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DOE OSTI2025

High-Intensity UV Exposure for the Rapid Screening of Silicon Photovoltaic Architectures

Advanced Si photovoltaic architectures incorporate different materials and processing pathways that influence degradation modes. Ultraviolet-induced degradation (UVID) is an understudied degradation mode for advanced cell architectures and is of increasing concern to industry due to growing adoption of UV-transparent encapsulation and bifacial technologies. In order to adopt new and evolving technologies confidently, novel component materials and processing techniques must be evaluated and designed for long-term stability, in addition to the conventional design focus on efficiency. In this work, a study protocol framework is presented for the rapid screening of unencapsulated devices against UVID. Unencapsulated passivated emitter rear contact (PERC) and tunnel oxide passivated contact (TOPCon) devices were aged under different UV irradiance intensities and measured via conventional nondestructive electrical characterization methods to assess performance degradation. Based on the results, protocol efficacy and recommendations for further study are discussed. As a result, this work is part of a broader effort to develop rapid screening processes that cut across architectures and exposure conditions to aid module manufacturers in vetting new materials choices for long-term stability.

Accelerated exposure↗

DOE OSTI2026

Small Nuclear Reactors for Maritime Ports

Maritime ports are entering a period of sharply rising electricity demand as operations are electrified, shore power adoption grows, and energy-intensive industries expand near ports. This report evaluates the feasibility of small nuclear reactors at U.S. ports, which could offer stable baseload power and reduced dependence on regional grids. The report describes the current state of advanced reactor technologies and other factors important for future deployment such as safety and operations, siting requirements, regulatory environments and policy, and other co-benefit considerations. A structured evaluation across a diverse group of U.S. ports highlights the wide variation in feasibility. Fifteen ports were analyzed through port interviews and data collection to assess the port-specific conditions that most impact advanced reactor deployment. The analysis found that the most feasible ports for deployment have favorable geotechnical stability, supportive regulatory environments, and substantial energy loads in a grid-constrained environment. Additionally, an initial reactor size matching was done for the ports based on their reported energy consumption across different modes of operation. However, further analysis and detailed data will be required in the future to determine the optimal reactor-port matching. The economic viability to adopt this technology will be dictated by competitive cost of nuclear-generated electricity compared to other alternatives. Overall, small nuclear reactors present a promising but highly site-dependent pathway for ports seeking resilient, high-capacity energy solutions that support future energy demands. This report identifies key areas for future research and highlights ports that warrant further evaluation to assess the viability of small nuclear reactor implementation. By establishing these priorities, the analysis provides support for the development of informed strategies for potential advanced nuclear technology deployment. The inclusion of ports in this report does not imply their endorsement of nuclear energy generation, and the authors are grateful for the information, expertise, and perspectives they contributed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Blending Behavioral Science and Physics-Based Models Inform Equitable Decarbonization Pathways in the US Housing Stock: Preprint

A just energy transition is an imperative of the Biden-Harris Administration, emphasizing the equitable distribution of benefits through energy-efficient and decarbonizing household technologies. Understanding the factors that increase a household's willingness to adopt these technologies helps policymakers implement more targeted and effective approaches. Our research addresses this by blending 550,000 housing stock types and energy simulation data with a nationally representative survey on residential technology adoption and decision-making (n=10,000). We identify energy equity gaps across tenure and income, highlighting disparities in energy burdens and insecurity. Findings show that households with prior modification experience are more willing to renovate, suggesting that small-scale retrofit programs could foster greater willingness. Energy secure but burdened homeowners are least willing to modify, highlighting the need to consider energy bill perceptions in policy design. Nearly half of US households that are energy burdened also face energy insecurity, with a significant gap in assistance for low-income households. We emphasize the need to understand household perceptions to improve policy. This research underscores the importance of understanding household behaviors to improve policy effectiveness, offering actionable insights for policymakers to promote equitable housing upgrades and advance a decarbonized future.

behavioral science↗

DOE OSTI2024

Rooftop Solar in Lawrence, MA: Community Perspectives, Deceptive Practices, and Financing Options

This report was prepared as part of the U.S. Department of Energy's Communities Local Energy Action Program (Communities LEAP) pilot competitive technical assistance for the Lawrence Massachusetts Stakeholder Coalition (LSC) composed of The City of Lawrence, All In Energy, MassDevelopment, Mill City Community Investments, BlocPower and Groundwork Lawrence, and led by Browning the Green Space. The LSC identified rooftop solar photovoltaics as a top priority for this technical assistance opportunity. Lawrence faces high energy burden and electricity prices, thus rooftop solar can be a tool to help lower those costs. However, the coalition received feedback that some solar companies were using deceptive and unfair practices when marketing, selling, or financing solar energy, costing residents more money than utility rates and increasing the energy burden. This project sought to address rooftop solar community priorities through two pathways: 1. facilitating community engagement to understand community perspectives and experiences with rooftop solar development; and 2. conducting a financial cash-flow analysis highlighting the varying fiscal outcomes for rooftop solar adopters based off rooftop solar leasing, ownership, or buying electricity from the utility (National Grid).

14 SOLAR ENERGY↗

DOE OSTI2024

Solar Pathways in Federal Energy Assistance Programs: Expanding Low Income Home Energy Assistance Program (LIHEAP) and Weatherization Assistance Program (WAP)

How can solar best fit within your LIHEAP or WAP activities? Come join NREL and learn about the various pathways and new resources available to help implement solar in low-income programs. Panelists will share results from a multi-year research project, including survey results on LIHEAP and WAP solar adoption across the United States. This session will highlight case studies from early implementers, key lessons learned and resources developed based on stakeholder feedback for interested organizations. Attendees can expect gain a better understanding of the perceived barriers and opportunities to solar implementation, including the importance of partner coordination and complementary funding sources, and the next steps for how to get started. Additionally, attendees will hear from a local implementer of solar in WAP about their program and process.

Colorado↗

DOE OSTI2024

Structural, biophysical, and biochemical insights into C–S bond cleavage by dimethylsulfone monooxygenase

Sulfur is an essential element for life. Bacteria can obtain sulfur from inorganic sulfate; but in the sulfur starvation–induced response,Pseudomonadsemploy two-component flavin-dependent monooxygenases (TC-FMOs) from themsuandsfnoperons to assimilate sulfur from environmental compounds including alkanesulfonates and dialkylsulfones. Here, we report binding studies of oxidized FMN to enzymes involved within theP. fluorescensenzymatic pathway responsible for converting dimethylsulfone (DMSO 2 ) to sulfite. In this catabolic pathway, SfnG serves as the initial TC-FMO for sulfur assimilation, which is investigated in detail by solving the 2.6-Å resolution crystal structure of unliganded SfnG and the 1.75-Å resolution crystal structure of the SfnG ternary complex containing FMN and DMSO 2 . We find that SfnG adopts a (β/α) 8 barrel fold with a distinct quaternary configuration from other tetrameric class C TC-FMOs. To probe the unexpected tetramer arrangement, structural heterogeneity is assessed by chromatography and light scattering to confirm ligand binding correlates with a tetramer. Binding of FMN and DMSO 2 accompanies ordering of the active site, with DMSO 2 bound on thesi-face of the flavin. A previously unobserved protein backbone conformation is found within the oxygen-binding site on there-face of the flavin. Functional assays and the positioning of ligands with respect to the oxygen-binding site are consistent with use of an N5-(hydro)peroxyflavin pathway. Biochemical endpoint assays and docking studies reveal SfnG breaks the C–S bond of a range of dialkylsulfones.

Science & Technology - Other Topics↗

DOE OSTI2026

SAF: a promising approach to meet growing jet fuel demand

SAF provides a promising approach to aid the rising jet fuel demand from increased travel around the world and reduce the lifecycle emissions from the aviation sector. Although the feasibility of SAF pathways has been demonstrated through economic and environmental metrics quantification, the models used to quantify these variables have a high degree of variability in terms of accuracy and thereby reliability. To understand how to adopt and commercialize SAF, we need to harmonize these process models and assess metrics and technical limitations related to their production technologies. We find the production cost of SAF using hydro processed fatty acids and esters (HEFA), Fischer-Tropsch (FT), and alcohol-to-jet (ATJ) to be $\$$3-$\$$6/gallon gasoline equivalent (gge) and life cycle emissions to be lower than Jet A, except for ATJ using corn grain (≤25%). HEFA utilizing oil feedstocks has the lowest production cost (~$\$$2.9/gge) and highest jet yield (>150 gge/dry ton), while FT has the largest emission reduction (94%) compared to fossil jet. A unique contribution of this study is a comparative analysis of metrics related to SAF processes across technical, economic, and sustainability aspects. A cross-comparison of these metrics shows HEFA using fats, oils, and grease have the most favorable ratings, while HEFA using algae and ATJ using corn stover have more neutral and unfavorable ratings, respectively. These ratings can be improved by implementing the right combination of practical and technological advancements.

09 BIOMASS FUELS↗

DOE OSTI2026

Optimizing Heat Recovery with Storage: Control Validation and Sensitivity Analysis of the Time-Independent Energy Recovery Plant Using Modelica

Heat recovery in large building central plants saves energy but traditionally requires simultaneous heating and cooling. The Time-Independent Energy Recovery (TIER) plant shifts this paradigm by integrating thermal energy storage (TES) to enable heat recovery regardless of concurrent demand, offering a highly efficient, space-saving solution to achieve California’s energy goals. However, its integration of heat recovery chillers, cooling-only chillers, cooling towers, and trim air-source heat pumps (ASHPs) creates growing control and sizing complexity. To overcome this, this study employs high-fidelity Modelica dynamic simulation to validate TIER control sequences and optimize equipment sizing. We translated the written Sequences of Operation into executable Control Description Language (CDL) to test logic against sub-hourly loads. This verification workflow successfully identified and resolved critical vulnerabilities, such as thermal storage freezing and equipment short-cycling, in a virtual environment prior to physical deployment. Then, the study analyzes TIER plant performance across three simulated building types in three locations, and a real building load profile, ensuring variety in heating and cooling loads, and simultaneity factors and explores sizing rules for the TES and ASHP capacity. The analysis shows that the TIER plant operates equipment efficiently leading to a plant SCOP of around 7.5 across all scenarios, higher than a traditional ASHP plant, and a viable pathway to de-risk complex system design and control through simulation to identify optimal designs that maximize energy efficiency, minimize operational costs, and ensure robust operation in varied environmental conditions, thereby facilitating the broader adoption of such a solution for large buildings.

Zanetti, Ettore↗

DOE OSTI2025

Optimization based process modeling of an anaerobic membrane bioreactor system: Application to swine wastewater

To maintain current levels of consumption in the economy with the dwindling supply of non-renewable material and energy, alternative resource streams more traditionally viewed as waste streams must be considered. Fermentation of high-strength wastewaters is one such pathway that allows for the recovery of energy, nitrogen, phosphorus, and carbon compounds. Anaerobic membrane bioreactors (AnMBRs) are an emerging technology that allow for the digestion of wastewater in a much smaller footprint than traditional anaerobic digesters. Adoption of this technology into industry has been limited by membrane capital and cleaning costs, but these costs may be offset through the recovery of valuable products. To evaluate the viability of AnMBR technology in the context of swine wastewater treatment, an optimization-based process model built upon Anaerobic Digestion Model No. 1 (ADM1) has been developed. Modeling results show that a swine wastewater stream provides potential for net positive energy generation from the AnMBR system in most cases. Sensitivity analyses around important variables were conducted to determine focus areas for future research into AnMBR technology and evaluate the robustness of the model to microbial variables that may change with different microbial communities.

09 BIOMASS FUELS↗

DOE OSTI2025

Computational Modeling to Advance Novel Medical Isotopes for Radiotheranostics: A DOE-NIH Joint Workshop Executive Summary

The DOE-NIH Joint Workshop on Computational Modeling to Advance Novel Medical Isotopes for Radiotheranostics, held on September 27, 2024, brought together experts from government, academia, and industry to address critical challenges in radionuclide production and clinical translation. Here, the workshop emphasized interdisciplinary collaboration, particularly between the Department of Energy (DOE) and the National Institutes of Health (NIH), to strengthen the domestic isotope supply, streamline regulatory pathways, and further integrate computational tools into radiopharmaceutical therapy (RPT). Key discussions explored the role of AI-driven modeling, machine learning, and digital twin technologies in optimizing dosimetry, dynamically personalizing treatments, and reducing time to clinical adoption. Advances in predictive computational modeling were highlighted as essential for improving radionuclide yield, purity, and synthesis efficiency. Regulatory considerations and equitable access were central themes, with participants advocating for harmonized global standards, adaptive trial designs, and expanded infrastructure for clinical implementation. DOE computational and production infrastructure was emphasized. Future priorities identified include increased investment in radionuclide production infrastructure, expanded workforce development in radiopharmaceutical sciences and computational modeling, and the creation of robust public-private partnerships. The workshop concluded that continued strategic collaboration and sustained resources will be vital for advancing next-generation radiotheranostics, ensuring safe and effective therapies accessible to all patients.

digital twins↗

DOE OSTI2026

Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The future of the grid will be powered by AI—or undermined by it. Artificial intelligence is rapidly reshaping grid operations, improving fault detection, forecasting accuracy, and real-time optimization. As AI systems move closer to operational decision loops, however, they introduce new consequence pathways: expanded attack surfaces, model integrity risks, regulatory exposure, and human-automation challenges. This talk presents a consequence-driven framework for deploying AI responsibly in the electric grid. Attendees will gain practical strategies to strengthen resilience, boost reliability, and deploy AI securely — ensuring the grid of the future is not only smarter but safer.

25 - ENERGY STORAGE↗

DOE OSTI2025

Technoeconomic analysis for near-term scale-up of bioprocesses

Growing the bioeconomy requires products and pathways that are cost-competitive. Technoeconomic analyses (TEAs) aim to predict the long-term economic viability and often use what are known as n th plant cost and performance parameters. However, as TEA is more widely adopted to inform everything from early-stage research to company and investor decision-making, the n th plant approach is inadequate and risks being misused to inform the early stages of scale-up. Some methods exist for conducting first-of-a-kind/pioneer plant cost analyses, but these receive less attention and have not been critically evaluated. This article explores TEA methods for early-stage scale-up, critically evaluates their applicability to biofuels and bioproducts, and recommends strategies for producing TEA results better suited to guiding prioritization and successful scale-up of bioprocesses.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Emerging Threats in Transportation Security Related to Intelligent Transportation Systems (ITS)

Transport of high-consequence shipments requires a resilient and robust systems of systems to guarantee cargo arrival. Furthermore, rising adoption of technologies such as connected and automated vehicles (CAVs), intelligent infrastructure, and vehicle-to-everything (V2X) communication presents unique challenges for securing transportation systems. Within these Intelligent Transportation Systems (ITS), several additional vulnerabilities exist that create pathways for adversarial attacks and cargo interception. For example, connectivity provides cyber pathways directly into vehicle systems and infrastructure for malicious actors. Furthermore, advanced vehicle automation exposes additional vehicle control necessary for shipment interception otherwise unavailable to adversaries. Within this paper, we will discuss the specific threats introduced by ITS-enabled technologies currently deployed and in development. These include those mentioned related to connectivity and automation, but will be expanded into grid, infrastructure, and vehicle specific threats. In addition, we will discuss how to potentially mitigate these emerging challenges as well as how to safeguard transportation systems from next generation attacks.

Cook, Adian [ORNL] (ORCID:0000000160825395)↗

DOE OSTI2026

Cost and Carbon Intensity Implications of Coprocessing Sustainable Aviation Fuel at Petroleum Refineries

Sustainable aviation fuel (SAF) will play a critical role in decarbonizing the aviation industry. Among SAF production pathways, alcohol-to-jet (ATJ) stands out for its scalability, supported by abundant feedstock availability and a well-established bioethanol industry. However, significant reductions in SAF carbon intensity (CI) require the use of future feedstocks (e.g., cellulosic) whose adoption is hindered by high capital costs for feedstock processing and ethanol upgrading. Here, we evaluate the financial viability and environmental implications of integrating an ATJ SAF biorefinery within a petroleum refinery, utilizing miscanthus and switchgrass as example feedstocks. Three scenarios are evaluated: standalone (benchmark), colocated, and repurposing (coprocessing SAF within the petroleum refinery). Results show repurposing reduces baseline capital costs by 36% and SAF minimum selling price (MSP) by 12% to 8.14 USD·gal −1 ; the superior performance of repurposing is consistent across both feedstocks. Integration has a limited effect on SAF CI, which remains stable across scenarios, whereas using cellulosic feedstocks reduces CI by over 70% relative to corn, with baseline values of 17.01 g CO 2 e· MJ −1 for miscanthus and 12.23 g CO 2 e·MJ −1 for switchgrass. Global sensitivity analysis reveals MSP declines with greater coprocessing levels.

09 BIOMASS FUELS↗

DOE OSTI2026

Nanocluster Rearrangement Forms a Family of Ordered Cerium–Titanium Bimetallic Metal–Organic Frameworks with Three Different Nodes, Nanocavities, and Thermal Stabilities

Metal–organic frameworks (MOFs) provide a versatile platform for incorporating multiple metal ions within a single crystalline framework, yet achieving spatial and stoichiometric order in heterometallic nodes remains a synthetic challenge. Building on our previously reported, highly thermally stable Ce/Ti bimetallic MOF NU-3000, we identified and isolated two additional crystalline phases, NU-2998 and NU-2999, that arise from the same Ce/Ti nanocluster precursor under modified solvothermal conditions. Systematic variation of reaction temperature, time, solvent ratio, and modulator concentration directs the assembly of these distinct frameworks. Structural analysis and comprehensive characterization studies reveal that these MOFs each feature an unreported nodal geometry with nanocavities of different sizes. NU-2998 even adopts an unreported topology, denoted nui , that features an elongated pore spanning 4 nm. Together, these findings establish a synthesis route that starts with a nanocluster and ends with a set of bimetallic MOFs, offering a glimpse into the pathway-dependent assembly of multimetallic porous materials. Finally, we evaluated the thermal stability of each additional analogue and compared them to NU-3000, providing further insight into material stability. NU-3000 maintained the highest thermal stability and was evaluated as a catalyst for CO oxidation at elevated temperatures.

bimetallic MOFs↗

DOE OSTI2026

Elongation Factor Tu Acts as a Chaperone to Activate an Antibacterial RNase Toxin

Many Gram-negative bacterial species use contact-dependent growth inhibition (CDI) systems to deliver toxic proteins into neighboring competitors. CDI + strains deploy CdiA effector proteins, which translocate their C-terminal toxin (CT) domains into target bacteria through a receptor-mediated delivery pathway. To protect against auto-intoxication, CDI + bacteria also produce CdiI immunity proteins that neutralize CT toxin activity. Here, we present the crystal structure of the CT·CdiI O32:H37 complex from Escherichia coli O32:H37. CT O32:H37 adopts the same fold as the tRNase domain of colicin D, and the nucleases share similar catalytic centers. However, unlike colicin D, which cleaves the anticodon loops of tRNA Arg isoacceptors, CT O32:H37 exhibits nonspecific RNase activity. Notably, we find that endogenous elongation factor Tu (EF-Tu) co-purifies with the over-produced CT·CdiI O32:H37 complex. Although EF-Tu does not bind stably to CT O32:H37 in the absence of CdiI O32:H37 , the translation factor is required for toxic RNase activity in vitro. AlphaFold 3 modeling and site-directed mutagenesis indicate that CT O32:H37 interacts with the N-terminal GTPase domain of EF-Tu. EF-Tu appears to stabilize residue Trp52 within the hydrophobic core of the toxin, which in turn supports the RNase active site through an unusual hydrogen-bonding interaction with the catalytic His67 residue. Furthermore, EF-Tu is hijacked as an essential co-factor to organize the toxin's catalytic center.

Nhan, Dinh Quan [University of California, Santa B↗

DOE OSTI2025

Diversifying the Materials and Technologies for the Future of Energy Storage

It is increasingly important to meet the growing global energy demand driven by factors such as population growth, electrification, and the rapid development of emerging economies, while minimizing the environmental harm caused by carbon dioxide emissions. Although fossil fuels remain an abundant and inexpensive energy source, there is a global consensus on the critical importance of addressing climate change and an increasing urgency to reduce carbon dioxide emissions without hindering economic growth. This challenge is particularly daunting due to the significant transformations required in electricity generation systems, transportation, and industrial processes. A significant portion of our energy still comes from burning fossil fuels, which poses harmful effects on the environment. Transitioning to renewable energy sources like solar and wind is essential, as these sources provide a low-carbon pathway for power generation and have become increasingly cost-competitive with fossil fuels. However, they face the inherent challenge of intermittency. Thus, energy storage systems (ESS) are essential not only to address this issue but also to accommodate the increasing adoption of electric vehicles (EVs). Lithium-ion batteries (LIBs) are still the predominant ESS used for these applications; however, they suffer from issues related to scarce and harmful resources, safety, and socio-economic impacts. This underscores the need for alternative energy storage systems beyond LIBs. Here, in this review, we discuss the diversification, repurposing, and recycling of ESS to meet the projected energy demand while minimizing environmental harm.

batteries↗

DOE OSTI2025

Fast-RF-Shimming: Accelerate RF shimming in 7T MRI using deep learning

Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) offers an elevated signal-to-noise ratio (SNR), enabling exceptionally high spatial resolution that benefits both clinical diagnostics and advanced research. However, the jump to higher fields introduces complications, particularly transmit radiofrequency (RF) field ($B^{+}_{1}$) inhomogeneities, manifesting as uneven flip angles and image intensity irregularities. These artifacts can degrade image quality and impede broader clinical adoption. Traditional RF shimming methods, such as Magnitude Least Squares (MLS) optimization, effectively mitigate $B^{+}_{1}$ inhomogeneity, but remain time-consuming. Recent machine learning approaches, including RF Shim Prediction by Iteratively Projected Ridge Regression and other deep learning architectures, suggest alternative pathways. Although these approaches show promise, challenges such as extensive training periods, limited network complexity, and practical data requirements persist. In this paper, we introduce a holistic learning-based framework called Fast-RF-Shimming, which achieves a 5000 × speed-up compared to the traditional MLS method. In the initial phase, we employ random-initialized Adaptive Moment Estimation (Adam) to derive the desired reference shimming weights from multi-channel $B^{+}_{1}$ fields. Next, we train a Residual Network (ResNet) to map $B^{+}_{1}$ fields directly to the ultimate RF shimming outputs, incorporating the confidence parameter into its loss function. Finally, we design Non-uniformity Field Detector (NFD), an optional post-processing step, to ensure the extreme non-uniform outcomes are identified. Comparative evaluations with standard MLS optimization underscore notable gains in both processing speed and predictive accuracy, which indicates that our technique shows a promising solution for addressing persistent inhomogeneity challenges.

Deep learning↗