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Results for “Proliferation”

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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Structural basis of Qng1-mediated salvage of the micronutrient queuine from queuosine-5′-monophosphate as the biological substrate

Abstract Eukaryotic life benefits from—and ofttimes critically relies upon—the de novo biosynthesis and supply of vitamins and micronutrients from bacteria. The micronutrient queuosine (Q), derived from diet and/or the gut microbiome, is used as a source of the nucleobase queuine, which once incorporated into the anticodon of tRNA contributes to translational efficiency and accuracy. Here, we report high-resolution, substrate-bound crystal structures of the Sphaerobacter thermophilus queuine salvage protein Qng1 (formerly DUF2419) and of its human ortholog QNG1 (C9orf64), which together with biochemical and genetic evidence demonstrate its function as the hydrolase releasing queuine from queuosine-5′-monophosphate as the biological substrate. We also show that QNG1 is highly expressed in the liver, with implications for Q salvage and recycling. The essential role of this family of hydrolases in supplying queuine in eukaryotes places it at the nexus of numerous (patho)physiological processes associated with queuine deficiency, including altered metabolism, proliferation, differentiation and cancer progression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Novobiocin blocks nucleic acid binding to Polθ and inhibits stimulation of its ATPase activity

Polymerase theta (Polθ) acts in DNA replication and repair, and its inhibition is synthetic lethal in BRCA1 and BRCA2-deficient tumor cells. Novobiocin (NVB) is a first-in-class inhibitor of the Polθ ATPase activity, and it is currently being tested in clinical trials as an anti-cancer drug. Here, we investigated the molecular mechanism of NVB-mediated Polθ inhibition. Using hydrogen deuterium exchange-mass spectrometry (HX-MS), biophysical, biochemical, computational and cellular assays, we found NVB is a non-competitive inhibitor of ATP hydrolysis. NVB sugar group deletion resulted in decreased potency and reduced HX-MS interactions, supporting a specific NVB binding orientation. Collective results revealed that NVB binds to an allosteric site to block DNA binding, both in vitro and in cells. Comparisons of The Cancer Genome Atlas (TCGA) tumors and matched controls implied that POLQ upregulation in tumors stems from its role in replication stress responses to increased cell proliferation: this can now be tested in fifteen tumor types by NVB blocking ssDNA-stimulation of ATPase activity, required for Polθ function at replication forks and DNA damage sites. Structural and functional insights provided in this study suggest a path for developing NVB derivatives with improved potency for Polθ inhibition by targeting ssDNA binding with entropically constrained small molecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Gene-by-environment interactions in plants: Molecular mechanisms, environmental drivers, and adaptive plasticity

Abstract Plants demonstrate a broad range of responses to environmental shifts. One of the most remarkable responses is plasticity, which is the ability of a single plant genotype to produce different phenotypes in response to environmental stimuli. As with all traits, the ability of plasticity to evolve depends on the presence of underlying genetic diversity within a population. A common approach for evaluating the role of genetic variation in driving differences in plasticity has been to study genotype-by-environment interactions (G × E). G × E occurs when genotypes produce different phenotypic trait values in response to different environments. In this review, we highlight progress and promising methods for identifying the key environmental and genetic drivers of G × E. Specifically, methodological advances in using algorithmic and multivariate approaches to understand key environmental drivers combined with new genomic innovations can greatly increase our understanding about molecular responses to environmental stimuli. These developing approaches can be applied to proliferating common garden networks that capture broad natural environmental gradients to unravel the underlying mechanisms of G × E. An increased understanding of G × E can be used to enhance the resilience and productivity of agronomic systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

The Chlamydomonas Genome Project, version 6: reference assemblies for mating type plus and minus strains reveal extensive structural mutation in the laboratory

Five versions of the Chlamydomonas reinhardtii reference genome have been produced over the last two decades. Here we present version 6, bringing significant advances in assembly quality and structural annotations. PacBio-based chromosome-level assemblies for two laboratory strains, CC-503 and CC-4532, provide resources for the plus and minus mating type alleles. We corrected major misassemblies in previous versions and validated our assemblies via linkage analyses. Contiguity increased over ten-fold and >80% of filled gaps are within genes. We used Iso-Seq and deep RNA-seq datasets to improve structural annotations, and updated gene symbols and textual annotation of functionally characterized genes via extensive manual curation. We discovered that the cell wall-less classical reference strain CC-503 exhibits genomic instability potentially caused by deletion of the helicase RECQ3, with major structural mutations identified that affect >100 genes. We therefore present the CC-4532 assembly as the primary reference, although this strain also carries unique structural mutations and is experiencing rapid proliferation of a Gypsy retrotransposon. We expect all laboratory strains to harbor gene-disrupting mutations, which should be considered when interpreting and comparing experimental results. Collectively, the resources presented here herald a new era of Chlamydomonas genomics and will provide the foundation for continued research in this important reference organism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Cytochrome b5 diversity in green lineages preceded the evolution of syringyl lignin biosynthesis

Abstract Lignin production marked a milestone in vascular plant evolution, and the emergence of syringyl (S) lignin is lineage specific. S-lignin biosynthesis in angiosperms, mediated by ferulate 5-hydroxylase (F5H, CYP84A1), has been considered a recent evolutionary event. F5H uniquely requires the cytochrome b5 protein CB5D as an obligatory redox partner for catalysis. However, it remains unclear how CB5D functionality originated and whether it coevolved with F5H. We reveal here the ancient evolution of CB5D-type function supporting F5H-catalyzed S-lignin biosynthesis. CB5D emerged in charophyte algae, the closest relatives of land plants, and is conserved and proliferated in embryophytes, especially in angiosperms, suggesting functional diversification of the CB5 family before terrestrialization. A sequence motif containing acidic amino residues in Helix 5 of the CB5 heme-binding domain contributes to the retention of CB5D function in land plants but not in algae. Notably, CB5s in the S-lignin–producing lycophyte Selaginella lack these residues, resulting in no CB5D-type function. An independently evolved S-lignin biosynthetic F5H (CYP788A1) in Selaginella relies on NADPH-dependent cytochrome P450 reductase as sole redox partner, distinct from angiosperms. These results suggest that angiosperm F5Hs coopted the ancient CB5D, forming a modern cytochrome P450 monooxygenase system for aromatic ring meta-hydroxylation, enabling the reemergence of S-lignin biosynthesis in angiosperms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Arabidopsis lipins mediate lipid droplet biogenesis to protect cells from lipotoxicity

Lipin proteins, a family of phosphatidic acid phosphatases (PAHs), are key regulators of lipid metabolism, storage, and homeostasis across eukaryotes. While Arabidopsis (Arabidopsis thaliana) lipins function in lipid biosynthesis and gene regulation, their roles in lipid droplet (LD) biogenesis and lipid homeostasis remain largely unknown. Here, we show that double knockout of two PAH genes (PAH1/2) results in impaired LD biogenesis, accelerated triacylglycerol (TAG) hydrolysis, and lipid imbalance. pah1/2 mutant leaves exhibited a marked reduction in TAG levels and a significant decrease in LD size, while the rates of TAG and diacylglycerol (DAG) synthesis remained largely unchanged. In seeds, PAH1/2 disruption minimally affected TAG content but significantly reduced LD size. Fatty acid feeding experiments demonstrated impaired LD formation and increased lipotoxicity in pah1/2 leaves and seedlings. Furthermore, knockout of PAH1/2 in mutants with enhanced fatty acid flux through phosphatidylcholine (PC) led to severe reductions in leaf TAG levels, despite increases in TAG synthesis rates, indicating accelerated TAG turnover. Phosphatidic acid, free fatty acids, and PC accumulated, leading to massive proliferation of endoplasmic reticulum membranes and severe growth and developmental defects. These findings demonstrate evolutionarily conserved roles for PAH1/2 in LD biogenesis, membrane lipid homeostasis, and cellular protection against lipotoxicity, particularly under conditions of elevated fatty acid flux.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Gene Expression Thresholds Derived From Short-term Exposures Identify Rat Liver Tumorigens

Abstract Traditional methods for cancer risk assessment are resource-intensive, retrospective, and not feasible for the vast majority of environmental chemicals. In this study, we investigated whether quantitative genomic data from short-term studies may be used to set protective thresholds for potential tumorigenic effects. We hypothesized that gene expression biomarkers measuring activation of the key early events in established pathways for rodent liver cancer exhibit cross-chemical thresholds for tumorigenesis predictive for liver cancer risk. We defined biomarker thresholds for 6 major liver cancer pathways using training sets of chemicals with short-term genomic data (3–29 days of exposure) from the TG-GATES (n = 77 chemicals) and DrugMatrix (n = 86 chemicals) databases and then tested these thresholds within and between datasets. The 6 pathway biomarkers represented genotoxicity, cytotoxicity, and activation of xenobiotic, steroid, and lipid receptors (aryl hydrocarbon receptor, constitutive activated receptor, estrogen receptor, and peroxisome proliferator-activated receptor α). Thresholds were calculated as the maximum values derived from exposures without detectable liver tumor outcomes. We identified clear response values that were consistent across training and test sets. Thresholds derived from the TG-GATES training set were highly predictive (97%) in a test set of independent chemicals, whereas thresholds derived from the DrugMatrix study were 96%–97% predictive for the TG-GATES study. Threshold values derived from an abridged gene list (2/biomarker) also exhibited high predictive accuracy (91%–94%). These findings support the idea that early genomic changes can be used to establish threshold estimates or “molecular tipping points” that are predictive of later-life health outcomes.

Hill, III,, Thomas↗
DOE OSTI2022

Integrating Data From In Vitro New Approach Methodologies for Developmental Neurotoxicity

Abstract In vivo developmental neurotoxicity (DNT) testing is resource intensive and lacks information on cellular processes affected by chemicals. To address this, DNT new approach methodologies (NAMs) are being evaluated, including: the microelectrode array neuronal network formation assay; and high-content imaging to evaluate proliferation, apoptosis, neurite outgrowth, and synaptogenesis. This work addresses 3 hypotheses: (1) a broad screening battery provides a sensitive marker of DNT bioactivity; (2) selective bioactivity (occurring at noncytotoxic concentrations) may indicate functional processes disrupted; and, (3) a subset of endpoints may optimally classify chemicals with in vivo evidence for DNT. The dataset was comprised of 92 chemicals screened in all 57 assay endpoints sourced from publicly available data, including a set of DNT NAM evaluation chemicals with putative positives (53) and negatives (13). The DNT NAM battery provides a sensitive marker of DNT bioactivity, particularly in cytotoxicity and network connectivity parameters. Hierarchical clustering suggested potency (including cytotoxicity) was important for classifying positive chemicals with high sensitivity (93%) but failed to distinguish patterns of disrupted functional processes. In contrast, clustering of selective values revealed informative patterns of differential activity but demonstrated lower sensitivity (74%). The false negatives were associated with several limitations, such as the maximal concentration tested or gaps in the biology captured by the current battery. This work demonstrates that this multi-dimensional assay suite provides a sensitive biomarker for DNT bioactivity, with selective activity providing possible insight into specific functional processes affected by chemical exposure and a basis for further research.

Carstens, Kelly E.↗
DOE OSTI2022

A Novel Zinc Binding Group for HDAC6 Inhibition

Histone deacetylases (HDAC’s) are key regulatory enzymes in gene transcription and cellular motility through the deacetylation of lysine residues. These enzymes bear a distinct clinical significance, as the upregulation of HDACs has been associated with oncogenesis for many hematological malignancies and proliferation of other neurodegenerative or immune disorders. There are four different classes of HDACs, three of which require zinc for catalysis. Among the zinc dependent isozymes, HDAC6 is thought to be a particularly desirable therapeutic target, as its selective inhibition in malignant cells is accompanied by fewer associated toxicities in comparison to pan‐HDAC inhibition. Therefore, optimizing HDAC6 inhibitor selectivity has the potential to yield great clinical significance. This selectivity is often conferred by designing inhibitors with bulky capping groups and a hydrophobic linker region, which make favorable interactions in the hydrophobic region of the HDAC6 active site. Many inhibitors contain a hydroxamate zinc‐binding group, which can coordinate with bidentate or monodentate geometry. In efforts to optimize HDAC6 selectivity by exploring alternative zinc‐binding groups, a unique inhibitor containing an oxadiazole ring was discovered. Surprisingly, the crystal structure of its complex with HDAC6 reveals that the oxadiazole undergoes a ring opening reaction to yield an acylhydrazide that binds with an extended conformation in the active site.

Cragin, Abigail↗
DOE OSTI2020

Theory of finite-temperature two-dimensional structural transformations in group-IV monochalcogenide monolayers

An account of two-dimensional (2D) structural transformations in 2D ferroelectrics predicts an evolution from a structure with Pnm 2 1 symmetry into a structure with square P4/nmm symmetry and is consistent with experimental evidence, while another argues for a transformation into a structure with rectangular Pnmm symmetry. An analysis of the assumptions made in these models is provided here, and six fundamental results concerning these transformations are contributed as follows: (i) Softened phonon modes produce rotational modes in these materials. (ii) The transformation to a structure with P4/nmm symmetry occurs at the lowest critical temperature T c . (iii) The hypothesis that one unidirectional optical vibrational mode underpins the 2D transformation is unwarranted. (iv) Being successively more constrained, a succession of critical temperatures ( T c < T c ' < T c " ) occurs in going from molecular dynamics calculations with the NPT and NVT ensembles onto models with unidirectional oscillations. (v) The choice of exchange-correlation functional impacts the estimate of the critical temperature. (vi) Importantly, the correct physical picture of these transformations is one in which rotational modes confer a topological character to the 2D transformation via the proliferation of vortices.

2d ferroelectrics↗
DOE OSTI2021

Frustrated Kondo impurity triangle: A simple model of deconfinement

We report that the concepts of deconfinement and topological order are of great current interest for quantum information science and for our understanding of quantum materials. Here, we introduce a simple model of three antiferromagnetically coupled Kondo impurities, a Kondo triangle, which can be used to further extend the application of these concepts to electronic systems. We show that, by tuning the magnetic frustration, the Kondo triangle undergoes a quantum phase transition between two phases of unbroken symmetry, signaling a phase transition beyond the Landau paradigm. We demonstrate that the frustrated spin liquid phase is described by a three-channel Kondo (3CK) fixed point and thus displays an irrational ground state degeneracy. Using an Abrikosov pseudofermion representation, this quantum state is categorized by an emergent U(1) gauge field and its projective symmetry group. The gauge theory is deconfining in the sense that a miniature Wilson loop orders and topological defects (instantons in the gauge field) are expelled. This phase persists in the presence of moderate Kondo screening until proliferation of topological defects leads to a quantum phase transition to an unfrustrated Fermi liquid phase. Based on this evidence, we propose that the 3CK phase displays topological order in a similar sense as gapless spin liquids.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Identification of a characteristic doping for charge order phenomena in Bi-2212 cuprates via RIXS

Identifying quantum critical points (QCPs) and their associated fluctuations may hold the key to unraveling the unusual electronic phenomena observed in cuprate superconductors. Recently, signatures of quantum fluctuations associated with charge order (CO) have been inferred from the anomalous enhancement of CO excitations that accompany the reduction of the CO order parameter in the superconducting state. Furthermore, to gain more insight about the interplay between CO and superconductivity, we investigate the doping dependence of this phenomenon throughout the Bi-2212 cuprate phase diagram using resonant inelastic x-ray scattering (RIXS) at the Cu L 3 edge. As doping increases, the CO wavevector decreases, saturating near a commensurate value of 0.25 r.l.u. beyond a characteristic doping p c , where the correlation length becomes shorter than the apparent periodicity (4a 0 ). Such behavior is indicative of the fluctuating nature of the CO; and the proliferation of CO excitations in the superconducting state also appears strongest at p c , consistent with expected behavior at a CO QCP. Intriguingly, p c appears to be near optimal doping, where the superconducting transition temperature T c is maximal.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Principles of two-dimensional terahertz spectroscopy of collective excitations: The case of Josephson plasmons in layered superconductors

Two-dimensional terahertz spectroscopy (2DTS), a terahertz analog of nuclear magnetic resonance, is a new technique poised to address many open questions in complex condensed matter systems. The conventional theoretical framework used ubiquitously for interpreting multidimensional spectra of discrete quantum level systems is, however, insufficient for the continua of collective excitations in strongly correlated materials. Here, in this work, we develop a theory for 2DTS of a model collective excitation, the Josephson plasma resonance in layered superconductors. Starting from a mean-field approach at temperatures well below the superconducting phase transition, we obtain expressions for the multidimensional nonlinear responses that are amenable to intuition derived from the conventional single-mode scenario. We then consider temperatures near the superconducting critical temperature T c , where dynamics beyond mean-field become important and conventional intuition fails. As fluctuations proliferate near T c , the dominant contribution to nonlinear response comes from an optical parametric drive of counterpropagating Josephson plasmons, which gives rise to 2D spectra that are qualitatively different from the mean-field predictions. As such, and in contrast to one-dimensional spectroscopy techniques, such as third harmonic generation, 2DTS can be used to directly probe thermally excited finite-momentum plasmons and their interactions. Our theory can readily be tested in cuprates, and we discuss implications beyond the present context of Josephson plasmons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

C 12 ( n , n 1 ′ γ ) partial γ -ray cross section measured using the GENESIS array

Improved neutron inelastic scattering cross sections have repeatedly been identified as a top priority nuclear data need, important for basic science and a range of applications in nuclear energy, stockpile stewardship, and proliferation detection. For the C 12 ( n , n ′ γ ) reaction in particular, recent measurements have unveiled some structural discrepancies, demonstrating incongruities among themselves and in relation to the ENDF/B-VIII.0 nuclear data evaluation. To help resolve these disagreements, a measurement was performed at the 88-Inch Cyclotron at Lawrence Berkeley National Laboratory using a broad-spectrum neutron beam and a 99.8% pure natural carbon target. The Gamma Energy Neutron Energy Spectrometer for Inelastic Scattering (GENESIS) was employed to measure energy-differential γ -ray emission spectra as a function of incident neutron energy in the energy range of 5.5 to 16.7 MeV. The C 12 partial γ -ray cross sections were extracted at 63 ∘ , 122 . 5 ∘ , and 150 ∘ with respect to the incoming neutron beam and integrated using angular distribution data available in the literature. The data show agreement with a recent literature measurement and evaluation from 11 to 15 MeV, but indicate a larger cross section for incident neutron energies between 5.5 and 8.5 MeV. The measured relative angular distributions are also reported and were found to agree with evaluation. Published by the American Physical Society 2025

Gordon, J. M. (ORCID:0009000789886897)↗
DOE OSTI2020

Relativistic hybrid stars with sequential first-order phase transitions and heavy-baryon envelopes

We compute the mass, radius and tidal deformability of stars containing phase transitions from hadronic to quark phase(s). These quantities are computed for three types of hadronic envelopes: purely nuclear, hyperonic, and Δ-resonance--hyperon admixed matter. We consider either a single first-order phase transition to a quark phase with a maximally stiff equation of state (EOS) or two sequential first-order phase transitions mimicking a transition from hadronic to a quark matter phase followed by a second phase transition to another quark phase. We explore the parameter space which produces low-mass twin and triplet configurations where equal-mass stars have substantially different radii and tidal deformabilities. We demonstrate that while for purely hadronic stiff EOS the obtained maximum mass is inconsistent with the upper limit on this quantity placed by GW170817, the inclusion of the hyperonic and Δ-resonance degrees of freedom, as well as the deconfinement phase transition at sufficiently low density, produces a configuration of stars consistent with this limit. The obtained hybrid star configurations are in the mass range relevant for the interpretation of the GW170817 event. We compare our results for the tidal deformability with the limits inferred from GW170817 showing that the onset of non-nucleonic phases, such as Δ-resonance--hyperon admixed phase and/or the quark phase(s), are favored by this data if the nuclear EOS is stiff. Also, we show that low-mass twins and especially triplets proliferate the number of combinations of possible types of stars that can undergo a merger event, the maximal number being six in the case of triplets. The prospects for uncovering the first-order phase transition(s) to and in quark matter via measurements of tidal deformabilities in merger events are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Data assimilation empowered neural network parametrizations for subgrid processes in geophysical flows

In the past couple of years, there has been a proliferation in the use of machine learning approaches to represent subgrid-scale processes in geophysical flows with an aim to improve the forecasting capability and to accelerate numerical simulations of these flows. Despite its success for different types of flow, the online deployment of a data-driven closure model can cause instabilities and biases in modeling the overall effect of subgrid-scale processes, which in turn leads to inaccurate prediction. To tackle this issue, we exploit the data assimilation technique to correct the physics-based model coupled with the neural network as a surrogate for unresolved flow dynamics in multiscale systems. In particular, we use a set of neural network architectures to learn the correlation between resolved flow variables and the parametrizations of unresolved flow dynamics and formulate a data assimilation approach to correct the hybrid model during their online deployment. We illustrate our framework in a set of applications of the multiscale Lorenz 96 system for which the parametrization model for unresolved scales is exactly known, and the two-dimensional Kraichnan turbulence system for which the parametrization model for unresolved scales is not known a priori. Our analysis, therefore, comprises a predictive dynamical core empowered by (i) a data-driven closure model for subgrid-scale processes, (ii) a data assimilation approach for forecast error correction, and (iii) both data-driven closure and data assimilation procedures. We show significant improvement in the long-term prediction of the underlying chaotic dynamics with our framework compared to using only neural network parametrizations for future prediction. Moreover, we demonstrate that these data-driven parametrization models can handle the non-Gaussian statistics of subgrid-scale processes, and effectively improve the accuracy of outer data assimilation workflow loops in a modular nonintrusive way.

42 ENGINEERING↗
DOE OSTI2022

Trotter Errors from Dynamical Structural Instabilities of Floquet Maps in Quantum Simulation

We study the behavior of errors in the quantum simulation of spin systems with long-range multibody interactions resulting from the Trotter-Suzuki decomposition of the time-evolution operator. We identify a regime where the Floquet operator underlying the Trotter decomposition undergoes sharp changes even for small variations in the simulation step size. This results in a time evolution operator that is very different from the dynamics generated by the targeted Hamiltonian, which leads to a proliferation of errors in the quantum simulation. These regions of sharp change in the Floquet operator, referred to as structural instability regions, appear typically at intermediate Trotter step sizes and in the weakly interacting regime, and are thus complementary to recently revealed quantum chaotic regimes of the Trotterized evolution [L. M. Sieberer et al. npj Quantum Inf. 5, 78 (2019); M. Heyl, P. Hauke, and P. Zoller, Sci. Adv. 5, eaau8342 (2019)]. We characterize these structural instability regimes in p-spin models, transverse-field Ising models with all-to-all p-body interactions, and analytically predict their occurrence based on unitary perturbation theory. We further show that the effective Hamiltonian associated with the Trotter decomposition of the unitary time-evolution operator, when the Trotter step size is chosen to be in the structural instability region, is very different from the target Hamiltonian, which explains the large errors that can occur in the simulation in the regions of instability. These results have implications for the reliability of near-term gate-based quantum simulators, and reveal an important interplay between errors and the physical properties of the system being simulated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

A Real-Time Implementation and Validation of Federated Learning for Grid Services

Grid-edge devices are becoming increasingly important in the energy transition. Preserving privacy was not previously considered an important aspect for power grid operations, but with the increased proliferation of customer-owned assets, it is now an essential consideration. Several mechanisms have been proposed to provide privacy for non-utility owned assets in the power grid. Federated learning (FL) is one method gaining prominence in this area. Although FL has been used for other applications, such as auto-complete in phones, there has not been much investigation into whether these approaches are feasible for grid applications. In this work, we use a research platform with real-time simulators and hardware-in-the-loop capabilities to investigate how FL can be applied to grid-edge devices, and we present the potential grid services that can be derived for these devices. We discuss the computational challenges with deploying complex FL approaches, and we explore several grid services, including participation in retail electricity markets, voltage control, and resilience-driven reconfiguration.

24 POWER TRANSMISSION AND DISTRIBUTION↗