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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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We report on an examination of mobile ion concentration ( N 0 ) in perovskite solar cells (PSCs) as a function of temperature and device architecture.
We present a new pre-processor tool written in Python that creates multicontinuum meshes for PFLOTRAN to simulate two-phase flow and transport in both the fracture and matrix continua. We discuss the multicontinuum modeling approach to simulate potentially mobile water and gas in the fractured volcanic tuffs at Aqueduct Mesa, at the Nevada National Security Site.
String theory models of axion monodromy inflation exhibit scalar potentials which are quadratic for small values of the inflaton field and evolve to a more complicated function for large field values. Oftentimes the large field behaviour is gentler than quadratic, lowering the tensor-to-scalar ratio. This effect, known as flattening, has been observed in the string theory context through the properties of the DBI+CS D-brane action. We revisit such flattening effects in type IIB flux compactifications with mobile D7-branes, with the inflaton identified with the D7-brane position. We observe that here, with a generic choice of background fluxes, flattening effects are larger than previously observed, allowing to fit these models within current experimental bounds. In particular, we compute the cosmological observables in scenarios compatible with closed-string moduli stabilisation, finding tensor-to-scalar ratios as low as r ~ 0.04. These are models of single field inflation in which the inflaton is much lighter than the other scalars through a mild tuning of the compactification data.
In nuclear engineering and industry electrochemical methods have been intensively employed in pyro-processing technology to recycle used nuclear fuels for substantial alleviation of the concern with the safe treatment of high-level radioactive nuclear wastes. Pyro-processing is based on sequential electrochemical reactions at high temperature (typically above 700 K at ambient pressure) to enhance the efficiency for decoupling nuclear fuels from unfavorable fission fragments. Using a molten salt in electrorefining process, at which actinides can be selectively deposited in solid cathode from ionic states, gives several advantages over an aqueous solution: higher thermal conductivity (it is liquid phase at high temperature, molten salt plays a role as medium at high temperature over 773 K in electrochemical reaction, lower kinetic barrier in ionic diffusion mobility and better stability against undesired side reactions with radioactive materials. Therefore, the volume of high-level nuclear wastes to be, otherwise, disposed into secured sites is dramatically reduced. Most of all it conforms to nuclear non-proliferation treaty. Electrochemical reactions in a molten salt medium are, however, much more complicated than in aqueous solution rendering the accurate understanding of thermodynamic and kinetic properties formidably challenging. It is represented by extensive researches in experiments and computations to identify underlying mechanisms on how U and other fission fragments behave in the electrorefining system. Regardless of the researches there is a general agreement that the initial stage of the nucleation and growth process of the U deposit is critical for determining the properties of final product and the electrorefining efficiency. In spite of the focused studies it still remains unclear. Theoretical and computational researches have been often carried out with various empirical parameter for interatomic potential energy, which are unknown variables until numerical fits to experimental measurements or just assumption is made. Thus, empirical simulations sometimes predicted outcomes are inconsistent depending on materials of interest with experimental measurements. This may be largely because the accuracy of an empirical interatomic potential energy models critically depends on the input parameters and thus, can be limited in transferability of the results. Furthermore, it may be devoid of fundamental physics or chemistry. This situation requires special caution when an electrorefining system is studied to recycle spent nuclear fuels because of the extreme difficulty in reliable acquisition of thermodynamic and kinetic data from direct experimental measurements. In this presentation, we extensively utilized first principles density functional theory (DFT) calculations and ab-initio molecular dynamic (AIMD) simulations to figure out underlying mechanisms of the initial stage of nucleation and growth behaviors of U on Mo(110) surface in a eutectic LiCl-KCl molten salt at T = 773 K. To rigorously investigate the effect of the molten salt electrolyte we compared the results with those calculated under vacuum condition.
Solid-oxide electrolyzer cells (SOECs) based on a yttria-stabilized zirconia (YSZ) oxide electrolyte produce hydrogen from water with the assistance of excess thermal energy; however, Sr diffusion within the Gd-doped CeO 2 (GDC) barrier layer during processing or operation can lead to the formation of unwanted secondary phases such as SrO and SrZrO 3 . Here, to establish and compare the degree of impact of these phases on SOEC performance, we conduct first-principles calculations to study their bulk oxide conductivities and compare them to that of the YSZ electrolyte. We find that SrO has a low conductivity arising from the poor mobility and low concentration of mobile oxygen vacancies, and its presence in SOECs should therefore be avoided. SrZrO 3 also has a lower oxide conductivity than YSZ; however, this discrepancy is primarily due to lower vacancy concentrations rather than low mobility. We find that sufficient levels of Y-doping on the Zr site can increase oxygen vacancy concentrations in SrZrO 3 to achieve an oxide ionic conductivity on par with that of YSZ, thereby mitigating any potential deleterious effect on transport performance. Energy-dispersive X-ray spectroscopy confirms that Y is the most common minority element present in SrZrO 3 forming near the GDC–YSZ interface, alleviating concerns regarding the impact of SrZrO 3 on device performance. These results from our combined computational–experimental analysis can inform future engineering strategies designed to limit the detrimental effects of Sr-induced secondary phase formation on SOEC performance.
This article develops a closed-loop error learning control (CLELC) algorithm for feedback linearizable systems with experimental validation on a mobile robot. Traditional feedback and feedforward controllers are designed based on the nominal model by using the feedback linearization control (FLC) method. Then, an intelligent controller is designed based on the sliding mode learning algorithm that utilizes closed-loop error dynamics to learn the system behavior. The controllers are working in parallel, and the intelligent controller can gradually replace the feedback controller from the control of the system. In addition to the stability of the sliding mode learning algorithm, the closed-loop stability of an nth-order feedback linearizable system is proven. The simulation results demonstrate that the CLELC algorithm can improve control performance (e.g., smaller rise time, settling time, and overshoot) in the absence of uncertainties, and also provides robust control performance in the presence of uncertainties as compared to traditional FLC method. To test the efficiency and efficacy of the CLELC algorithm, the trajectory tracking problem of a tracked mobile robot is studied in real time. The experimental results demonstrate that the CLELC algorithm ensures highly accurate trajectory tracking performance than traditional FLC method.
Here, this study addresses a large-scale multimodal transit network design problem, with Shared Autonomous Mobility Services (SAMS) as both transit feeders and an origin-to-destination mode. The framework captures spatial demand and modal characteristics, considers intermodal transfers and express services, determines transit infrastructure investment and path flows, and generates transit routes. A system-optimal multimodal transit network is designed with minimum total door-to-door generalized costs of users and operators, satisfying transit origin-destination demand within a pre-set infrastructure budget. Firstly, the geography, demand, and modes in each zone are characterized with continuous approximation. The decisions of network link investment and multimodal path flows in zonal connection optimization are formulated as a minimum-cost multi-commodity network flow (MCNF) problem and solved efficiently with a mixed-integer linear programming (MILP) solver. Subsequently, the route generation problem is solved by expanding the MCNF formulation to minimize intramodal transfers. The model is illustrated through a set of experiments with the Chicago network comprised of 50 zones and seven modes, under three scenarios. The computational results present savings in traveler journey time and operator cost demonstrating the potential benefits of collaboration between multimodal transit systems and SAMS.
Abstract Metal halide perovskites are an attractive class of semiconductors, but it has proven difficult to control their electronic doping by conventional strategies due to screening and compensation by mobile ions or ionic defects. Noble‐metal interstitials represent an under‐studied class of extrinsic defects that plausibly influence many perovskite‐based devices. In this work, doping of metal halide perovskites is studied by electrochemically formed Au + interstitial ions, combining experimental data on devices with a computational analysis of Au + interstitial defects based on density functional theory (DFT). Analysis suggests that Au + cations can be easily formed and migrate through the perovskite bulk via the same sites as iodine interstitials (I i + ). However, whereas I i + compensates n‐type doping by electron capture, the noble‐metal interstitials act as quasi‐stable n‐dopants. Experimentally, voltage‐dependent, dynamic doping by current density–time ( J–t ), electrochemical impedance, and photoluminescence measurements are characterized. These results provide deeper insight into the potential beneficial and detrimental impacts of metal electrode reactions on long‐term performance of perovskite photovoltaic and light‐emitting diodes, as well as offer an alternative doping explanation for the valence switching mechanism of halide‐perovskite‐based neuromorphic and memristive devices.
High Quality Mobile Virtual Reality (VR) is what the incoming graphics technology era demands: users around the world, regardless of their hardware and network conditions, can all enjoy the immersive virtual experience. However, the state-of-the-art software-based mobile VR designs cannot fully satisfy the realtime performance requirements due to the highly interactive nature of user's actions and complex environmental constraints during VR execution. Inspired by the unique human visual system effects and the strong correlation between VR motion features and realtime hardware-level information, we propose Q-VR, a novel dynamic collaborative rendering solution via software-hardware co-design for enabling future low-latency high-quality mobile VR. At software-level, Q-VR provides flexible high-level tuning interface to reduce network latency while maintaining user perception. At hardware-level, Q-VR accommodates a wide spectrum of hardware and network conditions across users by effectively leveraging the computing capability of the increasingly powerful VR hardware. Extensive evaluation on real-world games demonstrates that Q-VR can achieve an average end-to-end performance speedup of 3.4x (up to 6.7x) over the traditional local rendering design in commercial VR devices, and a 4.1x frame rate improvement over the state-of-the-art static collaborative rendering.
A summary of technical accomplishments from the Livewire Data Platform since the 2024 Annual Merit Review.
Abstract not provided
A benchmark comparison between two ion mobility and collision cross-section (CCS) calculators, MOBCAL and IMoS, is presented here as a standard to test the efficiency and performance of both programs. Utilizing 47 organic ions, results are in excellent agreement between IMoS and MOBCAL in He and N{sub 2,} when both programs use identical input parameters. Due to a more efficiently written algorithm and to its parallelization, IMoS is able to calculate the same CCS (within 1%) with a speed around two orders of magnitude faster than its MOBCAL counterpart when seven cores are used. Due to the high computational cost of MOBCAL in N{sub 2}, reaching tens of thousands of seconds even for small ions, the comparison between IMoS and MOBCAL is stopped at 70 atoms. Large biomolecules (>10000 atoms) remain computationally expensive when IMoS is used in N{sub 2} (even when employing 16 cores). Approximations such as diffuse trajectory methods (DHSS, TDHSS) with and without partial charges and projected area approximation corrections can be used to reduce the total computational time by several folds without hurting the accuracy of the solution. These latter methods can in principle be used with coarse-grained model structures and should yield acceptable CCS results. .
When exposed to strong shearing, the particles in a crystal will rearrange and ultimately, the crystal will break by forming large nonaffine defects. Even for the initial stage of this process, only little effort has been devoted to the understanding of the breaking process on the scale of the individual particle size for thermalized mixed crystals. Here, we explore the shear-induced breaking for an equimolar two-dimensional binary model crystal with a high interaction asymmetry between the two different species such that the initial crystal has an intersecting square sublattice of the two constituents. Using Brownian dynamics computer simulations, we show that the combination of shear and thermal fluctuations leads to a characteristic hierarchical breaking scenario where initially, the more strongly coupled particles are thermally distorted, paving the way for the weakly coupled particles to escape from their cage. This in turn leads to mobile defects which may finally merge, proliferating a cascade of defects, which triggers the final breakage of the crystal. This scenario is in marked contrast to the breakage of one-component crystals close to melting. Moreover, we explore the orientational dependence of the initial shear direction relative to the crystal orientation and compare this to the usual melting scenario without shear. Our results are verifiable in real-space experiments of superparamagnetic colloidal mixtures at a pending air-water interface in an external magnetic field where the shear can be induced by an external laser field.
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Amorphous oxide semiconductor materials have demonstrated numerous advantages without compromise of electrical properties as compared to their crystalline counterparts, yet understanding of the fundamental principles allowing this has remained elusive. To study the origins of enhanced optoelectronic properties, we apply high-throughput, combinatorial sputtering, structural and spectral mapping, and computationally intensive ab initio molecular dynamics simulations with density functional theory to a ternary, post-transition metal oxide system, namely, zinc tin oxide. The deposited thin films exhibit a high figure of merit, achieving carrier densities in the range of 1019 to 1020 cm–3 and carrier mobilities up to 35 cm2/Vs. These results highlight the role of local distortions and cation coordination in determining the microscopic origins of carrier generation and transport. In particular, we identify the strong likelihood of Sn undercoordination in both Zn-poor and Zn-rich phases leading to the high carrier concentrations observed. This not only diverges from the still widespread historical indictment of oxygen vacancies controlling carrier population in crystalline oxides but also provides a comprehensive framework to describe the unique structure–property relationships using specific structural and electronic descriptors in disordered phase materials.
Previously observed formation of substoichiometric titanium oxide dendritic structures across terraces of Au(111) is computationally studied and shown to follow the classical fractal formation mechanism of diffusion-limited aggregation (DLA). Globally optimized gas-phase oxide cluster structures are sampled in a variety of landing formations on gold surfaces and shown to favor isomers driving polymerization to Brownian tree fractal structures. Mobility of Ti 3 O 5 monomers is shown to be extremely high, with diffusion barriers of 0.21 eV or less. Through bonding stabilization, polymerization of these monomers is energetically favorable and irreversible on the 111 terrace but geometrically impossible to propagate along the step edge. Simulated scanning tunneling microscopy (STM) images show strong similarity to experiment. By contrast, observation of Ti 3 O 6 aggregating as wires along step edges is explained by the affinity of oxygen to step edges and statistical arguments for aggregation entropy at the step, in addition to low barriers for monomer diffusion and polymerization.
Quantum materials (QMs) with strong correlation and nontrivial topology are indispensable to next-generation information and computing technologies. Exploitation of topological band structure is an ideal starting point to realize correlated topological QMs. Here, we report that strain-induced symmetry modification in correlated oxide SrNbO 3 thin films creates an emerging topological band structure. Dirac electrons in strained SrNbO 3 films reveal ultrahigh mobility (μ max ≈ 100,000 cm 2 /Vs), exceptionally small effective mass (m* ~ 0.04m e ), and nonzero Berry phase. Strained SrNbO 3 films reach the extreme quantum limit, exhibiting a sign of fractional occupation of Landau levels and giant mass enhancement. Our results suggest that symmetry-modified SrNbO 3 is a rare example of correlated oxide Dirac semimetals, in which strong correlation of Dirac electrons leads to the realization of a novel correlated topological QM.
The EVs@Scale cybersecurity pillar deep dive focuses on the three main tasks that NREL has in the consortium: (1) Analysis of EV charging mobile applications, (2) Cybersecurity risk assessments of EVSE through DER-CF, and (3) PKI for EVSE.