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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Inverse Compton Cooling in the Coronae of Simulated Black Hole Accretion Flows

Here we present a formulation for a local cooling function to be employed in the diffuse, hot corona region of 3D GRMHD simulations of accreting black holes. This new cooling function calculates the cooling rate due to inverse Compton scattering by considering the relevant microphysics in each cell in the corona and approximating the radiation energy density and Compton temperature thereby integrating over the thermal seed photon flux from the disk surface. The method either assumes the ion and electron temperatures are equal (1T) or calculates them separately (2T) using an instantaneous equilibrium approach predicated on the actual relevant rate equations (Coulomb and Compton). The method is shown to be consistent with a more detailed ray-tracing calculation where the bulk of the cooling occurs, but is substantially less costly to perform. As an example, we apply these methods to a harm3d simulation of a 10M⊙, non-spinning black hole, accreting at nominally 1% the Eddington value. This new approach leads to radiative efficiency values sime65% above Novikov–Thorne, with a larger fraction of total cooling in the corona as compared to simulations performed using the original target-temperature cooling function. Time-averaged post-processing reveals that the continuum spectral observations predicted from these simulations are qualitatively similar to actual X-ray binary data, especially so for the 1T approach, which yields a harder power-law component (Γ = 2.25) compared to the 2T version (Γ = 2.53).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Extraction and Separation of Rare-Earth Elements from Coal Fly Ash and Leachate using a Recyclable Ionic Liquid

Coal fly ash (CFA) can be a promising source for recovering rare-earth elements (REEs), as it contains a broad range of REEs with average concentrations frequently exceeding those in traditional rare earth mines. Recent research from our group has demonstrated that REEs can be preferentially extracted from CFA solids using a recyclable ionic liquid (IL), betainium bis-(trifluoromethylsulfonyl)imide ([Hbet][Tf2N]). When CFA was heated with the mixture of IL and an aqueous solution above 65°C, most leached REEs partitioned into the IL phase and were separated from the bulk elements. Subsequent acid stripping of the REE-loaded IL removed the REEs and regenerated the IL for reuse in multiple extraction cycles. This IL-based REE-CFA recovery method has been applied to ten CFA samples derived from different coal sources, including ash recovered from disposal ponds. Analysis of 34 elements confirmed the process consistently achieved high REE recovery efficiency, with strong selectivity over bulk and trace elements across diverse CFA types. In addition to the IL-solid extraction, the performance of [Hbet][Tf2N] in extracting REEs from fly-ash leachates have been evaluated by four commonly used leaching reagents, including HCl, HNO3, H2SO4, and citrate. During the IL-leachate extraction, [Hbet][Tf2N] was mixed and heated with a Class C fly ash leachate generated from each leaching reagent, followed by an acid stripping. It was observed that the partitioning and recovery of REEs increased as the leachate pH increased from 3 to 11. Among the investigated leachates, HCl and citrate proved to be the most compatible with IL extraction, exhibiting a slightly higher REE recovery and a lower non-REE co-extraction compared to the IL-solid extraction. Sc, Y, Nd, Sm, Gd, Dy, and Yb consistently showed a high recovery rate from both CFA solids and leachates. Notably, Pr, Tb, and Ho, which were not previously leached from the CFA solids, were partially recovered from the leachates. Overall, our studies revealed the strong potential of [Hbet][Tf2N] for effectively recovering REEs from leachates, highlighting its applicability as a sustainable strategy for other aqueous REE feedstocks. Furthermore, a techno-economic analysis will be performed to quantify the economic viability of the IL-based REE recovery method and guide future process improvement.

42 ENGINEERING↗
DOE OSTI2020

Evaluation and mitigation of trace 210Pb contamination on copper surfaces

Clean materials are required to construct and operate many low-background physics experiments. High-purity copper has found broad use because of its physical properties and availability. In this paper, we describe methods to assay and mitigate Pb-210 contamination on copper surfaces, such as from exposure to environmental radon or coming from bulk impurities. We evaluated the efficacy of wet etching on commercial samples and observed that Po-210 contamination from the copper bulk does not readily pass into solution. During the etch, the polonium appears to trap at the copper-etchant boundary, such that it is effectively concentrated at the copper surface. We observed a different behavior for Pb-210; high-sensitivity measurements of the alpha emissivity versus time indicate the lowest level of Pb-210 contamination ever reported for a commercial copper surface: 0 +/- 12 nBq/cm2 (1-sigma). Additionally, we have demonstrated the effectiveness of mitigating trace Pb-210 and Po-210 surface backgrounds using custom, high-purity electroplating techniques. These approaches were evaluated utilizing assays performed with an XIA UltraLo-1800 alpha spectrometer.

radon, copper, copper cleaning, dark matter, Pb-21↗
DOE OSTI2026

Signal Whisperers: Enhancing Wireless Reception Using DRL-Guided Reflector Arrays

This paper presents a multi-agent reinforcement learning (MARL) approach for controlling adjustable metallic reflector arrays to enhance wireless signal reception in non-line-of-sight (NLOS) scenarios. Unlike conventional reconfigurable intelligent surfaces (RIS) that require complex channel estimation, our system employs a centralized training with decentralized execution (CTDE) paradigm where individual agents corresponding to reflector segments autonomously optimize reflector element orientation in three-dimensional space using spatial intelligence based on user location information. Through extensive ray-tracing simulations with dynamic user mobility, the proposed multi-agent beam-focusing framework demonstrates substantial performance improvements over single-agent reinforcement learning baselines, while maintaining rapid adaptation to user movement within one simulation step. Comprehensive evaluation across varying user densities and reflector configurations validates system scalability and robustness. The results demonstrate the potential of learning-based approaches for adaptive wireless propagation control.

deep reinforcement learning↗
DOE OSTI2022

Sweep-tracing algorithm: in silico slip crystallography and tension-compression asymmetry in BCC metals

Abstract Direct Molecular Dynamics (MD) simulations are being increasingly employed to model dislocation-mediated crystal plasticity with atomic resolution. Thanks to the dislocation extraction algorithm (DXA), dislocation lines can be now accurately detected and positioned in space and their Burgers vector unambiguously identified in silico, while the simulation is being performed. However, DXA extracts static snapshots of dislocation configurations that by themselves present no information on dislocation motion. Referred to as a sweep-tracing algorithm (STA), here we introduce a practical computational method to observe dislocation motion and to accurately quantify its important characteristics such as preferential slip planes (slip crystallography). STA reconnects pairs of successive snapshots extracted by DXA and computes elementary slip facets thus precisely tracing the motion of dislocation segments from one snapshot to the next. As a testbed for our new method, we apply STA to the analysis of dislocation motion in large-scale MD simulations of single crystal plasticity in BCC metals. We observe that, when the crystal is subjected to uniaxial deformation along its [001] axis, dislocation slip predominantly occurs on the {112} maximum resolved shear stress plane under tension, while in compression slip is non-crystallographic (pencil) resulting in asymmetric mechanical response. The marked contrast in the observed slip crystallography is attributed to the twinning/anti-twinning asymmetry of shears in the {112} planes relatively favoring dislocation motion in the twinning sense while hindering dislocations from moving in the anti-twinning directions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of the TREAT M2 experiment as a transient benchmark

A transient benchmark based on the Transient Reactor Test Facility (TREAT) M2 Calibration experiment (M2-CAL) is under development. TREAT, at Idaho National Laboratory, is a graphite moderated air-cooled research reactor which has been used extensively for fuel material testing under extreme and accident conditions. Accurate benchmark models are a beneficial component in the operations, experimental planning, and development of TREAT. In this work, we present a transient benchmark model for the M2-CAL experiment core loading. The benchmark model incorporates the coupling between the Monte Carlo Code SERPENT and the computational fluid dynamics code OpenFOAM to capture the temperature feedback mechanism. The M2-CAL transient 2580 was simulated in this work. A pre-transient analysis was performed to determine the optimum core composition and conditions before the beginning of the transient. The analysis was validated against historic TREAT kinetic measurements and the worth of the transient rod T-2. The axial power distribution in the flux wire for the M2-CAL experiment was determined and contrasted with the experiment. The model was then used to simulate the M2-CAL transient 2580 experiment based on the reported pre-transient and transient conditions. Several transient observables were calculated and compared to the experiment. The model shows good agreement with the experimental power traces, period, and average increase of power at the power ramp (time > 7.8 s). Inverse point kinetics analysis was performed during the period of the power ramp for the model and the experiment based on that, the temperature feedback component was isolated and contrasted with the experimental feedback. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

UV Degradation in Backsheets: A Ray-Tracing Irradiance Simulation Approach

Around 90% of current photovoltaic (PV) modules are less than ten years old. New PV technologies and materials are deployed without documented durability and performance histories. Accelerated testing attempts to capture degradation modes but can produce false results with such rapid deployment of new materials. Current testing assumes UV dosage on the rear of a module to be 10% of that incident on the front. We present a method to quantify degradation on PV backsheets in the field. We aim to evaluate if current acceleration factors for UV damage in chambers are properly estimating degradation for different PV site installations. The method leverages bifacial_radiance to ray-trace and evaluate irradiance on the front and the rear of the modules. Then an equation to estimate the relative degradation is proposed.

accelerated testing↗
DOE OSTI2021

SMC 2021 : Analyzing Resource Utilization and User Behavior on Titan Supercomputer

Resource utilization statistics of submitted jobs on a supercomputer can help us understand how users from various scientific domains use HPC platforms and better design a job scheduler. We explore to generate insight regarding workload distribution and usage pattern domains from job scheduler trace, GPU failure information, and project-specific information collected from Titan supercomputer. Furthermore, we want to know how the scheduler performance varies over time and how the users' scheduling behavior changes following a system failure. These observations have the potential to provide valuable insight, which is helpful to prepare for system failures. These practices will help us develop and apply novel machine learning algorithms in understanding system behavior, requirement, and better scheduling of HPC systems. There are two datasets, RUR and GPU. RUR: This dataset is the job scheduler traces collected from the Titan supercomputerfrom 01/01/2015 to 07/31/2019 (2015.csv - 2019.csv). These were collected usingResource Utilization Report (RUR), a Cray-developed resource-usage data collectionand reporting system. It contains the usage information of its critical resources (CPU,Memory, GPU, and I/O) of each running job on Titan during that period [2]. ProjectAreas: Every job is associated with a project ID. TheProjectAreas.csvdatasetprovides a mapping of the project ID to its domain science. GPU: There have been some hardware-related issues in the GPUs in Titan that caused some GPUs to fail, sometimes irrecoverably during some job runs. This dataset provides information regarding these failures during the execution of the submitted jobs. GPUs on Titan are uniquely identified by a serial number (SN), and they are installed in a location. A GPU can be installed in a location, then removed from that location following a failure, and then re-installed in a different location after fixing the problem. If the failure can't be recovered, the GPU might be removed entirely from Titan. There are two prominent types of failures that resulted in the removal of GPUs from Titan: Double Bit Error (DBE) and Out of the Bus (OTB). The dataset (gc_full.csv) has the following fields: 1. SN : Serial number of a GPU 2. location : The location where it is installed 3. insert : The time when it was inserted into that location 4. remove : The time when it was removed from that location 5. duration : Amount of time the GPU spent in this location 6. out : If the device was taken out entirely w/o a re-installment into a new location. 7. event : If the GPU was taken out entirely, the reason for its removal. To learn more about this dataset, please refer to the git repositoryhttps://github.com/olcf/TitanGPULifeand the related publication [1]. References [1] George Ostrouchov, Don Maxwell, Rizwan A Ashraf, Christian Engelmann, MallikarjunShankar, and James H Rogers. Gpu lifetimes on titan supercomputer: Survival analysisand reliability. InSC20: International Conference for High Performance Computing,Networking, Storage and Analysis, pages 1-14. IEEE, 2020. [2] Feiyi Wang, Sarp Oral, Satyabrata Sen, and Neena Imam. Learning from five-yearresource-utilization data of titan system. In2019 IEEE International Conference onCluster Computing (CLUSTER), pages 1-6. IEEE, 2019.

42 ENGINEERING↗
DOE OSTI2020

Effect of Water Concentration in LiPF 6 -Based Electrolytes on the Formation, Evolution, and Properties of the Solid Electrolyte Interphase on Si Anodes

A trace amount of water in an electrolyte is one of the factors detrimental to the electrochemical performance of silicon (Si)-based lithium-ion batteries that adversely affect the formation and evolution of the solid electrolyte interphase (SEI) on Si-based anodes and change its properties. Thus far, a lack of fundamental and mechanistic understanding of SEI formation, evolution, and properties in the presence of water has inhibited efforts to stabilize the SEI for improved electrochemical performance. As such, we investigated the SEI formed in a Gen2 electrolyte (1.2 M LiPF6 in ethylene carbonate/ethyl methyl carbonate, 3:7 wt %, water content: <10 ppm) with and without additional water (50 ppm) at varying potentials (1.0, 0.5, 0.2, and 0.01 V vs Li/Li + ). The impact of additional water on the morphological, (electro)chemical, and structural properties of SEI was studied using microscopic (atomic force microscopy and scanning spreading resistance microscopy) and spectroscopic (X-ray photoelectron spectroscopy, attenuated total reflection Fourier-transform infrared spectroscopy, and time-of-flight secondary ion mass spectrometry) techniques. The SEI exhibits both potential- and water concentration-dependent trends in its morphology and chemical composition. The presence of additional water in the electrolyte causes parasitic reactions, which onset at ~1.0 V, resulting in a reduction of electrolyte components and result in the formation of an insulating, fluorophosphate-rich SEI. In addition, hydrolysis of LiPF 6 creates hydrofluoric acid, which reacts with the surface oxide layer on the Si electrode, leading to a pitted and inhomogeneous SEI structure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Mixed halide bulk perovskite triplet sensitizers: Interplay between band alignment, mid-gap traps, and phonons

Photon upconversion, particularly via triplet-triplet annihilation (TTA), could prove beneficial in expanding the efficiencies and overall impacts of optoelectronic devices across a multitude of technologies. The recent development of bulk metal halide perovskites as triplet sensitizers is one potential step toward the industrialization of upconversion-enabled devices. In this work, we investigate the impact of varying additions of bromide into a lead iodide perovskite thin film on the TTA upconversion process in the annihilator molecule rubrene. We find an interplay between the bromide content and the overall device efficiency. In particular, a higher bromide content results in higher internal upconversion efficiencies, enabled by more efficient charge extraction at the interface, likely due to a more favorable band alignment. However, the external upconversion efficiency decreases, as the absorption cross section in the near infrared is reduced. The highest upconversion performance is found in our study for a bromide content of 5%. This result can be traced back to a high absorption cross section in the near infrared and higher photoluminescence quantum yield in comparison to the iodide-only perovskite, as well as an increased driving force for charge transfer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Linking chemical precursors to the synthesis of erythritol tetranitrate

Erythritol tetranitrate (ETN) is a homemade explosive with high explosive performance which can easily be synthesized using widely available chemical precursors. Ascertaining the manner in which ETN is synthesized and being able to trace the ETN back to its precursor materials may aid in the forensic identification. As a proof of concept, seven different types of ETN were synthesized with laboratory grade materials as well as commercially available chemicals from the hardware store and grocery store. The seven different types of solid ETN and the reaction quenches were analyzed using high performance liquid chromatography (HPLC). Partial least squares discriminant analysis (PLS-DA) was used to probe the different classes of ETN and reaction quenches. Several PLS-DA models were produced with the seven different types of ETN and quenches having their own classification, ETN and quenches based on their acid source, and ETN and the quenches based on their nitrate source. Regardless of which classification manner was used, there were no differences found between the different types of ETN or their reaction quenches. Furthermore, it is demonstrated that there is inherent variability in the synthesis of ETN making HPLC an unreliable method to determine the source of the synthesis materials. Elemental impurities were measured in seven solid ETN samples and their reaction quenches by inductively coupled plasma mass spectrometry (ICP-MS). No differences were discovered between the solid ETN samples, but there were trace metals found in the reaction quenches which were found to be identifiers of the source material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

SMC 2021 Data Challenge: Analyzing Resource Utilization and User Behavior on Titan Supercomputer

Resource utilization statistics of submitted jobs on a supercomputer can help us understand how users from various scientific domains use HPC platforms and better design a job scheduler. We explore to generate insight regarding workload distribution and usage pattern domains from job scheduler trace, GPU failure information, and project-specific information collected from Titan supercomputer. Furthermore, we want to know how the scheduler performance varies over time and how the users' scheduling behavior changes following a system failure. These observations have the potential to provide valuable insight, which is helpful to prepare for system failures. These practices will help us develop and apply novel machine learning algorithms in understanding system behavior, requirement, and better scheduling of HPC systems. There are two datasets, RUR and GPU: RUR dataset is the job scheduler traces collected from the Titan supercomputer from 01/01/2015 to 07/31/2019 (2015.csv - 2019.csv). These were collected using resource Utilization Report (RUR), a Cray-developed resource-usage data collection and reporting system. It contains the usage information of its critical resources (CPU, Memory, GPU, and I/O) of each running job on Titan during that period (https://ieeexplore.ieee.org/abstract/document/8891001). It includes ProjectAreas as additional information, every job is associated with a project ID. TheProjectAreas.csv dataset provides a mapping of the project ID to its domain science. GPU dataset has information regarding GPU failure on Titan. There have been some hardware-related issues in the GPUs in Titan that caused some GPUs to fail, sometimes irrecoverably during some job runs. This dataset provides information regarding these failures during the execution of the submitted jobs. GPUs on Titan are uniquely identified by a serial number (SN), and they are installed in a location. A GPU can be installed in a location, then removed from that location following a failure, and then re-installed in a different location after fixing the problem. If the failure can't be recovered, the GPU might be removed entirely from Titan. There are two prominent types of failures that resulted in the removal of GPUs from Titan: Double Bit Error (DBE) and Out of the Bus (OTB). The dataset (gc_full.csv) has seven attributes, we provided a short description of these attributes in the ReadMe file. To learn more about this dataset, please refer to the git repository https://github.com/olcf/TitanGPULife and the related publication (https://ieeexplore.ieee.org/abstract/document/9355319).

42 ENGINEERING↗
DOE OSTI2020

Pairing Directional Solar Inputs From Ray Tracing to Solar Receiver/Reactor Heat Transfer Models on Unstructured Meshes: Development and Case Studies

A novel method for pairing surface irradiation and volumetric absorption from Monte Carlo ray tracing to computational heat transfer models is presented. The method is well-suited to directionally and spatially complex concentrated radiative inputs (e.g., solar receivers and reactors). The method employs a generalized algorithm for directly mapping absorbed rays from a Monte Carlo ray tracing model to boundary or volumetric source terms in the computational mesh. The algorithm is compatible with unstructured, two and three-dimensional meshes with varying element shapes. Four case studies were performed on a directly irradiated, windowed solar thermochemical reactor model to validate the method. The method was shown to conserve energy and preserve spatial variation when mapping rays from a Monte Carlo ray tracing model to a computational heat transfer model in ansys fluent.

14 SOLAR ENERGY↗
DOE OSTI2025

Decentralized Distributed Proximal Policy Optimization (DD-PPO) for High Performance Computing Scheduling on Multi-User Systems

Resource allocation in High Performance Computing (HPC) environments presents a complex and multifaceted challenge for job scheduling algorithms. Beyond the efficient allocation of system resources, schedulers must account for and optimize multiple performance metrics, including job wait time and system throughput. Traditional heuristic-based scheduling algorithms increasingly struggle and lack the efficiency needed to meet the demands and address the complexity and scale of modern HPC systems. Consequently, recent research efforts have focused on leveraging advancements in Artificial Intelligence (AI) and Deep Learning (DL), particularly Reinforcement Learning (RL), to develop more adaptable and intelligent scheduling strategies. Previous RL-based scheduling approaches have explored a range of algorithms, from Deep Q-Networks (DQN) to Proximal Policy Optimization (PPO), and more recently, hybrid methods that integrate Graph Neural Networks (GNNs) with RL techniques. However, a common limitation across these methods is their reliance on relatively small datasets, with few methods being evaluated using large-scale, multi-million-job trace datasets representative of real-world HPC workloads. Moreover, existing RL schedulers face scalability issues due to centralized policy updates, which hinder training efficiency and performance when applied to large datasets. This study introduces a novel RL-based scheduler utilizing Decentralized Distributed Proximal Policy Optimization (DD-PPO) algorithm, which supports large-scale distributed training across multiple workers without requiring parameter synchronization at every step. By eliminating reliance on centralized updates to a shared policy, the DD-PPO scheduler enhances scalability, training efficiency, and sample utilization. Experimental validation using a large real-world dataset containing over 11.5 million job traces collected from petascale HPC systems over six years assesses the influence of dataset scale on training effectiveness and compares DD-PPO performance to traditional and advanced scheduling approaches. The experimental results demonstrate improved scheduling performance in comparison to both heuristic-based schedulers and existing RL-based scheduling algorithms.

AI↗
DOE OSTI2020

An empirical study of I/O separation for burst buffers in HPC systems

To meet the exascale I/O requirements for the High-Performance Computing (HPC), a new I/O subsystem, Burst Buffer, based on solid state drives (SSD), has been developed. However, the diverse HPC workloads and the bursty I/O pattern cause severe data fragmentation that requires costly garbage collection (GC) and increases the number of bytes written to the SSD. To address this data fragmentation challenge, a new multi-stream feature has been developed for SSDs. In this work, we develop an I/O Separation scheme called BIOS to leverage this multi-stream feature to group the I/O streams based on the user IDs. We propose a stream-aware scheduling policy based on burst buffer pools in the workload manager, and integrate the BIOS with the workload manager to optimize the I/O separation scheme in burst buffer. We evaluate the proposed framework with a burst buffer I/O traces from Cori Supercomputer including a diverse set of applications. Experimental results show that the BIOS could improve the performance by 1.44x on average and reduce the Write Amplification Factor (WAF) by up to 1.20x. Finally, these demonstrate the potential benefits of the I/O separation scheme for solid state storage systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

BrzostekEcologyLab/CORPSE-soil-jars

Efforts to manage soils for carbon (C) sequestration remain limited by our understanding of how differences in plant traits and microbial traits mechanistically drive soil organic C (SOC) storage. Addressing this uncertainty is particularly critical in bioenergy agriculture, due to its potential to enhance soil C and provide a C neutral fuel. As such, we examined differences between two contrasting feedstocks, Zea mays (corn) and Miscanthus x giganteus (miscanthus), in the ability of their litter to form new chemically resistant particulate SOC vs. physically protected mineral associated SOC and used this data to improve the parameterization of a microbial SOC model. We tested a hypothesized conceptual model whereby easy to decompose corn litters drive greater microbial carbon use efficiency (CUE) and the formation of more mineral associated SOC over particulate SOC than more complex miscanthus litters. To do this, we performed a soil microcosm experiment where we added 13C enriched aboveground and belowground litters to soils and traced the fate of the 13C into microbial respiration and SOC pools. We found that corn litters promoted higher microbial CUE (0.37) than miscanthus litters (0.24). In turn, corn litter formed approximately 50% more mineral associated SOC than miscanthus litters. Similarly, structurally complex root litters promoted a lower CUE and formed less mineral associated SOC than leaf and shoot litters for both crops. When we used our data to parameterize the SOC model, we found that modeling microbial trait differences uniquely allowed the model to capture the fate of litter C in SOC. Collectively, we found a robust link between litter quality, microbial efficiency, and the formation of SOC. This link bridges the empirical uncertainty in how different crops can form new soil C and provides an empirical basis for modeling SOC transformations.

Ridgeway, Joanna↗
DOE OSTI2021

Demonstrating SolarPILOT's Python API Through Heliostat Optimal Aimpoint Strategy Use Case: Preprint

SolarPILOT is a software package that generates heliostat field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. SolarPILOT was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL's System Advisor Model (SAM) in a simplified format. Prior means for user interaction with SolarPILOT have included the application's graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called "LK." This paper presents a new, full-featured Python-based application programmable interface (API) for SolarPILOT, which we hereafter refer to as CoPylot. CoPylot provides access to all SolarPILOT's capabilities to generate and characterize power tower CSP systems seamlessly through Python. Supported capabilities include (i) creating and destroying a model instances with message reporting tools; (ii) accessing and setting any SolarPILOT variable including custom land boundaries for field layout; (iii) programmatically managing receiver and heliostat objects with varied attributes for systems with multiple receiver or heliostat types; (iv) generating, assigning, and modifying heliostat field layouts including the ability to set individual heliostat locations, aimpoints, soiling rates, and reflectivity levels; (v) simulating heliostat field performance; (vi) returning detailed results describing performance of individual heliostats, the aggregate field, and receiver flux; and, (vii) exporting Python-based model instances to multiple file formats. CoPylot enables Python users to perform detailed tower CSP analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. In addition to CoPylot's functionality, Python users have access to the over 100,000 open-source libraries to develop, analyze, optimize, and visualize CSP tower research.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2022

Self-Adjusting Metal–Organic Framework for Efficient Capture of Trace Xenon and Krypton

The capture of the xenon and krypton from nuclear reprocessing off-gas is essential to the treatment of radioactive waste. Although various porous materials have been employed to capture Xe and Kr, the development of high-performance adsorbents capable of trapping Xe/Kr at very low partial pressure as in the nuclear reprocessing off-gas conditions remains challenging. Herein, we report a self-adjusting metal-organic framework based on multiple weak binding interactions to capture trace Xe and Kr from the nuclear reprocessing off-gas. The self-adjusting behavior of ATC-Cu and its mechanism have been visualized by the in-situ single-crystal X-ray diffraction studies and theoretical calculations. The self-adjusting behavior endows ATC-Cu unprecedented uptake capacities of 2.65 and 0.52 mmol g -1 for Xe and Kr respectively at 0.1 bar and 298 K, as well as the record Xe capture capability from the nuclear reprocessing off-gas. Further, our work not only provides a benchmark Xe adsorbent but proposes a new route to construct smart materials for efficient separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗