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DOE OSTI2021

Roles of Mn and Co in Ni-rich layered oxide cathodes synthesized utilizing a Taylor Vortex Reactor

It is reported that layered oxides, composed of nickel, manganese, and cobalt (NMC), are sought after as cathode materials which provide improved energy density, cycle life, and safety in commercial lithium ion batteries (LIBs). Increasing Ni contents higher than 80% can provide even higher practical discharge capacities >200 mAh/g and similar to ~4 V discharge potential vs Li/Li + , making them promising cathodes for next generation LIBs. However, rapid capacity fade during cycling and heat-related safety concerns are delaying their successful transition to industry. We report systematic performance optimization of LiNiO 2 , LiNi 0.9 Mn 0.1 O 2 , and LiNi 0.9 Co 0.1 O 2 high Ni layered oxide cathodes synthesized by utilizing a Taylor Vortex Reactor. Co-free LiNi 0.9 Mn 0.1 O 2 cathode showed 200 mAh/g highest discharge capacity at 0.1 C rate with 84% retention after 103 cycles at 0.3C rate while LiNi 0.9 Co 0.1 O 2 cathode showed higher initial but poor cycle life (225 mAh/g highest discharge capacity at 0.1C rate with only 56% capacity retention after 103 cycles at 0.3 C rate. Synchrotron based X-ray diffraction (SXRD), X-ray absorption spectroscopy (XAS) and focused ion beam (FIB) imaging of pristine and cycled cathodes after 103 cycles provided important information on degradation mechanism. The roles of Mn and Co on layered structure formation, charge balance, cationic mixing, and electrochemical performance were elucidated using the crystallographic information from XRD refinement and electronic state analysis from XAS providing valuable information to design future Ni-rich layered oxide cathodes.

25 ENERGY STORAGE↗

DOE OSTI2021

Theory-guided Design of Refractory MPEAs for High-Temperature, Harsh-Service Conditions

Focusing on novel materials for harsh-service environments (oxidation, corrosion, and load), durability, higher operational temperature, and direct impact on power-generation technology, the goal was, using a quantitative theory-guided design approach integrated with high-throughput synthesis and characterization for validation, to accelerate by 50% the development of high temperature, refractory-based multi-principal element alloys (MPEAs) materials platforms (with co-designed oxidation-resistant, self-healing coatings) that demonstrate phase-stable operation with desired properties at 10-20% higher temperatures in oxidizing environments over state-ofthe- art systems (like Ni-stainless steels, i.e., Haynes 282 – used in critical gas turbine applications, and refractory TZM, i.e., molybdenum-rich Mo99.4-Ti0.5-Zr0.08-C0.02 in wt%). Notably, refractory MPEAs may achieve higher operational temperatures with superior creep strength and offer 50-100% larger thermal conductivity (140-170 W/m-K) than Ni-based systems, potentially eliminating active cooling, reducing system weight, complexity, and cost. Achieving this goal addresses DOE material challenges in energy generation and efficiency (higher-temperature operation), reduced lifecycle energy (waste-heat recovery), and accelerating materials development in support of AMO’s Strategic Plan and QTR goals. DOE’s Advanced Manufacturing Office (AMO) goal of reducing industrial energy intensity and GHG emissions is addressed by development of coated refractory MPEAs exhibiting 20%+ higher operational temperature (direct increase of Carnot efficiency), higher melting temperatures (better phase stability), superior creep strength (better lifetime with creep rate lower by factor of 10), larger (50-100%) thermal conductivity (improved cooling without active cooling), reduced complexity (single-phase alloys), self-healing coating (reliable oxidation-resistance) and cost.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Dynamic response of 17-4 stainless steel as a function of manufacturing method and heat treatment

We present a series of plate-impact experiments on 17-4 stainless steel to study the effect of manufacturing method and heat treatment on the Hugoniot elastic limit (HEL), Hugoniot, phase transformation stress, and spallation strength. Two traditional manufacturing methods were considered, wrought processing and casting, as well as two additive manufacturing methods, laser powder-bed fusion (LPBF) and wire-fed electron beam (EBAM). For both LPBF and EBAM 17-4 stainless steel variants, two billets were printed, enabling the application of two unique heat treatments. The HEL stress depended heavily on the thermal history, with the HEL increasing after the formation of Cu-rich precipitates via heat treatment. The Hugoniot response both below and above the phase transition was unaffected by the manufacturing method or heat treatment. The phase transition stress depended heavily on the thermal history, with its variation being attributed to the presence of various microstructural features. This is supported by a marked increase in the phase transition stress after precipitation hardening. These results suggest that the notion of the phase transition stress being dictated by bulk composition is an oversimplification and the stress fields generated by the meso-scale structure are a dominant force. The spallation strength was lower in the cast material compared to all other 17-4 stainless steel variants due to the presence of brittle δ-ferrite inclusions. Additionally, a drop in the tensile strain-rate was observed in the spallation response above the phase transition stress, which was hypothesized to stem from the kinetics of the reversion to the low-pressure phase during spall.

Compressive stress↗

DOE OSTI2020

Perspectives on Quenching and Tempering 4340 Steel

Steels are ubiquitous due to their affordability and the landscape of useful properties that can be generated for engineering applications. But to further expand the performance envelope, one must be able to understand and control microstructure development by alloying and processing. In this paper we use multiscale, advanced characterization to better understand the structural and chemical evolution of AISI 4340 steel after quenching and tempering (Q&T), including the role of quench rate and short-time, isothermal tempering below 573 K (300 °C), with an emphasis on carbide formation. We compare the microstructure and/or property changes produced by conventional tempering to those produced by higher temperature, short-time “rapid” tempering. We underscore that no single characterization technique can fully capture the subtle microstructure changes like carbon redistribution, transition carbide and/or cementite formation, and retained austenite decomposition that occur during Q&T. Only the use of multiple techniques begins to unravel these complexities. After controlled fast or slow quenching, η transition carbides clearly exist in the microstructure, likely associated with autotempering of this high martensite start temperature (Ms) steel. Isothermal tempering below 598 K (325 °C) results in the relief of carbon supersaturation in the martensite, primarily by the formation of η transition carbides that exhibit a range of carbon levels, seemingly without substitutional element partitioning between the carbide and matrix phases. Hägg transition carbide is present between 300 °C and 325 °C. After conventional tempering at or above 598 K (325 °C) for 2 h, cementite is predominant, but small amounts of cementite are also present in other conditions, even after quenching. Previous work has indicated that silicon (Si) and substitutional elements partition between the cementite, which initially forms under paraequilibrium conditions, and the matrix. Phosphorous (P) may also be preferentially located at cementite/matrix interfaces after high temperature tempering. Slower quench rates result in greater amounts of retained austenite compared to those after fast quenching, which we attribute to increased austenite stability resulting from “autopartitioning”. Rapid, high temperature tempering is also found to diminish tempered martensite embrittlement (TME) believed to be associated with the extent of austenite decomposition, resulting in mechanical properties not attainable by conventional tempering, which may have important implications with respect to industrial heat treatment processes like induction tempering. Controlling the amount and stability of retained austenite is not only relevant to the properties of Q&T steels, but also next-generation advanced high strength steels (AHSS) with austenite/martensite mixtures.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Heat transfer enhancement due to cold cap motion from bubbling in a waste glass melter

In this study, a computational fluid dynamics (CFD) model was developed to model the motion of a solid cold cap in a waste glass melter. Forced convection bubblers at the base of the melter release air into the molten glass, which forms large bubbles that travel upwards to the cold cap and augment heat transfer from the glass to the cold cap. The CFD model employs the Navier- Stokes equations to solve for the fluctuating flowfield using a rigid body motion dynamic fluid body interaction module. This allows for movement of the floating body in response to the bubbling forces calculated at each time step. Further, the heat flux delivered to the cold cap by the convective bubbling is studied as a function of the bubbling rate. Results for the moving cold cap are compared with the computed heat flux trends for a stationary cold cap. The heat flux delivered to the cold cap from the glass is 25% higher for the case with the moving cold cap. The heat flux was found to be proportional to v0.6 as opposed to v0.9 (where v is the normalized bubbling rate) for the stationary cold cap.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application

As renewable power generation deployment increases, fossil fuel plants are increasingly required to operate more flexibly. Many coal-fired power plants were originally designed to operate at base load and do not operate optimally at partial load. Predictive first-principles plant-wide models can be employed to identify opportunities for flexibility improvements and diagnose low-load operating issues. This paper describes the application of the Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES) to model and optimize flexible power plant operations. The key benefits of using IDAES are that it provides an open-source, fully equation-oriented modeling framework for efficient modular model construction, reuse, and customization, together with a mathematical optimization framework leveraging powerful, state-of-the-art solvers. The process systems engineering workflow from predictive process simulation to parameter estimation, model validation, and plant optimization is applicable to a variety of existing and next-generation energy systems as well as other chemical and environmental processes. Here, to demonstrate this capability, a physics-based, steady-state model was developed to improve full- and part-load performance of the Escalante Generating Station, a 245 MWe (net) subcritical pulverized coal-fired power plant owned and operated by Tri-State Generation and Transmission Association. Specifically, sixty-nine model parameters were simultaneously estimated from several months of operating data enabling prediction of flow rates, temperatures, pressures, and steam quality throughout the plant. The validated model was leveraged by Escalante to reduce the minimum operating load from 90 MW to 50 MW by diagnosing a low-load water-hammer issue, enabling coal usage and emissions reductions during periods of low power demand. Additionally, opportunities for heat rate reduction (i.e., efficiency improvement) through a steeper sliding-pressure approach to load-following and optimization of other boiler operating variables were also identified and quantified. For example, a potential efficiency improvement of 0.7 percentage points was observed at half-load operation.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Dirty dishes or dirty laundry? Comparing two methods for quantifying American consumers' preferences for load management in a smart home

One challenge of transitioning to renewable energy is that household electricity use and renewable generation are often misaligned. Smart home energy management systems hold promise for shifting usage to match generation, but these systems need to be designed with the occupants’ preferences in mind. The purpose of the present research is to compare two approaches for collecting and modeling consumers’ load management preferences, both of which are amenable to use in a home energy management system. Specifically, we examine the performance of Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER) and Analytic Hierarchy Process (AHP) in quantifying consumers’ preferences regarding air temperature (air conditioning and heating), water heating, dishwashing, clothes washing and drying, monetary costs, environmental impacts, and comfort/convenience. Two studies are presented: Study 1 examines the SMARTER approach, and Study 2 focuses on the AHP approach. In both studies, online surveys (N SMARTER = 956 and N AHP = 1023) were conducted to elicit preferences from participants across the United States. The preferences modeled by both approaches were validated based on (a) their ability to predict participants’ choices in a Discrete Choice Experiment and (b) their convergence with previous research on load-shifting behavior. The validation procedure suggests that the SMARTER approach is superior in modeling consumers’ preferences for load management. Overall, this research lays the groundwork for designing a smart home interface capable of collecting occupants’ preferences and using those preferences to deliver improved occupant comfort, lower operating costs, reduced environmental impact, and more significant demand response than exists today.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Raman spectroscopic characterization of SiO 2 phase transformation and Si substrate stress relevant to EBC performance

To accurately model the long-term durability of environmental barrier coatings (EBCs), a more complete understanding of the phase composition and transformations of the thermally grown oxide SiO 2 (TGO) is desired. For the TGO formed during thermal cycling in steam, cristobalite formation and the subsequent β- to α-cristobalite transformation has been identified as a potentially life-limiting mechanism. In this study, Raman micro-spectroscopy was used to quantify the cristobalite transformation on a polycrystalline Si coupon that was exposed to steam at 1350°C for 100 h. The phase transformation was mapped at 200–260°C on the TGO surface at different ramp rates using a heating stage and a micro-positioning stage. The stress in the Si substrate was also determined using Raman spectroscopy by measuring the stress induced peak shift. The α→β phase transformation produced a 300–500 MPa tensile stress in the Si substrate, which compared well to the stress predicted from the volumetric expansion of the cristobalite. In conclusion, quantifying the phase transformation and residual stress are critical tools in developing the next generation of high performance EBCs.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Once-Through Steam Generator Model Analysis Using Python and Advanced Optimization Tools (Summer Internship Report)

This study focuses on the parametric analysis of design parameters for a once-through steam generator (OTSG) model, using python and advanced optimization tools to facilitate applications such as the flowing autoclave steam generator (FASG) test cases. Building on previous research involving another OTSG with a different design, this project aims to enhance our understanding of how steam generators (SGs) behave and how their outputs are influenced by changes in design. The reason for this design change is to allow for more precise modeling and optimization of SG performance, to provide a comparative analysis between the two designs, and to set up the model for integration with the FASG test case. The OTSG python-model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor-type small modular reactor system. Design studies involve changing the model’s input design parameters to observe the resulting effects on the output of the system. By using advanced optimization tools, such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory, detailed design parametric studies and model optimization were performed. Six input parameters—pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid), respectively, of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (i.e., ±1%, ±5% and ±10% relative changes) for 600 samples. The analysis provides valuable insights into SG optimization and can be used for sensor placement optimization to effectively monitor and obtain experimental data in other tests.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2025

Techno-Economic Viability of Flexible Dispatch of Unconventional Geothermal Systems

Flexible geothermal operations could boost project returns through the allocation of improved power purchase agreements and/or exploitation of power price arbitrage opportunities. In this study, we investigated the techno-economic feasibility of variable flow rate control and time-of-day pricing in closed-loop geothermal systems. We considered U-shaped multilateral system configurations and modeled a variety of technical system parameters. These designs were simulated using a slender-body theory (SBT) model for transient heat transfer and fluid flow. This subsurface model was integrated into the flexible geothermal economic model (FGEM) tool to evaluate the overall flexible geothermal system techno-economics. Future hourly ambient temperature conditions were based on the Sup3rCC dataset. Published datasets were used for future hourly wholesale electricity prices. We analyzed four operating strategies: 1) baseload operation, 2) seasonal dispatch (high flow rate during summer and nominal flow rate during the rest of the year), 3) net generation maximization by varying flow rate to maximize net power output, and 4) revenue maximization by varying flow rate to maximize revenue. We ran all four scenarios for a multiloop configuration with 12 lateral passes, 7-km vertical depth and 87-km total drilling length. Furthermore, we assumed a 60 degrees C/km geothermal gradient and ambient temperature and wholesale electricity prices for New Mexico as a typical state location. The nominal flow rate was set to 80 kg/s. When considering drilling costs of $1,000/m and a discount rate of 7%, the generation maximization scenario resulted in the lowest levelized cost of electricity (LCOE) of ~$150/MWh. When considering project return on investment (ROI), defined as lifetime net income divided by upfront capital costs, all flexible operation scenarios performed better than the base case scenario. The highest ROI of 80% was obtained with the revenue maximization scenario. With drilling costs of $200/m and a discount rate of 5%, the generation maximization scenario resulted in LCOE of $49/MWh.

flexible geothermal↗

DOE OSTI2026

On the uncertainties in helium generation predictions for fission and fusion alloys

With ongoing advances in fusion and advanced fission reactors, quantifying irradiation effects in materials is critical. Transmutation-induced helium in cladding and structural materials can drive swelling and embrittlement, thereby reducing these components’ lifespans. Yet most studies ignore the considerable uncertainties in predicting helium generation rates. In this work, we created a code wrapper, F-SCATTER, that automatically performs simulations in FISPACT-II. We used this tool to investigate potential variance in helium generation rate, or He/dpa, calculations based on deviations in alloy composition, irradiating neutron flux spectrum, computational methodology, and nuclear data sources. We used 12 wt% Cr HT9 steel as the reference case and observed a 6.5%–98.3% He/dpa spread based on compositional variation within a single chemical specification, a 1.8%–11.5% He/dpa variation upon the incorporation of a 15% artificial uncertainty in flux at each energy, and a He/dpa difference as high as 231% when using ENDF/B-VIII.0 versus TENDL-2021 data libraries. Similar results were found for other prominent iron-based alloys, including Grade 91, castable nano-structured alloy, and 316H—where additional variations exist based on reactor type (e.g. thermal, fast, or fusion) and alloying elements such as carbon, nitrogen, and nickel. Based on the simulated results, we conclude that a significant part of the heat-to-heat variability in swelling responses of Fe-based alloys can be driven by impurity content in alloy compositions, and, therefore, chemical control should be a key element in supply chain design for advanced nuclear energy systems. Furthermore, we provide critical recommendations on best practices for evaluating and reporting helium production and lattice damage rates when computing predictions with multiphysics programs such as FISPACT-II.

FISPACT-II↗

DOE OSTI2025

Explainable and Differentiable Reinforcement Learning for Multi-objective Optimization in Particle Accelerators

Operating particle accelerators involves optimizing multiple goals simultaneously, which can be challenging due to trade-offs among objectives. While evolutionary algorithms like the genetic algorithm (GA) have been used for various Multi-Objective Optimization (MOO) tasks, they are not inherently suited for complex control problems. This talk highlights two variations of Reinforcement Learning (RL) for concurrently optimizing heat load and trip rates at the Continuous Electron Beam Accelerator Facility (CEBAF). The problem involves strict constraints on individual states, actions, and overall energy requirements of the beam. First, this talk highlights how differentiability can be harnessed through a Deep Differentiable Reinforcement Learning (DDRL) approach to address MOO issues within particle accelerators. We examine the DDRL method alongside Model Free Reinforcement Learning (MFRL), GA, and Bayesian Optimization (BO). The performance of these methods is assessed by generating a Pareto-front for two objectives. Our findings indicate that DDRL excels in handling high-dimensional problems more effectively than MFRL, BO, and GA. Next, we will show integration of explainable physics-based constraints into RL algorithms to enhance trans- parency and trust in decision-making processes by enabling users to verify that agents adhere to established physical principles. This surrogate function can be modeled using neural networks or sparse dictionary mod- els. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment provided but the surrogate model. In addi- tion, we find that the introduction of a mathematical functional dictionary based surrogate model enables our reinforcement learning algorithms to reliably converge for difficult high-dimensional accelerator controls environments.

Rajput, Kishansingh [Thomas Jefferson National Acc↗

DOE OSTI2021

A novel lung-inspired 3D-printed desiccant-coated heat exchanger for high-performance humidity management in buildings

Offering an independent humidity management method for buildings, desiccant-coated heat exchangers (DCHXs) are deemed a promising approach to improve the overall energy efficiency of air conditioning (AC) systems. State-of-the-art DCHXs, however, are bound with conventional HX topologies either providing limited desiccant-air interfacial areas or introducing excessive pressure drop penalties. In this paper a novel 3D-printed DCHX concept inspired by the bronchi arrangement of a human lung is introduced to address the shortcomings inherent in existing DCHX designs. The proposed lung-inspired DCHX utilizes two intertwined bicontinuous flow networks enabling highly efficient heat and mass transfer characteristics for augmented adsorption and regeneration processes at low pressure drop penalties. While the first network evenly distributes an incoming air stream through the entire volume of the lung-inspired DCHX, the second network volumetrically splits a cooling water stream within and through the first network. Effects of various parameters including air flow rate, outdoor air humidity ratio, and regeneration temperature on dehumidification performance and energy efficiency of the proposed lung-inspired DCHX were investigated. Experimental results indicated the proposed lung-inspired 3D-printed DCHX outperforms existing DCHX systems by demonstrating an excellent balance between a high volumetric adsorption rate and a low pressure drop penalty. The volumetric adsorption rate of the proposed lung-inspired DCHX technology is 54.8 g/m 3 -s, a more than two-fold improvement compared with state-of-the-art DCHX systems. Additionally, the lung-inspired DCHX offers high thermal energy efficiency of 56% at a low regeneration temperature of 40 °C. Therefore, the proposed lung-inspired 3D-printed DCHX offers a new solid-desiccant-based air dehumidification pathway for next-generation high-performance AC systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Key Technical Issues for Greater-Than-Class-C (GTCC) Waste Disposal - 20164

Greater-than-Class C (GTCC) waste is low-level waste (LLW) that exceeds the Class C concentrations tabulated in Title 10, Code of Federal Regulations (CFR), Part 61. Disposal of GTCC waste in the near surface (i.e. upper 30 m of the earth's surface) is prohibited in the United States. Though GTCC waste disposal is generally prohibited, the Commission can approve disposal according to 10 CFR 61.55(a)(2)(iv) on a case-by-case basis. The waste classification tables, developed in the early 1980's, were based on model projections of dose to an inadvertent intruder in agricultural, construction, and discovery exposure scenarios. The assumptions and parameters used were documented in a series of public reports. Though different disposal facility designs and site conditions were considered, the waste classification tables were based on a disposal facility design located in a specific environment. The tables were based on shallow (i.e., top few meters) trench facility designs and did not consider deeper facilities. To determine the suitability of GTCC waste disposal in the near-surface, site-specific analyses must account for differences between GTCC waste and Class A, B, and C LLW (hereafter, traditional LLW). GTCC waste can have concentrations of radionuclides that are much higher than traditional LLW. Because of these higher concentrations, processes that are typically not significant for traditional LLW may be significant with respect to disposal of GTCC waste. These processes include, but are not limited to, heat generation, criticality, and radiolysis. The form of the waste as well as the barriers to release of the waste (e.g. waste package) could be substantially different than they are for traditional LLW. These barriers need to be considered when assessing the impacts of accidents during receipt and placement and in evaluating long-term performance. Some GTCC radioactivity is either embedded in stainless steel or contained in stainless steel barriers. Stainless steel can have very low corrosion rates under a variety of environmental conditions. Finally, and possibly most importantly, GTCC waste would likely need to be disposed deeper than traditional LLW to reduce the probability of disturbance. The waste classification table values of traditional LLW are based on an inadvertent intruder excavating into the waste and bringing some of the material to the land surface. If waste is deeper than approximately 5 m, the excavation scenario becomes very unlikely. Therefore, other intruder scenarios, such as drilling exposure scenarios, need to be evaluated. This paper summarizes key technical issues for the disposal of GTCC waste. Our previous study shows that certain GTCC waste may be suitable for near surface disposal whereas others may not. This study may support ongoing technical analyses assessing potential disposal of GTCC in a near surface disposal facility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Potential of Utilizing Thermal Energy Storage Integrated Ground Source Heat Pump System to Reshape Electricity Demand in the United States

Each year, more than 20% of electricity generated in the United States is consumed for meeting the thermal demands (e.g., space cooling, space heating, and water heating) in residential and commercial buildings. Integrating thermal energy storage (TES) with building’s HVAC systems has the potential to reshape the electric load profile of the building and mitigate the mismatch between the renewable generation and the demand of buildings. A novel ground source heat pump (GSHP) system integrated with underground thermal energy storage (UTES) has been proposed to level the electric demand of buildings while still satisfying their thermal demands. This study assessed the potential impacts of the proposed system with a bottom-up approach. The impacts on the electricity demand in various electricity markets were quantified. The results show that, within the capacity of the existing electric grids, the maximum penetration rate of the proposed system in different wholesale markets could range from 51% to 100%. Altogether, about 46 million single-family detached houses can be retrofitted into the proposed system without increasing the annual peak demand of the corresponding markets. By implementing the proposed system at its maximum penetration rate, the grid-level summer peak demand can be reduced by 9.1% to 18.2%. Meanwhile, at the grid level, the annual electricity consumption would change by –12% to 2%. The nationwide total electricity consumption would be reduced by 9%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Ultra-intense femtosecond laser interactions with aligned nanostructures

The interaction of ultrafast laser pulses of relativistic intensity with high aspect ratio nanostructures can efficiently and volumetrically heat matter to an ultra-high-energy-density regime encountered in the center of stars and within the core of fusion capsules compressed by the world’s largest lasers. It also generates gigantic quasi-static electromagnetic fields that accelerate particles to very high energy. Here, we present an overview of the physics and applications of these dense relativistic plasmas that can be created with pulses of relatively modest energy from lasers that can operate at a high repetition rate. Recent nanowire array experiments produced near-solid density plasmas with an extreme degree of ionization (e.g., Au +72 ), converted ultrafast pulses of laser light into intense x-ray flashes with record efficiency, and accelerated ions to MeV energies, efficiently driving micro-scale fusion reactions that generate flashes of quasi-monoenergetic neutrons. These plasmas also serve as a platform for advancing the understanding of atomic processes in extreme environments and open a new pathway to laser-driven fusion energy. The irradiation of nanostructures at intensities of > 1 x 10 22 W cm –2 is predicted to lead to an extreme ultra-high energy density plasma regime characterized by terabar pressures that is virtually unexplored.

Optics↗

DOE OSTI2023

Fuel Flow Modeling under Thermal Fluidics Considerations within Operational Domains of Molten Salt Reactors

Molten Salt Reactors (MSRs) offer significant versatility supported by their design flexibility and safety advantages due to high temperatures, design customization capabilities, strong negative reactivity feedback effects, and salt chemistry characteristics. Different control schedules and different mass flow rates in the MSR primary systems impact neutronics and thermal hydraulics coupling. The result is two-fold. First, it leads to adaptability in various applications when the customization of a MSR unit is desired. Second, it calls for the quantification of dynamics and safety characteristics to assess the operational domain and make sure reactor stability and inherent safety characteristics are maintained. This paper provides an in-depth transient analysis of the operational implications of MSRs having heat-generating fuel and heat-transporting salt mixed forming liquid fuel salts contained within primary systems. A coupling model was developed to simulate fuel flow in molten salt reactors. A zero-dimensional reactor kinetics model was used with a one-dimensional heat transfer model in the reactor core. The temperature reactivity feedbacks of the fuel salt resulting from the thermal-hydraulics model were used in the reactor kinetics model to complete the coupled code. The model was applied to simulate the Molten Salt Breeder Reactor (MSBR) response at steady state and transients. The developed model was shown to be a suitable tool for the dynamic analysis of molten salt reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Acceleration of Crystallization Kinetics in Ge‐Sb‐Te‐Based Phase‐Change Materials by Substitution of Ge by Sn

Abstract Thin films of (Ge 1– x Sn x ) 8 Sb 2 Te 11 are prepared to study the impact of Sn‐substitution on properties relevant for application in phase‐change memory, a next‐generation electronic data storage technology. It is expected that substitution decreases the crystallization temperature, but it is not known how the maximum crystallization rate is affected. Ge 8 Sb 2 Te 11 is chosen from the (GeTe) y (Sb 2 Te 3 ) 1– y system of phase‐change materials as a starting point due to its higher crystallization temperature as compared to the common material Ge 2 Sb 2 Te 5 . In situ X‐ray diffraction at 5 K min −1 heating rate is performed to determine the crystallization temperature and the resulting structure. To measure the maximum crystallization rate, femtosecond optical pulses that heat the material repetitively and monitor the resulting increase of optical reflectance are used. Glasses over the entire composition range are prepared using a melt‐quenching process. While at x = 0, 97, subsequent pulses are required for crystallization, one single pulse is enough to achieve the same effect at x = 0.5. The samples are further characterized by optical ellipsometry and calorimetry. The combined electrical and optical contrast and the ability to cycle between states with single femtosecond pulses renders Ge 4 Sn 4 Sb 2 Te 11 promising for photonics applications.

Zalden, Peter↗