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At least 1,495 records · Page 83

Carbon quantum dots coated BiVO{sub 4} inverse opals for enhanced photoelectrochemical hydrogen generation

Carbon quantum dots (CQDs) coated BiVO{sub 4} inverse opal (io-BiVO{sub 4}) structure that shows dramatic improvement of photoelectrochemical hydrogen generation has been fabricated using electrodeposition with a template. The io-BiVO{sub 4} maximizes photon trapping through slow light effect, while maintaining adequate surface area for effective redox reactions. CQDs are then incorporated to the io-BiVO{sub 4} to further improve the photoconversion efficiency. Due to the strong visible light absorption property of CQDs and enhanced separation of the photoexcited electrons, the CQDs coated io-BiVO{sub 4} exhibit a maximum photo-to-hydrogen conversion efficiency of 0.35%, which is 6 times higher than that of the pure BiVO{sub 4} thin films. This work is a good example of designing composite photoelectrode by combining quantum dots and photonic crystal.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Electron acceleration at oblique angles via stimulated Raman scattering at laser irradiance >10 16 W cm –2 μm 2

The generation of hot, directional electrons via laser-driven stimulated Raman scattering (SRS) is a topic of great importance in inertial confinement fusion (ICF) schemes. Little recent research has been dedicated to this process at high laser intensity, in which back, side, and forward scatter simultaneously occur in high energy density plasmas, of relevance to, for example, shock ignition ICF. In this paper, we present an experimental and particle-in-cell (PIC) investigation of hot electron production from SRS in the forward and near-forward directions from a single speckle laser of wavelength λ 0 = 1.053μm, peak laser intensities in the range I 0 = 0.2–1.0×10 17 Wcm –2 and target electron densities between ne = 0.3–1.6% n c , where n c is the plasma critical density. As the intensity and density are increased, the hot electron spectrum changes from a sharp cutoff to an extended spectrum with a slope temperature T = 34 ± 1 keV and maximum measured energy of 350 keV experimentally. Multidimensional PIC simulations indicate that the high energy electrons are primarily generated from SRS-driven electron plasma wave phase fronts with k vectors angled ~50° with respect to the laser axis. These results are consistent with analytical arguments that the spatial gain is maximized at an angle which balances the tendency for the growth rate to be larger for larger scattered light wave angles until the kinetic damping of the plasma wave becomes important. The efficiency of generated high energy electrons drops significantly with a reduction in either laser intensity or target electron density, which is a result of the rapid drop in growth rate of Raman scattering at angles in the forward direction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

High-power terahertz pulse generation from bias-free nanoantennas on graded composition InGaAs structures

We present a bias-free photoconductive emitter that uses an array of nanoantennas on an InGaAs layer with a linearly graded Indium composition. The graded InGaAs structure creates a built-in electric field that extends through the entire photoconductive active region, enabling the efficient drift of the photo-generated electrons to the nanoantennas. The nanoantenna geometry is chosen so that surface plasmon waves are excited in response to a 1550 nm optical pump to maximize photo-generated carrier concentration near the nanoantennas, where the built-in electric field strength is maximized. With the combination of the plasmonic enhancement and built-in electric field, high-power terahertz pulses are generated without using any external bias voltage. We demonstrate the generation of terahertz pulses with 860 µW average power at an average optical pump power of 900 mW, exhibiting the highest radiation power compared to previously demonstrated telecommunication-compatible terahertz pulse emitters.

42 ENGINEERING↗

Unraveling metabolism underpinning biomass composition shift in Scenedesmus obliquus under simulated outdoor conditions using 13 C-fluxomics

To render the resulting biomass more attractive and amenable for utilization as the basis for low-carbon intensity bioproducts, single-celled algae need to be biochemically and metabolically poised to assimilate and store the delivered carbon in the fastest and most efficient manner. Accelerating biochemical carbon storage, as primarily carbohydrates or lipids, is critical to achieve the high carbon capture potential that is assigned to algae. To guide strain optimization and engineering for maximizing carbon capture and storage, it is essential to elucidate the link between carbon metabolism and biomass composition. Most published metabolomics work in algae remains largely restricted to ideal and simplified environmental conditions in model organisms, thereby limiting their translation to outdoor implementation. In this work, we utilize 13 C isotopic labeling to characterize distinct intracellular metabolic fluxes before, during, and after nitrogen depletion-induced compositional shifts in Scenedesmus obliquus UTEX 393. The results indicate that a transition to carbohydrates is characterized by diverting flux to starch instead of replenishing the Calvin cycle for CO 2 fixation whereas the subsequent transition to lipids is fueled by NADPH produced by upregulating the phosphoenolpyruvate carboxylase (PEPC)–malic enzyme (ME) cycle flux. Our work highlights bottlenecks to carbohydrate- and lipid-rich biomass and can guide implementable strategies to control the fate of fixed carbon in S. obliquus.

09 BIOMASS FUELS↗

Advanced LOX/H sub 2 engine technologies for future OTVs

The optimization methods and trade studies which were used to define a 1980 state-of-the-art design of orbital transfer vehicles are summarized. The advanced thrust chamber, turbomachinery, and engine power cycle technologies recommended for development and verification during the 1980's are discussed. The state-of-the-art design serves as one of the reference points for evaluation of the advanced technology concepts. A second reference point is provided by the 1960 state-of-the-art RL-10 engine. Advanced heat energy extraction concepts in the combustor and injector are presented that will permit the high chamber pressures expected of the advanced expander cycle engine concept. Advanced turbomachinery concepts are selected that will help utilize efficiently the heat energy extracted in the thrust chamber and aid in uprating chamber pressures to values five times those realized with 1960 to 1980 technologies. The higher chamber pressure benefits are maximized with nozzle concepts that will package within a short retracted length and extend to the very high expansion area ratios required for specific impulse values significantly higher than those now realized by operational systems. Control system component concepts studied will allow utilization of the high turbine drive energy levels in a reliable repeatable manner that will reduce program risk and enhance overall space transportation system mission life cycle cost.

Glass, J.↗

OSA Spotlight Summary: Designing Miniature X-ray Optics for the SmallSat Lunar Science Mission Concept CubeX

The scientific demand for extended field X-Ray remote sensing for mapping of planetary bodies has produced the CubeSat X-ray Telescope (CubeX) lunar mission concept. Orbiting the Moon at 6,000 km for 1 year sometime during the mid-decade solar maximum, the primary objectives of CubeX are to map lunar surface elemental abundances and to assess feasibility of x-ray pulsar timing navigation. CubeX’s Miniature X-ray Optics (MiXO) design builds on heritage of existing X-ray imaging designs using new electroformed NiCo alloy replication (ENR) to create shells of 1 mm thickness. MiXO will provide 1 arcmin resolution X-Ray imaging for an extended instantaneous field of view, at various energy range sensitivities. Based on the classic Wolter-Type I design (using a paraboloid/hyperboloid grazing mirror pair), mirror parameters were expanded to allow both shell length and focal-plane offsets to vary independently. The design was optimized with a merit function that factored together four sub-merits: PSF sharpness (measured as half-power diameter), consistency across the field, minimized scattering, and maximized effective area. Monte Carlo analysis was used to predict final performance, including surface scatter effects. The demonstrated configurations include a compact 34 shell design with a diameter of 105 mm more efficient at higher energies, and a larger 130 mm/24 shell version with a larger overall effective area at lower energies. The compact design carries more expensive fabrication and assembly cost (with more shells) as well as a more challenging alignment (with denser packing). Both have overall resolution <1’ up to 26’ off-axis and <1.5’ up to 33’ off-axis, whereas a conventional design’s image quality degrades quickly beyond 15’ off-axis. This opens up new possibilities for future SmallSat missions that could use two different configurations for wide energy ranges or midsized instruments using multiple identical modules for larger collecting area.

x-ray↗

Real-time Ridesharing for Transportation Hubs with Demand and Supply Uncertainty

Transportation hubs in major cities generate a significant amount of trips by taxis and for-hail vehicles (FHV), with many of the trips sharing similar destinations. This suggests promising opportunities to leverage the collective travel needs with dedicated ridesharing solutions to reduce the externalities of excessive traffic at transportation hubs. In this study, we develop a novel dynamic ridesharing approach to serve trips from the transportation hub by considering (1) demand (new passengers) and supply (newly available vehicles) in the near future and (2) the uncertainty of future predictions. Our approach consists of two stages. In the first stage, we develop a data structure called hub mobility tree to generate potential combinations of shareable trips as candidate schedules efficiently. Then the generated schedules are used in the second stage to formulate the stochastic hub-based ridesharing problem (SHRP), which is a stochastic integer programming problem with the objective to maximize the total expected ridesharing profit over time. Due to the prohibitive number of shareable trips, we then approximately solve SHRP by the sample average approximate method (SAA), and a dual Lagrangian technique is implemented to further improve the scalability of the solution approach. We demonstrate the performances of the proposed method by simulating the ridesharing service at JFK airport using NYC taxi and FHV data. The results indicate that the proposed method outperforms the myopic ridesharing (maximize profit for a single time step) and the rolling horizon method with point estimation of future demand and supply.

dynamic ridesharing↗

Graph-based Simulation Framework for Power Resilience Estimation and Enhancement

The increasing frequency of extreme weather events poses significant risks to power distribution systems, leading to widespread outages and severe economic and social consequences. This paper presents a novel simulation framework for assessing and enhancing the resilience of power distribution networks under such conditions. Resilience is estimated through Monte Carlo simulations, which simulate extreme weather scenarios and evaluate the impact on infrastructure fragility. Due to the proprietary nature of power network topology, a distribution network is synthesized using publicly available data. To generate the weather scenarios, an extreme weather generation method is developed. To enhance resilience, renewable resources such as solar panels and energy storage systems (batteries in this study) are incorporated. A customized Genetic Algorithm is proposed to determine the optimal locations and capacities for solar panels and battery installations, maximizing resilience while balancing cost constraints. Experiment results demonstrate that on a large-scale synthetic distribution network with more than 300,000 nodes and 300,000 edges, the proposed framework can efficiently evaluate the resilience, and enhance the resilience through the installations of distributed energy resources (DERs), providing utilities with valuable insights for community-level power system resilience estimation and enhancement.

Wang, Xuesong [Wayne State Univ., Detroit, MI (Uni↗

Optimizing Power Line Undergrounding Decisions under Varying Wildfire Risk and Weather Scenarios

Abstract—The threat of wildfire ignitions from electric power equipment has led utilities to increasingly turn to preemptive power shutoffs, which, while effective in reducing grid-induced wildfire risk, can cause significant load loss. Undergrounding power lines is an alternative strategy for preventing grid-induced wildfires. However, undergrounding lines is costly, so an efficient undergrounding plan must balance reductions in wildfire risk and load loss with the cost of undergrounding lines. We propose a robust optimization model to identify which power lines to underground to maximize load served while limiting wildfire risk across a range of wildfire risk and weather scenarios. Since solving this problem may be computationally heavy for large power grids and many operating scenarios, we present a delayed constraint generation algorithm to iteratively add scenarios until an optimal solution is found. We evaluate the performance of this framework on the RTS-GMLC with scenarios representing a year of operating conditions and compare it with a stochastic programming formulation. Our results indicate that our undergrounding model is successful in reducing load shed and risk compared to baseline cases in which no mitigation action is taken and only power shutoffs are implemented (no undergrounding). The robust formulation also reduces more load shed than the stochastic formulation in the most extreme scenarios. Index Terms—grid resilience, optimization, transmission systems, underground power lines, wildfire risk.

Taylor, S. [Department of Electrical and Computer ↗

Fast Iterative Multi-site Hosting Capacity Analysis for Distribution Systems With Search Space Pruning

Interconnection studies for distributed energy resources (DERs) is a time-intensive process, primarily due to the necessity of solving large number of power flow scenarios. Hosting capacity analysis (HCA) is a time-consuming aspect of interconnection studies that is divided into single-site HCA (SHCA) and multi-site HCA (MHCA). From a computational and understandable standpoint, the industry seeks iteration-based solutions for SHCA, although it doesn't maximize the total DER hosting capacity (DERHC) of the grid, as MHCA does. While non-iterative solutions are available for MHCA, they involve a trade-off between the modeling accuracy of the distribution system, solution quality, and ease of understanding. In this work, we present a fast iterative solution for MHCA, reducing computational complexity by eliminating the need to solve power flows for a large amount of search space, thus making iterative solutions feasible. This iterative approach guarantees both a global optimal solution with sufficient time and a fast, close-to-optimal solution through efficient search space pruning. It also easily integrates with existing utility HCA tools. The results are demonstrated on select locations in the IEEE-123 bus system for community-scale interconnection studies. We highlight the benefits of skipping the need to solve millions of power flows, all while maximizing the grid's total DERHC.

Guddanti, Kishan Prudhvi↗

Balancing Charging Station Utilization and Throughput in Electric Vehicle Charging Stations with Queuing Theory

The rapid increase in electric vehicle (EV) adoption demands enhancements in the efficiency and adaptability of EV supply equipment (EVSE). Traditional EVSE systems often fail to optimize power delivery to meet the variable acceptance rates of EV batteries, resulting in significant energy wastage and reduced operational efficiency. This research addresses these challenges by integrating queuing theory with modular EVSE architectures, offering a dual strategy to optimize the operation of EV charging stations. A simulation model was developed to assess various configurations of charger capacities and outlet numbers. This model aimed to identify the optimal setup that maximizes station utilization while minimizing charging times and maximizing throughput. The model focused on charger capacities ranging from 50 to 250 kW and analyzed the different capacities’ effects on charging times and the number of vehicles served. The results indicate that a charger capacity of 125 kW is optimal, striking a balance between the charging time and the number of EVs served per hour, thus achieving the highest station utilization rate. This capacity allows for servicing a significant number of EVs with moderate increases in charging times. Lower capacities, although capable of serving more vehicles, lead to longer charging times and decreased throughput efficiency. The study underscores the effectiveness of combining queuing theory with flexible, modular charging systems that can dynamically adjust to EV charging demands.

Kumar, Praveen↗

Maximizing sunlight absorption in narrow bandgap semiconducting copper(I) iodides for enhanced photocatalytic dye degradation

Photocatalytic dye degradation leverages sunlight to break down dyes and pigments into safer, simpler molecules. Using a material that can absorb a broad range of the solar spectrum optimizes the speed and efficiency of this process. In this study, we explore a series of new, narrow bandgap copper iodide semiconductors (1.5–1.7 eV) with various dimensionalities (0D to 3D) to evaluate their photocatalytic efficiency in dye degradation. The most effective material achieved 95% degradation within just 27 minutes. Mass spectrometry provided a detailed insight and in-depth understanding into the degradation mechanism. All materials demonstrated excellent stability under ambient conditions, highlighting their promise as eco-friendly candidates for dye degradation in water purification.

Carignan, Gia M. [Rutgers Univ., Piscataway, NJ (U↗

Progressive evolutions of non-fused ring electron acceptors toward efficient organic solar cells with improved photocurrent and reduced energy loss

Resolving competitive counterbalance between high external quantum efficiency (EQE) response and low energy loss is critical for achieving efficient organic solar cells (OSCs), including those based on low-cost non-fused-ring electron acceptor (NFREA). In this work, we performed a comparable study by utilizing four NFREAs with progressive evolutions in molecular structures, energetic levels, spectral coverages, crystallinity, etc, to pair with polymer donor J52. By regulating the terminal and side chains of NFREAs, the enhanced intramolecular charge transfer (ICT) effect allows O-PC-EH possessing the broader spectral coverage for higher photocurrent, the reduced energetic offset enables O-PC-EH-based device owning higher luminescence property for lower energy loss, the strengthened crystallinity endows O-PC-EH-based blend better charge transport property for less charge recombination. With those comprehensive managements from molecule to blend properties, the J52:O-PC-EH-based OSCs achieved the best efficiency of 14.4% (certified: 14.1%) with benefits in all the three device parameters. Here, this work reveals the importance of fine-tuning molecular structures of NFREAs according to paired polymer donor for maximizing the device performances.

14 SOLAR ENERGY↗

Joint Optimization of Multimodal Transit Frequency and Shared Autonomous Vehicle Fleet Size with Hybrid Metaheuristic and Nonlinear Programming

Shared autonomous vehicles (SAVs) bring competition to traditional transit services but redesigning multimodal transit network can utilize SAVs as feeders to enhance service efficiency and coverage. This paper presents an optimization framework for the joint multimodal transit frequency and SAV fleet size problem, a variant of the transit network frequency setting problem. The objective is to maximize total transit ridership (including SAV-fed trips and subtracting boarding rejections) across multiple time periods under budget constraints, considering endogenous mode choice (transit, point-to-point SAVs, driving) and route selection, while allowing for strategic route removal by setting frequencies to zero. Due to the problem’s non-linear, non-convex nature and the computational challenges of large-scale networks, we develop a hybrid solution approach that combines a metaheuristic approach (particle swarm optimization) with nonlinear programming for local solution refinement. To ensure computational tractability, the framework integrates analytical approximation models for SAV waiting times based on fleet utilization, multimodal network assignment for route choice, and multinomial logit mode choice behavior, bypassing the need for computationally intensive simulations within the main optimization loop. Applied to the Chicago metropolitan area’s multimodal network, our method illustrates a 33.3% increase in transit ridership through optimized transit route frequencies and SAV integration, particularly enhancing off-peak service accessibility and strategically reallocating resources.

Ng, Max↗

Autonomous Experiments in Scanning Probe Microscopy and Spectroscopy: Choosing Where to Explore Polarization Dynamics in Ferroelectrics

Polarization dynamics in ferroelectric materials are explored via automated experiment in piezoresponse force microscopy/spectroscopy (PFM/S). A Bayesian optimization (BO) framework for imaging is developed, and its performance for a variety of acquisition and pathfinding functions is explored using previously acquired data. The optimized algorithm is then deployed on an operational scanning probe microscope (SPM) for finding areas of large electromechanical response in a thin film of PbTiO 3 , with results showing that, with just 20% of the area sampled, most high-response clusters were captured. Furthermore, this approach can allow performing more complex spectroscopies in SPM that were previously not possible due to time constraints and sample stability. Improvements to the framework to enable the incorporation of more prior information and improve efficiency further are modeled and discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High current density electroreduction of CO 2 into formate with tin oxide nanospheres

In this study, we demonstrate three-dimensional (3D) hollow nanosphere electrocatalysts for CO 2 conversion into formate with excellent H-Cell performance and industrially-relevant current density in a 25 cm 2 membrane electrode assembly electrolyzer device. Varying calcination temperature maximized formate production via optimizing the crystallinity and particle size of the constituent SnO 2 nanoparticles. The best performing SnO 2 nanosphere catalysts contained ~ 7.5 nm nanocrystals and produced 71–81% formate Faradaic efficiency (FE) between -0.9 V and -1.3 V vs. the reversible hydrogen electrode (RHE) at a maximum formate partial current density of 73 ± 2 mA cm geo -2 at -1.3 V vs. RHE. The higher performance of nanosphere catalysts over SnO 2 nanoparticles and commercially-available catalyst could be ascribed to their initial structure providing higher electrochemical surface area and preventing extensive nanocrystal growth during CO 2 reduction. Our results are among the highest performance reported for SnO 2 electrocatalysts in aqueous H-cells. We observed an average 68 ± 8% FE over 35 h of operation with multiple on/off cycles. In situ Raman and time-dependent X-ray diffraction measurements identified metallic Sn as electrocatalytic active sites during long-term operation. Further evaluation in a 25 cm 2 electrolyzer cell demonstrated impressive performance with a sustained current density of 500 mA cm geo -2 and an average 75 ± 6% formate FE over 24 h of operation. Our results provide additional design concepts for boosting the performance of formate-producing catalysts.

36 MATERIALS SCIENCE↗

Towards computational design of zeolite catalysts for CO 2 reduction

Carbon dioxide, an energy waste by-product with significant environmental consequences can be utilized and converted into useful chemical products such as formic acid, formaldehyde, methanol or methane, but more energy and cost efficient catalytic processes are required. Here we develop the methodology for the intelligent selection of porous zeolites for dual-adsorption of hydrogen and carbon dioxide as templates for preparing the optimal catalytic environment for carbon dioxide reduction. Useful zeolite catalysts were computationally screened from over 300 thousand zeolite structures using a combination of molecular simulation and machine-learning techniques. Several of the top candidates were very promising energy-efficient templates for catalysis with the potential to perform at 50% above conventional reactors. As a result, it is also found that an optimal cavity size of around 6 Å is required to maximize the change in entropy–enthalpy upon adsorption with a maximum void space >30% to boost product formation per volume of material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗