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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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At least 775 records · Page 43

A Non-Cooperative Game-Based Distributed Beam Scheduling Framework for 5G Millimeter-Wave Cellular Networks

Here, this paper studies the problem of distributed beam scheduling for 5G millimeter-Wave (mm-Wave) cellular networks where base stations (BSs) belonging to different operators share the same spectrum without centralized coordination among them. Our goal is to design efficient distributed scheduling algorithms to maximize the network utility, which is a function of the achieved throughput by the user equipment (UEs), subject to the average and instantaneous power consumption constraints of the BSs. We propose a Media Access Control (MAC) and a power allocation/adaptation mechanism utilizing the Lyapunov stochastic optimization framework and non-cooperative games. In particular, we first decompose the original utility maximization problem into two sub-optimization problems for each time frame, which are a convex optimization problem and a non-convex optimization problem, respectively. By formulating the distributed scheduling problem as a non-cooperative game where each BS is a player attempting to optimize its own utility, we provide a distributed solution to the non-convex sub-optimization problem via finding the Nash Equilibrium (NE) of the game whose weights are determined optimally by the Lyapunov optimization framework. Finally, we conduct simulation under various network settings to show the effectiveness of the proposed game-based beam scheduling algorithm in comparison to that of several reference schemes.

42 ENGINEERING↗

Rationalizing Calcium Electrodeposition Behavior by Quantifying Ethereal Solvation Effects on Ca 2+ Coordination in Well-Dissociated Electrolytes

Ca-ion electrochemical systems have been pushed to the forefront of recent multivalent energy storage advances due to their use of earth-abundant redox materials and their high theoretical specific densities in relation to monovalent or even other more widely explored multivalent-charge carriers. However, significant pitfalls in metal plating and stripping arise from electrolyte decomposition and can be related to the coordination environment around Ca 2+ with both the negatively charged anion and the organic–aprotic solvent. Here, we apply multiple spectroscopic techniques in conjunction with density functional theory to evaluate the coordination environment of Ca 2+ across a class of ethereal solvents. Through the combination of X-ray absorption fine structure and time-dependent density functional theory, descriptive measures of the local geometry, coordination, and electronic structure of Ca–ethereal complexes provide distinct structural trends depending on the extent of the Ca 2+ –solvent interaction. Finally, we correlate these findings with electrochemical measurements of calcium tetrakis(hexafluoroisopropoxy)borate (CaBHFIP 2 ) salts dissolved within this class of solvents to provide insight into the preferred structural configuration of Ca 2+ electrolytic solutions for optimized electrochemical plating and stripping.

25 ENERGY STORAGE↗

Nitrogen-dependent coordination of cell cycle, quiescence and TAG accumulation in Chlamydomonas

Abstract Microalgae hold great promises as sustainable cellular factories for the production of alternative fuels, feeds, and biopharmaceuticals for human health. While the biorefinery approach for fuels along with the coproduction of high-value compounds with industrial, therapeutic, or nutraceutical applications have the potential to make algal biofuels more economically viable, a number of challenges continue to hamper algal production systems at all levels. One such hurdle includes the metabolic trade-off often observed between the increased yields of desired products, such as triacylglycerols (TAG), and the growth of an organism. Initial genetic engineering strategies to improve lipid productivity in microalgae, which focused on overproducing the enzymes involved in fatty acid and TAG biosynthesis or inactivating competing carbon (C) metabolism, have seen some successes albeit at the cost of often greatly reduced biomass. Emergent approaches that aim at modifying the dynamics of entire metabolic pathways by engineering of pertinent transcription factors or signaling networks appear to have successfully achieved a balance between growth and neutral lipid accumulation. However, the biological knowledge of key signaling networks and molecular components linking these two processes is still incomplete in photosynthetic eukaryotes, making it difficult to optimize metabolic engineering strategies for microalgae. Here, we focus on nitrogen (N) starvation of the model green microalga, Chlamydomonas reinhardtii , to present the current understanding of the nutrient-dependent switch between proliferation and quiescence, and the drastic reprogramming of metabolism that results in the storage of C compounds following N starvation. We discuss the potential components mediating the transcriptional repression of cell cycle genes and the establishment of quiescence in Chlamydomonas, and highlight the importance of signaling pathways such as those governed by the target of rapamycin (TOR) and sucrose nonfermenting-related (SnRK) kinases in the coordination of metabolic status with cellular growth. A better understanding of how the cell division cycle is regulated in response to nutrient scarcity and of the signaling pathways linking cellular growth to energy and lipid homeostasis, is essential to improve the prospects of biofuels and biomass production in microalgae.

09 BIOMASS FUELS↗

Exploring Structural Diversity and Fluxionality of Pt n ( n = 10–13) Clusters from First-Principles

Subnanometer transition-metal clusters have been shown to possess catalytic activity that is size-dependent. It has been suggested that the fluxionality of these small clusters may be closely related to their catalytic activity. Here we use basin-hopping global optimization with density functional theory (DFT) to study the energy landscape of Ptn (n = 10–13) clusters. We analyze a large set of local minima obtained from the DFT-based global optimization. We find that Pt10 is unique with respect to the other studied sizes in its structural landscape, which shows a single, distinct structural motif corresponding to a tetrahedral global minimum. In contrast, Pt11–13 all display characteristics of high fluxionality with the presence of multiple significantly differing structural features in the low-energy region, as characterized by coordination number, interatomic distances, and shape. These observations demonstrate the structural diversity and fluxionality of the subnanometer Pt clusters that will have important implications for catalysis.

Fung, Victor↗

Nonequilibrium design strategies for functional colloidal assemblies

Here, we use a nonequilibrium variational principle to optimize the steady-state, shear-induced interconversion of self-assembled nanoclusters of DNA-coated colloids. Employing this principle within a stochastic optimization algorithm allows us to identify design strategies for functional materials. We find that far-from-equilibrium shear flow can significantly enhance the flux between specific colloidal states by decoupling trade-offs between stability and reactivity required by systems in equilibrium. For isolated nanoclusters, we find nonequilibrium strategies for amplifying transition rates by coupling a given reaction coordinate to the background shear flow. We also find that shear flow can be made to selectively break detailed balance and maximize probability currents by coupling orientational degrees of freedom to conformational transitions. For a microphase consisting of many nanoclusters, we study the flux of colloids hopping between clusters. We find that a shear flow can amplify the flux without a proportional compromise on the microphase structure. This approach provides a general means of uncovering design principles for nanoscale, autonomous, functional materials driven far from equilibrium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uncovering interpretable relationships in high-dimensional scientific data through function preserving projections

Abstract In many fields of science and engineering, we frequently encounter experiments or simulations datasets that describe the behavior of complex systems and uncovering human interpretable patterns between their inputs and outputs via exploratory data analysis is essential for building intuition and facilitating discovery. Often, we resort to 2D embeddings for examining these high-dimensional relationships (e.g. dimensionality reduction). However, most existing embedding methods treat the dimensions as coordinates for samples in a high-dimensional space, which fail to capture the potential functional relationships, and the few methods that do take function into consideration either only focus on linear patterns or produce non-linear embeddings that are hard to interpret. To address these challenges, we proposed function preserving projections (FPP), which construct 2D linear embeddings optimized to reveal interpretable yet potentially non-linear patterns between the domain and the range of a high-dimensional function. The intuition here is that humans are good at understanding potentially non-linear patterns in 2D but unable to interpret non-linear mapping from high-dimensional space to 2D. Therefore, we should restrict the projection to linear but not the pattern we are seeking. Using FPP on real-world datasets, one can obtain fundamentally new insights about high-dimensional relationships in extremely large datasets that could not be processed with existing dimension reduction methods.

97 MATHEMATICS AND COMPUTING↗

FOILPOLARS (Grassmannian Foil Shape Sweeps for Polar Generation) [SWR-26-095]

FOILPOLARS (Grassmannian Foil Shape Sweeps for Polar Generation): Multifidelity aerodynamic polar data generation for hydrofoil/tidal-turbine airfoil sections. Foilpolars ties together three pieces: *AeroSandbox supplies the baseline airfoil coordinates (UIUC database). *G2Aero parameterizes those shapes on a Grassmannian manifold (Karcher mean + PGA basis) and samples new perturbed shapes around that basis. *XFoil (panel method) and NeuralFoil (neural-network surrogate, shipped with AeroSandbox) each solve the resulting shapes for lift, drag, moment, and pressure at the swept angles of attack, Reynolds numbers, and n_crit values. Design optimization of foil shapes in a computationally efficient way requires polars data across many candidate shapes, not just a handful of baseline foils. However, high-fidelity CFD at that scale is too costly, and naive shape perturbation strays from realistic geometries. FOILPOLARS addresses this by loading baseline airfoils (via AeroSandbox) and mapping them onto a Grassmannian manifold (via G2Aero), computing a Karcher mean and principal geodesic analysis (PGA) basis. New shapes are sampled by perturbing PGA coefficients, keeping them close to the manifold of realistic foils. Each sampled shape is evaluated across a configurable sweep of angle of attack, Reynolds number, and critical amplification factor using two solvers: XFoil (panel method) and NeuralFoil (neural-network surrogate), producing a paired dataset of lift, drag, moment, pressure, convergence, and confidence, indexed alongside each shape's PGA coefficients and shared Grassmannian basis in a single xarray dataset. From this, FOILPOLARS produces convergence summaries and comparison plots per shape, Reynolds number, and n_crit. A command-line interface exposes each pipeline stage independently, supporting data-driven design, optimization, and machine-learning workflows for foils.

Sandhu, Rimple [National Laboratory of the Rockies↗

Electron Paramagnetic Resonance Characterization of the Triheme Cytochrome from Geobacter sulfurreducens

Periplasmic cytochrome A (PpcA) is a representative of a broad class of multiheme cytochromes functioning as protein “nanowires” for storage and extracellular transfer of multiple electrons in the δ-proteobacterium Geobacter sulfurreducens. PpcA contains three bis-His coordinated hemes held in a spatial arrangement that is highly conserved among the multiheme cytochromes c 3 and c 7 families, carries low potential hemes, and is notable for having one of the lowest number of amino acids utilized to maintain a characteristic protein fold and site-specific heme function. Low temperature X-band electron paramagnetic resonance (EPR) spectroscopy has been used to characterize the electronic configuration of the Fe(III) and the ligation mode for each heme. The three sets of EPR signals are assigned to individual hemes in the three-dimensional crystal structure. The relative energy levels of the Fe(III) 3d orbitals for individual hemes were estimated from the principal g-values. The observed g-tensor anisotropy was used as a probe of electronic structure of each heme, and differences were determined by specifics of axial ligation. To ensure unambiguous assignment of highly anisotropic low-spin (HALS) signal to individual hemes, EPR analyses of iron atom electronic configurations have been supplemented with investigation of porphyrin macrocycles by one-dimensional 1 H NMR chemical shift patterns for the methyl substituents. In conclusion, within optimized geometry of hemes in PpcA, the magnetic interactions between hemes were found to be minimal, similar to the c 3 family of tetraheme cytochromes.

1H NMR↗

Dynamically Unveiling Metal–Nitrogen Coordination during Thermal Activation to Design High-Efficient Atomically Dispersed CoN 4 Active Sites

We elucidate the structural evolution of CoN 4 sites during thermal activation by developing a zeolitic imidazolate framework (ZIF)-8-derived carbon host as an ideal model for Co 2+ ion adsorption. Subsequent in situ X-ray absorption spectroscopy analysis can dynamically track the conversion from inactive Co-OH and Co-O species into active CoN 4 sites. The critical transition occurs at 700 °C and becomes optimal at 900 °C, generating the highest intrinsic activity and four-electron selectivity for the oxygen reduction reaction (ORR). DFT calculations elucidate that the ORR is kinetically favored by the thermal-induced compressive strain of Co-N bonds in CoN 4 active sites formed at 900 °C. Further, we developed a two-step (i.e., Co ion doping and adsorption) Co-N-C catalyst with increased CoN 4 site density and optimized porosity for mass transport, and demonstrated its outstanding fuel cell performance and durability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mesoporous Fe-doped MgO nanoparticles as a heterogeneous photo-Fenton-like catalyst for degradation of salicylic acid in wastewater

Mesoporous Fe-doped MgO nanoparticles were synthesized using a facile sol-gel method and utilized for photo-Fenton-like degradation of salicylic acid (SA). The MgO surface dissolution facilitated an increase in the pH under the reaction conditions that allowed the Fe-MgO catalyst to be active without detectable iron leaching. Under simulated solar radiation, SA was completely degraded with an initial rate constant of 0.048 min -1 at the optimal reaction conditions of 500 ppm loading of 5% Fe-MgO, 20 mM H 2 O 2 concentration, and 50 ppm SA concentration. The catalyst was stable over 5 reaction cycles. The Fe-MgO catalyst was shown to have a surface area up to 171 m 2 /g and contain hematite (Fe 2 O 3 ) nanoparticles with octahedrally coordinated iron catalytic centers, as inferred from diffuse reflectance UV–vis measurements. Post-reaction catalyst characterization showed that some Fe 2+ was present in the catalyst due to the redox cycle during the chain initiation and propagation steps of the reaction.

36 MATERIALS SCIENCE↗

Materials research and development needs to enable efficient and electrified buildings

Because of the complexity of modern buildings—with many interconnected materials, components, and systems—fully electrifying buildings will require targeted R&D and efficient coordination across those material, component, and system levels. Because buildings that consume the smallest amount of energy are easier to electrify, energy efficiency is a crucial step toward fully electrified buildings. Materials advances will play an important role in both reducing the energy intensity of buildings and electrifying their remaining energy use. Materials are currently being explored, discovered, synthesized, evaluated, optimized, and implemented across many building components, including solid-state lighting; dynamic windows and opaque envelopes; cold climate heat pumps; thermal energy storage; heating, ventilating, and air conditioning (HVAC); refrigeration; non-vapor compression HVAC; and more. In this article, we review the current state-of-the-art of materials for various buildings end uses and discuss R&D challenges and opportunities for both efficiency and electrification.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Selective binding of choline by a phosphate-coordination-based triple helicate featuring an aromatic box

In nature, proteins have evolved sophisticated cavities tailored for capturing target guests selectively among competitors of similar size, shape, and charge. The fundamental principles guiding the molecular recognition, such as self-assembly and complementarity, have inspired the development of biomimetic receptors. In the current work, we report a self-assembled triple anion helicate (host 2) featuring a cavity resembling that of the choline-binding protein ChoX, as revealed by crystal and density functional theory (DFT)-optimized structures, which binds choline in a unique dual-site-binding mode. Here, this similarity in structure leads to a similarly high selectivity of host 2 for choline over its derivatives, as demonstrated by the NMR and fluorescence competition experiments. Furthermore, host 2 is able to act as a fluorescence displacement sensor for discriminating choline, acetylcholine, l-carnitine, and glycine betaine effectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Demand-Side Opportunity: The Roles of Distributed Solar and Building Energy Systems in a Decarbonized Grid

Building energy systems represent a significant and largely untapped demand-side grid resource. Buildings use about 75% of electricity in the United States, including around 80% of peak demand, meaning that changes in building energy use have significant implications for grid operations. Building energy technologies-including energy-efficient devices, flexible loads, and energy storage-can be coordinated and aggregated to perform similar functions as centralized grid assets. Recent advances in information and communication (ICT) technologies have significantly improved building energy technology automation, coordination, and aggregation capabilities. With declining costs and technological advances, building energy systems can increasingly compete with conventional grid assets such as natural gas plants. Building energy technologies enable the deployment of distributed solar photovoltaics (DPV). Energy-efficient buildings allow DPV to meet greater shares of building load while flexible loads and energy storage can reshape building load profiles to optimize the on-site use of DPV. Optimized on-site use of DPV increases the value proposition for DPV adoption and can help utilities cost-effectively integrate higher levels of DPV penetration. Together, DPV and building energy technologies could help grids achieve deep decarbonization more quickly and cost-effectively.

14 SOLAR ENERGY↗

Arbitrage and Capacity Firming in Coordination with Day-Ahead Bidding of a Hybrid PV Plant

A hybrid PV plant (HPP) combines a photovoltaic (PV) plant with a battery energy storage system (BESS), which is considered a promising step towards the future of renewable power plants by the U.S. Department of Energy. When the renewable penetration reaches a significant level, a hybrid PV plant can bid in as a controllable thermal plant in the future electricity market. In this study, a bidding and BESS scheduling model is proposed for the HPP. The robust optimization (RO) technique has been utilized to identify the worst-case scenario of uncertainties during the bidding process. To address the overly conservative issue of the single-stage RO, we have decoupled the BESS schedule for arbitrage and PV capacity firming by a two-stage RO formulation. By comparing the output of single-stage RO and two-stage RO, the two-stage RO bids and schedules in a more aggressive manner, which increases the income of HPP. Also, the penalty of under-generation is considered in our model so that the day-ahead bidding decision and arbitrage schedules can be adjusted based on the potential UNDER-GENERATION penalty. Because the proposed model is non-convex and contains multi-stages, the Column-and-Constraint Generation (C&CG) algorithm is applied to the model as the solution. The proposed model has shown better economic performance compared to a state-of-art single-stage bidding method in case studies.

BESS scheduling↗

Arbitrage and Capacity Firming in Coordination with Day-Ahead Bidding of a Hybrid PV Plant: Preprint

A hybrid PV plant (HPP) combines a photovoltaic (PV) plant with a battery energy storage system (BESS), which is considered a promising step towards the future of renewable power plants by the U.S. Department of Energy. When the renewable penetration reaches a significant level, a hybrid PV plant can bid in as a controllable thermal plant in the future electricity market. In this study, a bidding and BESS scheduling model is proposed for the HPP. The robust optimization (RO) technique has been utilized to identify the worst-case scenario of uncertainties during the bidding process. To address the overly conservative issue of the single-stage RO, we have decoupled the BESS schedule for arbitrage and PV capacity firming by a two-stage RO formulation. By comparing the output of single-stage RO and two-stage RO, the two-stage RO bids and schedules in a more aggressive manner, which increases the income of HPP. Also, the penalty of under-generation is considered in our model so that the day-ahead bidding decision and arbitrage schedules can be adjusted based on the potential UNDER-GENERATION penalty. Because the proposed model is non-convex and contains multi-stages, the Column-and-Constraint Generation (C&CG) algorithm is applied to the model as the solution. The proposed model has shown better economic performance compared to a state-of-art single-stage bidding method in case studies.

BESS scheduling↗

Coordinative Real-time Sub-Transmission Volt-VAr Control for Reactive Power Regulation between Transmission and Distribution Systems

This paper introduces an integrated voltage regulation approach to coordinate the Volt-VAr control between transmission and distribution systems. Distributed photovoltaic (PV) systems are aggregated as a virtual power plant (VPP). At the sub-transmission level, a Coordinated Real-time Sub-Transmission Volt-VAr Control Tool (CReST-VCT) is introduced to coordinate the operation of the shunt devices and the reactive power provided by the VPPs. The CReST-VCT uses an enhanced Volt-VAr control algorithm with weighted voltage control objects that include minimizing losses, maintaining the voltage within desirable levels, and minimizing the number of mechanical switching of shunt elements. The algorithm runs every 5 minutes and is solved using AC optimal power flow (OPF) solution technique. The outputs include the settings for each sub-transmission-level Volt-VAr control devices and the reactive power generation requirements for each VPP. Then, each VPP will run a distribution Volt-VAr control algorithm to select the PV inverters that provide the Volt-VAr control services considering the distribution network topology. The goal of the VPP reactive power control is to meet the transmission level service requirements while maintaining the voltage and line flow in the distribution system within limits. Each VPP will update its voltage regulation capacity every 5 minutes to allow the CReST-VCT to formulate the optimization problem for the next dispatch interval. The proposed tool is simulated on Duke Energy Carolina system to demonstrate the capability of providing voltage support service by dispatching of reactive power of distributed PV as VPP.

Ke, Xinda↗

Required toroidal confinement for fusion and omnigeneity

Deuterium–tritium (DT) burning requires a long energy confinement times compared to collision times, so the particle distribution functions must approximate local Maxwellians. Non-equilibrium thermodynamics is applicable, which gives relations among transport, entropy production, the collision frequency, and the deviation from a Maxwellian. The distribution functions are given by the Fokker–Planck equation, which is an advection–diffusion equation. A large hyperbolic operator, the Vlasov operator with the particle trajectories as its characteristics, equals a small diffusive operator, the collision operator. The collisionless particle trajectories would be chaotic in stellarators without careful optimization. This would lead to rapid entropy production and transport—far beyond what is consistent with a self-sustaining DT burn. Omnigeneity is the weakest general condition that is consistent with a sufficiently small entropy production associated with the thermal particle trajectories. Omnigeneity requires that the contours of constant magnetic field strength be unbounded in at least one of the two angular coordinates in magnetic surfaces and that there be a symmetry in the field-strength wells along the field lines. Even in omnigenous plasmas, fluctuations due to microturbulence can produce chaotic particle trajectories and the gyro-Bohm transport is seen in many stellarator and tokamak experiments. The higher the plasma temperature above 10 keV, the smaller the transport must be compared to gyro-Bohm for a self-sustaining DT burn. The hot alphas of DT fusion heat the electrons. When the ion–electron equilibration time is long compared to the ion energy confinement time, a self-sustaining DT burn is not possible, which sets a limit on the electron temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗