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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multifold Insights for Power System Dynamics From Data Assimilation: Meeting Current Challenges

The world’s electric power grids have evolved over the last 120 years from a single power line to today’s large networks. The evolution will continue at an accelerated rate with extensive smart grid development worldwide. Here for example, the U.S. government has set a goal of reaching 100 percent carbon pollution-free electricity by 2035, while the Department of Energy (DOE) shared a goal to deploy 30 GW and 110 GW of offshore wind by 2030 and 2050, respectively. To meet such ambitious goals, in the years to come, a significant percentage of electricity will come from intermittent renewable sources, electric vehicles (EVs), and be supplied to a vast number of loads that will actively respond to grid conditions and incentive signals. This development is largely driven by environmental and economic factors, such as reducing carbon emissions and saving electricity cost for consumers. These energy resources lead to new uncertain behaviors and dynamics which the grid has never seen and were not considered in its design. Operating such a dynamic grid with sufficient reliability and efficiency is a monumental challenge.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2000

Magnetic Flux Compression Concept for Nuclear Pulse Propulsion and Power

The desire for fast, efficient interplanetary transport requires propulsion systems having short acceleration times and very high specific impulse attributes. Unfortunately, most highly efficient propulsion systems which are within the capabilities of present day technologies are either very heavy or yield very low impulse such that the acceleration time to final velocity is too long to be of lasting interest, One exception, the nuclear thermal thruster, could achieve the desired acceleration but it would require inordinately large mass ratios to reach the range of desired final velocities. An alternative approach, among several competing concepts that are beyond our modern technical capabilities, is a pulsed thermonuclear device utilizing microfusion detonations. In this paper, we examine the feasibility of an innovative magnetic flux compression concept for utilizing microfusion detonations, assuming that such low yield nuclear bursts can be realized in practice. In this concept, a magnetic field is compressed between an expanding detonation driven diamagnetic plasma and a stationary structure formed from a high temperature superconductor (HTSC). In general, we are interested in accomplishing two important functions: (1) collimation of a hot diamagnetic plasma for direct thrust production; and (2) pulse power generation for dense plasma ignition. For the purposes of this research, it is assumed that rnicrofusion detonation technology may become available within a few decades, and that this approach could capitalize on recent advances in inertial confinement fusion ICF) technologies including magnetized target concepts and antimatter initiated nuclear detonations. The charged particle expansion velocity in these detonations can be on the order of 10 (exp 6)- 10 (exp 7) meters per second, and, if effectively collimated by a magnetic nozzle, can yield the Isp and the acceleration levels needed for practical interplanetary spaceflight. The ability to ignite pure fusion micro-bursts with reasonable levels of input energy is an equally challenging scientific problem. It remains to be seen, however, whether an effective ignition driver can be developed which meets the requirements for practical spaceflight application (namely high power density, compactness, low weight, and low cost). In this paper, system level performance and design issues are examined including generator performance, magnetic flux compression processes, magnetic diffusion processes, high temperature superconductor (HTSC) material properties, plasmadynamic processes, detonation plasma expansion processes, magnetohydrodynamic instabilities, magnetic nozzle performance, and thrust production performance. Representative generator performance calculations based on a simplified skin layer formulation are presented as well as the results of exploratory small-scale laboratory experiments on magnetic flux diffusion in HTSC materials. In addition, planned follow-on scientific feasibility experiments are described which utilize high explosive detonations and high energy gas discharges to simulate the plasma conditions associated with thermonuclear micro-detonations.

Litchford, Ronald J.↗
DOE OSTI2023

Development of an accelerator-based neutron source to prototype Mo-99 production, Part II: A liquid LBE loop under a high vacuum

To provide US domestic supply of Mo-99 without using high-enriched uranium (HEU), a subcritical uranium target assembly (UTA) is irradiated by an accelerator-based neutron source to create Mo-99 through fission. Part I of this work discusses the design of a liquid lead–bismuth eutectic (LBE) windowless target for an accelerator-based neutron source development. Part II discusses how to couple this windowless target to an accelerator operating at an ultra-high vacuum and the subcritical UTA cooled by water at room temperature. Due to the windowless design of the target, the liquid LBE flow shares an ultra-high vacuum (<1.3 × 10 -7 Pa or 10 -9 Torr) space with the accelerator. As a result of this shared vacuum space, the LBE system must operate at a high vacuum (10 -3 ~10 -6 Pa or 10 -5 ~10 -8 Torr). A magnetic rotary motion feedthrough unit utilizes magnetic fluid to allow rotation of the pump while maintaining a high vacuum environment. Prior to testing the LBE system under vacuum, a pump curve measurement is performed to estimate flowrate in the system. This measurement also generates data on orifice loss coefficients, which are compared to correlations in literature. The second experiment investigates vacuum level in the LBE system during operation. High vacuum is maintained (10 -3 ~10 -5 Pa or 10 -5 ~10 -7 Torr) during system operation, and a residual gas analyzer (RGA) scan shows that partial pressures of residual gases in the LBE system lower over the duration of LBE system operations. The third experiment investigates the gravity driven liquid LBE flowing out of the target chamber in the return line, which is partially full. If the liquid LBE is not drained quickly enough, flooding in the target chamber could occur. The coefficient n in the Manning equation is found to be around 0.008 s/m 1/3 . The last experiment performed is a demonstration that a vacuum jacket could provide sufficient thermal insulation to allow coupling between 300 °C LBE loop and a water tank at room temperature. In conclusion, the results from these experiments have influenced the development of the neutron source for the future commercial scale Mo-99 production system.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Electrification FY2020 Annual Progress Report

The Electric Drive Technologies (EDT) program’s mission is to conduct early-stage research and development on transportation electrification technologies that accelerate the development of cost-effective and compact electric traction drive systems that meet or exceed performance and reliability requirements of internal combustion engine (ICE)-based vehicles, thereby enabling electrification across all light-duty vehicle types.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Diagnosing nuclear power plant pipe wall thinning due to flow accelerated corrosion using a passive, thermal non-destructive evaluation method: Feasibility assessment via numerical experiments

Flow accelerated corrosion (FAC) in nuclear power plant pipes is one of the leading causes of accidents, fatalities, damage and outages. Current FAC identification methods employ expensive sensing technology and are “active” methods, where the response of the piping system to an externally-generated thermal, mechanical or optical excitation must be measured. As a result, these techniques require a disruptive and time-consuming setup. Here we propose a method that utilizes pipe surface temperature measurements to passively monitor for FAC-induced pipe wall thinning without the need for expensive equipment or post-installation setup time. This diagnostic method utilizes a simulation data-driven diagnostic model to estimate the amount of thickness reduction in a pipe based on changes in measured steady-state pipe temperatures. In order to reduce the computational burden of generating large, simulation-based datasets, the behavior of the insulation of the pipe was modeled using a suitably calibrated heat transfer boundary parameter. Additionally, global sensitivity analysis was performed to determine system parameter(s), such as the temperature of water flowing inside the pipe, which significantly affect the steady state pipe wall temperature and could cause errors in diagnosis. Two diagnostic models, one using only the change in steady-state temperature as an indicator for FAC-induced pipe wall thinning and the other using water temperature as an additional diagnostic model input were evaluated for their ability to estimate thickness reductions in a pipe using simulated pipe wall temperature data. For the numerical experiments conducted in this work, both models estimated wall thickness with errors within 0.5 mm, indicating that the proposed technique can potentially be used as a low-cost, first-pass method for FAC monitoring.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Physics constrained learning for data-driven inverse modeling from sparse observations

Deep neural networks (DNN) have been used to model nonlinear relations between physical quantities. Those DNNs are embedded in physical systems described by partial differential equations (PDE) and trained by minimizing a loss function that measures the discrepancy between predictions and observations in some chosen norm. This loss function often includes the PDE constraints as a penalty term when only sparse observations are available. As a result, the PDE is only satisfied approximately by the solution. However, the penalty term typically slows down the convergence of the optimizer for stiff problems. We present a new approach that trains the embedded DNNs while numerically satisfying the PDE constraints. We develop an algorithm that enables differentiating both explicit and implicit numerical solvers in reverse-mode automatic differentiation. This allows the gradients of the DNNs and the PDE solvers to be computed in a unified framework. We demonstrate that our approach enjoys faster convergence and better stability in relatively stiff problems compared to the penalty method. Furthermore, our approach allows for the potential to solve and accelerate a wide range of data-driven inverse modeling, where the physical constraints are described by PDEs and need to be satisfied accurately.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Accelerating Science Impact through Big Data Workflow Management and Supercomputing

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. ATLAS, one of the largest collaborations ever assembled in the the history of science, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. To manage the workflow for all data processing on hundreds of data centers the PanDA (Production and Distributed Analysis)Workload Management System is used. An ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF), is realizing within BigPanDA and megaPanDA projects. These projects are now exploring how PanDA might be used for managing computing jobs that run on supercomputers including OLCF’s Titan and NRC-KI HPC2. The main idea is to reuse, as much as possible, existing components of the PanDA system that are already deployed on the LHC Grid for analysis of physics data. The next generation of PanDA will allow many data-intensive sciences employing a variety of computing platforms to benefit from ATLAS experience and proven tools in highly scalable processing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

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

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

42 ENGINEERING↗
DOE OSTI2012

Plasma Power Station with Quasi Spherical Direct Drive Capsule for Fusion Yield and Inverse Diode for Driver-Target Coupling

The Meier-Moir economic model for Pulsed Power Driven Inertial Fusion Energy shows at least two approaches for fusion energy at 7 to 8 cents/kw-hr: One with large yield at 0.1 Hz and presented by M. E. Cuneo at ICENES 2011 and one with smaller yield at 3 Hz presented in this paper. Both use very efficient and low cost Linear Transformer Drivers (LTDs) for the pulsed power. Here, we report the system configuration and end-to-end simulation for the latter option, which is called the Plasma Power Station (PPS), and report the first results on the two, least mature, enabling technologies: a magnetically driven Quasi Spherical Direct Drive (QSDD) capsule for the fusion yield and an Inverse Diode for coupling the driver to the target. In addition, we describe the issues and propose to address the issues with a prototype of the PPS on the Saturn accelerator and with experiments on a short pulse modification of the Z accelerator test the validity of simulations showing megajoule thermonuclear yield with DT on a modified Z.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Impacts of Federal Tax Credit Extensions on Renewable Deployment and Power Sector Emissions

Federal tax credits for renewable energy (RE) have served as one of the primary financial incentives for RE deployment over the last two decades in the United States. In December 2015, the wind power production tax credit and solar investment tax credits were extended for five years as part of the Consolidated Appropriations Act of 2016. This report explores the impact that these tax credit extensions might have on future RE capacity deployment and power sector carbon dioxide (CO2) emissions. The analysis examines the impacts of the tax credit extensions under two distinct natural gas price futures as natural gas prices have been key factors in influencing the economic competitiveness of new RE development. The analysis finds that, in both natural gas price futures, RE tax credit extensions can spur RE capacity investments at least through the early 2020s and can help lower emissions from the U.S. electricity system. More specifically, the RE tax credit extensions are estimated to drive a net peak increase of 48-53 GW in installed RE capacity in the early 2020s -- longer term impacts are less certain. In the longer term after the tax credits ramp down, greater RE capacity is driven by a combination of assumed RE cost declines, rising fossil fuel prices, and other clean energy policies such as the Clean Power Plan. The tax credit extension-driven acceleration in RE capacity development can reduce fossil fuel-based generation and lower electric sector CO2 emissions. Cumulative emissions reductions over a 15-year period (spanning 2016-2030) as a result of the tax credit extensions are estimated to range from 540 to 1420 million metric tonnes CO2. These findings suggest that tax credit extensions can have a measurable impact on future RE deployment and electric sector CO2 emissions under a range of natural gas price futures.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

MO-G-201-04: Knowledge-Based Planning for Single-Isocenter Stereotactic Radiosurgery to Multiple Brain Metastases

Purpose: Single-isocenter, linac-based SRS for multiple brain metastases (multi-mets) can deliver highly conformal radiation doses and reduce overall patient treatment time compared to other therapy techniques. This study aims to quantify the dosimetric benefits of knowledge-based planning (KBP) for multi-met treatments. Methods: Using a previously-published KBP methodology (an artificial neural network (ANN) trained on single-target linac-based SRS plans), 3D dose distribution predictions for multi-met patients were obtained by treating each brain lesion as a solitary target and subsequently combining individual predictions into a single distribution using a dose-weighted geometric averaging to obtain the best results in the inter-target space. 17 previously-treated multi-met plans, with target numbers ranging from N=2–5, were used to validate the ANN predictions and subsequent KBP auto-planning routine. The fully-deliverable KBP plans were developed by converting dose distribution predictions into patient-specific optimization objectives while maintaining identical target normalizations (typically PTV V100%=D98%). Plan quality improvements were quantified by the difference between SRS quality metrics (QMs): δdQM=QM(clinical)-QM(KBP). QMs of interest were: gradient measure (GM), conformity index (CI), brain V10 and V5, brainstem D0.1cc and heterogeneity index (HI). Finally, overall plan quality was judged via blinded plan comparison by SRS-specializing physicians. Results: Two clinical plans were found to be significant outliers wherein plan quality was dramatically worse than KBP. Despite indicating KBP superiority, these were removed from the QM analysis to prevent skewing the results. In the remaining cases, clinical and KBP QMs were nearly identical with modest improvements in the KBP sample: δGM=0.12±0.56mm, δCI=−0.01±0.04, Brain δV10=0.8±2.6cc, brain δV5=6.3 ±10.7cc, brainstem δD0.1cc=0.06±1.19Gy and δHI= −0.04±0.05. Ultimately, 13/17 KBP plans were deemed superior to the manual plans in blinded physician review. Conclusion: The results demonstrate that KBP-driven automated planning in linac-based single-isocenter treatments for multiple brain metastases is indistinguishable from, or even better than, traditional manual planning. J. Hattangadi: Research Grant; Varian Medical Systems; K.L. Moore: Research Grant: Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Analysis of RF high power sources for 1MW – range, 10 MeV CW industrial accelerator.

Cobalt-60 is the dominant source of ionizing radiation for sterilizing products in the $200B/year medical device industry. Security and accessibility concerns around this radioactive material - sourced from countries including Russia and China - present national security and economic risks. There is a continued national urgency to replace such high-risk sources with low-risk alternatives such as electron or x-ray beams driven by accelerators. While e-beam sources have been in use for many years, they still represent a small portion of the market. X-ray sources are becoming economical alternatives. Meeting the processing capacity required to replace Co-60 requires a step-change in the capability, efficiency, and overall operating cost of electron accelerators to make adoption feasible. The radiofrequency (RF) power that drives accelerating cavities represents significant capital and operating costs for these accelerators. For accelerator-based systems to be a viable alternative for these applications, RF systems must be economical to manufacture, deploy, and operate.

43 PARTICLE ACCELERATORS↗
NASA NTRS2023

Changing Characteristics of Tropical Extreme Precipitation-Cloud Regimes in Warmer Climates

In this paper, we have investigated the changing characteristics of climatic scale (monthly) tropical extreme precipitation in warming climates using the Energy Exascale Earth System Model (E3SM). Results are from Atmospheric Model Intercomparison Project (AMIP)-type simulations driven by a) control experiment with present-day sea surface temperature (SST) and CO 2 concentration, b) P4K, same as in a) but with uniform increase by 4K in SST globally, and c) same as in a), but with imposed SST and CO 2 concentration from outputs of coupled E3SM forced by 4xCO 2 concentration. We find that as the surface warms under P4K and 4xCO 2 , both convective and stratiform rain increase. Importantly, there is increasing fractional contribution of stratiform rain as a function of precipitation intensity, with the most extreme but rare events occurring preferentially over land more than ocean, more so under 4xCO 2 than P4K. Extreme precipitation is facilitated by increased precipitation efficiency, reflecting accelerated rates of recycling of precipitation-cloud water (both liquid and ice phases) in regions with colder anvil cloud tops. Changes in vertical profiles of clouds, condensation heating and vertical motions indicate increasing precipitation-cloud-circulation organization from control, P4K to 4xCO 2 . Results suggest that large-scale ocean warming, i.e., P4K, is the primary cause contributing to organization structure resembling the well-known Mesoscale Convective System (MCS) for increased extreme precipitation on shorter (hourly to daily) time scales. Additional 4xCO 2 atmospheric radiative heating, and dynamically consistent anomalous SST further amplifies the MCS organization under P4K. Analyses of the surface moist static energy distribution show that increase in surface moisture (temperature) under P4K and 4xCO 2 is the key driver leading to enhanced convective instability over tropical ocean (land). However, the fast and large increase in land surface temperature and lack of available local moisture result in strong reduction in land surface relative humidity, reflecting severe drying and enhanced convective inhibition (CIN). It is argued that very extreme and rare “record-breaking” precipitation events found over land under P4K, more so under 4xCO 2 , are likely due to the delayed onset of deep convection, i.e., the longer the suppression of deep convection by CIN, the more severe the extreme precipitation when eventually occur, due to the release of large amount of stored surplus convective available potential energy in the lower troposphere during prolonged CIN.

climate-scale extreme tropical precipitation↗
DOE OSTI2024

Self-driving laboratories to autonomously navigate the protein fitness landscape

Abstract Protein engineering has nearly limitless applications across chemistry, energy and medicine, but creating new proteins with improved or novel functions remains slow, labor-intensive and inefficient. Here we present the Self-driving Autonomous Machines for Protein Landscape Exploration (SAMPLE) platform for fully autonomous protein engineering. SAMPLE is driven by an intelligent agent that learns protein sequence–function relationships, designs new proteins and sends designs to a fully automated robotic system that experimentally tests the designed proteins and provides feedback to improve the agent’s understanding of the system. We deploy four SAMPLE agents with the goal of engineering glycoside hydrolase enzymes with enhanced thermal tolerance. Despite showing individual differences in their search behavior, all four agents quickly converge on thermostable enzymes. Self-driving laboratories automate and accelerate the scientific discovery process and hold great potential for the fields of protein engineering and synthetic biology.

Rapp, Jacob T. (ORCID:0000000226835204)↗
NASA NTRS2016

Design and Performance of the NASA SCEPTOR Distributed Electric Propulsion Flight Demonstrator

Distributed Electric Propulsion (DEP) technology uses multiple propulsors driven by electric motors distributed about the airframe to yield beneficial aerodynamic-propulsion interaction. The NASA SCEPTOR flight demonstration project will retrofit an existing internal combustion engine-powered light aircraft with two types of DEP: small "high-lift" propellers distributed along the leading edge of the wing which accelerate the flow over the wing at low speeds, and larger cruise propellers co-located with each wingtip for primary propulsive power. The updated high-lift system enables a 2.5x reduction in wing area as compared to the original aircraft, reducing drag at cruise and shifting the velocity for maximum lift-to-drag ratio to a higher speed, while maintaining low-speed performance. The wingtip-mounted cruise propellers interact with the wingtip vortex, enabling a further efficiency increase that can reduce propulsive power by 10%. A tradespace exploration approach is developed that enables rapid identification of salient trades, and subsequent creation of SCEPTOR demonstrator geometries. These candidates were scrutinized by subject matter experts to identify design preferences that were not modeled during configuration exploration. This exploration and design approach is used to create an aircraft that consumes an estimated 4.8x less energy at the selected cruise point when compared to the original aircraft.

Borer, Nicholas K.↗
DOE OSTI2021

Evaluation of Topology Optimization to Achieve Energy Savings at the Urban District Level: Preprint

Advanced district thermal energy systems have the potential to achieve significant energy savings and facilitate the integration of renewable thermal resources and waste heat, contributing to reductions in carbon emissions. Such systems, also known as fifth generation district heating and cooling (5GDHC) systems, circulate water at temperatures close to ambient, and leverage electrically-driven water-source heat pumps located at connected buildings to further temper the water. However, barriers exist to the adoption of 5GDHC systems, including the factorial growth in potential network configurations as a function of the number of considered buildings. Topology optimization, which seeks to answer the questions, “Which is the best subset of buildings, if any, to connect to a district thermal energy system, and by what network should they be connected, to minimize life cycle cost?” can accelerate the adoption of 5GDHC systems. This study is part of an effort to develop a topology optimization framework for district thermal energy systems. In this study, a heuristic for one aspect of the topology optimization problem---the use of the minimal spanning tree network to connect a given set of buildings at the least life cycle cost---is validated.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2021

Pressure Response Optimization of an Eddy Current-Driven Flyer Plate Valve for the ITER Shattered Pellet Injection System

One technique for mitigating disruptions in a tokamak is shattered pellet injection (SPI). SPI is a process in which a large solid pellet consisting of deuterium, neon, or argon is desublimated in a pipe gun barsrel and launched downstream. Pellets are shattered just before entering the plasma by an impact with an angled tube. Injection of these materials into the plasma radiates stored thermal energy, limits current decay rates, suppresses the generation of runaway electrons, and dissipates runaway electrons if necessary. A critical element of the SPI system is a fast-acting valve that releases high-pressure gas to dislodge and accelerate pellets directly, or indirectly via a mechanical punch. A prototype valve sized for the ITER SPI system has been designed and fabricated. A pulsed high-voltage power supply energizes the valve’s internal magnetic coil, which induces eddy currents in the adjacent flyer plate resulting in a repulsive force between the flyer plate and the coil. The flyer plate action lifts a valve seat, allowing high-pressure gas to flow from the valve plenum to the downstream (breech) location of the pellet or mechanical punch. All of the valve’s internal components are designed to operate in ITER-level static background magnetic fields. Here, a study was conducted to optimize the downstream pressure response for a range of valve sizes and operating pressures. In particular, the study analyzes the breech pressure response associated with varying plenum pressures as well as varying breech volumes. A computational fluid dynamics simulation was built in STAR-CCM+ and validated against data from laboratory experiments. The resulting simulation outputs, in the form of downstream responses for a variety of initial plenum pressures and breech volumes, will be used as a complement to experimental data to ensure the pressure pulse is suitable for pellet survivability. These data, combined with studies on pellet shear strength and shock response, will be applied to optimization of overall operating parameters of the ITER SPI system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Operational stability of mixed Sn–Pb perovskite solar cells: Mechanisms, mitigation strategies, and perspectives

Mixed Sn–Pb perovskites provide the 1.2–1.3 eV narrow-bandgap absorber needed for high efficiency of all perovskite tandems, but their deployment is limited by operational instability under light. This review synthesizes mechanistic origins and recent mitigation strategies for mixed Sn–Pb perovskite solar cells. The oxidation of Sn 2+ to Sn 4+ , often driven by iodine formation under light and bias, is the primary failure pathway; it creates Sn vacancies, self-doping, and nonradiative loss. Surface/grain-boundary defects, halide migration, reactive oxygen species, and interfacial redox at charge-transport layers, along with hole accumulation from poor band alignment, further accelerate Sn–Pb perovskite degradation. Here we survey recent stability advances across additive chemistry, surface and grain-boundary passivation, buried-interface redesign with modified or alternative hole transport layers, and solvent systems that preserve Sn 2+ and correct Sn–Pb speciation for scalable coating. Together, these recent advances have enabled devices to retain 80%–90% output for hundreds to over a thousand hours. Lastly, we provide our perspectives on further improving the operational stability of Sn–Pb perovskite and solar cells.

14 SOLAR ENERGY↗