high surface energy substrates result in a preferred (110) out-of-plane orientation of pentaerythritol tetranitrate crystallites and denser films. Low surface energy substrates create more randomly textured pentaerythritol tetranitrate and lead to nanoscale porosity and lower density films. This work furthers the scientific basis for interfacial engineering of polycrystalline organic explosive films through control of surface energy, enabling future study of dynamic and reactive detonative phenomena at the microscale. Results of this study also have potential applications to active pharmaceutical ingredients, stimuli-responsive polymer films, organic thin film transistors, and other areas.
All-solid-state lithium batteries (ASSLBs) have the potential to increase energy density, improve safety, and allow for lower manufacturing costs compared to conventional, liquid-based Li-ion batteries. The thickness of solid electrolyte (SE) layer dictates the cell-level energy density and it is desirable to make the SE layer as thin as possible while maintaining uniformity and defect-free. Manufacturing a high- quality, thin sulfide SE layer at large-scale, however, is challenging. Previous studies have addressed the compatibility of materials used for manufacturing thin sulfide SE films, paving the way for further investigation of processing conditions and film quality. Here we report a strong correlation between the solid loading of dispersions and the quality of tape-casted thin sulfide SE films. We also demonstrate a method for quantifying the quality of thin SE films by observing both pin-hole defects and larger heterogeneous agglomerations of particles in the films. Our thin sulfide SE films containing ~5 wt% binder are defect-free and show similar ionic conductivity compared to a cold-pressed, binder-free, thick SE pellet, resulting in an ~11X reduction of area specific resistance. Here, this work on the solid loading of the dispersion used in a scalable tape casting process provides insight for manufacturing high-quality, thin sulfide SE films and to increase the cell-level energy density of ASSLB.
Abstract Lithium-sulfur all-solid-state batteries using inorganic solid-state electrolytes are considered promising electrochemical energy storage technologies. However, developing positive electrodes with high sulfur content, adequate sulfur utilization, and high mass loading is challenging. Here, to address these concerns, we propose using a liquid-phase-synthesized Li 3 PS 4 -2LiBH 4 glass-ceramic solid electrolyte with a low density (1.491 g cm −3 ), small primary particle size (~500 nm) and bulk ionic conductivity of 6.0 mS cm −1 at 25 °C for fabricating lithium-sulfur all-solid-state batteries. When tested in a Swagelok cell configuration with a Li-In negative electrode and a 60 wt% S positive electrode applying an average stack pressure of ~55 MPa, the all-solid-state battery delivered a high discharge capacity of about 1144.6 mAh g −1 at 167.5 mA g −1 and 60 °C. We further demonstrate that the use of the low-density solid electrolyte increases the electrolyte volume ratio in the cathode, reduces inactive bulky sulfur, and improves the content uniformity of the sulfur-based positive electrode, thus providing sufficient ion conduction pathways for battery performance improvement.
This talk introduced our research on developing sensing materials for harsh environmental applications. By combining first-principles density functional theory simulations with AI/ML approach, we have established a sensor database which can predict candidate materials at given operating conditions.
The high cost of density functional theory (DFT) has hitherto limited the ab initio prediction of the equation of state (EOS). In this article, we employ a combination of large scale computing, advanced simulation techniques, and smart data science strategies to provide an unprecedented ab initio performance analysis of the high explosive pentaerythritol tetranitrate (PETN). Comparison to both experiment and thermochemical predictions reveals important quantitative limitations of DFT for EOS prediction and thus the assessment of high explosives. In particular, we find that DFT predicts the energy of PETN detonation products to be systematically too high relative to the unreacted neat crystalline material, resulting in an underprediction of the detonation velocity, pressure, and temperature at the Chapman–Jouguet state. The energetic bias can be partially accounted for by high-level electronic structure calculations of the product molecules. Furthermore we demonstrate a modeling strategy for mapping chemical composition across a wide parameter space with limited numerical data, the results of which suggest additional molecular species to consider in thermochemical modeling.
Local lattice distortions (LLD) and structural stability of body-centered cubic (bcc) Nb–Ta–Ti–Hf high-entropy alloys (HEAs) are studied as functions of composition employing ab initio density-functional theory calculations, with specific focus on the role of the relative concentrations of group IV (Ti and Hf) versus group V (Nb and Ta) elements. Calculated results are presented as a function of composition x in Nb x Ta 0.25 Ti (0.75-x)/2 Hf (0.75-x)/2 alloys, for elastic moduli, phonon spectral functions, LLD and structural energy differences for the bcc and competing hexagonal close-packed (hcp) and ω phases. The results highlight the important role of group V elements and LLD in stabilizing the bcc structure. They further reveal how composition x can be tuned to alter both the magnitude of the LLD and structural energy differences. Specifically, the magnitude of the structural energy differences, and elastic and dynamic stability of the bcc phase, are enhanced with increasing x, while the LLD increase in magnitude as this concentration is decreased. The results also show evidence of correlated LLD at lower values of x, reflecting local structural distortions towards the ω phase, but not hcp. The degree of ω-collapse is nevertheless partial i.e., transformation towards this phase is not observed to be complete due to the presence of Ta and Nb. At lower values of x we further find an energy landscape characterized by multiple, nearly degenerate local energy minima for different values of the LLD.
The central importance of the nuclear data curated by the US Nuclear Data Program (USNDP) for clean energy generation, national security, nonproliferation, medical applications, and space exploration as well as basic science was described in a prior report issued by the DOE/NSF Nuclear Science Advisory Committee subcommittee on Nuclear Data (NSAC-ND) in September 2022. In this report, we present a set of fourteen (14) recommendations that will enhance and advance DOE-NP's stewardship of nuclear data. The first three recommendations focus on the existing core USNDP capabilities, namely: 1) Support the nuclear structure evaluation workforce to improve the currency, consistency, and accessibility of the Evaluated Nuclear Structure Data File (ENSDF); 2) Enhance nuclear reaction evaluation within the USNDP in support of the Evaluated Nuclear Data File (ENDF) through expansion of the workforce and integration of high-performance computing, automation, and machine learning and; 3) Continue atomic mass evaluation in support AME and NUBASE databases. This is followed by eight (8) recommendations representing new cross-cutting initiatives involving both measurement and evaluation to address outstanding nuclear data needs. These new initiatives require a highly trained, diverse workforce that includes personnel with expertise from both inside and outside the nuclear physics community from which evaluators have traditionally been recruited. As such, many of these initiatives are accomplished via a Topical Nuclear Data Collaborations (TNDC). A TNDC is made up of domestic and international stakeholders, subject matter and nuclear data experts, and nuclear data evaluators and features a workforce development plan to ensure that nuclear data evaluators maintain currency in the relevant applications and are seen as equity partners in the endeavor. These include: 1) Establish a coordinated effort to improve evaluation and modeling in nuclear astrophysics for stellar dynamics, multi-messenger astronomy and nucleosynthesis; 2) Initiate a TNDC to develop and maintain nuclear structure evaluation beyond discrete states, including nuclear level densities, photon strength functions and photonuclear data for improved reaction modeling, and exploring nuclear structure at finite temperature; 3) Create a TNDC to perform correlated fission data evaluation, including cross sections, fragment yields, v(A), v(E n ) for nuclear energy, national security, nonproliferation and basic science; 4) From a panel of subject matter experts to establish and annually update a roster of key decay data to nurture its accelerated dissemination including both measurement and evaluation for targeted high-value nuclides for national security, nonproliferation and medical applications; 5) Comprehensive, consistent neutron-induced structure and reaction data for nuclear energy, national security, nonproliferation and planetary nuclear spectroscopy; 6) Charged-particle stopping powers for detector design, space effects and ion beam therapy; 7) High-energy reactions for space exploration and medical nuclide production, and; 8) The creation of an infrastructure for open data and data preservation for use by the entire nuclear physics community. All told, these initiatives require approximately $6.5M increase in NP support of the USNDP in fiscal year 2023 dollars and would require at least 3-5 years to carry out due to the length of time needed to recruit and train new nuclear data researchers. This relatively modest investment would help ensure that the fruits of the nuclear data research carried out by DOE-NP and its collaborators would be brought to bear to address some of the most important needs of our nation and the world. To ensure effective execution of this plan, we present an overview of recruitment, training, and retention goals for the USNDP, the centerpiece of which is a mutually agreed upon code of conduct. Finally, we identify the facility and instrumentation needed to perform the recommended experimental activities. This includes a short review of target fabrication capabilities, reactors, neutron beam, light- and heavy-stable ion, gamma-ray, high-energy and radioactive ion beam facilities. Lastly, a more complete appendix of experimental facilities previously compiled is included with new input provided for 6 facilities.
Lithium iron phosphate (LiFePO 4 ) is widely applied as the cathode material for the energy storage Li-ion batteries due to its low cost and high cycling stability. However, the low theoretical specific capacity of LiFePO 4 makes its initial capacity loss more concerning. Therefore, lithium compensation by way of prelithiation and applications of sacrificial Li-rich additives in LiFePO 4 is imminent in elevating the energy density and/or prolonging the lifetime of the LiFePO 4 -based Li-ion batteries (LIBs). Prelithiation in LiFePO 4 is herein carried out by electrochemical and chemical methods and its feasibility is proved on the basis of the electrochemical evaluations such as the initial charge capacity and the cycling stability. In addition, the site of the pre-intercalated Li-ions is found via comprehensive physical characterizations and the density functional theory (DFT) calculations. Furthermore, these findings open a new avenue for elevating the energy density and/or prolonging the lifetime of the high-energy-density batteries.
In Li-excess transition-metal-oxide cathode materials, anionic oxygen redox can offer high capacity and high voltages, although peroxo and superoxo species may cause oxygen loss, poor cycling performance, and capacity fading. Previous work showed that undesirable formation of peroxide and superoxide bonds is controlled to some extent by Mn substitution, and the present work uses density functional calculations to examine the reasons for this by studying the anionic redox mechanism Li 8 MnO 6 . This material is obtained by substituting Mn for Sn in Li 8 SnO 6 or for Zr in Li 8 ZrO 6 , and we also compare to previous work on those materials. The calculations predict that Li 8 MnO 6 is stable at room temperature (with a band gap of 3.19 eV as calculated HSE06 and 1.82 eV as calculated with the less reliable with PBE+U), and they elucidate the chemical and structural effects involved in the inhibition of oxygen release in this cathode. Throughout the whole delithiation process, only O 2- ions are oxidized. The directional Mn-O bonds formed from unfilled 3d orbitals effectively inhibit the formation of O-O bonds, and the layered structure is maintained even after removing 3 Li per Li 8 MnO 6 formula unit. The calculated average voltage for removal of 3 Li is 3.69 V by HSE06, and the corresponding capacity is 389 mAh/g. The high voltage of oxygen anionic redox and the high capacity result in a high energy density of 1436 Wh/kg. The Li-ion diffusion barrier for the dominant interlayer diffusion path along the c-axis is 0.57 eV by PBE+U. Finally, these results help us to understand the oxygen redox mechanism in a new lithium-rich Li 8 MnO 6 cathode material and contribute to the design of high-energy-density lithium-ion-battery cathode materials with favorable electrochemical properties based on anionic oxygen redox.
Abstract Electrochemical CO 2 reduction (CO 2 R) is an attractive option for storing renewable electricity and for the sustainable production of valuable chemicals and fuels. In this roadmap, we review recent progress in fundamental understanding, catalyst development, and in engineering and scale-up. We discuss the outstanding challenges towards commercialization of electrochemical CO 2 R technology: energy efficiencies, selectivities, low current densities, and stability. We highlight the opportunities in establishing rigorous standards for benchmarking performance, advances in in operando characterization, the discovery of new materials towards high value products, the investigation of phenomena across multiple-length scales and the application of data science towards doing so. We hope that this collective perspective sparks new research activities that ultimately bring us a step closer towards establishing a low- or zero-emission carbon cycle.