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At least 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Localizing tetrahedral aluminum in nitrate-bearing gibbsite to constrain defect-impurity coupling

The enhanced radiolytic stability of gibbsite (α-Al(OH) 3 ) containing trace nitrate (NO 3 − ) is a phenomenon in nuclear waste management, but its structural origins remain unresolved. Motivated by the detection of minority tetrahedral aluminum (T d ) defects in synthetic gibbsite, we hypothesized that these sites may participate in NO 3 − retention or mediate H 2 suppression. To evaluate this, we combined orthogonal techniques comprised of spatially selective solid-state 27 Al MAS NMR, comparative spectroscopy, and density functional theory (DFT) modeling. Paramagnetic editing and dynamic nuclear polarization (DNP) MAS NMR confirm that T d defects are confined to the particle interior. DFT calculations reveal no energetic stabilization of NO 3 − near T d sites. Comparative NMR analysis shows that T d is also present in chloride-bearing gibbsite, which exhibits high radiolytic hydrogen yields. These three independent disqualifications rule out T d as a structural contributor to nitrate-mediated suppression and narrow the scope of defect-driven explanations. The findings redirect mechanistic attention away from coordination defects and toward redox-active impurity pathways, providing a refined foundation for understanding radiation tolerance in Al(OH) 3 .

Graham, Trent R. [Pacific Northwest National Labor↗
DOE OSTI2024

An unstructured body-of-revolution electromagnetic particle-in-cell algorithm with radial perfectly matched layers and dual polarizations

A novel electromagnetic particle-in-cell algorithm has been developed for fully kinetic plasma simulations on unstructured (irregular) meshes in complex body-of-revolution geometries. The algorithm, implemented in the BORPIC++ code, utilizes a set of field scalings and a coordinate mapping, reducing the Maxwell field problem in a cylindrical system to a Cartesian finite element Maxwell solver in the meridian plane. The latter obviates the cylindrical coordinate singularity in the symmetry axis. The choice of an unstructured finite element discretization enhances the geometrical flexibility of the BORPIC++ solver compared to the more traditional finite difference solvers. Symmetries in Maxwell’s equations are explored to decompose the problem into two dual polarization states with isomorphic representations that enable code reuse. The particle-in-cell scatter and gather steps preserve charge conservation at the discrete level. Our previous algorithm (BORPIC+) discretized the E and B field components of TE Φ and TM Φ polarizations on the finite element (primal) mesh. Here, we employ a new field-update scheme. Using the same finite element (primal) mesh, this scheme advances two sets of field components independently: (1) E and B of TE Φ polarized fields, (E z , E ρ , B Φ ) and (2) D and H of TM Φ polarized fields, (D Φ , H z , H ρ ). Since these field updates are not explicitly coupled, the new field solver obviates the coordinate singularity, which otherwise arises at the cylindrical symmetric axis, ρ = 0 when defining the discrete Hodge matrices (generalized finite element mass matrices). Here, a cylindrical perfectly matched layer is implemented as a boundary condition in the radial direction to simulate open space problems, with periodic boundary conditions in the axial direction. We investigate effects of charged particles moving next to the cylindrical perfectly matched layer. We model azimuthal currents arising from rotational motion of charged rings, which produce TMΦ polarized fields. Several numerical examples are provided to illustrate the first application of the algorithm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Uncovering the linear boron environment in Na 3 BP 2 through solid-state 11 B NMR spectroscopy

Boron-based compounds exhibit a wide range of structural diversity, with potential applications spanning organic and inorganic chemistry. Herein, we focus on the characterization of the linear boron-phosphorus unit P═B═P in Na 3 BP 2 using solid-state nuclear magnetic resonance (ssNMR) spectroscopy and density functional theory (DFT) calculations. High-resolution 11 B ssNMR spectra were recorded at two fields, and key parameters such as chemical shift anisotropy (CSA), quadrupolar coupling constants (C Q ), and electric field gradient (EFG) tensors were extracted. The 11 B NMR results revealed a distinct chemical environment for the two-coordinate boron atom, with a CSA span (Ω) of 280 ppm and a C Q of 3.0 MHz. These values were further validated through periodic plane-wave DFT calculations, which showed good agreement with experimental results. The obtained spectral parameters are compared to other linear boron units, such as the BO 2 motif, providing a broader context for understanding boron coordination in inorganic compounds. This work expands the body of NMR knowledge on boron-containing materials, particularly for linear boron motifs. The findings contribute to the growing field of boron chemistry and its potential applications in advanced materials.

Porter, Andrew P. [Ames Laboratory (AMES), Ames, I↗
DOE OSTI2024

A multi-model assessment of the early last deglaciation (PMIP4 LDv1): a meltwater perspective

Abstract. The last deglaciation (∼20–11 ka BP) is a period of a major, long-term climate transition from a glacial to interglacial state that features multiple centennial- to decadal-scale abrupt climate variations whose root cause is still not fully understood. To better understand this time period, the Paleoclimate Modelling Intercomparison Project (PMIP) has provided a framework for an internationally coordinated endeavour in simulating the last deglaciation whilst encompassing a broad range of models. Here, we present a multi-model intercomparison of 17 transient simulations of the early part of the last deglaciation (∼20–15 ka BP) from nine different climate models spanning a range of model complexities and uncertain boundary conditions and forcings. The numerous simulations available provide the opportunity to better understand the chain of events and mechanisms of climate changes between 20 and 15 ka BP and our collective ability to simulate them. We conclude that the amount of freshwater forcing and whether it follows the ice sheet reconstruction or induces an inferred Atlantic meridional overturning circulation (AMOC) history, heavily impacts the deglacial climate evolution for each simulation rather than differences in the model physics. The course of the deglaciation is consistent between simulations except when the freshwater forcing is above 0.1 Sv – at least 70 % of the simulations agree that there is warming by 15 ka BP in most places excluding the location of meltwater input. For simulations with freshwater forcings that exceed 0.1 Sv from 18 ka BP, warming is delayed in the North Atlantic and surface air temperature correlations with AMOC strength are much higher. However, we find that the state of the AMOC coming out of the Last Glacial Maximum (LGM) also plays a key role in the AMOC sensitivity to model forcings. In addition, we show that the response of each model to the chosen meltwater scenario depends largely on the sensitivity of the model to the freshwater forcing and other aspects of the experimental design (e.g. CO2 forcing or ice sheet reconstruction). The results provide insight into the ability of our models to simulate the first part of the deglaciation and how choices between uncertain boundary conditions and forcings, with a focus on freshwater fluxes, can impact model outputs. We can use these findings as helpful insight in the design of future simulations of this time period.

Snoll, Brooke (ORCID:0000000230914394)↗
DOE OSTI2025

Enhanced Ion Transport and Molecular Packing Stability in Asymmetric 2D Nanostructured π‐Conjugated Thieno[3,2‐b]Thiophene‐Based Liquid Crystal

Organic semiconductors based on liquid crystal (LC) molecules have attracted increasing interest. Here, in this work, two linear LCs based on 2,5‐bis(thien‐2‐yl)thieno[3,2‐b]thiophene (BTTT) mesogen are designed and synthesized, including BTTT/dEO3 with two symmetrically attached tri(ethylene oxide) groups and BTTT/mEO6 with one asymmetrically attached hexa(ethylene oxide) group. These two molecules have comparable functional‐group compositions but different molecular geometries, leading to their moderately different material performances. Both LCs show smectic mesophases with relatively low transition temperatures as confirmed by differential scanning calorimetry and polarized optical microscopy. A combination of experimental grazing incidence wide‐angle X‐ray scattering and molecular dynamics (MD) simulations reveals a herringbone packing motif of BTTT segments in both LCs while a smaller molecular tilt angle in BTTT/mEO6. Ionic conductivities are measured by doping LCs with different amounts of ionic dopants, lithium bis(trifluoromethanesulfonyl)imide (LiTFSI). BTTT/mEO6 shows better smectic phase stability to higher LiTFSI doping ratios. Both LCs exhibit similar ionic conductivities in the smectic phases, but BTTT/mEO6 outperforms BTTT/dEO3 by a factor of three in the amorphous phase at higher temperatures. MD simulations, performed to examine the ion solvation environment, reveal that BTTT/mEO6 is more efficient in coordinating Li‐ions and screening their interactions with TFSI‐ions which further promote ionic transport.

grazing incidence wide-angle X-ray scattering↗
DOE OSTI2026

Deciphering the Dynamic Balance Between Solvation Strength and Polysulfides Reaction Heterogeneity in Practical Lithium‐Sulfur Batteries

Achieving stable interfacial chemistry in lithium–sulfur batteries under practical conditions remains a key barrier to commercialization. Here, we demonstrate that interfacial dynamics can be effectively regulated by coupling solvation-power control with intrinsic heterogeneity of sulfur redox chemistry through the introduction of a weakly solvating fluorinated cosolvent, LIB 1200ET (1200ET). Compared with conventional fluorinated ethers, 1200ET efficiently shifts Li + solvation environment toward a more non-coordinated configuration at low volume fractions, enabling substantial solvation modulation without significantly impairing sulfur redox kinetics. This solvation transition weakens Li + –solvent interactions while strengthening Li + –anion and Li + –lithium polysulfide (LPS) coordination, suppressing LPS solubility and promoting reconstruction of solid–electrolyte interphase (SEI). Regulated LPS chemistry, together with 1200ET, leads to formation of a S 4+ -rich, LiF-reinforced SEI with enhanced ionic conductivity and mechanical robustness. Spatially resolved sulfur K-edge X-ray absorption spectroscopy on pouch cells reveals pronounced current-density-dependent chemical heterogeneity, distinguishing kinetically dominated and solvation-controlled regions. Under practical conditions (3.7 mg cm −2 sulfur loading, E/S = 6 µL mg −1 ), a single-layer pouch cell delivers 527 mAh g −1 over 200 cycles at C/3, while an Ah-level multilayer pouch cell achieves an energy density of 358 Wh kg −1 . These results establish non-coordinating cosolvent-driven solvation engineering as a scalable strategy for practical Li–S batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Materials Fingerprinting Classification

Significant progress in many classes of materials could be made with the availability of experimentally-derived large datasets composed of atomic identities and three-dimensional coordinates. Methods for visualizing the local atomic structure, such as atom probe tomography (APT), which routinely generate datasets comprised of millions of atoms, are an important step in realizing this goal. However, state-of-the-art APT instruments generate noisy and sparse datasets that provide information about elemental type, but obscure atomic structures, thus limiting their subsequent value for materials discovery. The application of a materials fingerprinting process, a machine learning algorithm coupled with topological data analysis, provides an avenue by which here-to-fore unprecedented structural information can be extracted from an APT dataset. As a proof of concept, the material fingerprint is applied to high-entropy alloy APT datasets containing body-centered cubic (BCC) and face-centered cubic (FCC) crystal structures. A local atomic configuration centered on an arbitrary atom is assigned a topological descriptor, with which it can be characterized as a BCC or FCC lattice with near perfect accuracy, despite the inherent noise in the dataset. Finally, this successful identification of a fingerprint is a crucial first step in the development of algorithms which can extract more nuanced information, such as chemical ordering, from existing datasets of complex materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Implementation of a Mesh refinement algorithm into the quasi-static PIC code QuickPIC

Plasma-based acceleration (PBA) has emerged as a promising candidate for the accelerator technology used to build a future linear collider and/or an advanced light source. In PBA, a trailing or witness particle beam is accelerated in the plasma wave wakefield (WF) created by a laser or particle beam driver. The WF is often nonlinear and involves the crossing of plasma particle trajectories in real space and thus particle-in-cell methods are used. The distance over which the drive beam evolves is several orders of magnitude larger than the wake wavelength. This large disparity in length scales is amenable to the quasi-static approach. Three-dimensional (3D), quasi-static (QS), particle-in-cell (PIC) codes, e.g., QuickPIC, have been shown to provide high fidelity simulation capability with 2-4 orders of magnitude speedup over 3D fully explicit PIC codes. In PBA, the witness beam needs to be matched to the focusing forces of the WF to reduce the emittance growth. In some linear collider designs, the matched spot size of the witness beam can be 2 to 3 orders of magnitude smaller than the spot size (and wavelength) of the wakefield. Such an additional disparity in length scales is ideal for mesh refinement where the WF within the witness beam is described on a finer mesh than the rest of the WF. A mesh refinement scheme is described that has been implemented into the 3D QS PIC code, QuickPIC. Very fine (high) resolution is used in a small spatial region that includes the witness beam and progressively coarser resolutions in the rest of the simulation domain. A fast multigrid Poisson solver has been implemented for the field solve on the refined meshes and a Fast Fourier Transform (FFT) based Poisson solver is used for the coarse mesh. The code has been parallelized with both MPI and OpenMP, and the parallel scalability has also been improved by using pipelining. A preliminary adaptive mesh refinement technique is described to optimize the computational time for simulations with an evolving witness beam size. Several test problems are used to verify that the mesh refinement algorithm provides accurate results. Additionally, the results are benchmarked against highly resolved simulations exhibiting near-azimuthal symmetry, performed using QPAD—a novel hybrid QS PIC code that uses a PIC description in the coordinates (r, ct – z) and a gridless description in the azimuthal angle, Φ.

Linear collider↗
DOE OSTI2020

Probing Conformational Evolution and Associated Dynamics of Mg(N(SO 2 CF 3 ) 2 ) 2 ·Dimethoxyethane Adduct Using Solid-State 19 F and 1 H NMR

Bis(trifluoromethanesulfonimide) or TFSI is widely used as a counter anion in electrolyte design due to its structural flexibility and chemical stability. Here we studied the conformational variations and associated dynamics of TFSI in adduct of Mg(TFSI) 2 with dimethoxyethane (DME), a solvate crystalline material using solid-state 1 H and 19 F NMR. TFSI molecular motion in this solvate structure falls within the timescale of the 19 F NMR experiment, yielding spectroscopic signatures for unique TFSI conformers under the coordination environment of Mg 2+ cation. Within the temperature range of -5 to 82 °C, we observe nine distinct TFSI sites in both crystalline and disordered regions using 19 F NMR, reflecting complexity of structural and dynamics of TFS1 anions within solvate structure. The four distinguishable sites in the disordered region for the two CF 3 groups of the same TFSI molecule are identified using chemical shift analysis. The exchange rate constants from site to site are calculated through variable temperature 19 F NMR and two-dimensional (2D) exchange spectroscopy (EXSY) experiments, along with respective activation enthalpies using Eyring's formulation. The flip rate of CF 3 around the S-C bond is estimated as ~ 15 s -1 at 8 °C with ΔH ≠ ~ 22 kJ/mol, but the rotation of the entire TFSI is 4.8 s -1 at 8 °C with a significantly greater ΔH ≠ = 98 ± 10 kJ/mol. Furthermore, the slow conversion of trans to cis conformers at a lower temperature (T ≤ 1 °C) in the crystalline region is monitored, with a conversion rate of ~ 2 x 10 -5 s -1 at -5 °C. Density functional theory (DFT)-based calculations were performed to support further the assignment of experimental chemical shifts, and the activation energy E a = 21.1 kJ/mol obtained for the cis to trans transition is consistent with experimental values. The combined set of 19 F and 1 H under both one-dimensional (1D) and 2D NMR methods demonstrated here can be further used for examining electrode-electrolyte interfaces to probe the motions of various constituents that can enable detailed studies of interfacial processes and dynamics. Ultimately, such studies will aid in the design and discovery of interfacial constructs in which directed defect chemistry, chemical moiety distribution, and nanostructure are employed to drive efficient charge transport.

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

Facile One-Pot Block Copolymer-Mediated Solvothermal Approach for Synthesis of High-Entropy Alloy with Enhanced OER Activity

Herein, we introduce a straightforward synthesis approach for highly active dendritic multimetallic high-entropy alloy (DMHEA@PtIrPdAgRu) nanoparticles with sufficient entropic mixing, featuring uniform distribution of five noble group metals (Pt, Ir, Pd, Ag, and Ru) via a block copolymer-mediated one-pot solvothermal reduction method for oxygen evolution reaction (OER). In this synthesis, N,N -dimethylformamide (DMF) is used as a reductant as well as solvent and core–shell-corona-type (poly(styrene)- block -poly(vinylpyridine)- block -poly(ethylene oxide)) (PS-PVP-PEO) block copolymer as a structure directing agent. The cooperative effect between the copolymer architecture and the reducing environment of DMF promoted a confined nucleation mechanism for forming a single-phase dendritic structure HEA with high compositional uniformity, thereby mitigating phase segregation, a common challenge in the synthesis of multimetallic nanoparticles. This prepared DMHEA@PtIrPdAgRu catalyst exhibits a low overpotential of 490 mV to attain a high current density of 100 mA cm –2 with a Tafel slope of 442 mV dec –1 for oxygen evolution. The superior OER performance is attributed to the synergistic cooperation among its active and coordinated metal centers as well as the incorporation of corrosion-resistant metal like platinum.

block copolymer↗
DOE OSTI2025

Colistin resistance plasmids dually enhance bacterial virulence and antibiotic resistance via surface polysaccharide biosynthesis

Plasmids carrying the mobilized colistin-resistance gene mcr-1 are prevalent among multidrug-resistant Gram-negative pathogens, yet their broad impact on bacterial physiology and virulence remains unclear. Here, we demonstrate that acquisition of an mcr-1 plasmid concurrently increases antimicrobial resistance and pathogenicity in Escherichia coli. On the same plasmid, the XRE-family transcriptional regulator EcaR cooperates with MCR-1 to activate the wec operon, driving biosynthesis of two surface polysaccharides: enterobacterial common antigen (ECA) and a high-molecular-weight O-chain. Expression of these surface polysaccharides increases bile resistance and virulence in a murine model and further elevates colistin resistance. MCR-1 enhances transcription of upstream genes in the wec operon, whereas EcaR directly activates an internal promoter (PwecE) to induce downstream gene expression. Thus, both components are required for surface polysaccharide expression, and deletion of either abolishes the phenotype. Genomic analysis of publicly available mcr plasmids reveals widespread co-occurrence of mcr-1 and ecaR on IncI2 and IncX4 plasmids, indicating their functional complementarity. These findings uncover a mechanism by which resistance plasmids remodel the bacterial surface, linking horizontal gene transfer to coordinated regulation of antimicrobial resistance and virulence.

Antimicrobial resistance↗
DOE OSTI2026

Solution structures in alkali nitrates and nitrites at high concentrations

In highly concentrated electrolyte solutions, where classical models often fail, specific ion–solvent interactions dictate bulk properties. Here, in this study, we combine small-angle X-ray scattering (SAXS) and Raman spectroscopy to link molecular coordination to mesoscale structure across alkali nitrate and nitrite solutions. Our results reveal a structural hierarchy driven by cation identity in that smaller cations (Li + , Na + ) form discrete contact ion pairs, while larger cations (K + , Rb + ) promote increasingly disordered local coordination and extended solute–solvent networks. Using nitrite salts as a structural control, we confirm this organizing principle across different anion geometries. Cs + undergoes a concentration-induced transition to a uniquely ordered state, resulting in a highly structured solution. This work provides a direct, mechanistic explanation for how cation choice dictates the ‘rules’ of solution architecture, offering a predictive basis for understanding phase behavior in complex industrial and environmental systems.

Mergelsberg, Sebastian T. [Pacific Northwest Natio↗
DOE OSTI2025

Molecular understanding of ion transport in a zwitterionic electrolyte

Zwitterions (ZIs) are unique molecules that carry both positive and negative charges, resulting in overall charge neutrality and high dielectric constants. These distinctive properties have enabled broad applications of zwitterionic functionality, including the emerging use of ZIs in lithium-ion battery electrolytes. As a contribution to this developing field, we use all-atom molecular dynamics simulations to investigate the ion transport mechanisms in amorphous mixtures of a zwitterionic liquid containing a range of LiTFSI salt concentrations. Furthermore, the local coordination environment around the Li + ions plays a strong role in governing ionic conductivity, as well as the enhancement of Li + transport numbers with increasing salt concentration. Addition of small amounts of water leads to increased conductivity and ion mobilities due to the water coordinating with the Li + ions, which reduces direct interactions with larger charged species.

Classical molecular dynamic simulations↗
DOE OSTI2025

A family of α/β hydrolases removes phytol from chlorophyll metabolites for tocopherol biosynthesis in Arabidopsis

Tocopherol synthesis requires phytyl diphosphate derived from phytol esterified to chlorophyll metabolites. The >600-member Arabidopsis thaliana α/β hydrolase (ABH) gene family contains 4 members that can release phytol from chlorophyll metabolites in vitro; however, only pheophytinase (PPH) affects tocopherol synthesis when mutated, reducing seed tocopherols by 5%. We report the biochemical analysis of 2 previously uncharacterized ABHs, chlorophyll dephytylase 2 (CLD2) and CLD3, and their respective mutants singly and in combinations with pph and cld1 alleles. While all CLDs localized to the thylakoid and could hydrolyze phytol from chlorophylls and Pheophytin a in vitro, CLD3 had the highest in vitro activity and the largest effect on tocopherol synthesis in vivo. The 3 CLDs acted cooperatively to provide phytol for 31% of tocopherols synthesized in light-grown leaf tissue. Dark-induced leaf senescence assays showed PPH is required for 18% of the tocopherols synthesized. Though the cld123 triple mutant had no impact on dark-induced tocopherol content, cld123 in the pph background reduced tocopherol levels by an additional 18%. In seeds, pph and cld123 each reduced tocopherol content by 5% and by 15% in the cld123pph quadruple mutant. VTE7 ( ViTamin E7 ) is an envelope-localized ABH that specifically affects chlorophyll biosynthetic intermediates in vivo and is required for 55% of seed tocopherol synthesis. The introduction of cld123pph into the vte7 background further reduced seed tocopherol levels to 23% of that of the wild type. Our findings demonstrate that phytol provision for tocopherol biosynthesis and homeostasis is a complex process involving the coordinated spatiotemporal expression of multiple ABH family members.

arabidopsis↗
DOE OSTI2020

Effective field theory for deformed odd-mass nuclei

We develop an effective field theory (EFT) for deformed odd-mass nuclei. These are described as an axially symmetric core to which a nucleon is coupled. In the coordinate system fixed to the core the nucleon is subject to an axially symmetric potential. Power counting is based on the separation of scales between low-lying rotations and higher-lying states of the core. In leading order, core and nucleon are coupled by universal derivative terms. These comprise a covariant derivative and gauge potentials which account for Coriolis forces and relate to Berry-phase phenomena. At leading order, the EFT combines the particle-rotor and Nilsson models. Here, we work out the EFT up to next-to-leading order and illustrate the results in 239 Pu and 187 Os . At leading order, odd-mass nuclei with rotational bandheads that are close in energy and differ by one unit of angular momentum are triaxially deformed. For bandheads that are well separated in energy, triaxiality becomes a subleading effect. The EFT developed in this paper presents a model-independent approach to the particle-rotor system that is capable of systematic improvement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Privacy-Preserving Robust Consensus for Distributed Microgrid Control Applications

Consensus-based distributed control has been proposed for coordinating distributed energy resources (DERs) in microgrids (MGs). As one key component, distributed average observers are used to estimate the average of a group of reference signals (e.g., voltage, current, or power). State-of-the-art distributed average observers could lead to loss of privacy due to information exchange on the communication channels. The DERs' reference signals, which contain private information, could be inferred by an eavesdropper. In this article, a privacy-preserving distributed average observer is proposed that is based on robust consensus and uses the state decomposition method to preserve privacy. Compared to the existing methods, the proposed observer does not require the knowledge of the reference signal's derivative and gives accurate and smooth estimation, and is thus applicable for MG distributed control applications. A detailed analysis regarding the convergence and privacy properties of the proposed observer is presented. Here, the proposed observer is implemented on hardware controllers and validated in the context of distributed MG control applications through hardware-in-the-loop (HIL) tests.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

SWARM: Reimagining scientific workflow management systems in a distributed world

Modern scientific workflows process massive amounts of data from diverse instruments and sensors, leveraging geographically distributed, heterogeneous compute and storage resources—from leadership-class systems to edge devices—connected by high-performance networks. The diversity of resources introduces challenges in harnessing their full potential, with resilience issues arising across applications, system software, networks, storage, and hardware. Today, workflow management systems (WMS) coordinate the execution of computation and data management tasks across target resources. However, WMS’s centralized nature makes them vulnerable to faults and scalability issues that may result in failures of entire computational campaigns. In conclusion, this paper introduces a novel agentic framework for workflow management, fully distributing and decentralizing the WMS functions and modeling them as swarm intelligence agents infused with advanced artificial intelligence solutions and traditional distributed computing algorithms that can make coordinated decisions in the presence of failures of the underlying cyberinfrastructure.

Swarm intelligence↗
DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗