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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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This chapter provides a broad overview of the various computational modeling techniques used to gain fundamental insights into coupled electrochemical processes that occur in battery materials at electronic-to-mesoscopic scales. Furthermore, representative successes of these techniques in modeling electrodes, electrolytes, and electrode-electrolyte interfaces are highlighted to establish the current state-of-the-art in the field.
Here in this work, a dynamic, multidomain, multiscale model of a novel Partial Pressure and Temperature Swing Adsorptive Reactor (PPTSAR) Process is developed and simulated for a Water Gas Shift Reaction (WGSR) application. The proposed model couples the reactor wall, catalyst/adsorbent pellet, and fluid mixture domains at their respective scales to comprehensively model mass, momentum, and energy transport phenomena occurring within each domain. The resulting model elucidates the PPTSAR’s start-up, transient, and long-term, periodic, dynamic behavior, during both adsorption/reaction and desorption operating modes. In the WGSR application considered, the use of two PPTSARs is shown to allow continuous operation that delivers CO conversion greater than 95% with simultaneous complete CO 2 capture.
The electrochemical performance of vanadium redox flow batteries (VRFBs) was enhanced via laser-patterned graphite felt (GF) electrodes. The laser-structured GF electrodes engineered via preparing a series of well-ordered microscopic channel structures with an average width of 200 μm, creating a three-dimensional carbon framework. The ultrafast laser patterning increased the porosity by 10%, as compared to pristine electrode. The analysis of the overpotential distribution using electrochemical impedance spectroscopy revealed that the electrode polarization involving charge transfer and diffusion resistance is strongly alleviated with the aid of carbon micro-perforation. The advanced design of laser-structured GF electrode also exhibits high rate capability, low internal resistance, and excellent cyclability. The improved performance was attributed to the synergistic effect involving (i) high electrochemically active surface area for rapid electrochemical reactions (i.e., V(II)/V(III) and V(IV)/V(V) redox couples) and (ii) excellent transport properties for facile electron/ion/species transport. The micro-scale channels created with the laser-ablation technique act as capillary structures and enabled homogeneous and rapid wetting of GF electrodes as formulated with the classical Washburn equation. The VRFB equipped with the laser-structured GF electrodes delivered a high discharge capacity with exceptional capacity retention upon extended cycling (>84.9%). In conclusion, accordingly, the design of laser-structured electrode paves the pathway towards finely tuning the electrode internal microstructure for improved cyclability, durability, and capacity retention in various electrochemical energy storage/conversion devices (e.g. all-vanadium redox flow batteries).
A lab-scale 316/L stainless steel diffusion-bonded heat exchanger was examined within a coupled high-temperature test facility consisting of an atmospheric-pressure nitrate salt loop and a supercritical carbon dioxide (sCO 2 ) loop operating between 10 and 16 MPa. Pressure loss measurements collected for flow rates up to 0.55 kg/s of Solar Salt and up to 0.6 kg/s of carbon dioxide were used to generate friction factor correlations for the respective circular and semicircular zig-zag flow passages. Heat transfer measurements were also performed over a wide range of conditions to produce Nusselt correlations for the CO 2 and nitrate salt geometries. The Nusselt number is deduced from a heat transfer resistance network and overall conductance measurements collected across the operating envelope of the coupled sCO 2 – nitrate salt test facility. The CO 2 side correlation showed excellent agreement with existing correlations in the literature. Further, the salt side, having nearly circular channels with a different zig-zag angle and hydraulic diameter, yielded a new correlation applicable to the laminar flow regime. To examine the similitude of the friction correlations, pressure drop testing with water was performed on both sides of the component as well. Finally, results from non-destructive examination are discussed to provide insights regarding inspection methods and draining performance of high-temperature liquids in compact heat exchangers.
Symmetric redox flow batteries utilizing a single redox active material as catholyte and anolyte, offer a plausible and unique strategy to alleviate cross-contamination issues during cycling, making them an ideal energy storage device for large scale applications. In this work, a low-cost riboflavin organic molecule is coupled with a 2,2,6,6-Tetramethylpiperidinyl-N-oxyl (TEMPO) radical molecule to form a single Riboflavin-TEMPO (RIBOTEMPO) bifunctional redox active material, which is used in both aqueous anolyte and catholyte. Cyclic voltammetry analysis of the combined molecule displays electrochemically reversible reactions for the redox couples at 0.72 V and 0.51 V versus Hg/Hg2SO4, leading to a theoretical cell voltage of 1.23 V. A symmetric cell testing demonstrated over 100 consecutive charge/discharge cycles with nearly 80% coulombic efficiency and capacity retention of 44.7% at a current density of 2.5 mA cm(-2). By utilizing a pH neutral supporting electrolyte, a lowcost, safe, and environmental-friendly redox flow battery is achieved. This work provides a pathway for the design and development of bifunctional redox active molecules for symmetric battery applications.
Ion energy–angle distributions (IEADs) at material surfaces are a critical input for plasma–material interaction (PMI) studies in fusion devices, yet they are computationally expensive to obtain using particle-in-cell (PIC) simulations. In this work, we develop a machine learning surrogate based on a deep deconvolutional neural network (DDeCNN) trained on large databases generated with the hPIC2 code. The surrogate is capable of reconstructing IEADs from sheath parameters for both thermal and radio-frequency (RF) plasmas, including cases with multiple ion species. Across thousands of test cases, the model achieves high accuracy, with over 97 % of predictions classified as good or average based on standard error metrics (MAE, MSE, L2). Even in the more challenging RF and multi-species regimes, the surrogate reliably captures the multi-peak structure of PIC results. Once trained, the surrogate produces IEADs in milliseconds on a common workstation, yielding speedups of six to seven orders of magnitude compared with running a full PIC simulation. This computational gain enables dense parameter scans and direct coupling of IEAD predictions with PMI and erosion models on whole-device scales in fusion-relevant conditions.
Twisted double bilayer graphene (tDBG) comprises two Bernal-stacked bilayer graphene sheets with a twist between them. Gate voltages applied to top and back gates of a tDBG device tune both the flatness and topology of the electronic bands, enabling an unusual level of experimental control. Metallic states with broken spin and valley symmetries have been observed in tDBG devices with twist angles in the range 1.2–1.3°, but the topologies and order parameters of these states have remained unclear. We report the observation of an anomalous Hall effect in the correlated metal state of tDBG, with hysteresis loops spanning hundreds of mT in out-of-plane magnetic field (B ⊥ ) that demonstrate spontaneously broken time-reversal symmetry. The B ⊥ hysteresis persists for in-plane fields up to several Tesla, suggesting valley (orbital) ferromagnetism. At the same time, the resistivity is strongly affected by even mT-scale values of in-plane magnetic field, pointing to spin-valley coupling or to a direct orbital coupling between in-plane field and the valley degree of freedom.
Abstract Weak transitions between quantum states are of fundamental importance for a broad range of phenomena from analytical biochemistry to precision physics, but generally challenge experimental detection. Due to their small cross sections scaling with the absolute square of their transition matrix elements, spectroscopic measurements often fail in particular in the presence of competing background processes. Here we introduce a general concept to break this scaling law and enhance the transition probability by exploiting a stronger laser-coupled pathway to the same excited state. We demonstrate the concept experimentally by attosecond transient absorption spectroscopy in helium atoms. The quasi-forbidden transitions from the ground state 1s 2 to the weakly coupled doubly excited 2p3dandsp 2,4− states are boosted by an order of magnitude. Enhancing single-photon-suppressed transitions can find widespread applicability, from spectral diagnostics of complex molecules in life and chemical sciences to precision spectroscopy of weak transitions in metastable atomic nuclei in the search for new physics.
Abstract A multi-phase field model is employed to study the microstructural evolution of an alloy undergoing liquid dealloying, specifically considering the role of grain boundaries. A semi-implicit time-stepping algorithm using spectral methods is implemented, which enables simulating large 2D and 3D domains over long time scales while still maintaining a realistic interfacial thickness. Simulations reveal a mechanism of coupled grain–boundary migration to maintain equilibrium contact angles with the topologically complex solid–liquid interface, which locally accelerates diffusion-coupled growth of a liquid channel into the precursor. This mechanism asymmetrically disrupts the ligament connectivity of the dealloyed structure in qualitative agreement with published experimental observations. The grain boundary migration-assisted corrosion channels form even for precursors with small amounts of the dissolving alloy species, below the parting limit . The activation of this grain boundary dealloying mechanism depends strongly on grain boundary mobility.
Nuclear spins are highly coherent quantum objects. In large ensembles, their control and detection via magnetic resonance is widely exploited, for example, in chemistry, medicine, materials science and mining. Nuclear spins also featured in early proposals for solid-state quantum computers and demonstrations of quantum search and factoring algorithms. Scaling up such concepts requires controlling individual nuclei, which can be detected when coupled to an electron. However, the need to address the nuclei via oscillating magnetic fields complicates their integration in multi-spin nanoscale devices, because the field cannot be localized or screened. Control via electric fields would resolve this problem, but previous methods relied on transducing electric signals into magnetic fields via the electron–nuclear hyperfine interaction, which severely affects nuclear coherence. In this work, we demonstrate the coherent quantum control of a single 123 Sb (spin-7/2) nucleus using localized electric fields produced within a silicon nanoelectronic device. The method exploits an idea proposed in 1961 but not previously realized experimentally with a single nucleus. Our results are quantitatively supported by a microscopic theoretical model that reveals how the purely electrical modulation of the nuclear electric quadrupole interaction results in coherent nuclear spin transitions that are uniquely addressable owing to lattice strain. The spin dephasing time, 0.1 seconds, is orders of magnitude longer than those obtained by methods that require a coupled electron spin to achieve electrical driving. These results show that high-spin quadrupolar nuclei could be deployed as chaotic models, strain sensors and hybrid spin-mechanical quantum systems using all-electrical controls. Integrating electrically controllable nuclei with quantum dots could pave the way to scalable, nuclear- and electron-spin-based quantum computers in silicon that operate without the need for oscillating magnetic fields.
Many liquid phase studies assume that the potential energy surfaces of reacting molecules are the same as in the gas phase, neglecting complex solvent dynamics that can completely alter the nature of chemical reactivity. Even studies that include solvent effects typically only consider them in an average, equilibrium way as part of a potential of mean force (PMF). In this work, we use mixed quantum/classical simulations to compare how equilibrium and non-equilibrium solvent motions affect the photodissociation of a simple diatomic molecule, NaK + , in liquid tetrahydrofuran. A PMF analysis shows that as the excited-state molecule dissociates with the solvent at equilibrium, the bonding electron remains associated with K + at short bond distances but eventually localizes on Na + at the end of dissociation. When we examine non-equilibrium dynamical photodissociation trajectories, however, we find that they fall into three distinct categories: about a quarter of them have the bonding electron mainly associated with Na + , another quarter stay mainly associated with K + , and about half have the bonding electron shared roughly equally between the two ions. The results show that equilibrium PMFs cannot accurately describe the dynamics of bond-breaking chemical reactions in solution because there is insufficient time for the solvent to reach equilibrium on the time scale over which bond dissociation occurs. Furthermore, our analysis shows that the solvent coupling between the electronic energy surfaces is similar at and away from equilibrium, suggesting that other factors, such as solute velocity-driven solvent memory effects, play a more important role in explaining the failure of the equilibrium PMF to predict the non-equilibrium dynamics.
The SAM code is under development as a modern system-level modeling and simulation tool for advanced non–light water reactor safety analyses, with recent efforts to add capabilities to evaluate radiological source term risks in these novel reactor concepts. By leveraging the established system-level multiphysics thermal-hydraulic models in SAM, a framework for tightly coupled species transport modeling has been integrated into the code for engineering-scale source term evaluation. This species transport framework was first applied to the simulation of tritium, which is a well-known source term in conventional light water reactors. Tritium poses a unique risk in salt-cooled reactors, especially those with lithium-bearing salts such as the fluoride salt–cooled high-temperature reactor (FHR) concept, as tritium is generated in the salt coolant in significant quantities due to neutron interactions. A compounding factor is the increased mobility of tritium at high temperatures, which is able to permeate through metals while also potentially being retained in graphite pebbles and structures. Engineering-scale models for the tritium transport pathways in a FHR have been developed using the new species transport framework in SAM. The capabilities are assessed through analytical verification problems and validated with data from a graphite retention experiment. In conclusion, the system-level model is demonstrated by performing an initial estimate of baseline tritium generation and flows in a generic reference SAM FHR model, setting a foundation for future studies of source term transient analysis with the potential for further multiscale and multiphysics integration.
We propose to probe light-quark dipole interactions at lepton colliders using the azimuthal asymmetry of a collinear dihadron pair (ℎ 1 ℎ 2 ) produced in association with another hadron ℎ′. This asymmetry, arising from quantum interference in the quark spin space, is exclusively sensitive to dipole interactions at the leading power of the new physics scale and simultaneously probes both the real and imaginary components of the dipole couplings. By combining all possible channels of ℎ′, this method allows for disentangling the up and down quark dipole moments and has the potential to significantly strengthen current constraints by one to two orders of magnitude.
Here, we present a detailed study of the local atomic and magnetic structure of the type-I multiferroic perovskite system (Sr,Ba)(Mn,Ti)O 3 using x-ray and neutron pair distribution function (PDF) analysis, polarized neutron scattering, and muon spin relaxation (μSR) techniques. The atomic PDF analysis reveals widespread nanoscale tetragonal distortions of the crystal structure even in the paraelectric phase with average cubic symmetry, corresponding to incipient ferroelectricity in the local structure. Magnetic PDF analysis, polarized neutron scattering, and μSR likewise confirm the presence of short-range antiferromagnetic correlations in the paramagnetic state, which grow in magnitude as the temperature approaches the magnetic transition. We show that these short-range magnetic correlations coincide with a reduction of the tetragonal (i.e., ferroelectric) distortion in the average structure, suggesting that short-range magnetism can play an important role in magnetoelectric and/or magnetostructural phenomena even without genuine long-range magnetic order. The reduction of the tetragonal distortion scales linearly with the local magnetic order parameter, pointing to spontaneous linear magnetoelectric coupling in this system. These findings provide greater insight into the multiferroic properties of (Sr,Ba)(Mn,Ti)O 3 and demonstrate the importance of investigating the local atomic and magnetic structure to gain a deeper understanding of the intertwined degrees of freedom in multiferroics.
Development of resource-friendly quantum algorithms remains highly desirable for noisy intermediate-scale quantum computing. Based on the variational quantum eigensolver (VQE) with unitary coupled-cluster Ansatz, we demonstrate that partitioning of the Hilbert space made possible by the point-group symmetry of the molecular systems greatly reduces the number of variational operators by confining the variational search within a subspace. In addition, we found that instead of including all subterms for each excitation operator, a single-term representation suffices to reach required accuracy for various molecules tested, resulting in an additional shortening of the quantum circuit by a factor of 4–8. With these strategies, VQE calculations on a noise-free quantum simulator achieve energies within a few meVs of those obtained with the full unitary coupled-cluster Ansatz with single and double excitations for the H 4 -square, H 4 -chain, and H 6 -hexagon molecules, while the number of cnot gates, a measure of the quantum-circuit depth, is reduced by a factor of as large as 35. Furthermore, we introduced an efficient “score” parameter to rank the excitation operators, so that the operators causing larger energy reduction can be applied first. Using the H 4 square and H 4 chain as examples, We demonstrated on noisy quantum simulators that the first few variational operators can bring the energy within the chemical accuracy, while additional operators do not improve the energy since the accumulative noise outweighs the gain from the expansion of the variational Ansatz.
This article studies the I/O write behaviors of the Titan supercomputer and its Lustre parallel file stores under production load. The results can inform the design, deployment, and configuration of file systems along with the design of I/O software in the application, operating system, and adaptive I/O libraries.We propose a statistical benchmarking methodology to measure write performance across I/O configurations, hardware settings, and system conditions. Moreover, we introduce two relative measures to quantify the write-performance behaviors of hardware components under production load. In addition to designing experiments and benchmarking on Titan, we verify the experimental results on one real application and one real application I/O kernel, XGC and HACC IO, respectively. These two are representative and widely used to address the typical I/O behaviors of applications.In summary, we find that Titan’s I/O system is variable across the machine at fine time scales. This variability has two major implications. First, stragglers lessen the benefit of coupled I/O parallelism (striping). Peak median output bandwidths are obtained with parallel writes to many independent files, with no striping or write sharing of files across clients (compute nodes). I/O parallelism is most effective when the application—or its I/O libraries—distributes the I/O load so that each target stores files for multiple clients and each client writes files on multiple targets in a balanced way with minimal contention. Second, our results suggest that the potential benefit of dynamic adaptation is limited. In particular, it is not fruitful to attempt to identify “good locations” in the machine or in the file system: component performance is driven by transient load conditions and past performance is not a useful predictor of future performance. For example, we do not observe diurnal load patterns that are predictable.
MuMMI Core is the central component of the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), a scalable and generalizable framework that couples pairs of models using machine learning and in situ feedback across three scales of resolution.