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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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High Pressure Effect on Structural and Electrochemical Properties of Anionic Redox-Based Lithium Transition Metal Oxides
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Inhibit the strain accumulation for 5V spinel cathode by mitigating the phase separation during high voltage stage
LiNi 0.5 Mn 1.5 O 4 (LNMO) spinel cathode is a potential cathode material for high-power, low-cost lithium-ion batteries (LIBs) due to its low raw material cost, high operating voltage and efficient lithium-ion transport channel. However, LNMO suffers from structural stability due to the two-phase-transformation during charge/discharge process, leading to poor cycling performance. Here, to address the issues, we have constructed a homogeneous aggregated LNMO cathode with a multifaceted primary particle, namely the LNMO with single-crystal secondary particles (SSP LNMO). Ex situ and in situ characterizations including the synchrotron X-ray diffraction, the neutron diffraction and full pouch cell validated that the SSP LNMO exhibit a single solid-solution reactions with a restrained lattice evolution during the delithiation/lithiation process. This is in contrast to the normal LNMO cathode, which demonstrates a significant two-phase transition from spinel Li 1-x Ni 0.5 Mn 1.5 O 4 to rock-salt MnO 2 at high voltage. Therefore, the SSP LNMO has greatly improved cycle life compared to the normal LNMO cathode. Overall, this study demonstrates the possibility of constructing LNMO based on primary-grain morphology modulation to improve the intrinsic stability of LIBs.
Regenerable solvents mediate accelerated low temperature CO 2 capture and carbon mineralization of ash and nano-scale calcium carbonate formation
The dual need to remove CO 2 from our emissions and treat alkaline industrial residues such as ash materials motivate the design of innovative pathways to simultaneously capture and convert CO 2 into mineralized carbonates. Direct carbon mineralization is one approach that addresses the need to simultaneously treat alkaline industrial residues and mineralize CO 2 emissions. Low CO 2 solubility in water and slow kinetics at ambient temperature have challenged the direct carbon mineralization of alkaline industrial residues. Here, to address these challenges, the use of CO 2 capture solvents that enhance CO 2 solubility and facilitate accelerated carbon mineralization of fly ash at temperatures below 90 °C is investigated. Calcium carbonate formation results in the inherent regeneration of the solvent. The carbon mineralization extents of non-calcium carbonate content in fly ash were 50% and 51% and in waste ash were 58% and 62% in 2.5 M sodium glycinate and 30 wt% MEA solutions, respectively. The experiments were performed at 50 °C for 3 hours with CO 2 partial pressure of 1 atm in a continuously stirred slurry environment with 15 wt.% solid. Furthermore, nanoscale CaCO 3 is successfully synthesized from dissolved calcium using CO 2 -loaded sodium glycinate and surfactants such as CTAB (Cetyl Trimethyl Ammonium Bromide). Surfactants such as CTAB bind to the calcium carbonate surface and regulate the growth of calcium carbonate particles. These innovative approaches demonstrate the feasibility of directly storing CO 2 in fly ash and waste ash as calcium carbonate and producing nanoscale calcium carbonate using regenerable CO 2 capture solvents.
DFAT: A web-based toolkit for estimating demand flexibility in building-to-grid integration
Demand Flexibility Assessment Tool (DFAT) is an open source web-based tool that estimates the demand flexibility potential of common control strategies in commercial buildings. The toolkit features a demand flexibility estimation tool that contains two calculators, basic and advanced, based on the level of input of customer data. The basic version calculates demand shed metrics for the control strategy “global temperature adjustment” and “cycle on/off compressors” using customer building information, local weather data, and electrical meter data. The advanced version, which uses detailed HVAC equipment data, calculates demand flexibility metrics for control strategies such as static pressure reset, global temperature adjustment, and cycle on/off compressors. In addition to the demand flexibility estimation tool, this toolkit offers a benchmarking tool that helps facility operators, aggregators, and utility resource managers assess demand flexibility opportunities, quantify/verify performance, and compare their performance against that of their peers.
Comparative evaluation of deep learning workloads for leadership-class systems
Deep learning (DL) workloads and their performance at scale are becoming important factors to consider as we design, develop and deploy next-generation high-performance computing systems. Since DL applications rely heavily on DL frameworks and underlying compute (CPU/GPU) stacks, it is essential to gain a holistic understanding from compute kernels, models, and frameworks of popular DL stacks, and to assess their impact on science-driven, mission-critical applications. At Oak Ridge Leadership Computing Facility (OLCF), we employ a set of micro and macro DL benchmarks established through the Collaboration of Oak Ridge, Argonne, and Livermore (CORAL) to evaluate the AI readiness of our next-generation supercomputers. In this paper, we present our early observations and performance benchmark comparisons between the Nvidia V100 based Summit system with its CUDA stack and an AMD MI100 based testbed system with its ROCm stack. We take a layered perspective on DL benchmarking and point to opportunities for future optimizations in the technologies that we consider.
Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19
In this work, we present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.
UiO-66 Metal–Organic Framework as an Anode for a Potassium-Ion Battery: Quantum Mechanical Analysis
The natural abundance of potassium in the earth’s crust is 1000 times higher than that of lithium, so energy technologies built on potassium are more sustainable. Potassium-ion batteries have attracted considerable attention because of their relatively low cost and high operating potential, but questions remain about the best anode material for such batteries. Here, in this paper, we report first-principles computations based on density functional theory to investigate the performance of the UiO-66 metal–organic framework as an anode material for potassium-ion batteries; the goal is to provide a fundamental understanding of metal–organic framework (MOF)-based electrodes to guide the design and development of high-performance potassium-ion batteries. Our study includes the stability and electronic properties of potassiated structures and the mechanisms of potassium intercalation and diffusion in the framework. The results indicate that UiO-66 has a maximum specific capacity of 644 mAh/g as the anode of a potassium-ion battery. During potassiation, we observe charge transfer from potassium to carbon or oxygen of UiO-66 near the intercalated K. During K diffusion, the K migrates along the UiO-66 framework with a maximal migration energy barrier of 0.377 eV in the optimal pathway, which is much lower than the barriers for Li and Na diffusion in UiO-66. The diffusion coefficient of K in the anode is several orders of magnitude larger than those of Li and Na. This favors potassium ions over lithium ions or sodium ions when UiO-66 is the anode.
Metallization of Quantum Material GaTa4Se8 at High Pressure
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Synthesis of Atomically Thin Hexagonal Diamond with Compression
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Bioresorbable Primary Battery Anodes Built on Core–Double-Shell Zinc Microparticle Networks
Bioresorbable implantable electronics require power sources that are also bioresorbable with controllable electrical output and lifetime. In this paper, we report a bioresorbable zinc primary battery anode filament based on a zinc microparticle (MP) network coated with chitosan and Al 2 O 3 double shells. When discharged in 0.9% NaCl saline, a Zn MP filament with a 0.17 × 2 mm 2 cross-sectional area exhibited a stable voltage output of 0.55 V at a current of 0.01 mA. Covered by chitosan and Al 2 O 3 double shells, the zinc MP filament exhibited a directional dissolution behavior with a tunable lifetime approximately linear to its length. A stable 200 h discharging time was achieved with a 15 mm Zn MP filament. The maximum output power was found to be 12 μW at 0.03 mA for one filament. The linearity relationship between the current output and the filament cross-sectional area suggested a facile strategy to raise the power output at constant discharging voltage. The filaments could also be connected in series and in parallel to boost its overall voltage and current output, demonstrating their excellent integration capability. Furthermore, this work presents a promising pathway toward bioresorbable transient batteries with controllable lifetime and power output, demonstrating a great potential for powering transient implantable biomedical devices.
Li 8 MnO 6 : A Novel Cathode Material with Only Anionic Redox
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.
Stress- and interface-compatible red phosphorus anode for high-energy and durable sodium-ion batteries
Sodium-ion battery is a promising candidate for energy storage application, but the absence of high-capacity and low-cost anode materials significantly limit their practical specific energy and cost. Red phosphorus (RP) possesses a high theoretical specific capacity but suffers from large volume change, low electronic conductivity and unstable solid-electrolyte interphase (SEI). Herein, a hierarchical micro/nanostructured antimony-doped RP/carbon anode was developed, which demonstrate extraordinary electrochemical performance with high initial Coulombic efficiency of ~90%, high areal (~1.7 mAh cm-2) capacity together with good cycle stability and rate capability. Combined experimental and computational studies consistently revealed that such a unique structural design can dramatically accommodate the mechanical stress and moreover effectively restrain the undesired decomposition of electrolyte solvents regardless of electrolytes formulation, resulting in superior structural integrity and thin/robust SEI formation during cycling. The present finding has offered an alternative strategy for stress management and interface engineering on high-capacity alloying-based anode materials.
Enzymatic β-Oxidation of the Cholesterol Side Chain in Mycobacterium tuberculosis Bifurcates Stereospecifically at Hydration of 3-Oxo-cholest-4,22-dien-24-oyl-CoA
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Nicotine Monitoring with a Wearable Sweat Band
The tobacco epidemic is a public health threat that has taken a heavy toll of lives around the globe each year. Smoking affects both the smokers and those who are exposed to secondhand smoke, and careful tracking of exposure can be key to mitigating the potential hazards. For smokers, the variation of chemical compositions between commercial cigarettes has led to ambiguity in estimating the health risks, both for active smokers and others involuntarily exposed to tobacco smoke and byproducts. In this regard, sweat possesses an attractive opportunity to monitor smoke exposure due to sweat's abundance in biomolecules and its great accessibility. In this paper, we present a wearable sweat band to monitor nicotine, a prominent ingredient in cigarettes, as a viable way to quantitatively assess a wearer's exposure to smoking. Both smokers and normal subjects are tested to demonstrate the use of this device for smoke-related health monitoring. Our results exhibit confirmable and elevated nicotine levels in sweat for subjects inhaling cigarette smoke. This continuous and personalized sweat sensing device is leverage to monitor smoke pollution for a potentially broad population.
Reconciling Contrasting Relationships Between Relative Dispersion and Volume-Mean Radius of Cloud Droplet Size Distributions
Cloud droplet spectral relative dispersion is critical to parameterizations of cloud radiative properties, warm-rain initiation, and aerosol-cloud interactions in models; however, there is no consistent relationship between relative dispersion and volume-mean radius in literature, which hinders improving relative dispersion parameterization and calls for physical explanation. Here we show, by analyzing aircraft observations of cumulus clouds during Routine AAF [Atmospheric Radiation Measurement (ARM) Aerial Facility] Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations, that the correlation between relative dispersion and volume-mean radius changes from positive to negative as volume-mean radius increases. With the new observation, we postulate that the sign of the correlation is determined by whether or not condensation (evaporation) occurs simultaneously with significant new activation (deactivation). The hypothesis is validated by simulations of both an adiabatic cloud parcel model and a parcel model accounting for entrainment-mixing. A new quantity, first bin strength, is introduced to quantify this new observation. Theoretical analysis of truncated gamma and modified gamma size distributions further supports the hypothesis and reconciles the contrasting relationships between relative dispersion and volume-mean radius, including the results in polluted fog observations. The results could shed new light on the so-called “twilight zone” between cloudy and cloud-free air, which in turn affects evaluation of aerosol-cloud interactions and retrieval of aerosol optical depth.
Orbital-selective Dirac fermions and extremely flat bands in frustrated kagome-lattice metal CoSn
Layered kagome-lattice 3d transition metals are emerging as an exciting platform to explore the frustrated lattice geometry and quantum topology. However, the typical kagome electronic bands, characterized by sets of the Dirac-like band capped by a phase-destructive flat band, have not been clearly observed, and their orbital physics are even less well investigated. Here, we present close-to-textbook kagome bands with orbital differentiation physics in CoSn, which can be well described by a minimal tight-binding model with single-orbital hopping in Co kagome lattice. The capping flat bands with bandwidth less than 0.2 eV run through the whole Brillouin zone, especially the bandwidth of the flat band of out-of-plane orbitals is less than 0.02 eV along Γ-M. The energy gap induced by spin-orbit interaction at the Dirac cone of out-of-plane orbitals is much smaller than that of in-plane orbitals, suggesting orbital-selective character of the Dirac fermions.