Exciton Lifetime Distributions and Population Dynamics in the FMO Protein Complex from Prosthecochloris aestuarii
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
SEARCH · Engineering Papers
Results for “distributed analytics”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Probabilistic Failure Criterion of SiC/SiC Composites Under Multiaxial Loading
Owing to its excellent mechanical properties and stability under high temperature and neutron irradiation conditions, SiC/SiC composites have emerged as a promising material for light water reactors (LWRs) in the development of accident-tolerant fuel (ATF) systems. Structural integrity and retention of hermeticity are two crucial requirements for SiC/SiC claddings during normal operations, and both of them are closely related to the proportional limit stress (PLS) of the material. Understanding the behavior of SiC/SiC composites under multiaxial stress states and developing a probabilistic approach for evaluating the structural vulnerability are of paramount importance for reliability-based analysis and design of SiC/SiC composite claddings. So far, there has been very limited effort towards experimental and analytical investigations of probabilistic failure of SiC/SiC claddings. This critical knowledge gap motivates this research. A probabilistic failure criterion for SiC/SiC composites under multi-axial loading is developed, and this criterion is incorporated into reliability analysis of the structural integrity of SiC/SiC fuel cladding. The research consists of two parts: 1) experimental investigation of multiaxial failure behavior of SiC/SiC composites, and 2) theoretical modeling of time-dependent probabilistic failure of SiC/SiC cladding. In the experimental investigation, the PLS is determined through the examination of stress-strain response, the acoustic emission measurement, as well as the X-ray computed tomography. The theoretical framework is derived by combin- ing the finite weakest-link statistical model and the subcritical damage growth model. This theoretical model captures the time-dependent failure mechanism of the material, which has a major consequence for predicting the lifetime distribution of the cladding. Meanwhile, the model also predicts that the failure statistics of the cladding depends strongly on the cladding length. The results of the multiaxial experiments reveal the level of statistical variation of the PLS of SiC/SiC materials under different stress states. The theoretical model provides a robust analytical tool for extrapolation of small-scale laboratory test results to the behavior of full-scale claddings. These findings establish a scientific foundation for the development of reliability-based design of SiC/SiC fuel claddings, which will play an essential role in improving the structural safety and integrity of LWRs.
42 ENGINEERING↗
Deconstructing the Local Intermolecular Ordering and Dynamics of Liquid Chloroform and Bromoform
Local intermolecular structure and dynamics of the polar molecular liquids chloroform and bromoform are studied by molecular dynamics simulation. Structural distribution functions, including 1- and 2-D pair correlations and dipole contour plots allow direct comparison and show agreement with recent analyses of diffraction experiments. Studies of the haloforms’ reorientational dynamics and longevity of structural features resulting from intermolecular interaction extend previous work toward deeper understanding of the factors controlling these features. Analyses of ensemble average structures and dynamical properties isolate mass, electrostatics, and steric packing as driving forces or contributing factors for the observed ordering and dynamics.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Isochronous Architecture-Based Voltage-Active Power Droop for Multi-Inverter Systems
This article proposes an isochronous architecture for parallel inverters with only voltage-active power droop (VP-D) control for improving active power sharing as well as plug-and-play of multi-inverter-based distributed energy resources (DERs). The isochronous framework obviates the need for an explicit regulation of the frequency while allowing for sharing of reactive power. The article shows that the detrimental effects of circulating currents between inverters can be addressed in the framework developed. The isochronous architecture is implemented by employing a GPS to disseminate clock timing signals that enable the microgrid to maintain the nominal system frequency. Small signal eigenvalue analysis of a Multi-inverter Microgrid system near the steady-state operating point is presented to evaluate the system stability. Moreover, unlike traditional droop-based methods, the isochronous strategy lends itself to analytical guarantees which are developed in the article. Furthermore, the effect of delays in receiving GPS clock signals by an inverter is experimentally characterized and an inverter isolation mechanism is proposed that disconnects inverters facing large GPS communication delays. Hardware experiments on an 1.2 kVA-prototype and controller-hardware-in-the-loop validation on the CIGRE distribution network are conducted to demonstrate the effectiveness of the proposed architecture towards active and reactive power sharing between inverters with load scenarios.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Olefin methylation over iron zeolites and the methanol to hydrocarbons reaction
The effect of olefin addition to a stream of dimethyl ether on the methanol homologation reaction is investigated using iron-substituted zeolites Fe-beta and Fe-ZSM-5. The reaction was investigated using plug-flow microreactors in the temperature range of 240–400 °C, at a total pressure of 0.239 MPa and a WHSV of 6.12 (g DME/ gcat -hr). For Fe-beta (Si/Fe= 9.2) catalysts, isobutene co-feeding almost doubles dimethyl ether (DME) consumption rate and shifts selectivity towards larger olefins with carbon numbers from 5 to 7. Addition of isobutene above 6.3%, however, resulted in a reduction of DME consumption rates, an effect assigned to the replacement of surface methoxy groups for adsorbed olefins in the zeolite pores. Below a temperature of 340 °C hydride-transfer rates are negligible; reaction rates are stable for over 5.5 h and the products consist almost exclusively of olefins and a small amount of methane. Above 360 °C the onset of catalytic hydride transfer processes is observed leading to fast catalyst deactivation rates and an increase in the concentration of aromatic species. Iron ZSM-5 (Si/Fe = 21.4) catalysts under similar reaction conditions consumes methanol faster than Fe-beta at approximately three times the TOF (on a per iron basis). The Fe-ZSM-5 catalyst was selective to a distribution of products (C5 to C8) as compared to Fe-beta which was selective to primarily C5 and C7. Co-feeding larger olefins (2-methyl-2-butene, 2,3-dimethyl-2-butene, 2,3,3-trimethyl-1-butene, and 2,4,4-trimethyl-2-pentene) at a 3.9% olefin concentration over Fe-beta changed selectivity towards cracking products (C4 compounds such as isobutene). As the size of the olefin increases, a reduction of DME consumption rate is also observed. Here these results show that co-feeding olefins with DME over Fe-zeolites is a promising route to increase methylation rates at relatively low temperatures producing larger branched olefins and that the product distribution is highly dependent on the zeolite pore size and structure of the olefin.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Compact ammonia reforming at low temperature using catalytic membrane reactors
Ammonia is a leading carrier for the storage and transport of renewable hydrogen, but its deployment requires scalable technologies for efficient decomposition and purification. In this work, we report on the efficient delivery of high purity hydrogen from ammonia decomposition using a catalytic membrane reactor (CMR). Improvements to the electroless plating process reduced the Pd membrane thickness by >35%, resulting in commensurate increases in hydrogen permeance without sacrificing selectivity. To increase throughput a commercial Ru/Al 2 O 3 catalyst was added to the lumen, and the CMR could process ammonia flowrates 10–50 times higher than an equivalent packed bed reactor while maintaining the same level of conversion. It is shown that the earth-abundant zeolite clinoptilolite could reduce ammonia impurities in the permeated H 2 to the levels required by PEM fuel cells (<25 ppb). Performance increased significantly across a >500-h durability test due to improvements in membrane permeability. Finally, the results show that CMRs are a viable technology for distributed production of hydrogen from ammonia.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Zinc Speciation and Propane Dehydrogenation in Zn/H-ZSM-5 Catalysts
Zn/H-ZSM-5 catalysts have been frequently investigated for propane dehydrogenation (PDH); however, the active site remains unresolved due to the complexity of the system. We employed in situ FTIR spectroscopy and a kinetics method to correlate the Zn speciation and PDH activity in Zn/H-ZSM-5 with two Si/Al ratios (15 and 39) and a range of Zn/Al ratios (0–1.7). Incremental additions of zinc show that Zn 2+ sites are preferentially formed on H-ZSM-5 over a fraction of paired Al sites followed by [Zn-O-Zn] 2+ and [ZnOH] + sites and then ZnO x clusters. The [Zn-OH] + and [Zn-O-Zn] 2+ sites in H-ZSM-5 are more active and selective than isolated Zn 2+ for PDH. [Zn-OH] + species sublimate over time on stream, leading to catalyst deactivation, while [Zn-O-Zn] 2+ species are stable even after high-temperature reduction (750 °C for 60 min). Three distinct Zn sites ([Zn-O-Zn] 2+ , Zn 2+ , and [ZnOH] + ) show a similar propane reaction order (close to 1) and H 2 reaction order (close to 0). Combined with the lack of Zn hydride when propane flows over the catalyst at 550 °C, it is concluded that propane adsorption and dissociation is a rate-determining step and H 2 desorption is fast. This work indicates that the preparation of H-ZSM-5 with abundant Al pairs may be a strategy to form stable and selective Zn/H-ZSM-5 catalysts for propane dehydrogenation. Furthermore, it is also highlighted that examining the effect of both metal/Al ratios and Al distribution of the zeolite is crucial in identifying the metal cations in metal–zeolite systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Negatively Charged Lipids Exhibit Negligible Effects on the Water Repellency of Montmorillonite Films
Amphiphilic molecules can alter the wettability of soil minerals. To determine how the headgroup chemistry of amphiphiles determines these effects, we investigate a system of the clay montmorillonite with long-chain phospholipids. We use phosphatidylglycerol (PG) phospholipids to contrast with our previous work using phosphatidylethanolamine lipids (PE). Zwitterionic PE lipids can sorb to the negatively-charged montmorillonite surface, whereas negatively-charged PG lipids cannot. Employing a suite of techniques from molecular dynamics, atomic force microscopy, fluorescence microscopy, and contact angle measurements, we define sample characteristics from molecular scale structure to the macroscopic wettability. We find that PG lipids do not significantly alter montmorillonite wetting characteristics, such as the contact angle, flow viscosity, and the characteristic timescale for droplet imbibition. In comparing PE and PG lipid/clay films, we find that, among the phospholipids compared, they must have three characteristics in order to change clay/lipid film wettability: they must bind to the mineral surface, be solid at room temperature, and have a relatively continuous distribution throughout the film.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The binding of atomic hydrogen on graphene from density functional theory and diffusion Monte Carlo calculations
In this research, density functional theory (DFT) and diffusion Monte Carlo (DMC) methods are used to calculate the binding energy of a H atom chemisorbed on the graphene surface. The DMC value of the binding energy is about 16% smaller in magnitude than the Perdew–Burke–Ernzerhof (PBE) result. The inclusion of exact exchange through the use of the Heyd–Scuseria–Ernzerhof functional brings the DFT value of the binding energy closer in line with the DMC result. It is also found that there are significant differences in the charge distributions determined using PBE and DMC approaches.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Ensuring thermodynamic consistency with invertible coarse-graining
Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insights by isolating the essential degrees of freedom that dictate the thermodynamic properties of a complex, condensed-phase system. The reduced complexity of the model typically leads to lower computational costs and more efficient sampling compared with atomistic models. Designing “good” coarse-grained models is an art. Generally, the mapping from fine-grained configurations to coarse-grained configurations itself is not optimized in any way; instead, the energy function associated with the mapped configurations is. In this work, we explore the consequences of optimizing the coarse-grained representation alongside its potential energy function. We use a graph machine learning framework to embed atomic configurations into a low-dimensional space to produce efficient representations of the original molecular system. Because the representation we obtain is no longer directly interpretable as a real-space representation of the atomic coordinates, we also introduce an inversion process and an associated thermodynamic consistency relation that allows us to rigorously sample fine-grained configurations conditioned on the coarse-grained sampling. We illustrate that this technique is robust, recovering the first two moments of the distribution of several observables in proteins such as chignolin and alanine dipeptide.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Computing Nonequilibrium Responses with Score-Shifted Stochastic Differential Equations
Using equilibrium fluctuations to understand the response of a physical system to an externally imposed perturbation is the basis for linear response theory, which is widely used to interpret experiments and shed light on microscopic dynamics. For nonequilibrium systems, perturbations cannot be interpreted simply by monitoring fluctuations in a conjugate observable and general response results rely on path ensemble averaging. Furthermore, these techniques do not apply to perturbations that affect the diffusion tensor in a stochastic system. Here, we introduce an “effective” physical process that represents the diffusion perturbed dynamics and enables accurate calculations of responses to a change in the diffusion. Interestingly, the effective dynamics contain an additional drift involving the instantaneous “score” of the system, and we leverage score matching algorithms to carry out nonequilibrium response calculations on systems for which the exact stationary distribution is unknown.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Ordering in GaAs co-doped with Bi and N
Introducing only a few atomic percent of Bi or N in GaAs has a large effect on the band gap of the material. Specifically Bi doped GaAs shows potential for local band gap engineering in optoelectronic applications. The incorporation of Bi and N into GaAs is difficult due to strain effects. In this work we study the ordering of these dopants at the atomic scale in order to get a better understanding of the behavior of these dopants in the host lattice. Cross-sectional scanning tunneling microscopy is used to find the exact position of Bi and N dopants in the GaAs matrix, allowing us to study both their nearest neighbor pair occurrences and pair correlation functions. An attractive interaction between Bi dopants at short ranges (1-2 nm) is found and a similar effect is observed between N dopants. Here, we find a repulsive interaction with a similar length scale between Bi and N dopants. A similar repulsion is found in the Bi-N nearest neighbor pairs. Density functional theory is used to calculate the different nearest neighbor pair energies and test these results to the experimental pair occurrences. It is concluded from the experimental and theoretical results that the growth conditions and N inclusion greatly affects the Bi distribution in GaAs.
36 MATERIALS SCIENCE↗
High-Energy X-ray Diffraction Microscopy for Nuclear Forensics FY2022 Project Report
Morphological information on nuclear material has been identified using visible light and scanning electron microscopy. These identify qualitative differences in particle morphology. Three-dimensional imaging of materials through alternating scanning electron microscopy imaging and focused ion beam milling has also been used. Unfortunately, these techniques are time- and labor-intensive, with significant sample preparation required and lengthy analysis times. Further, the resulting 3D images are qualitative, require manual identification, and do not capture statistically-representative populations. High energy X-ray 3D imaging using a direct-beam or diffracted-beam (High-Energy Diffraction Microscopy) have been developed at the Advanced Photon Source and can produce quantitative information on grains (phase, location, etc.) and pores (size distribution, sphericity) in a material. These techniques require only minutes to characterize a sample volume and are non-destructive, thus suitable for a wide range of existing samples and for confirmatory analyses to be carried out using conventional microscopy techniques. In this first year of the project, all uranium oxide samples were synthesized and characterized using conventional analyses by the analytical chemistry laboratory. Conventional analysis methods included powder x-ray diffraction, scanning electron microscopy, impurity analysis via inductively coupled plasma mass spectrometry, and infrared spectroscopy. Impurity analysis shows a drop in boron content from UO 3 to the lowest U 3 O 8 calcination temperature, but otherwise no appreciable difference in any sample. Analysis of diffraction data shows a flip of peaks from UO 3 dominated for the 600 °C calcined sample to U 3 O 8 dominated at 700 °C and 800 °C. Analysis of scanning electron microscopy images shows that with increased calcination temperature the size distribution of particles seems to increase and broaden. Both of these last findings are in line with previously published data, though this work used significantly fewer particles to simply show similar trends instead of getting truly quantitative particle analysis. Infrared analysis similarly shows ingrowth of U 3 O 8 as calcination temperature is increased, along with depression of peaks associated with UO 3 and water. Samples were prepared for analysis at the Advanced Photon Source at beamline 1-ID. It is anticipated that analysis will occur in November of 2022. AI/ML techniques to de-noise data coming out of 1-ID during the analyses was also developed during this time using previously gathered data. Preliminary results using a self-supervision technique called Noise2Selfshow good de-noising of data. Once the uranium oxide samples are analyzed, real data will be used to test the de-noising and other AI/ML techniques that may be developed in the second year of the project.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Computational modeling of charge hopping dynamics along a disordered one-dimensional wire with energy gradients in quantum environments
This computational study investigates the effects of energy gradients on charge hopping dynamics along a one-dimensional chain of discrete sites coupled to quantum bath, which is modeled at the level of Pauli master equation (PME). This study also assesses the performance of different approximations for the hopping rates. Three different methods for solving the PME, a fourth order Runge–Kutta method, numerical diagonalization of the rate matrix followed by analytic propagation, and kinetic Monte Carlo simulation method, are tested and confirmed to produce virtually identical values of time dependent mean square displacement, diffusion constant, and mobility. Five different rate expressions, exact numerical evaluation of Fermi’s Golden Rule (FGR) rate, stationary phase interpolation (SPI) approximation, semiclassical approximation, classical Marcus rate, and Miller–Abrahams rate, are tested to help understand the effects of approximations in representing quantum environments in the presence of energy gradients. The results based on direct numerical evaluation of FGR rate exhibit transition from diffusive to non-diffusive behavior with the increase in the gradient and show that the charge transport in the quantum bath is more sensitive to the magnitude of the gradient and the disorder than in the classical bath. Among all the four approximations for the hopping rates, the SPI approximation is confirmed to work best overall. A comparison of two different methods to calculate the mobility identifies drift motion of the population distribution as the major source of non-diffusive behavior and provides more reliable information on the contribution of quantum bath.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Back-to-back inclusive dijets in DIS at small x: gluon Weizsäcker-Williams distribution at NLO
In [1], we performed the first complete computation of the back-to-back inclusive dijet cross-section in Deeply Inelastic Scattering (DIS) at small x Bj to next-to-leading order (NLO) in the Color Glass Condensate effective field theory (CGC EFT). We demonstrate here that for dijets with relative transverse momentum P ⊥ and transverse momentum imbalance q ⊥ , to leading power in q ⊥ /P ⊥ , the cross-section for longitudinally polarized photons can be fully factorized into the product of a perturbative impact factor and the non-perturbative Weizsäcker-Williams (WW) transverse momentum dependent (TMD) gluon distribution to NLO accuracy. The impact factor can further be expressed as the product of a universal soft factor which resums Sudakov double and single logs in P ⊥ /q ⊥ and a coefficient function given by a remarkably compact analytic expression. We show that in the CGC EFT the WW TMD satisfies a kinematically constrained JIMWLK renormalization group evolution in rapidity. This factorization formula is valid to all orders in Q s /q ⊥ for q ⊥ , Q s << P ⊥ , where Q s is the semi-hard saturation scale that grows with rapidity.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Multidisciplinary benchmarks of a conservative spectral solver for the nonlinear Boltzmann equation
The Boltzmann equation describes the evolution of the phase-space probability distribution of classical particles under binary collisions. Approximations to it underlie the basis for several scholarly fields, including aerodynamics and plasma physics. While these approximations are appropriate in their respective domains, they can be violated in niche but diverse applications which require direct numerical solution of the original nonlinear Boltzmann equation. An expanded implementation of the Galerkin–Petrov conservative spectral algorithm is employed to study a wide variety of physical problems. Enabled by distributed precomputation, solutions of the spatially homogeneous Boltzmann equation can be achieved in seconds on modern personal hardware, while spatially-inhomogeneous problems are solvable in minutes. Here, several benchmarks are presented focusing on accuracy compared to both analytic theoretical predictions and other Boltzmann solvers. These benchmarks span several physical domains including weakly ionized plasma, gaseous fluids, and atomic-plasma interaction.
97 MATHEMATICS AND COMPUTING↗
Approximating accelerator impedances with resonator networks
It is common in the accelerator community to use the impedance of accelerator components to describe wake interactions in the frequency domain. However, it is often desirable to understand such wake interactions in the time domain in a general manner for excitations that are not necessarily Gaussian in nature. Here, the conventional method for doing this involves taking the inverse Fourier Transform of the component impedance, obtaining the Green's Function, and then convolving it with the desired excitation distribution. This method can prove numerically cumbersome, for a convolution integral must be evaluated for each individual point in time when the wake function is desired. An alternative to this method would be to compute the wake function analytically, which would sidestep the need for repetitive integration. Only a handful of cases, however, are simple enough for this method to be tenable. One of these cases is the case where the component in question is an RLC resonator, which has a closed-form analytical wake function solution. This means that a component which can be represented in terms of resonators can leverage this solution. As it happens, common network synthesis techniques may be used to map arbitrary impedance profiles to RLC resonator networks in a manner the accelerator community has yet to take advantage of. In this work, we will use Foster Canonical Resonator Networks and partial derivative descent optimization to develop a technique for synthesizing resonator networks that well approximate the impedances of real-world accelerator components. We will link this synthesis to the closed-form resonator wake function solution, giving rise to a powerful workflow that may be used to streamline beam dynamics simulations.
43 PARTICLE ACCELERATORS↗
Artificial Intelligence-Driven Management of Sustainable Energy Resources: Visibility, Operation, and Control
The rapid global transition toward sustainable energy resources (SERs) is reshaping how modern power systems are observed, optimized, and controlled. While SERs have significantly advanced decarbonization, their weather dependence, variability, and inverter-dominated characteristics challenge traditional, centralized, and deterministic grid operation. At the same time, the proliferation of high-resolution data from inverters, smart meters, and sensors offers unprecedented visibility into system dynamics. Yet, it also exceeds the analytical capability of conventional model-based approaches. Artificial intelligence (AI) provides a new foundation for addressing these challenges by bridging physical laws with data-driven learning, enabling accurate state awareness, adaptive operation, and coordinated control across distributed assets. This article examines how AI transforms the management of SER-rich power systems along three critical dimensions: 1) enhancing visibility by inferring behind-the-meter (BTM) activities, assessing SER flexibility, and reconstructing system states from sparse or noisy measurements; 2) improving operation through AI-enhanced SER service provision, volt/var control (VVC), and dynamic operating envelopes (DOE) for efficiency and security; and 3) advancing control by embedding learning-based intelligence into inverter coordination, voltage and frequency regulation, and long-term dispatch. Together, these developments reveal how AI can convert the variability of SERs from an operational challenge into a source of flexibility, resilience, and intelligence, paving the way toward sustainable, adaptive, and self-optimizing power systems.
24 POWER TRANSMISSION AND DISTRIBUTION↗