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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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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

An RTDS-Based Testbed for Investigating the Impacts of Transmission-Level Disturbances on Solar PV Operation

The increasing penetration of renewable energy resources such as solar and wind via power electronic inverters is challenging grid dynamics, as well as grid planning, operation, and protection. Recently, the North American Electric Reliability Corporation (NERC) has reported a series of similar events of the unintended loss of solar generation in Southern California over a large geographic area following the transmission-level disturbances. These events highlight the importance of understanding the characteristics of the transmission-side disturbances propagating into the distribution systems and their impacts on the operation of inverter-based resources. In this paper, a real-time electromagnetic simulation testbed is constructed for real-time electromagnetic simulations to generate realistic transmission-level disturbances and investigate their impacts on the solar PV operation under different fault types and locations, solar penetration levels, and loading levels. Through the simulation analysis and grid strength assessment, it is found that the grid strength at points of integration (POIs) of solar PVs significantly affects the transient stability of solar generators. Particularly, undesirable transient stability events are more likely to occur at the weak POIs following the transmission-level disturbances. Moreover, undesirable transient stability events become severer when the transmission-level disturbance is closer to the weak POIs or the disturbances become more serious. Additionally, the impact of the transmission-level disturbances on the solar PVs at the weak POIs exacerbate with the increasing solar penetration levels and loading levels. Thus, it is important to study and develop new technologies for grid planning, operation, and protection in weak grid conditions to address the emerging issues of integrating the high penetration of solar PVs and other IBRs.

14 SOLAR ENERGY↗
DOE OSTI2025

Solid Wastes from Geothermal Energy Production and Implications for Direct Lithium Extraction

Direct lithium extraction (DLE) of brines after geothermal power production offers opportunities to produce environmentally benign “green” lithium; however, some environmental impact is inevitable. We examined solid waste production at geothermal power plants in southern California that are also locations for planned DLE facilities. Currently, the geothermal plants in this region produce approximately 79,800 metric tons (wet weight) per year of solid waste, which represents about 28 metric tons per GWh of net electricity production or approximately 500 mg solids per kg geothermal brine. Approximately 15% of this waste requires management as hazardous waste. Solids produced during power production represent about 0.2% of the total dissolved solids in the brine. Lithium production will require the removal of silica, iron, and other metals as part of the DLE process. Using a mass balance approach, we calculate that precipitation of silica and metals could produce up to an additional 6800 mg solids per kg brine. Calcium occurs at very high concentrations, and the amount of solids disposed in landfills will be dependent on the amount of calcium removed during lithium recovery. Our analysis shows that evaluation of brine chemistry in the context of the DLE process is useful for evaluating the potential solid waste impacts of producing lithium from brines.

42 ENGINEERING↗
DOE OSTI2022

Earthquake Nowcasting with Deep Learning

We review previous approaches to nowcasting earthquakes and introduce new approaches based on deep learning using three distinct models based on recurrent neural networks and transformers. We discuss different choices for observables and measures presenting promising initial results for a region of Southern California from 1950–2020. Earthquake activity is predicted as a function of 0.1-degree spatial bins for time periods varying from two weeks to four years. The overall quality is measured by the Nash Sutcliffe efficiency comparing the deviation of nowcast and observation with the variance over time in each spatial region. The software is available as open source together with the preprocessed data from the USGS.

Fox, Geoffrey Charles (ORCID:0000000310171391)↗
DOE OSTI2021

Real-Time Optimization and Control of Next-Generation Distribution Infrastructure

This presentation highlights the key developments of the ARAP-e NODES project, including the innovative real-time optimal power flow (RT-OPF) algorithm for distributed energy resource (DER) management, trip planning for T+D coordination, and extensive validation of the RT-OPF algorithm in NREL ESIF laboratory with 100+ physical hardware devices, controller-hardware-in-the-loop test at Southern California Edison (SCE), and two field demonstrations.

hardware-in-the-loop↗
DOE OSTI2021

ROP model for PDC bits in Geothermal drilling

Geothermal energy is a renewable source of energy, where heat extraction is preferentially balanced with the reservoir's natural heat recharge rate. The objective of this paper is to present and validate a novel rate of penetration (ROP) model for drilling hard and abrasive formations including granite formations for polycrystalline diamond compact (PDC) bits. The ROP model was developed based on a derived relationship of a threshold weight on cutter (WOC) and its corresponding depth of cut (DOC) for a single cutter. Laboratory data was used to scale the derived single cutter relationship to a full-hole ROP model for PDC bits. The ROP model includes a non-linear correlation for Phase I (inefficient drilling due to low WOB values) and a linear Phase II (efficient drilling) ROP response to WOB. The ROP model was verified using measured drilling parameter data from Utah FORGE well# 58-32 and data from Chocolate Mountains well # 17-8 in Southern California. When compared to oil and gas well drilling, geothermal drilling in granitic formations can be more difficult and complicated due to rock hardness and high temperatures. PDC bits can increase ROP and optimize drilling for these types of hard formations. This paper provides novel insight into the ROP response of PDC bits to drilling operational parameters.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

DERMS Online: A New Voltage Sensitivity-Enabled Feedback Optimization Framework: Preprint

This paper proposes a distributed energy resource management system (DERMS) solution by developing a new voltage sensitivity enabled feedback optimization framework. The key idea is to adopt a measurement feedback scheme to reformulate the original nonlinear optimization into a linear programming (LP) problem via perturb and observe-based voltage sensitivity analysis. The proposed solution eliminates the dependence on load knowledge and can be implemented online thanks to an efficient open-source solver for LP problems. The proposed DERMS online platform is generalizable to deal with various types of distributed energy resources (DERs), including distributed photovoltaics (PVs), energy storage, electric vehicles, demand response, etc. Comparison results with other control methods on a realistic distribution feeder in Southern California highlight the feasibility as well as benefits for the proposed framework.

distributed energy resources management↗
DOE OSTI2022

A Hybrid Data-Driven and Model-Based Anomaly Detection Scheme for DER Operation: Preprint

This paper proposes a hybrid data and model-based anomaly detection for securing the operation of distributed energy resources (DERs) in distribution grids. Data-driven autoencoders (AE) are set up at the edge level by taking local DER data and detect anomalous operations by leveraging the reconstruction ability. In parallel, model-based state estimation (SE) is running at the system level by taking system models and measurements, the anomalies are identified by analyzing the measurements residual. The hybrid scheme preserves the benefits of both data-driven and model-based analysis and thus improves the robustness and accuracy of anomaly detection. It can be established by getting full use of the existing infrastructures in distribution grids. Numerical tests on a realistic distribution feeder in Southern California highlight the effectiveness as well as benefits of the proposed scheme.

anomaly detection↗
DOE OSTI2023

Biomethanation to Upgrade Biogas to Pipeline Grade Methane

NREL is working closely with DOE, Electrochaea GmbH, and Southern California Gas Company (SoCalGas) to reduce costs of a biomethanation process capable of megawatt-scale deployment that upgrades organic biogas waste streams to produce pipeline quality renewable natural gas (RNG). Biomethanation is a two-step process using a single-celled methanogenic archaea that converts low-carbon low-cost hydrogen (H2) and waste carbon dioxide (CO2) to produce renewable methane (CH4). The process upgrades the biogenic CO2 - while allowing the CH4 to pass through - from biogas sources like dairies, wastewater treatment plants, and landfills. The CH4 produced is a drop-in direct replacement fuel and producers can participate in the growing number of carbon markets; like California's Low Carbon Fuel Standard and the Federal Renewable Fuel Standard. NREL and Argonne National Laboratory have completed a life cycle analysis using the GREET model to show that the biomethanation process produces RNG that is carbon negative even when H2 production via low-temperature water electrolysis is driven by the existing carbon intensity of California's electricity grid. And of course, even further carbon negative (-233 kg CO2e/kWh) when the electricity is produced from low-carbon sources like wind and solar. Leveraging lessons learned from operating SoCalGas' 700L 18-bar bioreactor system, NREL is designing and building a flexible RD&D platform that will enable field trials at biogas and other CO2 sources. A custom 16' long trailer will house a 20L 18-bar bioreactor, 3 - 25 kW proton exchange membrane electrolyzer, and dosing, thermal, and controls systems to support operations with only power, biogas, and water feedstocks required by the field locations. The end-of-project goal is to demonstrate pipeline quality RNG production (> 95% CH4, < 4% H2, <1% CO2, < 0.2% O2 and < 4 parts per million H2 sulfide) using real biogas feedstocks - thereby recycling both greenhouse gases for injection into the natural gas network or to be used onsite.

biogas upgrading↗
DOE OSTI2026

Luminescent Zr Complexes with Long-lived Intraligand Charge Transfer Excited States

Understanding and establishing design principles to tune the excited states of earth-abundant sensitizers is crucial for identifying new photosensitizers for sustainable technological advancements. Here, we report a series of three bis Zr (IV) complexes of tridentate, dianionic ligands incorporating two phenoxide donors and aza arene acceptors of increasing electron affinity (pyridine < pyrimidine < pyrazine ) that are air and water-stable. These complexes emit via thermally assisted delayed fluorescence from an intraligand charge transfer excited state with varying metal contributions. The electronic structural changes from different acceptors vary the excited state character and the photophysical properties significantly between the complexes. The variation in photophysics that includes emission lifetime (76 μs to 265 ns), intersystem crossing (ISC) lifetime ( 390 – 290 ps), and the energy difference between the singlet and triplet excited states (∆EST. 170 -100 meV). We observe solvent-independent ISC rates when the excited state has metal contributions (acceptor = pyridine), and the ISC rates vary significantly with solvent polarity when the excited state is an intra-ligand charge transfer state (acceptor = pyrimidine and pyrazine). Transient absorption measurements provided the basis spectra and verified the metal contribution in the excited state. This work provides a basis for developing new sensitizers based on Zr (IV) by providing design principles that can be used to modulate the character of the excited state and its photophysics.

Nattikallungal, Thabassum A. [University of Southe↗
DOE OSTI2026

Bimetallic Coinage Metal Complexes of Tetradentate ortho Ter arylene Ligands

The synthesis, structural and photophysical properties of five bimetallic coinage metal complexes of three tetradentate charge-transfer (CT) ligands are presented. The ligand structures incorporate donor/acceptor moieties electronically decoupled by ortho connection to a bridging biphenylene group. The M M distances observed in the crystal structures of the bimetallic complexes are shorter than the sum of the Van der Waals radii of the metal ions, suggesting stabilizing interactions between the d10 metal centers. Additionally, short distances between the bridging biphenylene and metal atoms suggest arylene metal interactions. Bimetallic Cu, Ag, and Au complexes of the ligand incorporating a carbazole donor and pyridyl acceptor (N2R22-) show absorption and emission energies that trend with the ionization potential of each metal, indicating metal character in the excited state. These properties contrast with our previously reported mononuclear Zn complex of N2R22-The structural and photophysical properties of five bimetallic d10 coinage metal complexes were presented. The M M distances observed in the crystal structures of the bimetallic complexes are shorter than the sum of the metals’ Van der Waals radii, suggesting attractive interactions between the d10 metal centers. Additionally, short distances between the bridging biphenylene and metal atoms suggest arylene metal interactions. The absorption and emission spectra of the bimetallic complexes redshift based on the oxidation potential of the metal ion. This suggests involvement of metal based orbitals in the excited state transitions of the bimetallic complexes, which was corroborated by molecular modeling. High photoluminescent quantum yields were observed in solution and in rigid media (up to PL = 0.75), and the excited state lifetimes in solution were found to exceed several microseconds.

Shariaty, Darius Allen [University of Southern Cal↗
DOE OSTI2025

Lone Pairs of Carbogenic Center Enable Thermally Activated Delayed Fluorescence from Carbon to Ligand Charge Transfer Excited States

Carbogenic compounds of the type L→C(0)←L, where L represents various ligands such as phosphines or carbenes, and C(0) denotes zerovalent carbon with two orthogonal lone pairs, are widely utilized in organic and coordination chemistry; however, in-depth photophysical and optical properties remain largely unknown. In the following work, we report detailed luminescent properties of one of the most prominent examples of carbogenic compounds, hexaphenylcarbodiphosphorane (CDP). Combined spectroscopic/TD-DFT studies demonstrate that both lone pairs of CDP participate in the observed visible light absorption and emission, which are associated with carbon lone pairs π*(PPh3) carbon to ligand charge transfer states (CLCTs). The CLCT exhibits a considerably decoupled electron-hole pair, resulting in a small S1-T1 gap and thermally assisted delayed fluorescence (TADF). Moreover, two lone pairs teamed up around C(0) provide numerous close-lying σ- and π-CLCT singlet and triplet states, which allow, for organic TADF emitters, extremely fast rates of exergonic intersystem crossing up to 1.27×109 s-1, competitive with some 3d and 4d metal-based TADF luminophores. These results open fresh directions for innovative design of novel luminescent materials for high-end photonic applications, utilizing lone pairs of carbogenic centers as donors of electron density in the excited states.

Mrózek, Ondřej [University of Southern California]↗
DOE OSTI2025

A Route to Design Novel Functional Peptides by Applying a Denoising Diffusional Model to mRNA Display Libraries

In vitro directed evolution techniques, such as mRNA display, enable peptide ligand discovery and optimization. However, physical libraries that rely on a genetic code can only search a small fraction of sequence space due to inherent biases in the genetic code and experimental limitations. To address this challenge, denoising diffusion implicit models (DDIMs) are applied to generate novel peptide ligands against B‐cell lymphoma extra‐large (Bcl‐x L ), a key cancer target. Starting with high‐throughput sequencing data from previous selections, a DDIM is trained to produce novel sequences with high affinity binding. Experimental validation confirms that most generated sequences are functionally equivalent to the original library members for Bcl‐x L binding and demonstrated comparable binding kinetics and affinity relative to the wildtype and nearest original neighbors. Importantly, this approach generated rare sequences not easily accessible via mutation and directed evolution. These results indicate that DDIMs can complement and expand directed evolution data, efficiently exploring underrepresented regions of sequence space. This approach provides a broadly applicable framework for accelerating ligand discovery and optimizing molecular properties across diverse targets.

Qi, Pearl [Mork Family Department of Chemical Engi↗
DOE OSTI2025

Secretory stimuli distinctly regulate insulin secretory granule maturation through structural remodeling

Insulin secretory granule (ISG) maturation is a crucial aspect of insulin secretion and glucose homeostasis. The regulation of this maturation remains poorly understood, especially how secretory stimuli affect ISG maturity and subcellular localization. In this study, we used soft X-ray tomography (SXT) to quantitatively map ISG morphology, density, and location in single INS-1E and mouse pancreatic β cells under the effect of various secretory stimuli. We found that the activation of glucokinase (GK), gastric inhibitory polypeptide receptor (GIPR), glucagon-like peptide-1 receptor (GLP-1R), and G protein-coupled receptor 40 (GPR40) promotes ISG maturation. Each stimulus induces unique structural remodeling in ISGs, by altering size and density, depending on the specific signaling cascades activated. These distinct ISG subpopulations mobilize and redistribute in the cell, altering the overall cellular structural organization. Our results provide insight into how current diabetes and obesity therapies impact ISG maturation and may inform the development of future treatments that target maturation specifically.

insulin granule maturation↗
DOE OSTI2025

High-Pressure Phase Transition of Metastable Wurtzite-Like CuInSe 2 Nanocrystals

Ternary I–III–VI 2 semiconductors, such as CuInSe 2 , exhibit diverse polymorphs with unique structural characteristics and optoelectronic properties. This study investigates the pressure-induced phase transitions of metastable wurtzite-like CuInSe 2 nanocrystals. Using a combination of synchrotron X-ray diffraction, pair distribution function analysis, and density functional theory calculations, we reveal a transition from cation-ordered wurtzite-like (Pmc2 1 ) to cation-disordered NaCl-like (Fm3̅m) structures at 7.7 GPa. The cation-disordered NaCl-like phase persists upon decompression. Bulk modulus calculations highlight size-dependent deviations from bulk material behavior. These findings deepen our understanding of phase stability in colloidal I–III–VI 2 semiconductor nanocrystals, with implications for tailoring functional materials under extreme conditions.

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

Assessing Indoor versus Outdoor PM 2.5 Concentrations during the 2025 Los Angeles Fires Using the PurpleAir Sensor Network

In January 2025, a series of fast-moving wildland-urban-interface (WUI) fires swept through the Los Angeles (LA) metropolitan area, causing severe air pollution. While the impacts of WUI fires on outdoor air quality have been extensively studied, indoor exposure remains less understood, despite most people sheltering indoors during WUI fires. Here, this study investigates the spatial and temporal patterns of indoor and outdoor PM 2.5 concentrations across the South Coast Air Basin, with a focus on LA County during the LA fires. Using high-resolution data from co-located indoor and outdoor PurpleAir (PA) sensors, we analyze hourly PM 2.5 levels and indoor/outdoor ratios. Outdoor PM 2.5 concentrations spiked sharply during the fires, reaching unhealthy levels exceeding 130 μg/m 3 , compared to the mean concentration (12 μg/m 3 ) during non-fire hours. Indoor concentrations also increased, though to a lesser extent, peaking around 60 μg/m 3 compared to a mean of 7 μg/m 3 during non-fire hours. This reflects the partial shielding that indoor environments provide from outdoor air pollution. The mean (0.42) and median (0.29) indoor/outdoor PM 2.5 ratios during LA fire hours were lower than the mean (0.93) and median (0.66) ratios during non-fire hours. Indoor/outdoor PM 2.5 ratios across sensors showed a wide distribution, reflecting differences in building characteristics and occupant behavior, such as indoor activities and the use of air purifiers. These findings emphasize the need for guidance and interventions to reduce indoor PM 2.5 exposure and protect public health during extreme WUI fire events.

2025 Los Angeles Fires↗
DOE OSTI2026

Component-Level Inverse Design of Transmon Qubits Using Neural Networks

Designing a superconducting qubit to realize specific Hamiltonian parameters typically requires iterating through a time and compute-intensive forward loop in which the designer chooses a layout geometry, simulates it, extracts circuit parameters such as capacitances, and refines the geometry. We study the inverse version of this task using a neural-network workflow that maps target Hamiltonian parameters directly to component-level layout parameters, which we subsequently demonstrate on a planar transmon layout. During training, we pair the inverse model with a frozen forward surrogate model and evaluate the loss in Hamiltonian space rather than in layout-parameter space. In validation against a conventional EM solver, 97% of generated designs produce usable geometries, and the inverse-plus-surrogate pipeline reaches mean percent errors of 0.73% for qubit frequency and 1.58% for anharmonicity, comparable to or below the fabrication and simulation-to-measurement uncertainty expected for academic-process transmon devices of this type. A single pipeline query takes ~60 ms on CPU, versus ~2 min for a conventional EM capacitance extraction on the same hardware, a speedup of approximately 2,000x. Batching minimizes the AI model inference overhead, reducing the runtime to 3.1 microseconds per sample on CPU and 2.6 microseconds per sample on GPU at a batch size of 2048, resulting in speedups of 3.9 x 10^7 and 4.6 x 10^7, respectively, relative to a single conventional CPU EM extraction. Our results indicate that component-level inverse design usefully extends and complements conventional EM simulation, including for small datasets on the order of 1,000 samples.

Seidel, Olivia [Fermilab; Texas U., Arlington]↗