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All sources NASA NTRS DOE OSTI

DOE OSTI2024

Performance enhancement of aqueous ionic liquids with lower critical solution temperature (LCST) behavior through ternary mixtures

Thermally responsive ionic liquids (ILs) exhibit liquid–liquid phase separation when mixed with water and heated above a lower critical solution temperature (LCST), resulting in a water-rich (WR) and an IL-rich (ILR) phase. These binary IL–water mixtures can be employed in a variety of thermodynamic processes such as forward osmosis (FO) desalination, for which two solution properties are desirable: low phase separation temperature and high osmotic strength (osmolality). However, these two properties are interlinked, with ILs that exhibit higher osmotic strengths typically requiring higher phase separation temperatures. This behavior tends to arise from the hydrophilicity of the IL cations, which enhances osmotic strength while also elevating the phase separation temperature. In this work, we highlight a pathway to overcome this tradeoff by developing ternary IL mixtures (two ILs with varying cation hydrophilicity mixed with water), which lowers the phase separation temperature while maintaining and even enhancing the osmotic strength of the solution. We characterize the mixing behavior (osmolality, phase separation temperature, WR phase purity, and WR to ILR phase mass ratio) of four ILs as a function of their concentration in solution. We find that an enhancement of up to 81.6% in the osmolality with a concomitant reduction of up to 15.4% in the phase separation temperature can be achieved using this approach. The ternary mixture is also shown to improve the phase separation kinetics by nearly 95% compared to the binary mixture. Overall, this work highlights a new pathway to improve the performance of LCST ILs for water and energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Molecular catalyst and co-catalyst systems based on transition metal complexes for the electrochemical oxidation of alcohols

Molecular catalysts allow deeper study of underlying mechanisms relative to heterogeneous systems by offering a discrete active site to monitor. Mechanistic study with knowledge of key intermediates subsequently enables the development of design principles through an understanding of how improved reactivity or selectivity can be achieved through modification of the catalyst structure. The co-catalytic inclusion of redox mediators (RM), which are small molecules that can aid in the transfer of protons and electrons, has been shown to improve product conversion and selectivity in many molecular systems, through intercepting key intermediates to direct reaction pathways. The primary focus for the majority of molecular electrocatalysts has been on optimizing design for reductive reactions, such as the hydrogen evolution reaction (HER), the oxygen reduction reaction (ORR), and the carbon dioxide reduction reaction (CO 2 RR). By comparison, there has been much less focus on key oxidative reactions by molecular species, apart from the oxygen evolution reaction (OER). The focus of this review is to highlight molecular catalyst systems optimized for the electrochemical oxidation of alcohols. The electrochemical alcohol oxidation reaction (AOR) can serve a role in synthesizing value-added chemicals and can serve as the counterpart to the CO 2 RR by releasing electricity from energy-rich molecules. State-of-the-art molecular systems for the AOR are divided between single-site catalysts and co-catalytic systems with redox mediators. The AOR is contextualized as an energy relevant reaction, an overview of the area is provided, foundational improvements in catalyst systems are highlighted, and future development principles for incorporating redox mediators are suggested.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Mechanistic understanding of carbon mineralization in fracture systems using microfluidics

Carbon mineralization in mafic and ultramafic rocks presents an opportunity for permanent carbon storage in the Earth's subsurface. However, due to their lower permeability, pre-existing fracture networks are key for mineralization to occur. Therefore, to fully develop this technology, a mechanistic understanding of the mineralization behavior in fractures with the consideration of hydrodynamic components is required. We use high-pressure microfluidics to investigate key mechanisms influencing dissolution–precipitation in a fracture network. The experiments were conducted in micromodels made of natural rocks with a comb-shaped flow channel to mimic a fracture network. This enabled studying the effect of injection rate on coupled dissolution–precipitation in advection and diffusion-dominated flow paths. We used gypsum carbonation as an analog reaction to allow for realistic experimental time frames due to its rapid reaction kinetics. The experimental work is coupled with high-fidelity numerical simulations to enhance our understanding of the parameters affecting the mineralization reaction. Our results demonstrate the importance of flow rate on the rate and nature of the gypsum carbonation reaction revealing that higher flow rates enable deeper penetration of the mineral precipitation front into the dead-end channels. This is an important finding since for sustained mineralization in a fracture network, precipitation in dead-ends while still allowing for flowing fractures is critical. Detailed characterization of the precipitates showed that lower flow rates led to porous and loose precipitates in the form of aragonite while higher flow rates mimicked supersaturation behavior leading to the formation of calcite. The reactive transport simulations further demonstrated the significance of flow velocity in advection-dominated channels to influence the efficiency of carbon mineralization in diffusion-dominated channels, potentially clogging of dead-end channels. These findings highlight the need for coupling chemical, mechanical, and hydrodynamic processes to evaluate the nature and extent of carbon mineralization in fractured media critical for permanent storage in mafic and ultramafic formations. This research further highlights the need for more investigation in potential subsurface fracture generation techniques to aid carbon mineralization.

25 ENERGY STORAGE↗

DOE OSTI2025

Advances in vat photopolymerization: early-career researchers shine light on a path forward

Vat photopolymerization (VP) has emerged as a promising additive manufacturing technique to allow rapid light-based fabrication of 3D objects from a liquid resin. Research in the field of vat photopolymerization spans across multiple disciplines from engineering and materials science to applied chemistry and physics. This perspective brings together early-career researchers from various disciplines in academia and national laboratories around the world to summarize the most recent advancements with special emphasis on the research highlighted as part of the Gordon Research Conference (GRC) 2024 meeting on Additive Manufacturing of Soft Materials. We provide an outlook on next-generation polymer processing methods from synthesis of novel materials to multimodality manufacturing and performance engineering. Further, this article combines the ideas of many of these junior researchers to present a vision for the future of the field by highlighting the challenges and opportunities that lie ahead.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Mass spectral molecular mapping shows benefits of thermal evaporation in prelithiated silicon-based electrodes

Silicon based composites have become increasingly popular as potential anodes for lithium-ion batteries due to their large storage capacity and potential ability to generate batteries with energy densities greater than 350 Wh kg −1 . These anodes often see reduced initial columbic efficiency (ICE) due to disruptive volume expansionup to 300% and continuous solid electrolyte interphase (SEI) layer formation. Prelithiation, where an excess reservoir of Li is added to the electrode to compensate for irreversible SEI formation losses during their sample preparation, has proven to solve the issue of immediate capacity loss. Thermal evaporation is a prelithiation technique with limited studies on its effectiveness. In this study, time-of-flight secondary ion mass spectrometry (ToF-SIMS) is used to highlight the benefits of prelithiation via thermal evaporation. ToF-SIMS provides chemical mapping and spatial information in 2D and 3D visualizing the deposition of lithium, identifying Li x Si y alloy and Li x Si y O z silicate formation, and the distribution of lithium passivation into the electrodes. Passivation under different atmospheric conditions, such as inert Argon (Ar) and Ar/ carbon dioxide (CO 2 ), highlights the impact of the environment on the passivation effectiveness and formation of Li x Si y alloy and Li x Si y O z silicate. The ToF-SIMS molecular imaging and depth profiling results indicate that prelithiation via thermal evaporation effectively distributes lithium throughout the depth profile thickness of several hundred nanometers. It induces a greater degree of Li x Si y O z silicate formation over Li x Si y alloy. Our ToF-SIMS characterization results show the effectiveness of thermal evaporation in producing a more stable electrode and an electrode with an effective lithium reserve that can preserve its capacity.

Parker, Gabriel D. [Oak Ridge National Laboratory ↗

DOE OSTI2025

From the laboratory to space: unveiling isomeric diversity of C 5 H 2 in the reaction of tricarbon (C 3 , X 1 Σ g + ) with the vinyl radical (C 2 H 3 , X 2 A′)

By connecting laboratory dynamics with cosmic observables, this work highlights the critical role of reactions between highly reactive species in shaping the molecular inventory of the interstellar medium and opens new windows into the spectroscopically elusive corners of astrochemical complexity. The gas phase formation of distinct C 5 H 2 isomers is explored through the bimolecular reaction of tricarbon (C 3 , X 1 Σ + g ) with the vinyl radical (C 2 H 3 , X 2 A′) at a collision energy of 44 ± 1 kJ mol −1 employing the crossed molecular beam technique augmented by electronic structure and Rice–Ramsperger–Kassel–Marcus (RRKM) calculations. This barrierless and exoergic reaction follows indirect dynamics and is initiated by the addition of tricarbon to the radical center of the vinyl radical forming a Cs symmetric doublet collisional complex (CCCCHCH 2 ). Subsequent low-barrier isomerization steps culminate in the resonantly stabilized 2,4-pentadiynyl-1 radical (CHCCCCH 2 ), which decomposes via atomic hydrogen loss. Statistical calculations identify linear, triplet pentadiynylidene (p2, X 3 Σ − g ) as the dominant product, while singlet carbenes ethynylcyclopropenylidene (p1, X 1 A′), pentatetraenylidene (p3, X 1 A 1 ), and ethynylpropadienylidene (p4, X 1 A′) are formed with lower branching ratios. The least stable isomer, 2-cyclopropen-1-ylidenethenylidene (‘eiffelene’; p5, X 1 A 1 ), remains thermodynamically feasible, but exhibits negligible branching ratios. Two isomers detected in TMC-1 to date (p1 and p3) possess significant dipole moments making them amenable to radio telescopic observations, whereas linear pentadiynylidene (p2; D ∞h ) is only traceable via infrared spectroscopy or through its cyanopentadiynylidene derivative (HCCCCCCN). This study highlights the isomer diversity accessed in the low temperature hydrocarbon chemistry of barrierless and exoergic bimolecular reactions involving two unstable, reactants in cold molecular clouds.

Medvedkov, Iakov A. [University of Hawai'i at Mano↗

DOE OSTI2026

Dynamic control of quantum phases in two-dimensional materials via Floquet engineering

The dynamical engineering of quantum states through periodic optical driving, known as Floquet engineering, has emerged as a powerful frontier in condensed matter physics, offering a pathway to realize material properties inaccessible in static equilibrium. This review provides a comprehensive overview of recent theoretical and experimental advances in the optical manipulation of two-dimensional (2D) quantum materials. We begin by systematically reviewing the evolution of the field from its pioneering applications in graphene and twisted moiré superlattices, highlighting the experimental realization of the light-induced anomalous Hall effect (AHE) to the complex spin-valley physics in transition metal dichalcogenides (TMDs). Furthermore, we briefly examine recent advances in 2D magnetic materials, demonstrating how optical driving can actively compete with intrinsic magnetism to dynamically switch magnetic orders and topological invariants. Moreover, we discuss the emerging frontiers of multi-frequency driving, quantum optimal control theory (QOCT), and ultrafast lightwave electronics. We highlight how tailored waveforms, such as bicircular light fields, and sub-cycle attosecond control can selectively break spatial symmetries to generate novel nonlinear photocurrents, mitigate dissipation, and extend the boundaries of quantum control well beyond the perturbative steady-state regime. Finally, we summarize the key experimental challenges for Floquet engineering, including effects such as heating and scattering, which limit coherent quantum control.

Wang, Wenpeng [Northeastern University, Shenyang, ↗

DOE OSTI2020

Biomolecular complex viewed by dynamic nuclear polarization solid-state NMR spectroscopy

Solid-state nuclear magnetic resonance (ssNMR) is an indispensable tool for elucidating the structure and dynamics of insoluble and non-crystalline biomolecules. The recent advances in the sensitivity-enhancing technique magic-angle spinning dynamic nuclear polarization (MAS-DNP) have substantially expanded the territory of ssNMR investigations and enabled the detection of polymer interfaces in a cellular environment. This article highlights the emerging MAS-DNP approaches and their applications to the analysis of biomolecular composites and intact cells to determine the folding pathway and ligand binding of proteins, the structural polymorphism of low-populated biopolymers, as well as the physical interactions between carbohydrates, proteins, and lignin. Furthermore, these structural features provide an atomic-level understanding of many cellular processes, promoting the development of better biomaterials and inhibitors. It is anticipated that the capabilities of MAS-DNP in biomolecular and biomaterial research will be further enlarged by the rapid development of instrumentation and methodology.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Automated ICRF heating surrogate modeling via machine learning

This work introduces automated machine learning workflows that address critical bottlenecks in surrogate model development for Ion Cyclotron Range of Frequencies (ICRF) heating applications. The automated framework includes data analysis tools that transform raw datasets into actionable insights in seconds, replacing weeks of manual exploratory effort and ensuring consistent, reproducible dataset characterization. By integrating advanced hyperparameter optimization (HPO) methods including Bayesian optimization via BoTorch and Tree-structured Parzen Estimators (TPE), the framework significantly reduces model development time from weeks to hours, decreasing computational cost and required expertise, while enabling high-accuracy surrogate models. Compared to traditional hyperparameter scanning (HPS) techniques such as methodical, randomized, and grid searches, HPO methods achieve superior convergence and predictive performance, even when compared to already well-tuned reference models. On NSTX High Harmonic Fast Wave (HHFW) heating datasets, both Random Forest Regressor (RFR) and neural network surrogates demonstrate improved accuracy, achieving R 2 values beyond 0.97 and 0.98, respectively. The results show that while HPO gains are modest for robust architectures like RFR, they become essential for more sensitive models such as neural networks, highlighting the trade-offs across optimization strategies. Through automated workflows that eliminate manual hyperparameter tuning and require minimal ML expertise, this work enables widespread adoption of high-fidelity surrogate models across the fusion community for real-time plasma control, uncertainty quantification, rapid experimental scenario development, and integrated system optimization.

Sanchez-Villar, Alvaro [Princeton Plasma Physics L↗

DOE OSTI2020

A practical guide for crystal growth of van der Waals layered materials

This Tutorial provides an overview of the techniques that are most commonly utilized to grow bulk van der Waals crystals. The materials discussed were selected to highlight various challenges that are often encountered during crystal growth. Additionally, in relatively equal parts, the text covers melt-based techniques, vapor transport growths, and the characterization of crystal quality with an emphasis on structural and chemical homogeneities. Furthermore, pertinent details are given regarding the growth and characterization of many specific compounds, with examples mostly drawn from our own research, and an effort is made to highlight cases where the growths offer a particular lesson or the conditions have a significant impact on the crystal’s physical properties. A primary goal is to motivate more researchers to grow crystals by providing general descriptions and considerations for different growth techniques and equipment while sharing some of our own lessons learned and best practices for the growth and characterization of layered van der Waals crystals. The Tutorial is not written solely for aspiring crystal growers, however, because any researcher who collaborates with a crystal grower can benefit from having a greater understanding and appreciation of the processes of crystal growth and materials development.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Advances in imaging of chemically reacting flows

Many important chemically reacting systems are inherently multi-dimensional with spatial and temporal variations in the thermochemical state, which can be strongly coupled to interactions with transport processes. Fundamental insights into these systems require multi-dimensional measurements of the thermochemical state as well as fluid dynamics quantities. Laser-based imaging diagnostics provide spatially and temporally resolved measurements that help address this need. The state of the art in imaging diagnostics is continually progressing with the goal of attaining simultaneous multi-parameter measurements that capture transient processes, particularly those that lead to stochastic events, such as localized extinction in turbulent combustion. Development efforts in imaging diagnostics benefit from advances in laser and detector technology. This article provides a perspective on the progression of increasing dimensionality of laser-based imaging diagnostics and highlights the evolution from single-point measurements to 1D and 2D multi-parameter imaging and 3D high-speed imaging. This evolution is demonstrated using highlights of laser-based imaging techniques in combustion science research as an exemplar of a complex multi-dimensional chemically reacting system with chemistry–transport coupling. Imaging diagnostics impact basic research in other chemically reacting systems as well, such as measurements of near-surface gases in heterogeneous catalysis. The expanding dimensionality of imaging diagnostics leads to larger and more complex datasets that require increasingly demanding approaches to data analysis and provide opportunities for increased collaboration between experimental and computational researchers in tackling these challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Transitions between electron emission and gas breakdown mechanisms across length and pressure scales

This Perspective outlines theoretical, simulation, and experimental studies linking electron emission and gas breakdown. Many studies have investigated field emission-driven microscale gas breakdown, including recent reviews [Garner et al., IEEE Trans. Plasma Sci. 48, 808–824 (2020); Fu et al., Plasma Res. Express 2, 013001 (2020)]. This Perspective focuses on generalizing field emission-driven microscale gas breakdown to consider the contribution of other forms of electron emission, specifically thermionic and space-charge limited. Recent theoretical studies have unified thermionic, field, and space-charge limited emission with and without collisions to derive “nexuses” where the individual solutions match, indicating transitions in the mechanisms. Reducing device size to nanoscale at atmospheric pressure leads to a transition from field emission to space-charge limited emission for nitrogen at ~250 nm. This Perspective summarizes the derivation of these nexuses and future extensions. We next describe simulation and theoretical studies for field emission-driven microscale gas breakdown and highlight how the nexus theory may be integrated to account for temperature, space-charge, and pulse parameters. Finally, we summarize the development of optical techniques to assess microscale gas breakdown and recent nanoscale experiments at atmospheric pressure that suggest that space-charge may begin to contribute to field emission prior to gas breakdown. We highlight the combination of theory, simulation, and experiment to link electron emission and gas breakdown mechanisms across length, pressure, and temperature scales for applications that include vacuum electronics, pulsed power, and medicine.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Recent Advances in Small Angle X-ray Scattering for Superlattice Study

Small-angle x-ray scattering is used for the structure determination of superlattice for its superior resolution, nondestructive nature, and high penetration power of x rays. With the advent of high brilliance x-ray sources and innovative computing algorithms, there have been notable advances in small angle x-ray scattering analysis of superlattices. High brilliance x-ray beams have made data analyses less model-dependent. Additionally, novel data acquisition systems are faster and more competitive than ever before, enabling a more accurate mapping of the superlattices' reciprocal space. Fast and high-throughput computing systems and algorithms also make possible advanced analysis methods, including iterative phasing algorithms, non-parameterized fitting of scattering data with molecular dynamics simulations, and the use of machine learning algorithms. As a result, solving nanoscale structures with high resolutions has become an attainable task. In this review, we highlight new developments in the field and introduce their applications for the analysis of nanoscale ordered structures, including nanoparticle supercrystals, nanoscale lithography patterns, and supramolecular self-assemblies. Particularly, we highlight the reciprocal space mapping techniques and the use of iterative phase retrieval algorithms. We also cover coherent-beam-based small angle x-ray scattering techniques such as ptychography and ptycho-tomography in view of the traditional small angle x-ray scattering perspective.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Development of the materials analysis and particle probe for Proto-MPEX

The Prototype Material Plasma Exposure eXperiment (Proto-MPEX) is a linear plasma device being used in plasma source research and development (R&D) for the proposed MPEX. Once the R&D is completed, this device can also be used to perform plasma–material interaction studies. To perform these studies, a new materials analysis and particle probe (MAPP) has been constructed. The MAPP’s components are a sample holder and manipulator and a custom vacuum chamber with ports to facilitate surface chemistry diagnostics. The MAPP’s overall design enables rapid sample turnaround and in vacuo surface characterization. The surface analysis vacuum chamber has ports for x-ray photoelectron spectroscopy, thermal desorption spectroscopy, back-scatter ion scattering spectroscopy, forward-scatter ion scattering spectroscopy, and direct recoil spectroscopy. The sample manipulator and holder is a Lesker/UHV Multi-Centre Analytical Stage, which is used to place the samples in the exposure region of the Proto-MPEX or the analysis position in the MAPP vacuum chamber. The sample holder has a heating capability of up to 1200 °C for heated exposure and for desorption studies. In this work, we present the MAPP’s design and the first tungsten sample exposure with ex situ analysis that shows a surface deposition layer on the exposed target, highlighting the need for additional in situ measurements on the Proto-MPEX.

Beers, C. J. (ORCID:0000000150985459)↗

DOE OSTI2021

Methods for neutron diffraction studies on hydride superconductors and other metal hydrides

High-pressure neutron diffraction is an extremely useful technique in the quest for making and understanding novel hydride superconductors. Neutron diffraction can be used to directly determine elemental stoichiometries and atomic positions of many light elements such as hydrogen or deuterium, even in the presence of heavy elements such as rare-earth metals. In this work, we report on the current status and ongoing developments on high-pressure neutron diffraction for hydride superconductors and other metal hydrides with a special focus on current advancements at the Spallation Neutrons and Pressure (SNAP) beamline of the Spallation Neutron Source at Oak Ridge National Laboratory. For broader context, an overview of high-pressure neutron diffractometers and pressure cells is included together with insight into critical sample considerations. There, attention is given to the requirements for powdered hydride samples and the need for deuterium rather than hydrogen. Additionally, the advantages of angular access and data representation as possible at SNAP are described. We demonstrate the current capability for high-pressure neutron diffraction on two different samples created via hydrogen gas loading, specifically pure deuterium and nickel-deuteride. The deuterium example highlights the usefulness of adding sample materials that facilitate the formation of a good powder while the nickel-deuteride example demonstrates that atomic deuterium positions and stoichiometry can be directly determined. Both examples highlight the importance of large scattering apertures. These enable investigation of the data resolved by scattering angle that is needed to identify parasitic peaks and background features. Finally, future directions beyond current high-pressure neutron powder diffraction are also discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Techno-Economic Analysis of CSP Incorporating sCO2 Brayton Power Cycles: Trade-Off Between Cost and Performance

Concentrating solar power (CSP) plants, thanks to the implementation of cost-competitive thermal energy storage, represent a dispatchable zero-emission alternative to traditional fossil fuel power plants. Next generation solar towers are expected to adopt high temperature receivers (>700 degrees C) coupled to sCO2-based power blocks, which optimal design is generally pushed towards the maximum cycle efficiency, often neglecting the economic impact with the justification that the main share of the capital cost is represented by the heliostat field. As result, the scientific literature lacks in comprehensive studies on techno-economic evaluation of CSP+sCO2 power plants addressing the important correlation that exists between system cost and performances. This work provides a preliminary techno-economic analysis of a solar power tower comparing four different cycle configurations for the sCO2 power block. Results have been reported on a Pareto front, highlighting the tradeoff between the plant investment cost and the solar-to-electricity plant efficiency. The trends of the optimization variables and cycle results have been reported to give useful insights about proper assumptions for the sCO2 power block design. The recompressed cycle with intercooling resulted as the most promising configuration and it has been further analyzed through a comparison of different solutions on the Pareto front. The cost breakdown of the sCO2 power block has been reported to highlight which components have the greatest impact on the overall plant cost and how they vary along the optimal solutions front. Eventually, the optimization has been repeated introducing a correlation to compute the turbomachinery isentropic efficiencies, to investigate their effect on the techno- economic analysis.

concentrated solar power↗

DOE OSTI2023

Advanced data analysis in inertial confinement fusion and high energy density physics

Bayesian analysis enables flexible and rigorous definition of statistical model assumptions with well-characterized propagation of uncertainties and resulting inferences for single-shot, repeated, or even cross-platform data. This approach has a strong history of application to a variety of problems in physical sciences ranging from inference of particle mass from multi-source high-energy particle data to analysis of black-hole characteristics from gravitational wave observations. The recent adoption of Bayesian statistics for analysis and design of high-energy density physics (HEDP) and inertial confinement fusion (ICF) experiments has provided invaluable gains in expert understanding and experiment performance. In this Review, we discuss the basic theory and practical application of the Bayesian statistics framework. We highlight a variety of studies from the HEDP and ICF literature, demonstrating the power of this technique. Due to the computational complexity of multi-physics models needed to analyze HEDP and ICF experiments, Bayesian inference is often not computationally tractable. Two sections are devoted to a review of statistical approximations, efficient inference algorithms, and data-driven methods, such as deep-learning and dimensionality reduction, which play a significant role in enabling use of the Bayesian framework. We provide additional discussion of various applications of Bayesian and machine learning methods that appear to be sparse in the HEDP and ICF literature constituting possible next steps for the community. We conclude by highlighting community needs, the resolution of which will improve trust in data-driven methods that have proven critical for accelerating the design and discovery cycle in many application areas.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Machine learning for modern power distribution systems: Progress and perspectives

The application of machine learning (ML) to power and energy systems (PES) is being researched at an astounding rate, resulting in a significant number of recent additions to the literature. As the infrastructure of electric power systems evolves, so does interest in deploying ML techniques to PES. However, despite growing interest, the limited number of reported real-world applications suggests that the gap between research and practice is yet to be fully bridged. To help highlight areas where this gap could be narrowed, this article discusses the challenges and opportunities in developing and adapting ML techniques for modern electric power systems, with a particular focus on power distribution systems. These systems play a crucial role in transforming the electric power sector and accommodating emerging distributed technologies to mitigate the impacts of climate change and accelerate the transition to a sustainable energy future. The objective of this article is not to provide an exhaustive overview of the state-of-the-art in the literature, but rather to make the topic accessible to readers with an engineering or computer science background and an interest in the field of ML for PES, thereby encouraging cross-disciplinary research in this rapidly developing field. To this end, the article discusses the ways in which ML can contribute to addressing the evolving operational challenges facing power distribution systems and identifies relevant application areas that exemplify the potential for ML to make near-term contributions. At the same time, key considerations for the practical implementation of ML in power distribution systems are discussed, along with suggestions for several potential future directions.

Marković, Marija (ORCID:0000000247839837)↗