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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 595 records · Page 33

Impact of FERC Order 2222 on DER Participation Rules in US Electricity Markets

Electricity markets in the bulk grid are beginning to implement market mechanisms that support the procurement of flexible capabilities from wide range of technologies, including distributed energy resources (DERs). The flexibility of these resources will help counterbalance supply uncertainties from large-scale integration of variable renewable generation. To encourage development of distributed and aggregated market participants, FERC Order 2222 was issued in September 2020 to require each Independent System Operator (ISO) in the US to implement rules that enable broader participation from aggregations of DERs in the bulk market. The following paper first describes the generic design of ISO markets before introducing the new market participation rules that ISOs have proposed for compliance with Order 2222. The paper then describes how software performance issues may continue to affect the eligibility requirements and offer structures for DER aggregations participating in ISOs, noting that continued research on computational methods may help reduce burdens for DER integration. The prospects for transmission and distribution system coordination is second major issue discussed, which will require minor changes to existing processes in the short term. In the longer term, there is more opportunity for more wide-ranging reforms, such as the development of a Distribution System Operator (DSO) framework. Newly proposed market rules may affect how Transactive Energy Systems (TES) will help facilitate efficient formation of DER aggregations and operation of the individual DERs within an aggregation. Within the TES context, the challenge is to fully understand how resource eligibility and operational and planning coordination methods will affect the design and implementation of TES.

24 POWER TRANSMISSION AND DISTRIBUTION↗

High Performance Metal-Supported SOFC System for Range Extension of Commercial Aviation

The DOE ARPA-E REEACH program [1] has enabled this Phase 1 study that conceptualizes a commercial 154 passenger electric aircraft using renewable aviation fuel for range extension while meeting similar mission performance levels as current commercial aircraft. Commercial aviation accounts for about 2.5% of global CO2 emissions, and close to 5% of overall anthropogenic climate change due to the added accounting of contrail’s effects [2]. The sector has adopted a goal of carbon neutrality by 2050 [3]. 110 nations, and recently the new US administration, have embarked on work to address this important challenge. The US DOE has released a roadmap to enable the further development of sustainable aviation fuel (SAF) in the hopes that it could meet all of aviation’s fuel needs by 2050 [4]. However, SAF fuel price and sufficient future feedstock availability remains a concern [5]. Considering the first commercial biofuel flight demonstration 14 years ago [6] and that SAF still only comprises less than 0.1% of jet fuel use, the question arises as how it can ramp up to 100% use in the next 27 years. One option that has the potential to substantially reduce the need for SAF is to implement light-weight Solid Oxide Fuel Cells (SOFCs) that can efficiently utilize SAF or other sulfur-free hydrocarbon fuels. As opposed to lower temperature PEM (Proton Exchange Membrane) fuel cells that can use high-purity hydrogen, SOFC’s fuels are very flexible, ranging from low cost liquefied natural gas (LNG), renewable liquefied natural gas (RLNG), to SAF, to generate clean electrical power for use in aviation propulsion and auxiliary power units [7] [8]. Research progress is needed to enable SOFCs to achieve 3.0 kW/kg power density, making them viable for aviation [9]. The DOE’s Advanced Research Projects Agency – Energy (ARPA-E) has therefore initiated an aviation SOFC R&D program that is anticipated to dramatically reduce aircraft fuel use though the implementation of “Range Extenders for Electric Aviation with low Carbon and High efficiency” (REEACH) [1] for medium range commercial aircraft. This report summarizes the progress during phase 1 of the REEACH program.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An Evolutionary Algorithm to Personalize Stool-Based Colorectal Cancer Screening

Fecal immunochemical testing (FIT) is an established method for colorectal cancer (CRC) screening. Measured FIT-concentrations are associated with both present and future risk of CRC, and may be used for personalized screening. However, evaluation of personalized screening is computationally challenging. In this study, a broadly applicable algorithm is presented to efficiently optimize personalized screening policies that prescribe screening intervals and FIT-cutoffs, based on age and FIT-history. We present a mathematical framework for personalized screening policies and a bi-objective evolutionary algorithm that identifies policies with minimal costs and maximal health benefits. The algorithm is combined with an established microsimulation model (MISCAN-Colon), to accurately estimate the costs and benefits of generated policies, without restrictive Markov assumptions. The performance of the algorithm is demonstrated in three experiments. In Experiment 1, a relatively small benchmark problem, the optimal policies were known. The algorithm approached the maximum feasible benefits with a relative difference of 0.007%. Experiment 2 optimized both intervals and cutoffs, Experiment 3 optimized cutoffs only. Optimal policies in both experiments are unknown. Compared to policies recently evaluated for the USPSTF, personalized screening increased health benefits up to 14 and 4.3%, for Experiments 2 and 3, respectively, without adding costs. Generated policies have several features concordant with current screening recommendations. The method presented in this paper is flexible and capable of optimizing personalized screening policies evaluated with computationally-intensive but established simulation models. It can be used to inform screening policies for CRC or other diseases. For CRC, more debate is needed on what features a policy needs to exhibit to make it suitable for implementation in practice.

60 APPLIED LIFE SCIENCES↗

Findings of the African Combustion Aerosol Collaborative Intercomparison Analysis (ACACIA) Pilot Project to Understand the Optical Properties of Biomass Burning Smoke

Africa is a critical source of biomass burning (BB) aerosols, and its importance is increasing. The African Combustion Aerosol Collaborative Intercomparison Analysis (ACACIA) Pilot Project set to optically characterize BB aerosol generated from sub-Saharan African fuels. We used a photoacoustic spectrometer as a reference instrument to determine the multiple-scattering correction factor C λ for an AE33 aethalometer at three wavelengths, which produced weighted mean values of C 370 =3.69, C 470 =5.65, and C 520 =6.39. C λ increased with wavelength and C 370 was statistically independent of the others, suggesting a single C λ is insufficient, especially in BB scenarios. While a dependence of C λ on burning state was not found, C λ was shown to strongly relate to particle single scattering albedo (SSA, ω). When Cλ was plotted against SSA, values slowly rose at low SSA values, followed by a sharp rise around an SSA of ∼ 0.9; indicating a larger correction needed for less absorbing aerosol. A number of functions operating on either SSA or C λ were explored and the best function was -C λ /(1-C λ )=Aω+B. This is an important parametrization of C λ specifically geared towards BB aerosol from African fuels under different aging states, and is of particular importance for future field work in that continent. An Ångström matrix plot shows that African BB aerosol can have values more akin to dust, which demonstrates that these fuels are distinct in their wavelength dependence from more typical BB aerosol. Lastly, we examined the mass extinction and absorbance cross sections for BB aerosol generated for the same fuels with two different tube furnace setups. Not only is this combustion method flexible, it was found to be reproducible between labs.

47 OTHER INSTRUMENTATION↗

An Organic, Direct Bonded Copper, Multi-Layered, Ultra-Low Inductance Package for High-Power UWBG MOSFETs

The most common metalized substrates used in high-power switching packages consist of a ceramic layer such as Aluminum Nitride (AlN) sandwiched between two copper layers. Ceramic substrates are used because it has the key characteristic of having high dielectric strength while being thermally conductive. A large drawback to ceramic substrates is that they do not allow for a multi-layered circuit design. By replacing the traditional ceramic substrate with organic direct bonded copper (ODBC) we can open a wide range of possibilities when it comes to power module layout such as multi-layered circuits and double-sided cooling. Both benefits are critical while packaging high-performance Gallium Oxide (Ga2O3) MOSFETs. Because of Ga2O3's relatively poor thermal conductivity, a double-sided cooled package becomes necessary. Therefore, the use of ODBC provides the flexibility to fabricate copper traces carrying much higher currents, and by creating a multi-layered package, we can drastically reduce the parasitic inductance inside the power module. Achieving lower parasitic inductance is critical for an ultra-fast Ga2O3 package to avoid excessive voltage overshoot and ringing. Using ODBC, we have designed novel packages capable of handling the challenges presented by fast Ga2O3 switching. Using multi-physics modeling software, we can validate our design before building the prototype. Due to the simple process parameters needed to work with ODBC, we can rapidly create prototypes without using external vendors. This flexibility allows us to quickly design, build, and validate highly complex switching power modules to accommodate next generation, Ga2O3 switching devices.

ADVANCED PROPULSION SYSTEMS,ENGINEERING↗

Adaptive Stiffness Power Take-Off System for a Hydraulic Hose-Pump Point Absorber Wave Energy Converter

Two crucial challenges faced in the design of ocean wave energy converters (WECs) are maintaining high capacity factors and remaining robust in everchanging, harsh ocean environments. This study introduces a novel mechanism for achieving reactive WEC control with a soft hydraulic power take-off, thereby addressing both challenges. The device of interest involves a hydraulic pump, constructed from a fluidic flexible matrix composite (F2MC), which is cyclically stretched by driving waves and pressurizes working fluid through a turbine-generator. This class of fiber-reinforced stretch hoses is established for ocean use as robust moorings and shock absorbers. The dynamic properties of the F2MC pump depend on internal pressure, which can be controlled by a continuously variable transmission between the turbine and generator, allowing the system to be adapted for better performance over a wide range of wave conditions. This work presents a dynamic model for operation and adaptive behavior of this power take-off system, experimentally validates components of the model, and performs dynamic simulations of the system that show increases in power production and capacity factor compared to non-adaptive operation for a variety of driving wave conditions. This work develops the basis for future large-scale experimental testing and controller design of this system.

Wave energy conversion, fluidic flexible matrix co↗

Cyote-attack Chain Estimator

Attack Chain Estimator (ACE) Application Overview The Attack Chain Estimator (ACE) Application is a sophisticated tool designed for the ingestion, classification, sequencing, and enrichment of cybersecurity threat reports. This application leverages advanced machine learning models and extensive historical data to provide comprehensive insights into cyber threats, specifically targeting Industrial Control Systems (ICS). Purpose The primary functions of the ACE Application include: Ingestion of Cybersecurity Threat Reporting: Capable of ingesting text-based threat reports in markdown or text file format. Supports ingestion of structured data from other sources in STIX/JSON format. Classification of Report’s Text-Based Events: Utilizes a DeBERTa classifier, specifically trained on cybersecurity data, to map the events to MITRE ATT&CK for ICS Tactics and Techniques. Classification is performed using multiple Jupyter notebooks and machine learning workflows hosted as FastAPI microservices: regex_data deberta_base_35_train_hft_classifier_mlflow.ipynb hft_regex_classifier_mlflow.ipynb param_train_hft_classifier_mlflow.ipynb regex_tactic_tech.ipynb Ordering of Tactics, Techniques, and Observable Events: Sequences the identified tactics, techniques, and events to form a coherent attack chain. Enrichment with Historical Attack Chain Details: Enhances the attack chain with details from historical attacks using a Markov model developed from CyOTE Precursor Analysis Report data. The Markov model is available as a FastAPI endpoint for seamless integration. Enrichment with Adversary Emulation Capabilities Data: Integrates adversary emulation capabilities data using MITRE Caldera for OT adversary abilities UUIDs. Export of Output Files: Provides options to export the enriched attack chain in JSON or CSV formats. Routing of Output to Other Applications: Facilitates routing of output to various platforms and applications, including: Threat Intelligence Platforms COREII Scout for Threat Intelligence Analysis COREII Modeling and Simulation for Adversary Emulation Technical Description The ACE Application is an advanced cybersecurity tool designed to provide detailed threat analysis and sequence generation. It is built on a robust architecture that integrates natural language processing, machine learning, and historical data modeling. Key Components: Data Ingestion Module: Handles the input of threat reports and data from various formats, ensuring flexibility in data sources. Classification Engine: Employs DeBERTa-based classifiers hosted as FastAPI microservices to analyze and classify threat report events in accordance with the MITRE ATT&CK framework for ICS. Sequence Generator: Orders the classified events into a logical attack chain, providing clear insight into the sequence of tactics and techniques used in the threat. Enrichment Engine: Integrates historical data and adversary emulation capabilities to enhance the attack chain with valuable context and additional details. The historical data enrichment is powered by a Markov model, which is available as a FastAPI endpoint. Export and Routing Module: Facilitates the export of the enriched attack chain in multiple formats and routes the output to designated applications for further analysis or emulation.

Paul, Tony [Idaho National Laboratory (INL), Idaho↗

Cradle to grave: the importance of the fuel cycle to molten salt reactor sustainability

Advanced reactor technologies are being considered for the next-generation of nuclear power plants. These plants are designed to have a smaller footprint, run more efficiently at higher temperatures, have the flexibility to meet specific power or heating needs, and have lower construction costs. This paper offers a perspective on molten salt reactors, promoted as having a flexible fuel cycle and close-to-ambient pressure operation. A complexity introduced by reducing the reactor footprint is that it may require low-enriched fuel for efficient operation, available from enrichment of the feed salt or by reusing actinides from existing used nuclear fuel (UNF). Recycling UNF has the potential to reduce high-level waste, if done correctly. Release limits from UNF processing are stringent, and processes for waste reduction, fission gas trapping, and stable waste-form generation are not yet ready for commercial deployment. These complex processes are expensive to develop and troubleshoot because the feed is highly radioactive. Thus, fuel production and supply chain development must keep abreast of reactor technology development. Another aspect of reactor sustainability is the non-fuel waste streams that will be generated during operation and decommissioning. Some molten salt reactor designs are projected to have much shorter operational lifetimes than light-water reactors: less than a decade. A goal of the reactor sustainability effort is to divert these materials from a high-level waste repository. However, processing of reactor components should only be undertaken if it reduces waste. Economic and environmental aspects of sustainability are also important, but are not included in this perspective.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Flexible Soft X-Ray Image Sensors based on Metal Halide Perovskites With High Quantum Efficiency

Soft X-ray imaging is a powerful tool to explore the structure of cells, probe material with nanometer resolution, and investigate the energetic phenomena in the universe. Conventional soft X-ray image sensors are by and large Si-based charge coupled devices that suffer from low frame rates, complex fabrication processes, mechanical inflexibility, and required cooling below -60 °C. Here, a soft X-ray photodiode is reported based on low-cost metal halide perovskite with comparable performance to commercial Si-based device. Nanothrough network electrode minimized the optical loss due to the shadowing of insensitive layers, while a multidimensional perovskite heterojunction is generated to reduce the photo-generated carrier loss. Further, this strategy promoted a record quantum efficiency of 8 × 10 3 % without cooling, several orders of magnitude greater than the previously achieved. Flexible and curved soft X-ray imaging arrays are fabricated based on this high-performance device structure, demonstrating stable soft X-ray response and sharp imaging capabilities. This work highlights the low-cost and efficient perovskite photodiode as a strong candidate for the next-generation soft X-ray image sensors.

36 MATERIALS SCIENCE↗

Technical Performance of Refractory Liners for Molten Chloride Salt Thermal Energy Storage Systems

A chloride-based molten-salt system that uses a ternary blend of MgCl2/KCl/NaCl is investigated to provide higher temperature thermal energy storage capability. Despite higher thermal stability, molten chlorides present several unique challenges, including the design of internal refractory-ceramic liners to prevent the corrosion and thermal stress of alloy tank shells. This work discusses issues and potential solutions related to containment of molten chloride salt, specifically the optimization of the refractory material at the molten salt interface (hot face). The down-selected hot face candidate limits permeation of salt through the material and forms a highly stable secondary surface phase in equilibrium with the molten salt. A mortar is created using the corrosion resistant hot face brick. Brick and mortar composite are subjected to mechanical stress/strain analysis, in order to calculate composite material properties and better inform thermomechanical models. The U.S. Department of Energy Generation 3 (DOE Gen3) program seeks to develop higher efficiency CSP plants that can provide cost-competitive, flexible power in the U.S. electric grid. The proposed Gen3 Liquid Pathway CSP plant closely resembles the configuration of current nitrate salt power towers with two-tank storage (Gen2). The differences between Gen2 and Gen3 include the types of compatible materials used in salt storage tank construction. Stainless steel loses strength at Gen3 temperatures, and although nickel superalloys would be capable of withstanding sustained high temperatures, these materials are prohibitively expensive at scale. Uninsulated tank shells also pose a significant risk as common steels are highly susceptible to chemical attack from molten chloride salt. To address these concerns, refractory-ceramic based containment materials are proposed to line the inside of the hot and cold storage tanks. In doing so, stainless or carbon steel shells may be used in construction depending on the level of insulation provided. The composition of the internal liner requires careful consideration to maximize the efficacy of multiple parameters including corrosion resistance, strength at operating temperature, durability, and cost. This is particularly true for the material at the interface with the salt, known as the "hot face", which is responsible for protecting the insulating layers between the tank shell and the hot face brick layer. The molten salt in this system is superheated over 300 °C above its freeze temperature. Therefore, unlike other industrial processes which use refractory-lined vessels, it is not expected that a freeze plane will develop in the hot face. Therefore, the hot face must be designed to withstand chemical corrosion and inhibit permeation of molten salt into the insulating layers. A down selection was performed to identify a hot face candidate best equipped to maintain thermal, mechanical, and chemical integrity when exposed to molten salt over extended periods of time. Long-duration chemical capability experiments were conducted with the down selected hot face refractory fully immersed in molten chloride salt for up to 3000 hours. The average salt penetration does not exceed 100 microns. When extrapolated to 20 and 30 years of continuous exposure, the expected salt penetration depth is approximately 2.0 mm and 2.9 mm, respectively. A magnesium-rich secondary phases develops at the salt/refractory interface. X-ray diffraction identifies the material as forsterite (Mg2SiO4), which is reported to form synthetically in molten chloride salt solutions. These results suggest the selected hot face will adequately inhibit salt permeation. While there is optimism that the hot face brick will inhibit salt permeation, mortar joints are typically the weakest point of a refractory brick liner. From a thermochemical perspective, differing thermal expansion coefficients may result in the mortar and brick to grow independent of each other, creating gaps through which molten salt can penetrate. To address this issue, NREL has developed an in-house mortar composed of the down selected hot face brick that has been shown to be compatible with the salt. Compressive stress/strain analyses have been performed on the brick/ mortar composites to generate stress/strain curves. Modulus of elasticity and Poisson's ratio of the composite may be calculated from the stress/strain curves, in order to provide more representative data to finite element mechanical models for accurate approximation of stress on the tank shell and the amount of thermal expansion expected within the tank liner.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Complementary relationship between small-hydropower and increasing penetration of solar photovoltaics: Evidence from CAISO

To achieve the 100% green electricity goal, we need to understand the relationship between resources in the market and identify the flexible clean resources (i.e., hydropower) to integrate power from wind and photovoltaic (PV). This paper reveals a complementary relationship between small hydropower plants and solar PVs in the California Independent System Operator (CAISO) based on the system-wide hourly generation data from 2013 to 2017. When the solar PV increases its portion in the generation mix by 1%, small hydro will increase its portion by 0.01–0.06%. Such response is obvious in the net demand peak hours, both morning and evening. The low operation cost, flexibility, and dispatchability of small hydro in CAISO explain this complementarity. Due to its benefit in emission and low Levelized Cost of Electricity (LCOE), it is suggested to consider more small hydro projects to accommodate additional PV capacity for the 100% green electricity goal. Our estimation indicates that the current feasible potential of small hydro is sufficient, if the relation stays the same over years. If developers can mitigate the environmental impact, more technical potential will become feasible. Thus, small hydro could integrate more solar PV and reduce the demand for natural gas plants and batteries.

13 HYDRO ENERGY↗

Tri-level hybrid interval-stochastic optimal scheduling for flexible residential loads under GAN-assisted multiple uncertainties

Various building loads, such as heating, ventilation, and air conditioners (HVACs), electric water heaters (EWHs), and electric vehicles (EVs), can introduce opportunities for improving the flexibility of electricity consumption while satisfying the needs of building owners as well as benefiting the resilience of distribution system. To utilize such flexibility, a tri-level distribution market framework is established, including residential consumers, load aggregators (LAs), and the distribution system operator (DSO). In this work, the uncertainties from all three levels are considered. The random consumption behavior at the consumer level is modeled as a Gaussian noise that is also aggregated and transmitted to the LA level. The weather temperature in the LA level is forecasted as an interval, and the photovoltaic (PV) power in the market-clearing level is modeled by a set of power scenarios generated by Generative Adversarial Networks (GANs). Then, a hybrid interval-stochastic programming is proposed to transform the uncertain problems in the first two levels into deterministic ones. For real-time implementations, a rolling horizon optimization (RHO) scheme is employed to continuously optimize the power consumption based on the latest operating information. Finally, case studies on a modified IEEE 69-bus system validate the effectiveness of the proposed uncertainty modeling strategies and the RHO scheme.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Information-entropy-driven generation of material-agnostic datasets for machine-learning interatomic potentials

In contrast to their empirical counterparts, machine-learning interatomic potentials (MLIAPs) promise to deliver near-quantum accuracy over broad regions of configuration space. However, due to their generic functional forms and extreme flexibility, they can catastrophically fail to capture the properties of novel, out-of-sample configurations, making the quality of the training set a determining factor, especially when investigating materials under extreme conditions. We propose a novel automated dataset generation method based on the maximization of the information entropy of the feature distribution, aiming at an extremely broad coverage of the configuration space in a way that is agnostic to the properties of specific target materials. The ability of the dataset to capture unique material properties is demonstrated on a range of unary materials, including elements with the FCC (Al), BCC (W), HCP (Be, Re and Os), graphite (C), and trigonal (Sb, Te) ground states. MLIAPs trained to this dataset are shown to be accurate over a range of application-relevant metrics, as well as extremely robust over very broad swaths of configurations space, even without dataset fine-tuning or hyper-parameter optimization, making the approach extremely attractive to rapidly and autonomously develop general-purpose MLIAPs suitable for simulations in extreme conditions.

36 MATERIALS SCIENCE↗

Co-optimization of nuclear reactor flexible power operation and maintenance scheduling

As flexible power operation of nuclear power plants becomes more attractive due to the reduction in fossil-fueled dispatchable generation on energy grids, finding optimal power production strategies that balance revenue generation with operational concerns becomes more complex. This article presents a general framework to aid operators in designing economically optimal long term dispatch strategies for nuclear power plants. The principal novelty is the linking of estimated system remaining useable life (RUL) to strategic operational decisions. It is shown that, depending on the relationship between the fixed costs from maintenance and the associated lost revenue from an outage, it can be economically optimal in the long term to delay a maintenance outage and not perform this alongside refueling. For a given relationship between power ramping and degradation, optimal strategies were found that discouraged load following in some situations while minimizing unnecessary maintenance. It is shown that heavy load following can cause maintenance and refueling outages to diverge due to their inverse relationships with respect to load following, potentially leading to a significant loss in capacity factor. As a result, this general framework can be applied to specific reactor dispatch allowing operators to adapt operational strategies as future grid conditions change.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations

We propose InSituNet, a deep learning based surrogate model to support parameter space exploration for ensemble simulations that are visualized in situ. In situ visualization, generating visualizations at simulation time, is becoming prevalent in handling large-scale simulations because of the I/O and storage constraints. However, in situ visualization approaches limit the flexibility of post-hoc exploration because the raw simulation data are no longer available. Although multiple image-based approaches have been proposed to mitigate this limitation, those approaches lack the ability to explore the simulation parameters. Our approach allows flexible exploration of parameter space for large-scale ensemble simulations by taking advantage of the recent advances in deep learning. Specifically, we design InSituNet as a convolutional regression model to learn the mapping from the simulation and visualization parameters to the visualization results. With the trained model, users can generate new images for different simulation parameters under various visualization settings, which enables in-depth analysis of the underlying ensemble simulations. We demonstrate the effectiveness of InSituNet in combustion, cosmology, and ocean simulations through quantitative and qualitative evaluations.

deep learning↗

Structures of respiratory syncytial virus G bound to broadly reactive antibodies provide insights into vaccine design

Abstract Respiratory syncytial virus (RSV) is a leading cause of severe lower respiratory tract disease in infants and older adults. The attachment glycoprotein (RSV G) binds to the chemokine receptor CX3CR1 to promote viral entry and modulate host immunity. Antibodies against RSV G are a known correlate of protection. Previously, several broadly reactive, high-affinity anti-RSV G human monoclonal antibodies were isolated from RSV-exposed individuals and were shown to be protective in vitro and in vivo. Here, we determined the structures of three of these antibodies in complex with RSV G and defined distinct conformational epitopes comprised of highly conserved RSV G residues. Binding competition and structural studies demonstrated that this highly conserved region displays two non-overlapping antigenic sites. Analyses of anti-RSV G antibody sequences reveal that antigenic site flexibility may promote the elicitation of diverse antibody germlines. Together, these findings provide a foundation for next-generation RSV prophylactics, and they expand concepts in vaccine design for the elicitation of germline lineage-diverse, broadly reactive, high-affinity antibodies.

Science & Technology - Other Topics↗

Progress with applications of three-ion ICRF scenarios for fusion research: A review

The viability of magnetic confinement fusion as an energy source depends on achieving the high ion temperatures required for D-T fusion. Among the available techniques, plasma heating with waves in the ion cyclotron range of frequencies (ICRF) is a prominent method for bulk ion heating in fusion plasmas. Furthermore, a detailed understanding of the non-linear physics of alpha heating and the complex impact of MeV-range fast ions on plasma dynamics becomes progressively more important. This paper provides a comprehensive overview of recent developments with the three-ion ICRF scenarios on Alcator C-Mod, ASDEX Upgrade and JET tokamaks. The results demonstrate the flexibility of these novel scenarios for heating bulk ions in D-T ≈ 50%-50% plasmas and efficient generation of MeV-range fast ions in multi-ion species plasmas. In conclusion, several key results relevant for ITER and future fusion reactors are highlighted.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗