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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems: Preprint

We present the PowerGridworld software package to provide users with a light-weight, modular, and customizable framework for creating power systems-focused, multi-agent gym environments that readily integrate with existing training frameworks for reinforcement learning (RL). While many frameworks exist for training multi-agent (MA) RL policies, none exist to rapidly prototype and develop the environments themselves, especially in the context of heterogeneous (composite, multi-device) power systems where power flow solutions are required to define grid-level variables and costs. PowerGridworld is an open-source software package that helps to fill this gap. To highlight PowerGridworld's key features, we present two case studies and demonstrate learning multi-agent RL policies using both OpenAI's MADDPG and RLLib's PPO algorithms where, in both cases, at least some subset of agents incorporate elements of the power flow solution at each time step as part of their reward (negative cost) structures.

MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Digital twin framework for PIP-II linac: AI-driven multi-scale modeling from ion source to 800 MeV

The PIP-II superconducting linac at Fermilab is designed to deliver multi-megawatt proton beams for neutrino physics and other high-intensity applications. To expedite commissioning and enhance operational reliability, we have developed an EPICS-based data flow framework that seamlessly integrates digital twins (DT) with physical twins (PT). These digital twins comprise high-fidelity beam dynamics models or data-driven surrogate models connected to their physical counterparts through real-time diagnostics and advanced machine-learning algorithms.Central to this framework is Linac_Gen, an accelerated simulation tool that incorporates convolutional neural networks, random forests, and genetic algorithms to provide up to a tenfold speedup in optimizing the accelerator geometry model. An EPICS translator layer ensures interoperability by efficiently mapping lattice parameters across diverse simulation platforms.Our EPICS-based framework supports multiple operational modes—monitoring, passive learning, closed-loop control, and online learning—covering the entire machine lifecycle. By leveraging HPC resources and multi-objective optimization techniques, the digital twin enables adaptive trajectory correction, real-time fault detection, and predictive modeling of beam stability. This comprehensive approach paves the way for robust, high-intensity operation and data-driven accelerator R&D at Fermilab.

Pathak, Abhishek [Fermilab]↗
DOE OSTI2026

Machine Learning Interatomic Potentials for Modeling Framework Flexibility and Water Uptake in NbOFFIVE-1-Ni Metal–Organic Framework

Metal–organic frameworks (MOFs), with their distinctive porous structures and tunable chemical properties, have shown immense promise in the separation and storage of gases. Currently, the accurate simulation of their adsorptive properties remains challenging, especially for systems where the molecules fit very tightly into the pores. Traditional simulation methods often approximate the frameworks as rigid and do not account for the framework flexibility seen in materials such as NbOFFIVE-1-Ni. First-principles molecular dynamics (FPMD) simulations offer the desired accuracy in modeling this flexibility but are limited by their extensive computational demands, rendering them impractical for long simulations. Conversely, classical force field-based simulations offer computational efficiency but lack the necessary accuracy. Here, to break this accuracy-efficiency trade-off, we have developed machine learning interatomic potentials trained on energies and forces from FPMD to model the framework flexibility of NbOFFIVE-1-Ni in the presence of water over nanosecond time scales. Furthermore, by integrating MLIP-driven molecular dynamics (MLIP-MD) with grand canonical Monte Carlo (GCMC) simulations, we further incorporated framework flexibility into adsorption predictions, yielding water adsorption isotherms that better align with experimental data compared to those of conventional GCMC simulations. These advances offer new opportunities for the design and optimization of MOFs in gas storage and separation applications.

adsorption↗
DOE OSTI2019

An Americium-Containing Metal-Organic Framework: A Platform for Studying Transplutonium Elements

The synthesis, structural and spectroscopic characterization of the first transplutonium metal-organic framework (MOF) is described. The preparation and structure of Am GWMOF-6, [Am2(C6H8O4)3(H2O)2][(C10H8N2)], is analogous to that of the isostructural trivalent lanthanide-only containing material GWMOF-6. The presented MOF architecture is used as a plat-form to probe Am3+ coordination chemistry and guest-enhanced luminescent emission, whereas the framework itself provided a means to monitor the effects of self-irradiation upon crystallinity over time. Presented here is a discussion of these properties and the opportunities that metal-organic frameworks provide in the structural and spectroscopic study of actinides.

Ridenour, James A.↗
DOE OSTI2024

GDSA framework, a computational framework for complex modeling problems in radioactive waste management

This paper details a computational framework to produce automated, graphical workflows, and how this framework can be deployed to support complex modeling problems like those in nuclear engineering. Key benefits of the framework include: automating previously manual workflows; intuitive construction and communication of workflows through a graphical interface; and automated file transfer and handling for workflows deployed across heterogeneous computing resources. This paper demonstrates the framework's application to probabilistic post-closure performance assessment of systems for deep geologic disposal of nuclear waste. However, the framework is a general capability that can help users running a variety of computational studies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

All-Inorganic Open-Framework Chalcogenides, A 3 Ga 5 S 9 · x H 2 O ( A = Rb and Cs), Exhibiting Ultrafast Uranyl Remediation and Illustrating a Novel Post-Synthetic Preparation of Open-Framework Oxychalcogenides

Fast and effective uranyl sequestration is of interest to the nuclear industry. Recently layered chalcogenide materials have demonstrated fast, selective, and efficient sorption properties towards uranyl cations and the development and investigation of new types of chalcogenide materials continues to be of interest and represents an intriguing option for uranyl remediation. Three new all-inorganic A 3 Ga 5 S 9 ·xH 2 O (A = Rb, Rb/Cs, and Cs) open-framework chalcogenides were obtained via an in-situ alkali carbonate to alkali sulfide conversion process achieved under mild hydrothermal conditions. The structures of the all-inorganic open framework chalcogenides consist of a 2-fold interpenetrated diamond-like 3D framework containing pseudo-T 3 [Ga 10 S 20 ] 10– supertetrahedra. 48% of the structural volume is occupied by A + cations and water species, as established by single-crystal X-ray diffraction (SCXRD), infrared (IR) and energy-dispersive (EDS) spectroscopies. The dynamic nature of the A + cations and water molecules within the pores was investigated via single crystal X-ray diffraction as well as by IR spectroscopy monitored H 2 O to D 2 O exchange experiments. Framework stability was probed with post-synthetic treatment of A 3 Ga 5 S 9 ·xH 2 O (A = Rb and Cs) samples in acidic solutions that resulted in the formation of the oxysulfide (A/H) 3 Ga 5 S 9–y O y ·xH 2 O (A = Rb and Cs; y = 0–1), as shown by SCXRD and IR. Ion-exchange studies on A 3 Ga 5 S 9 ·xH 2 O (A = Rb and Cs) samples were carried out utilizing a uranyl acetate solution. The presence of the UO 2 2+ species in the ion-exchanged product was supported by IR and EDS spectroscopies. Batch method ion-exchange experiments on Cs 3 Ga 5 S 9 ·xH 2 O powder demonstrated fast kinetics with 95% uranyl removal from the uranyl acetate solution during the first minute, a maximum uranyl uptake capacity of 15mg/g, and the subsequent elution of uranyl species with KCl solution. Furthermore, the porous and dynamic nature of the A 3 Ga 5 S 9 ·xH 2 O framework coupled with effective UO 2 2+ ···S 2– bonding interactions makes it a good potential sorbent for uranyl remediation from aqueous media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A competition between 2D and 3D magnetic orderings in novel mixed valent copper frameworks

Low-dimensional hybrid inorganic–organic frameworks exhibit high structural flexibility and allow for the inclusion of various magnetic and optically-active species into their host structures. The emergence of copper-based hybrid structures for various optical applications provides a promising foundation for exploring the integration of magnetic sublattices, paving the way for advancements in magneto-optical coupling and multifunctional materials. Herein, we introduce a novel class of hybrid copper frameworks with covalently-connected alternating magnetic 2D copper(II) formate and non-magnetic copper(I) bromide layers. The anionic framework is stabilized by A + cations to form ACu 5 Br 4 (COOH) 4 (A + = Na + , K + , Rb + , NH 4 + ) semiconductors (bandgaps 2.1–2.2 eV) with optical transitions suitable for optoelectronic applications. Comprehensive magnetometry studies show that ACu 5 Br 4 (COOH) 4 compounds exhibit low-dimensional 2D short-range antiferromagnetic order within the formate layers, characterized by strong exchange coupling (J/k B ∼ −100 K). Upon further temperature reduction, interactions between Cu(II) layers give rise to 3D long-range magnetic order at ∼40 K, despite the large (8.6–8.8 Å) spatial separation of the magnetic Cu(II) formate layers by nonmagnetic Cu(I)–Br bridging layers. This transition is further supported by electron paramagnetic resonance (EPR) spectroscopy. In conclusion, this study expands our understanding of low-dimensional hybrid frameworks and opens new avenues for the design of 2D multifunctional materials.

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

Role of Zeolite Structural Properties toward Iodine Capture: A Head-to-head Evaluation of Framework Type and Chemical Composition

This study evaluated zeolite-based sorbents for iodine gas [I2(g)] capture. Based on the framework structures and porosities, five zeolites, including two faujasite (FAU), one ZSM-5 (MFI), one mesoMFI, one ZSM-22 (TON), as well as two mesoporous materials, were evaluated for I2(g) capture at room temperature and 150 °C in an iodine-saturated environment. From these preliminary studies, the three best-performing zeolites were ion-exchanged with Ag+ and evaluated for I2(g) capture under similar conditions. Energy-dispersive X-ray spectroscopy data suggest that Ag-FAU frameworks were the materials with the highest capacity for I2(g) in this study, showing ~3× higher adsorption compared to Ag-mordenite (Ag-MOR) at room temperature, but X-ray diffraction measurements show that the faujasite structure collapsed during the adsorption studies because of dealumination. The Ag-MFI zeolites are decent sorbents in real-life applications, showing both good sorption capacities and higher stability. In-depth analyses and characterizations, including synchrotron X-ray absorption spectroscopy, revealed the influence of structural and chemical properties of zeolites on the performance for iodine adsorption from the gas phase.

aluminosilicate zeolites, iodine, porosity, acidit↗
DOE OSTI2026

Supramolecular Metal‐Organic Framework Electrocatalysts With Hydration‐Adaptive Gallery Expansion and Linker‐Mediated Distal Ni‐Co Cooperation Enable Framework‐Retentive Oxygen Evolution

Atomic‑level tailoring of electronic communication between spatially separated metal sites offers a route to accelerate multielectron electrocatalysis. We report Ni-TPTC, Co-TPTC, and heterobimetallic Ni-Co-TPTC supramolecular metal-organic frameworks (SMOFs) for the oxygen evolution reaction (OER) built from a terphenyl‑tetracarboxylate (TPTC) linker. Single-crystal X-ray diffraction of heterobimetallic Ni–Co–TPTC reveals trans-bis-aqua octahedral chains assembled into a π-stacked, hydrogen-bonded lattice and confirms retention of the parent architecture, while powder X-ray diffraction supports an isostructural Co analog. In 1.0 M KOH, Ni-Co-TPTC reaches 20 mA cm −2 at 350 mV and maintains operation at ∼60 mA cm −2 for 45 h with modest decay of the initial current. Time‑dependent ex situ diffraction shows dominant framework reflections with low‑angle shifts consistent with gallery dilation (d‑spacing ∼7.7 → ∼9.2 Å) during early operation, while Co K‑edge X‑ray absorption and microscopy reveal Co‑rich oxide/oxyhydroxide‑like domains at longer times that correlate with decay. X‑ray photoelectron spectroscopy, quantified by the Remote Binding‑Energy Differential, tracks composition‑dependent Ni-Co polarization, and DFT free‑energy analysis suggests that a model Ni-Co environment lowers the Co‑centered potential‑limiting step by ∼0.24 eV relative to the Co‑only framework. Furthermore, these results suggest that framework‑retentive expansion and distal Ni-Co coupling can drive OER activity before gradual deligation and oxide formation mark longer‑time degradation.

Supramolecular metal-organic frameworks (SMOFs)↗
DOE OSTI2020

Rational design of a uranyl metal-organic framework for the capture and colorimetric detection of organic dyes

A new uranyl containing metal-organic framework, RPL-1: [(UO2)2(C28H18O8)] · H2O (RPL for Radiochemical Processing Laboratory), was prepared, structurally characterized, and the solid-state photoluminescence properties explored. The single crystal X-ray diffraction data reveal the structure of RPL-1 consists of two crystallographically unique three dimensional, interpenetrating nets with a 4,3-connected tbo topology. Each net contains large pores with an average width of 22.8 Å and is formed from monomeric, hexagonal bipyramidal uranyl nodes that are linked via 1,2,4,5-tetrakis(4-carboxyphenyl)benzene (TCPB) linkers. The thermal and photophysical properties of RPL-1 were investigated using thermogravimetric analysis and absorbance, fluorescence, and lifetime spectroscopies. The material displays excellent thermal stability and temperature dependent uranyl and TCBP luminescence. The framework is stable in aqueous media and due to the large void space (constituting 76% of the unit cell by volume) can sequester organic dyes, the uptake of which induces a visible change to the color of the material.

Surbella, Robert G.↗
DOE OSTI2019

Inorganic Gel-Derived Metallic Frameworks Enabling High-Performance Silicon Anodes

Metallic matrix materials have emerged as an ideal platform to hybridize with next-generation electrode materials such as silicon for practical applications in Li-ion batteries. However, these metallic species commonly exist in the form of isolated particles, failing to provide enough free space for silicon volume changes as well as continuous charge transport pathways. Herein, three-dimensional (3D) metallic frameworks with interconnected pore channels and conductive skeletons, have been synthesized from inorganic gel precursors as buffering/conducting matrices to boost lithium storage performance of silicon anodes. As a proof-of-concept demonstration, commercial Si particles are in situ immobilized within the Sn–Ni alloy framework via a facile gel-reduction route, and the rearrangement of Si particles during cycling increases the dispersity of Si in the Sn–Ni framework as well as their synergic effects toward lithium storage. Furthermore, the Si@Sn–Ni all-metallic framework manifests high structural integrity, 3D Li + /e – mixed conduction pathway, and synergic effects of interfacial bonding and concurrent reaction dynamics between active Si and Sn, enabling long-term cycle life (1205 mA h g –1 after 100 cycles at 0.5 A g –1 ) and superior rate capability (653 mA h g –1 at 10 A g –1 ).

25 ENERGY STORAGE↗
DOE OSTI2022

Multivariate zeolitic imidazolate frameworks with an inverting trend in flexibility

Here, through systematic linker substitution in a flexible zeolitic imidazolate framework (ZIF) with step-shaped adsorption–desorption, structural intermediates between the known open and closed phases were isolated. Reflecting this, modulative sorption behaviour with an inverting adsorption pressure trend—in which the step pressure decreases and then increases again with increasing mixed linker concentration—is observed, highlighting how linker substitution modifies the energetic landscape of framework flexibility

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

Hybrid Porous Crystalline Materials from Metal Organic Frameworks and Covalent Organic Frameworks

Abstract Two frontier crystalline porous framework materials, namely, metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs), have been widely explored owing to their outstanding physicochemical properties. While each type of framework has its own intrinsic advantages and shortcomings for specific applications, combining the complementary properties of the two materials allows the engineering of new classes of hybrid porous crystalline materials with properties superior to the individual components. Since the first report of MOF/COF hybrid in 2016, it has rapidly evolved as a novel platform for diverse applications. The state‐of‐art advances in the various synthetic approaches of MOF/COF hybrids are hereby summarized, together with their applications in different areas. Perspectives on the main challenges and future opportunities are also offered in order to inspire a multidisciplinary effort toward the further development of chemically diverse, multi‐functional hybrid porous crystalline materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Conductive Metallophthalocyanine Framework Films with High Carrier Mobility as Efficient Chemiresistors

Abstract The poor electrical conductivity of two‐dimensional (2D) crystalline frameworks greatly limits their utilization in optoelectronics and sensor technology. Herein, we describe a conductive metallophthalocyanine‐based NiPc‐CoTAA framework with cobalt(II) tetraaza[14]annulene linkages. The high conjugation across the whole network combined with densely stacked metallophthalocyanine units endows this material with high electrical conductivity, which can be greatly enhanced by doping with iodine. The NiPc‐CoTAA framework was also fabricated as thin films with different thicknesses from 100 to 1000 nm by the steam‐assisted conversion method. These films enabled the detection of low‐concentration gases and exhibited remarkable sensitivity and stability. This study indicates the enormous potential of metallophthalocyanine‐based conductive frameworks in advanced stand‐off chemical sensors and provides a general strategy through tailor‐make molecular design to develop sensitive and stable chemical sensors for the detection of low‐concentration gases.

Yue, Yan↗
DOE OSTI2019

Parallel beamlet dose calculation via beamlet contexts in a distributed multi‐GPU framework

Purpose Dose calculation is one of the most computationally intensive, yet essential tasks in the treatment planning process. With the recent interest in automatic beam orientation and arc trajectory optimization techniques, there is a great need for more efficient model‐based dose calculation algorithms that can accommodate hundreds to thousands of beam candidates at once. Foundational work has shown the translation of dose calculation algorithms to graphical processing units ( GPU s), lending to remarkable gains in processing efficiency. But these methods provide parallelization of dose for only a single beamlet, serializing the calculation of multiple beamlets and under‐utilizing the potential of modern GPU s. In this paper, the authors propose a framework enabling parallel computation of many beamlet doses using a novel beamlet context transformation and further embed this approach in a scalable network of multi‐ GPU computational nodes. Methods The proposed context‐based transformation separates beamlet‐local density and TERMA into distinct beamlet contexts that independently provide sufficient data for beamlet dose calculation. Beamlet contexts are arranged in a composite context array with dosimetric isolation, and the context array is subjected to a GPU collapsed‐cone convolution superposition procedure, producing the set of beamlet‐specific dose distributions in a single pass. Dose from each context is converted to a sparse representation for efficient storage and retrieval during treatment plan optimization. The context radius is a new parameter permitting flexibility between the speed and fidelity of the dose calculation process. A distributed manager‐worker architecture is constructed around the context‐based GPU dose calculation approach supporting an arbitrary number of worker nodes and resident GPU s. Phantom experiments were executed to verify the accuracy of the context‐based approach compared to Monte Carlo and a reference CPU ‐ CCCS implementation for single beamlets and broad beams composed by addition of beamlets. Dose for representative 4 π beam sets was calculated in lung and prostate cases to compare its efficiency with that of an existing beamlet‐sequential GPU ‐ CCCS implementation. Code profiling was also performed to evaluate the scalability of the framework across many networked GPU s. Results The dosimetric accuracy of the context‐based method displays <1.35% and 2.35% average error from the existing serialized CPU ‐ CCCS algorithm and Monte Carlo simulation for beamlet‐specific PDD s in water and slab phantoms, respectively. The context‐based method demonstrates substantial speedup of up to two orders of magnitude over the beamlet‐sequential GPU ‐ CCCS method in the tested configurations. The context‐based framework demonstrates near linear scaling in the number of distributed compute nodes and GPU s employed, indicating that it is flexible enough to meet the performance requirements of most users by simply increasing the hardware utilization. Conclusions The context‐based approach demonstrates a new expectation of performance for beamlet‐based dose calculation methods. This approach has been successful in accelerating the dose calculation process for very large‐scale treatment planning problems ‐ such as automatic 4 π IMRT beam orientation and VMAT arc trajectory selection, with hundreds of thousands of beamlets ‐ in clinically feasible timeframes. The flexibility of this framework makes it as a strong candidate for use in a variety of other very large‐scale treatment planning tasks and clinical workflows.

Neph, Ryan↗
DOE OSTI2019

An anomaly detection framework for dynamic systems using a Bayesian hierarchical framework

Complex systems are susceptible to many types of anomalies, faults, and abnormal behavior caused by a variety of off-nominal conditions that may ultimately result in major failures or catastrophic events. Early and accurate detection of these anomalies using system inputs and outputs collected from sensors and smart devices has become a challenging problem and an active area of research in many application domains. In this article, we present a new Bayesian hierarchical framework that is able to model the relationship between system inputs (sensor measurements) and outputs (response variables) without imposing strong distributional/parametric assumptions while using only a subset of training samples and sensor attributes. Then, an optimal cost-sensitive anomaly detection framework is proposed to determine whether a sample is an anomalous one taking into consideration the trade-off between misclassification errors and detection rates. The model can be used for both supervised and unsupervised settings depending on the availability of data regarding the behavior of the system under anomaly conditions. The unsupervised model is particularly useful when it is prohibitive to identify in advance the anomalies that a system may present and where no data are available regarding the behavior of the system under anomaly conditions. A Bayesian hierarchical setting is used to structure the proposed framework and help with accommodating uncertainty, imposing interpretability, and controlling the sparsity and complexity of the proposed anomaly detection framework. A Markov chain Monte Carlo algorithm is also developed for model training using past data. Furthermore, the numerical experiments conducted using a simulated data set and a wind turbine data set demonstrate the successful application of the proposed work for system response modeling and anomaly detection.

17 WIND ENERGY↗
DOE OSTI2018

A Modeling Framework for Evaluating the Drought Resilience of a Surface Water Supply System under Non-stationarity

The future resilience of water supply systems is unprecedentedly challenged by non-stationary processes, such as fast population growth and a changing climate. A thorough understanding of how these non-stationarities impact water supply resilience is vital to support sustainable decision making, particularly for large cities in arid and/or semi-arid regions. In this study, a novel modeling framework, which integrates hydrological processes and water management, was established over a representative water limited metropolitan area to evaluate the impacts of water availability and water demand on reservoir storage and water supply reliability. In this framework, climate change induced drought events were selected from statistically downscaled Coupled Model Intercomparison Project Phase 5 outputs under the Representative Concentration Pathway 8.5 scenario, while future water demand was estimated by the product of projected future population and per capita water use. Compared with the first half of the 21st century (2000–2049), reservoir storage and water supply reliability during the second half century (2050–2099) are projected to reduce by 16.1% and 14.2%, respectively. While both future multi-year droughts and population growth will lower water supply resilience, the uncertainty associated with future climate projection is larger than that associated with urbanization. To reduce the drought risks, a combination of mitigation strategies (e.g., additional conservation, integrating new water sources, and water use redistribution) was found to be the most efficient approach and can significantly improve water supply reliability by as much as 15.9%.

Zhao, Gang (ORCID:0000000327370530)↗