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DOE OSTI2022

Power and Communications Hardware-in-the-Loop CPS Architecture and Platform for DER Monitoring and Control Applications: Preprint

The rapid growth of distributed energy resources (DERs) has prompted increasing interest in the monitoring and control of DERs through hybrid smart grid communications. The deployment of communications and computation has transformed the traditional physical power grid into a smart cyber-physical system (CPS). To fully understand the interdependency between physical grid and cyber netowrks, this study designed a power and communications hardware-in-the-loop (PCommHIL) CPS architecture, which enables the flexible verification of DER monitoring and control with hybrid communications architectures and Internet protocols. Design, development and case study of a PCommHIL testbed for the DER coordination are discussed in detail, and the proposed platform integrates DER devices, Advanced Metering Infrastructures (AMIs), and a suite of hybrid communications networks for distribution automation applications. Case study on DER situational awareness and Volt-Var control validates the efficacy of this proposed PCommHIL platform with hybrid communications designs. Results show that the HAN communication technologies play a critical role in hybrid designs and it is the bottleneck for DER applications. High performance communication technologies are highly recommended to be applied in the HAN for enhanced monitoring and real-time control of DERs.

AMIs↗

DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗

DOE OSTI2022

An MILP-Based Distributed Energy Management for Coordination of Networked Microgrids

An MILP-based distributed energy management for the coordination of networked microgrids is proposed in this paper. Multiple microgrids and the utility grid are coordinated through iteratively adjusted price signals. Based on the price signals received, the microgrid controllers (MCs) and distribution management system (DMS) update their schedules separately. Then, the price signals are updated according to the generation–load mismatch and distributed to MCs and DMS for the next iteration. The iteration continues until the generation–load mismatch is small enough, i.e., the generation and load are balanced under agreed price signals. Through the proposed distributed energy management, various microgrids and the utility grid with different economic, resilient, emission and socio-economic objectives are coordinated with generation–load balance guaranteed and the microgrid customers’ privacy preserved. In particular, a piecewise linearization technique is employed to approximate the augmented Lagrange term in the alternating direction method of multipliers (ADMM) algorithm. Thus, the subproblems are transformed into mixed integer linear programming (MILP) problems and efficiently solved by open-source MILP solvers, which would accelerate the adoption and deployment of microgrids and promote clean energy. The proposed MILP-based distributed energy management is demonstrated through various case studies on a networked microgrids test system with three microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Pro‐ L * ‐ A Probabilistic L * Mapping Tool for Ground Observations

Abstract Both ground and space observations are used extensively in the modeling of space weather processes within the Earth’s magnetosphere. In radiation belt physics modeling, one of the key phase‐space coordinates is L *, which indicates the location of the drift paths of energetic electrons. Global magnetic field models allow a subset of locations on the ground (mainly subauroral) to be mapped along field lines to a location in space and transformed into L *, provided that the initial ground location maps to a closed drift path. This allows observations from ground, or low‐altitude space‐based platforms to be mapped into space in order to inform radiation belt modeling. Many data‐based magnetic field models exist; however, these models can significantly disagree on mapped L * values for a single point on the ground, during both quiet times and storms. We present a state of the art probabilistic L * mapping tool, Pro‐ L *, which produces probability distributions for L * corresponding to a given ground location. Pro‐ L * has been calculated for a high resolution magnetic latitude by magnetic local time grid in the Earth’s Northern Hemisphere. We have developed the probabilistic model using 11 years of L * calculations for seven widely used magnetic field models. Usage of the tool is highlighted for both event studies and statistical models, and we demonstrate a number of potential applications.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Growth rate as a link between microbial diversity and soil biogeochemistry

The growth rate of a microorganism is a simple yet profound way to quantify its impact on the world. The absolute growth rate of a microbial population reflects rates of resource assimilation, biomass production, and element transformation, some of the many ways that organisms affect Earth’s ecosystems and climate. Microbial fitness in the environment depends on the ability to reproduce quickly when conditions are favorable and adopt a survival physiology when conditions worsen, which cells coordinate by adjusting their relative growth rate. At the population level, relative growth rate is a sensitive metric of fitness, linking survival and reproduction to the ecology and evolution of populations. Techniques combining ‘omics and stable isotope probing enable sensitive measurements of growth rates of microbial assemblages and individual taxa in soil. Microbial ecologists can explore how the growth rates of taxa with known traits and evolutionary histories respond to changes in resource availability, environmental conditions, and interactions with other organisms. We anticipate that quantitative and scalable data on the growth rates of soil microorganisms, coupled with measurements of biogeochemical fluxes, will allow scientists to test and refine ecological theory and advance process-based models of carbon flux, nutrient uptake, and ecosystem productivity. Finally, measurements of in situ microbial growth rates provide insights into the ecology of populations and can be used to quantitatively link microbial diversity to soil biogeochemistry.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Gravitational memory and Ward identities in the local detector frame

Gravitational memory, which describes the permanent shift in the strain after the passage of gravitational waves, is directly related to Weinberg’s soft graviton theorems and the Bondi-Metzner-Sachs (BMS) symmetry group of asymptotically flat space-times. In this work, we provide an equivalent description of the phenomenon in local coordinates around gravitational wave detectors, such as transverse-traceless (TT) gauge. We show that gravitational memory is encoded in large residual diffeomorphisms in this gauge, which include time-dependent anisotropic spatial rescalings, and prove their equivalence to BMS transformations when translated to TT gauge. We then derive the associated Ward identities and associated soft theorems, for both scattering amplitudes and equal-time (in-in) correlation functions, and explicitly check their validity for planar gravitational waves. Furthermore, the in-in identities are recognized as the flat-space analog of the well-known inflationary consistency relations.

General relativity↗

DOE OSTI2021

Mechanistic Investigation of Dimethylmercury Formation Mediated by a Sulfide Mineral Surface

Mercury (Hg) pollution is a global environmental problem, but many key transformations among 29 various Hg species are not well understood. Although anaerobic microorganisms are the primary 30 producers of monomethylmercury (MMeHg), the abiotic formation of dimethylmercury (DMeHg) 31 from MMeHg have been suggested to account for a large portion of DMeHg in the ocean. It has 32 been shown that abiotic formation of DMeHg from MMeHg can be facilitated by reduced sulfur 33 groups on mineral surfaces. However, a detailed mechanistic understanding of this reaction is 34 lacking. Here we perform density functional theory (DFT) calculations to explore mechanisms of 35 DMeHg formation on the 110 surface of a CdS(s) (hawleyite) nanoparticle. We show that 36 coordination of MMeHg substituents to adjacent reduced sulfur groups protruding from the surface 37 facilitate DMeHg formation and that the reaction proceeds through direct transmethylation from 38 one MMeHg substituent to another. Solvation effects were found to play an important role in the 39 surface reconstruction of the nanoparticle and in decreasing the energetic barrier for DMeHg 40 formation. We also investigate DMeHg formation from MMeHg mediated by organic dithiols and 41 compare the results to those mediated by the mineral surface. In contrast to the surface reaction, 42 the calculations suggest that dithiol-mediated formation of DMeHg instead proceeds through a 43 mechanism in which Hg–Hg interactions activate a methyl group from one MMeHg substituent 44 for intramolecular transfer to the adjacent MMeHg substituent. These findings refine previously 45 proposed mechanisms of abiotic DMeHg formation and fill gaps in our understanding of global 46 Hg cycling in the environment.

Lian, Peng↗

DOE OSTI2026

From Bricks to Clicks: Mapping the White Space in Building Innovation

It is a critical national imperative to transform the buildings sector, yet innovation is impeded by deployment failures that leave promising technologies stranded. Conventional market reports and techno-economic analysis provide an insufficient understanding of markets and resource allocation for emerging building technologies. They omit crucial commercialization factors such as ecosystem maturity and adoption friction, where the coordinated participation of a network of suppliers, contractors, financiers, regulators, and integrators is required to scale solutions. This study addresses these gaps by introducing an evaluation framework grounded in front-line data from six years of the DOE's IMPEL incubator, comprising experience from 300 building-sector innovators and the adjacent, complex ecosystem. Our methodology synthesizes top-down market analysis with bottom-up, practitioner-level data across five megatrends: (M1) Affordable materials and industrialized construction; (M2) Healthy and efficient mechanical systems; (M3) Intelligent building operations; (M4) Buildings as grid assets; and (M5) High-density power and cooling for data centers and therein identify twelve "white space" technology opportunities. Next, we develop a multi-criteria scoring rubric to rank these opportunities based on parameters, i.e., Affordability, Quality of Life, Reliability, and Security, yielding composite ‘Demand’ and ‘Maturity’ indices. Our results indicate that the most significant white spaces may not be incremental products but a new class of ‘Ecosystem Enablers’, such as logistics platforms, orchestration layers, and automated compliance software that solve structural deployment gaps. This paper summarizes this transparent, evidence-based, practitioner-informed evaluation framework for policymakers and investors to re-evaluate policy and resource allocation and unlock scalable market transformation.

Singh, Reshma↗

DOE OSTI2024

Robust Machine Learning Inference from X-ray Absorption Near Edge Spectra through Featurization

X-ray absorption spectroscopy (XAS) is a commonly employed technique for characterizing functional materials. In particular, X-ray absorption near edge spectra (XANES) encode local coordination and electronic information, and machine learning approaches to extract this information are of significant interest. To date, most ML approaches for XANES have primarily focused on using the raw spectral intensities as input, overlooking the potential benefits of incorporating spectral transformations and dimensionality reduction techniques into ML predictions. Here, in this work, we focused on systematically comparing the impact of different featurization methods on the performance of ML models for XAS analysis. We evaluated the classification and regression capabilities of these models on computed data sets and validated their performance on previously unseen experimental data sets. Our analysis revealed an intriguing discovery: the cumulative distribution function feature achieves both high prediction accuracy and exceptional transferability. This remarkably robust performance can be attributed to its tolerance to horizontal shifts in the spectra, which is crucial when validating models using experimental data. While this work exclusively focuses on XANES analysis, we anticipate that the methodology presented here will hold promise as a versatile asset to the broader spectroscopy community.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Multigene engineering in plants: Technologies, applications, and future prospects

The emerging bioeconomy presents a promising solution to both economic and environmental challenges. Within the bioeconomy, plants serve as a renewable, sustainable, and cost-effective source of foods, fuels, chemicals, and materials. However, traditional breeding and single-gene engineering approaches fall short in addressing complex traits (e.g., drought tolerance, disease resistance, yield, nutrient use efficiency) which are controlled by multiple genes. The complexity of plant biology often necessitates the use of multigene engineering (MGE), which involves simultaneous ectopic expression, up/down-regulation, or editing of multiple genes, to enhance plant traits relevant to the bioeconomy. These genes may be associated with distinct traits or function as components of specific metabolic and regulatory pathways. This review summarizes current technologies for MGE within the synthetic biology-driven Design-Build-Test-Learn (DBTL) framework, detailing its four key stages: Design – gene construct development; Build – DNA assembly and plant transformation; Test – the molecular, biochemical, and physiological characterization of engineered plants; and Learn – computational modeling to refine, multiplex and iterate the process. Despite good progress in the applications of MGE in biofortification, metabolic engineering, and stress resilience, challenges remain in construct stability, coordinated gene expression, and regulatory predictability. We identified optimization paths and future directions to accelerate MGE deployment in sustainable agriculture, with possible societal benefits including reduced production costs, increased yield, and improved food and nutritional security.

AI-aided plant engineering↗

DOE OSTI2023

Photoexcitation of Fe 3 O Nodes in MOF Drives Water Oxidation at pH=1 When Ru Catalyst Is Present

Abstract Artificial photosynthesis strives to convert the energy of sunlight into sustainable, eco‐friendly solar fuels. However, systems with light‐driven water oxidation reaction (WOR) at pH=1 are rare. Broadly used [Ru(bpy) 3 ] 2+ (bpy=2,2’‐bipyridine) photosensitizer has a fixed +1.23 V potential which is insufficient to drive most water oxidation catalysts (WOCs) in acid, while Fe 2 O 3 , featuring the highly oxidizing holes, is not stable at low pH. Here, the key examples of Fe‐based metal–organic framework (MOF) water oxidation photoelectrocatalysts active at pH=1 are presented. Fe‐MIL‐126 and Fe MOF‐dcbpy structures were formed with 4,4’‐biphenyl dicarboxylate (bpdc), 2,2’‐bipyridine‐5,5’‐dicarboxylate (dcbpy) linkers and their mixtures. Presence of dcbpy linkers allows integration of metal‐based catalysts via coordination to 2,2’‐bipyridine fragments. Fe‐based MOFs were doped with Ru‐based precursors to achieve highly active MOFs bearing [Ru(bpy)(dcbpy)(H 2 O) 2 ] 2+ WOC. Materials were analyzed with X‐ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infra‐red (FTIR) spectroscopy, resonance Raman, X‐ray absorption spectroscopy, fs optical pump‐probe, electron paramagnetic resonance (EPR), diffuse reflectance and electric conductivity measurements and were modeled by band structure calculations. It is shown that under reaction conditions, Fe III and Ru III oxidation states are present, indicating rate‐limiting electron transfer in MOF. Fe 3 O nodes emerge as photosensitizers able to drive prolonged O 2 evolution in acid. Further developments are possible via MOF's linker modification for enhanced light absorption, electrical conductivity, reduced MOF solubility in acid, Ru‐WOC modification for faster WOC catalysis, or Ru‐WOC substitution to 3d metal‐based systems. The findings give further insight for development of light‐driven water splitting systems based on Earth‐abundant metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Transformation of CeO 2 Nanoparticles into Atomically Dispersed Ce Cations Leads to Enhanced Reactivity for Automotive Emissions Control

Nanosized cerium oxide (CeO 2 ) has been extensively used as the oxygen storage component in automotive emission control systems. However, the possible influence of atomically dispersed Ce in these catalysts has not been recognized. Here, in this study, we demonstrate the controllable transformation of ceria nanoparticles into isolated cerium cations on γ-Al 2 O 3 via reductive atom trapping in 10% H 2 at 800 °C, achieving over half-monolayer coverage. Dispersed Ce 1 ions anchored by surface penta- and octa-coordinated Al sites exhibit outstanding thermal stability in air up to 500 °C, enabling further loading of active metals with well-defined catalyst structures. With this strategy, supported single-atom Rh 1 surrounded by dispersed Ce 1 is confirmed to exhibit much superior performance to Rh 1 on bare Al 2 O 3 or nanocrystalline CeO 2 in catalyzing NO reduction by CO, exhibiting a striking one-order-of-magnitude increase in activity. Dispersed Ce 1 exhibits greatly enhanced oxygen transfer capability compared to ceria nanoparticles and introduces a modified reaction mechanism that involves an adjacent Rh 1 –Ce 1 motif, resulting in a greatly decreased activation barrier (from 192 to 96 kJ/mol). The reactivity enhancements are also seen with Ce 1 -promoted Pt nanoparticles for oxidation of CO and hydrocarbons.

Jiang, Dong [Washington State Univ., Pullman, WA (↗

DOE OSTI2026

Jahn–Teller distortion controls electron transfer in photoexcited Cu( I ) donor–acceptor systems

The Jahn–Teller distortion (JTD) is a defining structural response to electronic excitation in Cu( I )-based transition metal complexes, yet its role in photoinduced electron transfer (PET) remains largely unexplored. Here, we demonstrate that the JTD governs charge separation (CS) through a vibronically controlled conical intersection in heteroleptic Cu( I ) bisphenanthroline–naphthalene diimide (CuHETPHEN-NDI) donor–acceptor dyads. Using 20-fs broadband transient absorption spectroscopy combined with coherent vibrational wavepacket (CVWP) analysis and quantum chemical calculations, we directly track nuclear motions that steer the system from the metal-to-ligand charge-transfer ( 1 MLCT) state to the CS state. Steric bulkiness of the pendant groups at the 2,9-positions of the phenanthroline ligand systematically slows both JTD and CS. Short-time Fourier transformation and Fourier filtering analyses identify two key vibrational signatures: a low-frequency breathing mode (∼100 cm −1 ) via a bond distance change between Cu and ligated Ns (Cu–N) that modulates the NDI anion absorption and acts as a vibronic coupling coordinate, and a higher-frequency mode (∼313 cm −1 ) that evolves along the PET trajectory. Normal mode analysis and potential energy surface calculations show that the JTD brings the 1 MLCT and CS states into degeneracy, while the Cu–N breathing motion dynamically modulates donor–acceptor electronic coupling to enable ultrafast nonadiabatic electron transfer. Steric hindrance exerted by the groups at the 2,9 positions of the phenanthroline ligands suppresses this vibronic coupling, leading to faster CVWP decoherence for the 313 cm −1 mode and slower CS. These findings unravel JTD-controlled vibronic coupling at conical intersection as a governing factor for CS and provide insight into designing Cu-based photosensitizers by harnessing structural dynamics to control PET.

Kim, Pyosang [Argonne National Laboratory (ANL), A↗

DOE OSTI2022

Three-dimensional Skyrme Hartree-Fock-Bogoliubov solver in coordinate-space representation

The coordinate-space representation of the Hartree-Fock-Bogoliubov theory is the method of choice to study weakly bound nuclei whose properties are affected by the quasiparticle continuum space. To describe such systems, we developed a three-dimensional Skyrme-Hartree-Fock-Bogoliubov solver HFBFFT based on the existing, highly optimized and parallelized Skyrme-Hartree-Fock code Sky3D. The code does not impose any self-consistent spatial symmetries such as mirror inversions or parity. The underlying equations are solved in HFBFFT directly in the canonical basis using the fast Fourier transform. To remedy the problems with pairing collapse, we implemented the soft energy cutoff and pairing annealing. The convergence of HFB solutions was improved by a sub-iteration method. The Hermiticity violation of differential operators brought by Fourier-transform-based differentiation has also been solved. Furthermore, the accuracy and performance of HFBFFT were tested by benchmarking it against other HFB codes, both spherical and deformed, for a set of nuclei, both well-bound and weakly-bound.

3D coordinate-space representation↗

DOE OSTI2022

Effect of Redox-Inactive Metal Ion–Nickel(III) Interactions on the Redox Properties and Proton-Coupled Electron Transfer Reactivity

We report Mononuclear nickel(II) and nickel(III) complexes of a bisamidate-bisalkoxide ligand, (NMe 4 ) 2 [Ni- II (HMPAB)] (1) and (NMe 4 )[Ni III (HMPAB)] (2), respectively, have been synthesized and characterized by various spectroscopic techniques including X-ray crystallography. The reaction of redox-inactive metal ions (M n+ = Ca 2+ , Mg 2+ , Zn 2+ , Y 3+ , and Sc 3+ ) with 2 resulted in 2-M n+ adducts, which was assessed by an array of spectroscopic techniques including X-ray absorption spectroscopy (XAS), electron paramagnetic resonance (EPR), and reactivity studies. The X-ray structure of Ca 2+ coordinated to Ni(III) complexes, 2Ca 2+ T, was determined and exhibited an average Ni-Ca distance of 3.1253 angstrom, close to the metal ions' covalent radius. XAS analysis of 2-Ca 2+ and 2-Y 3+ in solution further revealed an additional coordination to Ca and Y in the 2-M n+ adducts with shortened Ni-M distances of 2.15 and 2.11 Å, respectively, implying direct bonding interactions between Ni and Lewis acids (LAs). Such a short interatomic distance between Ni(III) and M is unprecedented and was not observed before. EPR analysis of 2 and 2-M n+ species, moreover, displayed rhombic signals with g av > 2.12 for all complexes, supporting the +III oxidation state of Ni. The Ni III /Ni II redox potential of 2 and 2-M n+ species was determined, and a plot of E 1/ 2 of 2-M n+ versus pK a of [M(H 2 O) n ] m+ exhibited a linear relationship, implying that the Ni III /Ni II potential of 2 can be tuned with different redox-inactive metal ions. Reactivity studies of 2 and 2-M n+ with different 4-X-2,6-ditert-butylphenol (4-XDTBP) and other phenol derivatives were performed, and based on kinetic studies, we propose the involvement of a proton-coupled electron transfer (PCET) pathway. Analysis of the reaction products after the reaction of 2 with 4-OMe-DTBP showed the formation of a Ni(II) complex (1a) where one of the alkoxide arms of the ligand is protonated. A pK a value of 24.2 was estimated for 1a. The reaction of 2-M n+ species was examined with 4-OMe-DTBP, and it was observed that the k 2 values of 2-M n+ species increase by increasing the Lewis acidity of redox-inactive metal ions. However, the obtained k 2 values for 2-M n+ species are much lower compared to the k 2 value for 2. Such a variation of PCET reactivity between 2 and 2-M n+ species may be attributed to the interactions between Ni(III) and LAs. Our findings show the significance of the secondary coordination sphere effect on the PCET reactivity of Ni(III) complexes and furnish important insights into the reaction mechanism involving high-valent nickel species, which are frequently invoked as key intermediates in Ni-mediated enzymatic reactions, solar-fuel catalysis, and biomimetic/synthetic transformation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Black Start of Unbalanced Microgrids Harmonizing Single- and Three-Phase Grid-Forming Inverters

As power systems are transforming with increasing penetrations of inverter-based resources (IBRs), system restoration using IBRs has drawn attention. Using distributed grid-forming (GFM) assets located near critical loads, either three-phase or single-phase, to establish microgrid voltages in the absence of a bulk grid, a distribution system could obtain high system survivability. For swift and secure recovery of a critical load in a single-phase lateral, local single-phase GFM inverters can form a microgrid, and then it can be combined with a neighbouring grid with the inverters remaining in GFM mode for voltage and frequency regulation until the bulk grid comes online. It leads to dynamic interoperation of single-phase GFM inverters with three-phase ones in the black start process. This paper studies the novel approach with electromagnetic transient (EMT) simulations. To evaluate the potential and the technical challenges of the heterogeneous IBR-driven black start, three-phase and single-phase GFM inverter models are developed, including negative-sequence control for voltage balance and a phase-by-phase current limiter (three-phase) and current magnitude limiter (single-phase). To examine dynamic aspects of the black-start process, the EMT simulation also models transformer and motor dynamics emulating their inrush and startup behavior as well as network dynamics. Involvement of grid-following assets to facilitate the black-start process is also modeled. By allowing multiple GFM inverters to collectively black start without leader-follower coordination, regardless of phases, a system can achieve extreme resilience. An inverter-driven black start of a heavily unbalanced 2-MVA distribution feeder using 1 three-phase and 3 single-phase GFM inverters is demonstrated. The simulation shows the heterogeneous system can maintain stability with the single-phase GFM dynamics coupled with the three-phase one.

grid-forming inverter↗

DOE OSTI2023

Black Start of Unbalanced Microgrids Harmonizing Single- and Three-Phase Grid-Forming Inverters: Preprint

grid-forming inverter↗

DOE OSTI2026

Polar primary aerosols across the ocean-sea ice-snow-atmosphere interface: From sources to impacts

Primary aerosols play a critical role in polar climate systems, influencing cloud formation, precipitation, radiative balance, and surface energy budgets. This paper provides a comprehensive synthesis of primary aerosol sources, transformation and removal processes, and broader atmospheric impacts in polar regions, emphasizing their links to ocean and sea ice biogeochemistry. These aerosols (including sea salt, primary organic aerosol, and primary biological aerosol particles) originate from marine and cryospheric environments and are emitted through physical processes, such as wave breaking, bubble bursting, and blowing snow. Emission sources include seawater, sea ice, snow, and freshwater from river discharge and glacial runoff. Once airborne, these particles can serve as a chemical reservoir, influencing atmospheric composition and reactivity, and as seeds for cloud droplet and ice crystal formation, influencing cloud microphysics and polar climate. Despite their importance, many of the processes governing primary aerosol emissions and transformations remain poorly constrained. The most pressing knowledge gaps pertain to emission processes, limited spatiotemporal observational coverage, instrumentation constraints, parameterization development, and the integration of interdisciplinary expertise. To improve our understanding of primary aerosol drivers and their response to climate, future research efforts should prioritize strategically coordinated and cross-disciplinary process studies, advancements in measurement technologies and coverage, and close collaboration between modelers and observational scientists to inform and refine model parameterizations. As polar regions continue to undergo profound changes marked by increased precipitation, reduced sea and land ice, freshening oceans, and shifting ecosystem dynamics, characterizing present-day primary aerosol populations is vital. Improved understanding will be essential for anticipating future changes in aerosol-radiation and aerosol-cloud interactions and their implications for polar and global climate systems.

Aerosol-cloud↗