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At least 775 records · Page 43

Self-Anchored Platinum-Decorated Antimony-Doped-Tin Oxide as a Durable Oxygen Reduction Electrocatalyst

The lifetime of commercial Proton Exchange Membrane Fuel Cells (PEMFCs) is circumscribed by the insufficient durability of commercial catalysts. The use of metal oxide supports in place of carbon significantly increases electrocatalyst durability. Herein, following density functional theory (DFT) predictions of improved Platinum (Pt) stability on antimony doped tin oxide (ATO) supports, we synthesized ATO whose morphology and crystal structure was engineered using a Pt anchoring technique. X-ray photoelectron spectroscopy (XPS) indicated that the Pt anchor sites aided in the reduction of Pt precursors to Pt on the ATO surface. X-ray absorption near-edge spectroscopy (XANES) revealed the existence of strong-metal-support interactions (SMSI) between Pt and ATO. The combination of SMSI and high control over Pt dispersion enabled the Pt/Pt-aerogel-ATO (Pt supported on aerogel ATO with Pt anchor sites) electrocatalyst to achieve 2x the area specific activity of Pt/C in ex-situ testing. In a H 2 /air PEMFC Pt/Pt-aerogel-ATO cathodes enabled 20% higher peak power density and <1/6 the loss of active surface area as compared to Pt/C. Notably, in a PEMFC under rigorous potential cycling, the Pt/Pt-aerogel-ATO retained its initial peak power density as opposed to a 58% loss for Pt/C. Further, cost models indicate that Pt/Pt-aerogel-ATO is 26% less expensive than Pt/C over its useful lifetime.

25 ENERGY STORAGE↗

Load‐Balancing Intense Physics Calculations to Embed Regionalized High‐Resolution Cloud Resolving Models in the E3SM and CESM Climate Models

Abstract We design a new strategy to load‐balance high‐intensity sub‐grid atmospheric physics calculations restricted to a small fraction of a global climate simulation's domain. We show why the current parallel load balancing infrastructure of Community Earth System Model (CESM) and Energy Exascale Earth Model (E3SM) cannot efficiently handle this scenario at large core counts. As an example, we study an unusual configuration of the E3SM Multiscale Modeling Framework (MMF) that embeds a binary mixture of two separate cloud‐resolving model grid structures that is attractive for low cloud feedback studies. Less than a third of the planet uses high‐resolution (MMF‐HR; sub‐km horizontal grid spacing) relative to standard low‐resolution (MMF‐LR) cloud superparameterization elsewhere. To enable MMF runs with Multi‐Domain cloud resolving models (CRMs), our load balancing theory predicts the most efficient computational scale as a function of the high‐intensity work's relative overhead and its fractional coverage. The scheme successfully maximizes model throughput and minimizes model cost relative to precursor infrastructure, effectively by devoting the vast majority of the processor pool to operate on the few high‐intensity (and rate‐limiting) high‐resolution (HR) grid columns. Two examples prove the concept, showing that minor artifacts can be introduced near the HR/low‐resolution CRM grid transition boundary on idealized aquaplanets, but are minimal in operationally relevant real‐geography settings. As intended, within the high (low) resolution area, our Multi‐Domain CRM simulations exhibit cloud fraction and shortwave reflection convergent to standard baseline tests that use globally homogenous MMF‐LR and MMF‐HR. We suggest this approach can open up a range of creative multi‐resolution climate experiments without requiring unduly large allocations of computational resources.

54 ENVIRONMENTAL SCIENCES↗

Techno-economic analysis of a conceptual biofuel production process from bioethylene produced by photosynthetic recombinant cyanobacteria

Ethylene is a petrochemical produced in large volumes worldwide. It serves as a building block for a wide variety of plastics, textiles, and chemicals, and can be converted into liquid transportation fuels. There is great interest in the development of technologies that produce ethylene from renewable resources, such as biologically derived CO 2 and biomass. One of the metabolic pathways used by microbes to produce ethylene is via an ethylene-forming enzyme (EFE). By expressing a bacterial EFE gene in a cyanobacterium, ethylene has been produced through photosynthetic carbon fixation. Here, we present a conceptual design and techno-economic analysis of a process of biofuel production based on the upgradation of ethylene generated by the recombinant cyanobacterium. This analysis focuses on potential near-term to long-term cost projections for the integrated process of renewable fuels derived from ethylene. The cost projections are important in showing the potential of this technology and determining research thrusts needed to reach target goals. The base case for this analysis is a midterm projection using tubular photobioreactors for cyanobacterial growth and ethylene production, cryogenic distillation for ethylene separation and purification, a two-step Ziegler oligomerization process with subsequent hydrotreatment and upgradation for fuel production, and a wastewater treatment process that utilizes anaerobic digestion of cyanobacterial biomass. The minimum fuel selling price (MFSP) for the midterm projection is 15.07 per gallon gasoline equivalent (GGE). Near-term and long-term projections are 28.66 per GGE and 5.36 per GGE, respectively. Single- and multi-point sensitivity analyses are conducted to determine the relative effect that chosen variables could have on the overall costs. This analysis identifies several key variables for improving the overall process economics and outlines strategies to guide future research directions. Finally, the productivity of ethylene has the largest effect on cost and is calculated based on a number of variables that are incorporated into this cost model (i.e., quantum requirement, photon transmission efficiency, and the percent of energy going to either ethylene or cyanobacterial biomass production).

09 BIOMASS FUELS↗

Multi-timescale operations of nuclear-renewable hybrid energy systems for reserve and thermal product provision

In this paper, an optimal operation strategy of a nuclear-renewable hybrid energy system (N-R HES), in conjunction with a district heating network, is developed within a comprehensive multi-timescale electricity market framework. The grid-connected N-R HES is simulated to explore the capabilities and benefits of N-R HES of providing energy products, different reserve products, and thermal products. An N-R HES optimization and control strategy is formulated to exploit the benefits from the hybrid energy system in terms of both energy and ancillary services. A case study is performed on the customized NREL-118 bus test system with high renewable penetrations, based on a multi-timescale (i.e., three-cycle) production cost model. Both day-ahead and real-time market clearing prices are determined from the market model simulation. In conclusion, the results show that the N-R HES can contribute to the reserve requirements and also meet the thermal load, thereby increasing the economic efficiency of N-R HES (with increased revenue ranging from 1.55% to 35.25% at certain cases) compared to the baseline case where reserve and thermal power exports are not optimized.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Coordination Chemistry and Stoichiometry of Extracted Diglycolamide Complexes of Lanthanides in Extraction Chromatography Materials

Industrial rare earth element (REE) separations predominantly utilize solvent extraction processes tailored toward conventional resources such as bastnäsite, monazite, and ion adsorption clays. Advances in diglycolamide (DGA) chemistry have shown effective extraction characteristics for REE separations. However, limitations associated with traditional DGA solvent extraction techniques, such as third-phase formation and gelling, have hindered commercial viability. By supporting DGA extractants on porous resins such as polystyrene divinyl benzene (PS-DVB), the desirable combination of solvent extraction selectivity and ease of operation of sorbent columns can be achieved. To design a low-cost model for such solid-supported DGAs, extraction characteristics as influenced by the underlying coordination chemistry must be explored to achieve efficient functional systems. Within this study, we report novel DGA resin materials, each incorporating one of the DGAs N,N,N’,N’-tetra-(1-octyl)-3-oxapentane-1,5-diamide (TODGA), N,N'-dimethyl-N,N'-dioctyl-3-oxapentane-1,5-diamide (DMDODGA), and 2,2'-oxybis(1-(3-(((2-ethylhexyl)thio)methyl)-4-methylpyrrolidin-1-yl)ethan-1-one) (DEHPDGA). The affinity of DGAs across the lanthanide (Ln) series was evaluated for both hydrochloric acid and nitric acid media with varying Ln feed concentrations to study distribution ratios and loading characteristics. Focusing on dysprosium, extended X-Ray Absorption Fine Structure (EXAFS) and density functional theory (DFT) calculations were also utilized to explore coordination chemistry and their effects on ligand performance. The general trend for both acid media resulted in DMDODGA having the highest extraction strength of all three DGAs at varying acid concentrations. Coordination-chemistry analysis supported by loading data, DFT calculations, and EXAFS results under forced loading conditions posited less than the expected 3:1 ligand-to-metal coordination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analyzing the Impact of Solar Power on Multi-Hourly Thermal Generator Ramping

Solar power generation, unlike conventional forms of electricity generation, has higher variability and uncertainty in its output because solar plant output is strongly impacted by weather. As the penetration rate of solar capacity increases, grid operators are increasingly concerned about accommodating the increased variability and uncertainty that solar power provides. This paper illustrates the impacts of increasing solar power penetration on the ramping of conventional electricity generators by simulating the operation of the Independent System Operator -- New England power system. A production cost model was used to simulate the power system under five different scenarios, one without solar power and four with increasing solar power penetrations up to 18%, in terms of annual energy. The impact of solar power is analyzed on six different temporal intervals, including hourly and multi-hourly (2- to 6-hour) ramping. The results show how the integration of solar power increases the 1- to 6-hour ramping events of the net load (electric load minus solar power). The study also analyzes the impact of solar power on the distribution of multi-hourly ramping events of fossil-fueled generators and shows increasing 1- to 6-hour ramping events for all different generators. Generators with higher ramp rates such as gas and oil turbine and internal combustion engine generators increased their ramping events by 200% to 280%. For other generator types--including gas combined-cycle generators, coal steam turbine generators, and gas and oil steam turbine generators--more and higher ramping events occurred as well for higher solar power penetration levels.

14 SOLAR ENERGY↗

Renewable Generation Effect on Net Regional Energy Interchange: Preprint

Using production-cost model (PLEXOS), we simulate the Western Interchange (WECC) at several levels of the yearly renewable energy (RE) generation, between 13% and 40% of the total load for the year. We look at the overall energy exchange between a region and the rest of the system (net interchange, NI), and find it useful to examine separately (i) (time-)variable and (ii) year-average components of the NI. Both contribute to inter-regional energy exchange, and are affected by wind and PV generation in the system. We find that net load variability (in relatively large portions of WECC) is the leading factor affecting the variable component of inter-regional energy exchange, and the effect is quantifiable: higher regional net load correlation with the rest of the WECC lowers net interchange variability. Further, as the power mix significantly varies between WECC regions, effects of ‘flexibility import’ (regions ‘borrow’ ramping capability) are also observed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication.

There is a growing interest in custom spatial accelerators for machine learning applications. These accelerators employ a spatial array of processing elements (PEs) interacting via custom buffer hierarchies and networks-on-chip. The efficiency of these accelerators comes from employing optimized dataflow (i.e., spatial/temporal partitioning of data across the PEs and fine-grained scheduling) strategies to optimize data reuse. The focus of this work is to evaluate these accelerator architectures using a tiled general matrix-matrix multiplication (GEMM) kernel. To do so, we develop a framework that finds optimized mappings (dataflow and tile sizes) for a tiled GEMM for a given spatial accelerator and workload combination, leveraging an analytical cost model for runtime and energy. Finally, our evaluations over five spatial accelerators demonstrate that the tiled GEMM mappings systematically generated by our framework achieve high performance on various GEMM workloads and accelerators.

42 ENGINEERING↗

Preliminary Component Design and Cost Estimation of a Novel Electric-Thermal Energy Storage System Using Solid Particles

Energy storage will become indispensable to complement the uncertainty of intermittent renewable resources and to firm the electricity supply as renewable power generation becomes the mainstream new-built energy source and fossil fuel power plants are phased out to meet carbon-neutral utility targets. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system is projected to have promising cost and performance characteristics to meet the future growing energy storage needs. This paper introduces the system and components required for particle TES to become technically and economically competitive. The system integrates electric particle heaters, particle TES within insulated concrete silos, and an efficient air-Brayton combined-cycle power system to provide power for storage durations up to several days via low-cost, high-performance storage cycles. Design specifications and cost estimation of major components in a commercial-scale system are presented in this paper. A techno-economic analysis based on preliminary component designs and performance indicates that particle TES integrated with an air-Brayton combined-cycle power system has a path to achieve the targeted levelized cost of storage of 5 ¢/kWh-cycle at a round-trip efficiency of 50% when taking low-cost energy-specific components and leveraging basic assets from existing thermal power plants. The cost model provides insights for further development and economic potentials for long-duration energy storage.

14 SOLAR ENERGY↗

A Microchannel Heat Exchanger Produced From a Metal Matrix Composite by Hybrid Laser Powder Bed Fusion and Inkjet Printing

Abstract This paper explores the production of an oxide dispersion strengthened (ODS) 304L stainless steel microchannel heat exchanger (HX) using a hybrid additive manufacturing process of laser powder bed fusion and inkjet printing. The study investigates the capabilities and economics of the hybrid inkjet-laser powder bed fusion (LPBF) process and evaluates the dimensional accuracy, functionality, and mechanical properties of the resulting ODS alloy. The effectiveness and pressure drop of the ODS heat exchangers produced by the hybrid LPBF tool are also determined. Results show that the inkjet-doped samples have a lower mean channel height with higher standard deviation than samples produced by LPBF alone. This is attributed to greater absorption of laser energy for the powder coated with the oxide precursor. The economic analysis shows that the hybrid process has a potential for reducing the unit cost of the heat exchanger based on cost modeling assumptions.

Engineering↗

Beyond the Hype: An Evaluation of Commercially Available Machine-Learning-Based Malware Detectors

There is a lack of scientific testing of commercially available malware detectors, especially those that boast accurate classification of never-before-seen (i.e., zero-day) files using machine learning (ML). Consequently, efficacy of malware detectors is opaque, inhibiting end users from making informed decisions and researchers from targeting gaps in current detectors. In this paper, we present a scientific evaluation of four prominent commercial malware detection tools to assist an organization with two primary questions: To what extent do ML-based tools accurately classify previously and never-before-seen files? Is purchasing a network-level malware detector worth the cost? To investigate, we tested each tool against 3,536 total files (2,554 or 72% malicious, 982 or 28% benign) of a variety of file types, including hundreds of malicious zero-days, polyglots, and APT-style files, delivered on multiple protocols. We present statistical results on detection time and accuracy, consider complementary analysis (using multiple tools together), and provide two novel applications of the recent cost-benefit evaluation procedure of Iannacone & Bridges. Although the ML-based tools are more effective at detecting zero-day files and executables, the signature-based tool might still be an overall better option. Both network-based tools provide substantial (simulated) savings when paired with either host tool, yet both show poor detection rates on protocols other than HTTP or SMTP. Our results show that all four tools have near-perfect precision but alarmingly low recall, especially on file types other than executables and office files—37% of malware, including all polyglot files, were undetected. Priorities for researchers and takeaways for end users are given. Code for future use of the cost model is provided.

97 MATHEMATICS AND COMPUTING↗

rplexos [SWR-14-19]

rplexos is a R (statistical software framework; more? details below) package that processes and facilitates analysis of solution from PLEXOS. PLEXOS is a production cost model that is utilize to simulate the behavior of the power.systems and is developed and commercialized by Energy Exomplar. The intention is to make rptexos open-source so other PLEXOS users can utilize it.

Ibanez, Eduardo↗

DEPRECATED MAGMA (Multi-area Grid Metrics Analyzer) [SWR-16-31]

The DEPRECATED MAGMA software package is a package created in the R scripting language that reads a SQL database and outputs tables and figures of important data. The SQL database is created by another R package called “rplexos” and uses the .zip solution file output by PLEXOS, which is commercially available production cost modeling software.

Barrows, Clayton↗

PLEXOS Input Data Generator

The PLEXOS Input Data Generator (PIDG) is a tool that enables PLEXOS users to better version their data, automate data processing, collaborate in developing inputs, and transfer data between different production cost modeling and other power systems analysis software. PIDG can process data that is in a generalized format from multiple input sources, including CSV files, PostgreSQL databases, and PSS/E .raw files and write it to an Excel file that can be imported into PLEXOS with only limited manual intervention.

Source record↗

Demand Response Dispatch Tool

The Demand Response (DR) Dispatch Tool uses price profiles to dispatch demand response resources and create load modifying profiles. These annual profiles are used as inputs to production cost models and regional planning tools (e.g., PROMOD). The tool has been effectively implemented in transmission planning studies conducted by the Western Electricity Coordinating Council via its Transmission Expansion Planning and Policy Committee. The DR Dispatch Tool can properly model the dispatch of DR resources for both reliability and economic conditions.

Satchwell, Andrew↗