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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Multi-Stage and Multi-Timescale Robust Co-Optimization Planning for Reliable and Sustainable Power Systems. Final Report

In this project, Clarkson University, in collaboration with Southern Methodist University and University of Pittsburgh, conducted the research to model, design, and implement a sophisticated generation and transmission co-optimization planning decision tool, called Multi-stage and Multi-timescale robust Co-Optimization Planning (MMCOP). The MMCOP decision tool intends to facilitate generation and transmission co-optimization planning of emerging power systems, while mitigating risks and uncertainties in both short-term operation dynamics and long-term policy and technology changes. Long-term power system planning aims at optimizing asset utilization by investing in a proper mix of various generation technologies and transmission lines to supply the future load growth. In particular, the Clean Power Plan (CPP), which is designed to combat climate change and reduce carbon emissions by setting a national limit on carbon pollution from power plants, may dramatically change the landscape of the power industry by further promoting clean energy and phasing out emissions-intensive generation technologies. In addition, novel non-wire alternatives (e.g., demand response (DR), distributed generation (DG), energy efficiency (EE), and smart grid technologies) and the computational complexity for large-scale systems significantly complicate the system planning procedure even further. However, existing conventional planning approaches neglect short-term variability and uncertainty of renewable energy, hourly chronological operation details, and physical nonlinear characteristics of the alternating current transmission network. As a result, existing conventional planning approaches may not work properly, and power systems reliability could be in jeopardy. In observing the limitations of existing conventional planning approaches and addressing new challenges of emerging power systems, the main scope of this project to develop co-optimization planning models within a multi-stage and multi-timescale framework. In particular, random contingencies, key uncertainty factors, and AC power flows are included to derive expansion plans while considering both long-term reliability and short-term flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

State-Constrained Grid-Forming Inverter Control for Robust Operation of AC Microgrids

The control of grid-forming inverters has become an important problem to achieve high efficiency, reliability, and resilience of the future power grid. The distributed control that utilizes a sparse communication network has been proposed for AC microgrids, in which each DG only has access to the information of a small number of its neighboring DGs, reducing the computational complexity and improving the resiliency to faults and unknown parameters. However, these approaches have not provided a clear analysis of the coupling between active/reactive power injections and the voltage magnitude/frequency or a distributed updating law with a solid theoretical foundation. Additionally, in the existing approaches, tracking the references from the secondary control may violate operational constraints.

Xu, Ying↗
DOE OSTI2023

Mechanical behavior analysis using small-size graphite disc compression testing with digital image correlation methods

The ASTM International Standard Test Method for Tensile Stress-Strain of Carbon and Graphite (ASTM C749) requires dog-bone shaped specimens. Unfortunately, specimen sizes required in ASTM C749 are much too large for irradiation within a test reactor and are incompatible with irradiation capsule volumes, molten salt degradation facilities, or oxidation apparatus. The ASTM International Standard Test Method for Tensile Strength Estimate by Disc Compression of Manufactured Graphite (ASTM D8289) was developed as an alternative that provides a means for testing tensile properties using smaller specimens when geometric constraints are present. However, the important stress–strain relation throughout the test loading history that could be recorded using ASTM C749 is lost by using ASTM D8289 because of the difficulties involved with using traditional strain gauges or extensometers on such a small specimen. In this work, a digital image correlation (DIC) method, which uses a full-field noncontact surface displacement measurement technique, was applied along with the ASTM D8289 splitting tensile test on eight small samples of graphite grade Mersen 2114 to track their deformation during compressive loading. Initial results showed that the DIC technique can measure the surface displacement/strain on these small (Ø6 × 3 mm) graphite specimens with high accuracy and good repeatability, indicating that the DIC technique, combined with the small-disc splitting tensile test in ASTM D8289, can capture the strain evolution in the test. In conclusion, further comparison of measured strains with analytical and numerical simulation results provides additional understanding of the mechanical behaviour of this nuclear graphite material in complex stress states.

36 MATERIALS SCIENCE↗
DOE OSTI2022

MPEX High Heat Flux Plasma Dump Design, Manufacture, and Articles Test

Here, the Material Plasma Exposure eXperiment (MPEX) device is a steady-state linear plasma device currently in the final design phase at the Oak Ridge National Laboratory. This device will reach ion fluences up to 10 31 m -2 and will be used to expose neutron-irradiated materials to divertor-relevant plasmas and to study the effects of plasma-material interactions. These studies will elucidate the complex effects of plasmas with divertor candidate materials capable of withstanding high heat flux and high fluences for next-generation fusion devices. Bidirectional plasma will be generated using a high-power (200 kW) helicon source. Plasma will be confined by superconducting magnets. The last plasma-facing component on the upstream side of the MPEX device is the dump, which has been designed to intercept plasma and energetic particles. The dump will have a total heat load of 9.2 kW. A copper alloy (Glidcop AL-15) was selected for use in the water-cooled flange design because of its high thermal conductivity, its retaining strength at elevated temperatures, and its ability to be used in the high-temperature braze joints used in this application. Titanium-zirconium-molybdenum (TZM) tiles are brazed to the Glidcop AL-15 flange using high-temperature braze alloy. External water-cooling channels are used on the dump flange to prevent water leakage inside the vacuum space. This article discusses the details of the high heat flux dump design, including the computational fluid dynamics (CFD) and structural analyses performed to validate the design to meet the operational requirements of the MPEX device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Microbial and Environmental Processes Shape the Link between Organic Matter Functional Traits and Composition

Dissolved organic matter (DOM) is a large and complex mixture of molecules that fuels biogeochemical reaction in virtually all ecosystems on Earth. However, the relative importance of deterministic and stochastic processes in structuring DOM composition remains poorly characterized. Here we develop a framework for partitioning molecular composition based on key molecular traits, including lability vs. recalcitrance and activity vs. inactivity. Within this framework, we examine the ecological processes governing the assembly of DOM fractions by deploying aquatic microcosms on mountainsides that span gradients of temperature and nutrient loading in subtropical and subarctic ecosystems. Across study regions, deterministic and stochastic processes primarily structure active and inactive fractions, respectively. However, recalcitrant molecules are more deterministically assembled than labile molecules in the inactive fraction. Deterministic processes leading to variable selection generally exhibit more variation across the energy supply gradient for inactive fractions, and their importance increases with energy supply for recalcitrant molecules in both active and inactive fractions. Together, our results indicate that active and inactive fractions of DOM assemblages are structured by contrasting ecological processes, and their recalcitrant components are sensitive to global change. In conclusion, our framework opens new avenues to understand the assembly and turnover of DOM in a changing world, which can be used to predict carbon cycling at local to global scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Novel Three-Phase Oak Ridge AC / DC Converter for Wireless EV Charger Applications

In this paper, a novel three-phase converter is proposed for ac to dc wireless power transfer (WPT) systems for electric vehicle (EV) charging applications. The proposed innovative solution, called as Oak Ridge Converter, reduces the design complexity and cost by eliminating the front-end converter stage compared to the conventional systems. Additionally, grid side requirements can be met with the proposed creative concept. In this concept, the three-phase single-stage Oak Ridge Converter directly converts the 60 Hz grid frequency into high-frequency voltage and utilizes hybrid grid-source and high-frequency to realize power transfer from AC source through resonant network and coupling coils to the battery load. Simulation validation of the proposed three-phase system is currently being carried on and the results will be will be provided to validate the theoretical studies with the input of 277 VAC,RMS and output of 675 VDC at 35 kW power. The system current total harmonic distortion (THD) is measured 5% with a power factor (PF) of 0.98 and overall hardware development of the system that will be used for experiments is presented.

Asa, Erdem↗
DOE OSTI2021

IDAES Enterprise: Generation Expansion Planning with Enhanced Requirements for Capacity Adequacy Under Renewable Intermittency

Achieving net zero carbon emissions likely requires future power systems to integrate new, flexible energy technologies to accommodate higher levels of capacity from variable renewable energy sources. To determine the optimal deployment of new electricity capacity and to study the likelihood of deployments of new energy technologies, an expansion planning model has been developed as part of the IDAES-Enterprise suite of grid models. The Generation Expansion Planning (GEP) model is a multi-period model in which investment decisions occur yearly, and a Unit Commitment (UC) problem is examined on an hourly timescale. To reduce computational complexity of the GEP model, the UC problem is solved for average “representative days” which leaves out extreme, but relatively common, scenarios in which low renewable generation occurs, leaving the system with inadequacy in capacity. The IDAES-Enterprise GEP model has been modified to include these extreme scenarios while keeping the model reasonably tractable. Specifically, a lazy constraint technique was implemented to check for capacity adequacy on an hourly basis over a large data set of aligned load-wind-solar profiles. As a vast majority of the capacity constraints will not be violated, the technique lowers computational expense by searching for violated capacity constraints over an “iterative manner,” adding those infeasible constraints back into the model. Results on a test case of the Southwest Power Pool shows that the lazy constraint technique significantly reduces retirements and increases installments of natural gas combined cycles and flexible natural gas units. It also reduces some retirements of coal units. These modifications provide a more reasonable estimation of required dispatchable power generation capacity to ensure feasibility during peak net load.

Liu, Peng↗
DOE OSTI2023

Reducing the matrix effect in mass spectral imaging of biofilms using flow-cell culture

The interactions between soil microorganisms and soil minerals play a crucial role in the formation and evolution of minerals and the stability of soil aggregates. Due to the heterogeneity and diversity of the soil environment, the under-standing of the functions of bacterial biofilms in soil minerals at the microscale is limited. A soil mineral-bacterial biofilm system was used as a model in this study, and it was analyzed by time-of-flight secondary ion mass spectrometry (ToF-SIMS) to acquire molecular level information. Static culture in multi-wells and dynamic flow-cell culture in microfluidics of biofilms were investigated. Our results show that more characteristic molecules of biofilms can be observed in SIMS spectra of the flow-cell culture. In contrast, biofilm signature peaks are buried under the mineral components in SIMS spectra in the static culture case. Spectral overlay was used in peak selection prior to performing Principal component analysis (PCA). Comparisons of the PCA results between the static and flow-cell culture show more pronounced molecular features and higher loadings of organic peaks of the dynamic cultured specimens. For example, fatty acids secreted from bacterial biofilm extracellular polymeric substance are likely to be responsible for biofilm dispersal due to mineral treatment up to 48 h. Such findings suggest that the use of microfluidic cells to dynamically culture biofilms be a more suitable method for reducing the matrix effect arisen from the growth medium and minerals as a perturbation fac-tor for improved spectral and multivariate analysis of complex mass spectral data in ToF-SIMS. These results show that the interaction mechanism between biofilms and soil minerals at the molecular level can be better studied using the flow-cell culture and advanced mass spectral imaging techniques like ToF-SIMS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Adverse Effect of Polyelectrolyte Complexation on the CO 2 Permeability of Polyvinylamine Copolymers

Polyvinylamine (PVAm) is one of the most studied polymers for facilitated transport membranes (FTMs) in CO 2 separation applications. In this study, poly(N-vinylformamide) (PNVf) was hydrolyzed to prepare a range of PNVf-PVAm copolymer compositions and the effect of PVAm fraction on CO 2 permeability and CO 2 /N 2 selectivity these polymers examined. The most permeable film was the polymer containing 52 mol% PVAm units with a CO 2 permeability of 353 Barrer and CO 2 /N 2 selectivity of 96, when tested at 60°C with humidified 14/86 CO 2 /N 2 mixed gas. Despite containing a higher loading of amines to act as CO 2 carriers, higher PVAm contents yielded significantly lower CO 2 permeability, without a loss of selectivity. This trend was not due to polymer crystallization since none of the PVAm films exhibited crystallinity in X-ray diffraction analysis. The loss of gas permeability at high PVAm content was instead due to strong polyelectrolyte interactions between polymer chains formed when PVAm reacts with CO 2 . Since only the PVAm units are ionized upon reaction with CO 2 , with the PNVf units remaining neutral, the density of these ionic effects increased as PVAm content increased, leading to increased resistance to gas permeation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Insights into Sorption and Molecular Transport of Aqueous Glucose into Zeolite Nanopores

Liquid-phase heterogeneous catalysis using zeolites is important for biomass conversion to fuels and chemicals. There is a substantial body of work on gas-phase sorption in zeolites with different topologies; however, studies investigating the diffusion of complex molecules in liquid medium into zeolitic nanopores are scarce. Here, we present a molecular dynamics study to understand the sorption and diffusion of aqueous β-d-glucose into β-zeolite silicate at T = 395 K and P = 1 bar. Through 2-μs-long molecular dynamics trajectories, we reveal the role of the solvent, the kinetics of the pore filling, and the effect of the water model on these properties. We find that the glucose and water loading is a function of the initial glucose concentration. Although the glucose concentration increases monotonically with the initial glucose concentration, the water loading exhibits a nonmonotonic behavior. At the highest initial concentration (~20 wt %), we find that the equilibrium loading of glucose is approximately five molecules per unit cell and displays a weak dependence on the water model. Glucose molecules follow a single-file diffusion in the nanopores due to confinement. Here, the dynamics of glucose and water molecules slows significantly at the interface. The average residence time for glucose molecules is an order of magnitude larger than that in the bulk solution, while it is about twice as large for the water molecules. Our simulations reveal critical molecular details of the glucose molecule’s local environment inside the zeolite pore relevant to catalytic conversion of biomass to valuable chemicals.

09 BIOMASS FUELS↗
DOE OSTI2021

Collective Nanoparticle Dynamics Associated with Bridging Network Formation in Model Polymer Nanocomposites

The addition of nanoparticles (NPs) to polymers is a powerful method to improve the mechanical and other properties of macromolecular materials. Such hybrid polymer–particle systems are also rich in fundamental soft matter physics. Among several factors contributing to mechanical reinforcement, a polymer-mediated NP network is considered to be the most important in polymer nanocomposites (PNCs). Here, we present an integrated experimental–theoretical study of the collective NP dynamics in model PNCs using X-ray photon correlation spectroscopy and microscopic statistical mechanics theory. Silica NPs dispersed in unentangled or entangled poly(2-vinylpyridine) matrices over a range of NP loadings are used. Static collective structure factors of the NP subsystems at temperatures above the bulk glass transition temperature reveal the formation of a network-like microstructure via polymer-mediated bridges at high NP loadings above the percolation threshold. The NP collective relaxation times are up to 3 orders of magnitude longer than the self-diffusion limit of isolated NPs and display a rich dependence with observation wavevector and NP loading. A mode-coupling theory dynamical analysis that incorporates the static polymer-mediated bridging structure and collective motions of NPs is performed. It captures well both the observed scattering wavevector and NP loading dependences of the collective NP dynamics in the unentangled polymer matrix, with modest quantitative deviations emerging for the entangled PNC samples. Here, we identify an unusual and weak temperature dependence of collective NP dynamics, in qualitative contrast with the mechanical response. Hence, the present study has revealed key aspects of the collective motions of NPs connected by polymer bridges in contact with a viscous adsorbing polymer medium and identifies some outstanding remaining challenges for the theoretical understanding of these complex soft materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A novel methodology for assessing the hygroscopicity of aerosol filter samples

Abstract. Due to US regulations, concentrations of hygroscopic inorganic sulfate and nitrate have declined in recent years, leading to an increased importance of the hygroscopic nature of organic matter (OM). The hygroscopicity of OM is poorly characterized because only a fraction of the multitude of organic compounds in the atmosphere is readily measured, and there is limited information on their hygroscopic behaviors. Hygroscopicity of aerosol is traditionally measured using a humidified tandem differential mobility analyzer (HTDMA) or electrodynamic balance (EDB). EDB measures water uptake by a single particle. For ambient and chamber studies, HTDMA measurements provide water uptake and particle size information but not chemical composition. To fill this information gap, we developed a novel methodology to assess the water uptake by particles collected on Teflon filters. This method uses the same filter sample for both hygroscopicity measurements and chemical characterization, thereby providing an opportunity to link the measured hygroscopicity with ambient particle composition. To test the method, hygroscopic measurements were conducted in the laboratory for ammonium sulfate, sodium chloride, glucose, and malonic acid, which were collected on 25 mm Teflon filters using an aerosol generator and sampler. Constant-humidity solutions (CHSs), including potassium chloride, barium chloride dihydrate, and potassium sulfate, were employed in a saturated form to maintain the relative humidity (RH) at approximately 84 %, 90 %, and 97 % in small chambers. Our preliminary experiments revealed that, without the pouch, water uptake measurements were not feasible due to rapid water loss during weighing. Additionally, we observed some absorption by the aluminum pouch itself. To account for this, concurrent measurements were conducted for both the loaded and the blank filters at each RH level. Thus, the dry loaded and blank Teflon filters were placed in aluminum pouches with one side open and in RH-controlled chambers for more than 24 h. The wet loaded samples and wet blanks were then weighed using an ultramicrobalance to determine the water uptake by the respective compound and the blank Teflon filter. The net amount of water absorbed by each compound was calculated by subtracting the water uptake of the blank filter from that of the wet loaded filter. Hygroscopic parameters, including the water-to-solute (W / S) ratio, molality, mass fraction solute (mfs), and growth factors (GFs), were calculated from the measurements. The results obtained are consistent with those reported by the Extended Aerosol Inorganics Model (E-AIM) and previous studies utilizing HTDMA and EDB for these compounds, highlighting the accuracy of this new methodology. This new approach enables the hygroscopicity and chemical composition of individual filter samples to be assessed so that in complex mixtures, such as chamber and ambient samples, the total water uptake can be parsed between the inorganic and organic components of the aerosol.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Alfalfa Virtual Building Service: Software Engineering Best Practices Applied to Runtime Interaction with Building Energy Models

Buildings are active participants in increasingly complex energy systems. Building Energy Modeling (BEM) has a key role to play in planning and de-risking an equitable energy transition, with BEM-backed "virtual buildings" critical path for diverse applications that include workforce training tools, Hardware-in-the-Loop (HIL) experimentation to study equipment performance under a range of conditions, Control-Hardware-in-the-Loop (CHIL) experimentation to de-risk commercial control implementations at equipment through grid orchestration levels, and integration of dynamic load profiles into grid modeling tools for energy system experimentation at the urban scale. Modeling requirements vary across these applications, but many software engineering tasks do not. The Alfalfa Virtual Building Service (AVBS, see https://github.com/NREL/alfalfa/wiki) is an open-source web service that solves these common tasks robustly in one place, providing a foundational platform for power users to bootstrap their own applications. AVBS abstracts the specifics of runtime interaction with OpenStudio, Modelica, and Spawn of EnergyPlus models behind a unified REST API. Additionally, AVBS provides resources for cloud deployment and scaling to 100s of parallel simulations, a growing library of modular Operational Technology (OT) integrations for emulation of real-world interfaces, and scripts to automate the population of communities of virtual buildings from URBANopt, ResStock and ComStock.

building automation↗
DOE OSTI2025

Material Extrusion Printing of Poly(Acrylonitrile‐Styrene‐Acrylate) and Poly(Acrylonitrile‐Butadiene‐Styrene) Structures Reinforced with Poly(Phenylene Oxide) Additives for Improved Thermomechanical Properties and their Surface Analysis by Time‐of‐Flight Secondary Ion Mass Spectrometry

Fused filament fabrication offers the ability to 3D print complex geometries made from plastic filament materials; however, these parts are mechanically outperformed by parts created by traditional fabrication methods. To overcome this challenge, a high-performance polymer poly(2,6-dimethyl-1,4-phenylene oxide) (PPO) is incorporated as an additive into two common engineering thermoplastics, poly(acrylonitrile-styrene-acrylate) (ASA) and poly(acrylonitrile-butadiene-styrene) (ABS). Structures printed from these polymer blends are more mechanically robust compared to those prepared from the parent polymers, with low loading levels (1–5 wt%) of PPO improving the elastic strength by up to ≈30% relative to the parent terpolymers. Even at higher loading levels (10 and 20 wt% PPO), there is no evidence of additive aggregation in the model thin films, which is supported by compositional analysis of the copolymers and chemical analysis via time-of-flight secondary ion mass spectrometry. The enhancements in mechanical properties of ASA and ABS blends appear to be a consequence of homogeneous incorporation of the PPO additive. In conclusion, this work explores expanding materials-property space using miscible blends of engineering thermoplastics to improve mechanical performance as a general approach to overcoming challenges with parts created by melt-based material extrusion printing.

additive manufacturing↗
DOE OSTI2021

Tripal, a community update after 10 years of supporting open source, standards-based genetic, genomic and breeding databases

Abstract Online, open access databases for biological knowledge serve as central repositories for research communities to store, find and analyze integrated, multi-disciplinary datasets. With increasing volumes, complexity and the need to integrate genomic, transcriptomic, metabolomic, proteomic, phenomic and environmental data, community databases face tremendous challenges in ongoing maintenance, expansion and upgrades. A common infrastructure framework using community standards shared by many databases can reduce development burden, provide interoperability, ensure use of common standards and support long-term sustainability. Tripal is a mature, open source platform built to meet this need. With ongoing improvement since its first release in 2009, Tripal provides full functionality for searching, browsing, loading and curating numerous types of data and is a primary technology powering at least 31 publicly available databases spanning plants, animals and human data, primarily storing genomics, genetics and breeding data. Tripal software development is managed by a shared, inclusive governance structure including both project management and advisory teams. Here, we report on the most important and innovative aspects of Tripal after 11 years development, including integration of diverse types of biological data, successful collaborative projects across member databases, and support for implementing FAIR principles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Tree mortality during long-term droughts is lower in structurally complex forest stands

Increasing drought frequency and severity in a warming climate threaten forest ecosystems with widespread tree deaths. Canopy structure is important in regulating tree mortality during drought, but how it functions remains controversial. Here, we show that the interplay between tree size and forest structure explains drought-induced tree mortality during the 2012-2016 California drought. Through an analysis of over one million trees, we find that tree mortality rate follows a “negative-positive-negative” piecewise relationship with tree height, and maintains a consistent negative relationship with neighborhood canopy structure (a measure of tree competition). Trees overshadowed by tall neighboring trees experienced lower mortality, likely due to reduced exposure to solar radiation load and lower water demand from evapotranspiration. Our findings demonstrate the significance of neighborhood canopy structure in influencing tree mortality and suggest that re-establishing heterogeneity in canopy structure could improve drought resiliency. Our study also indicates the potential of advances in remote-sensing technologies for silvicultural design, supporting the transition to multi-benefit forest management.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Discovery of a Hybrid System for Photocatalytic CO 2 Reduction via Attachment of a Molecular Cobalt-Quaterpyridine Complex to a Crystalline Carbon Nitride

While recent reports have demonstrated the attachment of molecular catalysts to amorphous, graphitic carbon nitrides (g-CN) for light-driven CO 2 reduction, approaches to the utilization of crystalline carbon nitrides have remained undiscovered. Herein, a functional hybrid photocatalyst system has been found using a crystalline carbon nitride semiconductor, poly(triazine imide) lithium chloride (PTI-LiCl), with a surface-attached CoCl 2 (qpy-Ph-COOH) catalyst for CO 2 reduction. The molecular catalyst attaches to PTI-LiCl at concentrations from 0.10 to 4.30 wt % and exhibits ∼96% selectivity for CO production in a CO 2 -saturated, aqueous 0.5 M KHCO 3 solution. Optimal loadings were found to be within 0.42–1.04 wt % with rates between 1,400 and 1,550 μmol CO/g·h at an irradiance of 172 mW/cm 2 (λ = 390 nm) and apparent quantum yields of ∼2%. This optimized loading is postulated to represent a balance between maximal turnover frequency (TOF; 300+ h –1 ) and excess catalyst that can limit excited-electron lifetimes, as probed via transient absorption spectroscopy. An increase in the incident irradiance yields a concomitant increase in the TOFs and CO rates only for the higher catalyst loadings, reaching up to 2,149 μmol CO/g·h with a more efficient use of the catalyst surface capacity. The lower catalyst loadings, by comparison, already function at maximal TOFs. Higher surface loadings are also found to help mitigate deactivation of the molecular catalysts during extended catalytic testing (>24 h) owing to the greater net surface capacity for CO 2 reduction, thus representing an effective strategy to extend lifetime. The hybrid particles can be deposited onto an FTO substrate to yield ∼60% Faradaic efficiency for photoelectrochemical CO production at −1.2 V vs Ag/AgCl bias. In conclusion, these results demonstrate the synergistic combination of a crystalline carbon nitride with a molecular catalyst that achieves among the highest known rates in carbon-nitride systems for the light-driven CO 2 reduction to CO in aqueous solution with >95% selectivity.

CO2 reduction↗
DOE OSTI2022

Enhanced Oblique Decision Tree Enabled Policy Extraction for Deep Reinforcement Learning in Power System Emergency Control

Deep reinforcement learning (DRL) algorithms have successfully solved many challenging problems in various power system control scenarios. However, their decision-making process is usually regarded as black-boxes. Furthermore, how DRL models interact with human intelligence remains an open problem. Thus, this paper proposes a policy extraction framework to extract a complex DRL model into an explainable policy. This framework includes three parts: 1) DRL training and data generation. We train an agent for a specific control task and generate data, which contains the control policy of the agent. 2) Policy extraction. We propose an information gain rate based weighted oblique decision tree (IGR-WODT) for DRL policy extraction. 3) Policy evaluation. We define three metrics to evaluate the performance of the proposed approach. A case study for the under-voltage load shedding problem shows that the IGR-WODT presents a performance enhancement compared with DRL, weighted oblique decision tree, and univariate decision tree. The proposed policy extraction method could provide an intuitive explanation of the neural network decision-making process to the dispatchers when making final decisions on power grid operation. Also, the resulted rule-based controller could replace the deep neural network-based controller in many field edge devices with limited computing resources, providing comparable performance.

deep reinforcement learning↗