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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

3D_MolGNN_RL

3D-MolGNNRL, couples reinforcement learning (RL) to a deep generative model based on 3D-Scaffold to generate target candidates specific to a protein pocket building up atom by atom from the core scaffold. 3D-MolGNNRL provides an efficient way to optimize key features within a protein pocket using a parallel graph neural network model. The agent learns to build molecules in 3D space while optimizing the binding affinity, potency, and synthetic accessibility of the candidates generated for the SARS-CoV-2 Main protease

Kumar, Neeraj↗
DOE OSTI2017

The Institute for Sustained Performance, Energy, and Resilience Final Project Report

Over the course of the five years of the Scientific Discovery through Advanced Computation (SciDAC-3) program, computational scientists working on behalf of the Department of Energy's Office of Science (DOE SC) exploited a new generation of petascale computing resources to make previously inaccessible discoveries in a broad range of disciplines including physics, chemistry, and materials science. The computing systems underpinning this work increased in performance potential from tens to hundreds of PFlop/s, but in the process evolving significantly from architectures in 2011, when SciDAC-3 began. Although Moore's law continues unabated, the end of Dennard scaling has necessitated a fundamental shift in computer architecture focused on power efficiency. To that end, processors are increasingly varied as they strive to satisfy performance, productivity, reliability, and energy efficiency in the face of divergent computational requirements. The diversity among these machines presents a number of challenges to merely porting today's scientific applications, much less achieving good performance. Therefore, at the beginning of SciDAC-3, USC and its collaborators anticipated that both vastly increased scale (e.g., more chips, more cores per chip, wider SIMD) and heterogeneity would exacerbate performance optimization challenges while simultaneously promoting the issues of energy and heterogeneity will exacerbate performance optimization challenges while simultaneously promoting the issues of energy consumption and resilience to the forefront. To ensure that DOE's computational scientists could successfully exploit emerging high performance computing (HPC) systems, DOE SC’s Advanced Scientific Computing Research Program (ASCR) funded the SciDAC-3 Institute for Sustained Performance, Energy, and Resilience (SUPER). Led by USC, this was a broadly based project with expertise in compilers and system tools, performance engineering, energy management, and resilience. SUPER followed the successful model developed in the previous SciDAC-2 Performance Engineering Research Institute (PERI) of leveraging the research investments DOE and others have made and integrating the results to create new capabilities beyond the reach of any one group. To accomplish this, SUPER was organized into multi-institution teams conducting the research activities in performance portability, energy efficiency, exascale resilience, and overall optimization. SUPER researchers also collaborated with other SciDAC-3 institutes, 13 of the 19 Scientific Computation Application Partnerships (SAP), as well as the broader DOE computational sciences community. These collaborations both focused our research on the real challenges facing petascale scientific computing as well as ensured the broad and immediate impact of the results of our research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

CBETA 4-pass Orbit Correction and Tolerance Study (CBETA Machine Note #037)

The main goal of this study is to find the tolerance of the CBETA FFAG lattice subjected to various errors. Common error sources include non-ideal magnet positioning and alignment, undesired multipole field strengths, and BPM offsets. In order to fix the beam trajectories (orbits) affected by the errors, dipole kickers have been allocated throughout the FFAG beamline to serve as correctors. Since there are four coexisting orbits in the FFAG, the correction scheme must aim to correct all four of them simultaneously. The simulation is performed using Bmad, developed by Cornell University to model relativistic beam dynamics in customized accelerator lattices. The core of orbit correction is the singular value decomposition (SVD) optimization. As the error magnitudes increase, the beam size and emittance after correction could undesirably increase, and our goal is to find the "individual limit" of each error type beyond which the increases become unacceptable. Typically this limit is reached before the orbits become un-correctable. Similarly we can also find the "combined limit" of various errors. Both limits will be properly defined in the later section.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

A New Method to Contain Molten Corium in Catastrophic Nuclear Reactor Accidents

The catastrophic nuclear reactor accident at Fukushima damaged public confidence in nuclear energy and a demand for new engineered safety features that could mitigate or prevent radiation releases to the environment in the future. We have developed a novel use of sacrificial material (SM) to prevent the molten corium from breaching containment during accidents as well as a validated, novel, high-fidelity modeling capability to design and optimize the proposed concept. Some new reactor designs employ a core catcher and a SM, such as ceramic or concrete, to slow the molten corium and avoid the breach of the containment. However, existing reactors cannot easily be modified to include these SMs but could be modified to allow injectable cooling materials (current designs are limited to water). The SM proposed in this Laboratory Development Research and Development (LDRD) project is based on granular carbonate minerals that can be used in existing light water reactor plants. This new SM will induce an endothermic reaction to quickly freeze the corium in place, with minimal hydrogen explosion and maximum radionuclide retention. Because corium spreading is a complex process strongly influenced by coupled chemical reactions (with underlying containment material and especially with the proposed SM), decay heat and phase change. No existing tool is available for modeling such a complex process. This LDRD project focused on two research areas: experiments to demonstrate the feasibility of the novel SM concept, and modeling activities to determine the potential applications of the concept to actual nuclear plants. We have demonstrated small-scale to large-scaled experiments using lead oxide (Pb0) as surrogate for molten corium, which showed that the reaction of the SM with molten Pb0 results in a fast solidification of the melt and the formation of open pore structures in the solidified Pb0 because of CO 2 released from the carbonate decomposition.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Final Project – Technical PresentationUnlocking the Tight Oil Reservoirs of the Powder River Basin, Wyoming

The project established a Tight Oil Field Laboratory to address technical challenges in developing stacked unconventional reservoirs in the Powder River Basin. Key activities included data compilation, subsurface mapping, drilling, logging, coring, deployment of fiber optics and microseismic, completion and stimulation optimization, and well performance evaluation.

Mowry↗
DOE OSTI2024

Halogenated Dibenzo[ f , h ]quinoxaline Units Constructed 2D‐Conjugated Guest Acceptors for 19% Efficiency Organic Solar Cells

Abstract Halogenation of Y‐series small‐molecule acceptors (Y‐SMAs) is identified as an effective strategy to optimize photoelectric properties for achieving improved power‐conversion‐efficiencies (PCEs) in binary organic solar cells (OSCs). However, the effect of different halogenation in the 2D‐structured large π‐fused core of guest Y‐SMAs on ternary OSCs has not yet been systematically studied. Herein, four 2D‐conjugated Y‐SMAs (X‐QTP‐4F, including halogen‐free H‐QTP‐4F, chlorinated Cl‐QTP‐4F, brominated Br‐QTP‐4F, and iodinated I‐QTP‐4F) by attaching different halogens into 2D‐conjugation extended dibenzo[ f , h ]quinoxaline core are developed. Among these X‐QTP‐4F, Cl‐QTP‐4F has a higher absorption coefficient, optimized molecular crystallinity and packing, suitable cascade energy levels, and complementary absorption with PM6:L8‐BO host. Moreover, among ternary PM6:L8‐BO:X‐QTP‐4F blends, PM6:L8‐BO:Cl‐QTP‐4F obtains a more uniform and size‐suitable fibrillary network morphology, improved molecular crystallinity and packing, as well as optimized vertical phase distribution, thus boosting charge generation, transport, extraction, and suppressing energy loss of OSCs. Consequently, the PM6:L8‐BO:Cl‐QTP‐4F‐based OSCs achieve a 19.0% efficiency, which is among the state‐of‐the‐art OSCs based on 2D‐conjugated Y‐SMAs and superior to these devices based on PM6:L8‐BO host (17.70%) and with guests of H‐QTP‐4F (18.23%), Br‐QTP‐4F (18.39%), and I‐QTP‐4F (17.62%). The work indicates that halogenation in 2D‐structured dibenzo[ f , h ]quinoxaline core of Y‐SMAs guests is a promising strategy to gain efficient ternary OSCs.

14 SOLAR ENERGY↗
DOE OSTI2019

Stability of push–pull small molecule donors for organic photovoltaics: spectroscopic degradation of acceptor endcaps on benzo[1,2- b :4,5- b ′]dithiophene cores

High efficiency organic photovoltaic devices have relied on the development of new donor and acceptor materials to optimize opto-electronic properties, promote free carrier generation, and suppress recombination losses. With single junction efficiencies exceeding 15%, materials development must now target long-term stability. This work focuses on the photobleaching dynamics and degradation chemistries of a class of small molecule donors inspired by benzodithiophene terthiophene cores (BDT-3T) with rhodanine endcaps, which have demonstrated 9% efficiency in single junction devices and >11% in ternary cells. Density functional theory was used to design three additional molecules with similar synthetic pathways and opto-electronic properties by simply changing the electron accepting endcap to benzothiazoleacetonitrile, pyrazolone, or barbituric acid functional groups. This new class of semiconductors with equivalent redox properties enables systematic investigation into photobleaching dynamics under white light illumination in air. Degradation chemistries are assessed via unique spectroscopic signatures for the BDT-3T cores and the endcaps using photoelectron spectroscopies. We show that the pyrazolone undergoes significant degradation due to ring opening, resulting in complete bleaching of the chromophore. The barbituric and rhodanine endcap molecules have moderate stability, while the benzothiazoleacetonitrile group produces the most stable chromophore despite undergoing some oxidative degradation. Collectively, our results suggest the following: (i) degradation is not just dependent on redox properties; (ii) core group stability is not independent of the endcap choice; and (iii) future design of high efficiency materials must consider both photo and chemical stability of the molecule as a whole, not just individual donor or acceptor building blocks.

14 SOLAR ENERGY↗
DOE OSTI2019

DECA: scalable XHMM exome copy-number variant calling with ADAM and Apache Spark

Abstract Background XHMM is a widely used tool for copy-number variant (CNV) discovery from whole exome sequencing data but can require hours to days to run for large cohorts. A more scalable implementation would reduce the need for specialized computational resources and enable increased exploration of the configuration parameter space to obtain the best possible results. Results DECA is a horizontally scalable implementation of the XHMM algorithm using the ADAM framework and Apache Spark that incorporates novel algorithmic optimizations to eliminate unneeded computation. DECA parallelizes XHMM on both multi-core shared memory computers and large shared-nothing Spark clusters. We performed CNV discovery from the read-depth matrix in 2535 exomes in 9.3 min on a 16-core workstation (35.3× speedup vs. XHMM), 12.7 min using 10 executor cores on a Spark cluster (18.8× speedup vs. XHMM), and 9.8 min using 32 executor cores on Amazon AWS’ Elastic MapReduce. We performed CNV discovery from the original BAM files in 292 min using 640 executor cores on a Spark cluster. Conclusions We describe DECA’s performance, our algorithmic and implementation enhancements to XHMM to obtain that performance, and our lessons learned porting a complex genome analysis application to ADAM and Spark. ADAM and Apache Spark are a performant and productive platform for implementing large-scale genome analyses, but efficiently utilizing large clusters can require algorithmic optimizations and careful attention to Spark’s configuration parameters.

Linderman, Michael D. (ORCID:0000000296437148)↗
DOE OSTI2025

White Paper: Research & Development for the Time at Temperature Approach

Recent advancements in nuclear power research are greatly improving reactor safety and performance through the development of Accident Tolerant Fuel (ATF) and Low-Enriched Uranium Plus (LEU+). These innovations can address Departure from Nucleate Boiling (DNB) margins, which are vital for reactor safety. DNB happens when the coolant switches to film boiling, significantly decreasing heat transfer and posing a risk of fuel cladding failure. The U.S. Nuclear Regulatory Commission (NRC) employs conservative DNB criteria, which can potentially restrict the operational flexibility and efficiency of reactors. The Time at Temperature (TaT) approach could provide a more detailed and adaptable operational guideline by establishing acceptable time-temperature limits, accounting for the duration a material can withstand elevated temperatures without losing its integrity. This method allows reactors to operate more efficiently and safely, offering additional operational margins, faster power adjustments, and improved fuel cycle economics. TaT criteria allow for higher power levels and more flexible responses to operational transients, particularly applicable for anticipated operational occurrences (AOOs) that result in short durations of post-DNB conditions. It enhances plant operational flexibility, allows faster startup times, and enables quicker power level adjustments, optimizing fuel loading patterns and improving fuel cycle economics. Implementing TaT limits reduces core design constraints, lowers fuel usage, and reduces costs, essential for the long-term sustainability of Light Water Reactors (LWRs). TaT maximizes the use of advanced fuel technologies like ATF and LEU+, further enhancing their economic and environmental benefits. To apply the TaT approach in existing LWRs, collaborative research activities among various DOE-sponsored programs are essential. These efforts should incorporate fuel experiments, physics-based high-fidelity modeling, ML-based surrogate modeling, and optimization techniques. This whitepaper proposes four research and development areas: 1) Investigation of the feasibility of new operations of LWR with updated safety limits; 2) Assessment of reactor operation limits through uncertainty reduction; 3) Evaluation of power uprate in virtual environment; and 4) Lattice and reactor core design for power uprate. Each area includes why this research is in need and a suggested scope of work. These comprehensive research areas ensure practical and beneficial advancements for existing reactors, translating innovations in nuclear fuel and cladding technology into improved reactor performance and safety.

42 - ENGINEERING↗
DOE OSTI2020

Characterizing the Performance of Executing Many-tasks on Summit

Many scientific workloads are comprised of many tasks, where each task is an independent simulation or analysis of data. The execution of millions of tasks on heterogeneous HPC platforms requires scalable dynamic resource management and multi-level scheduling. RADICAL-Pilot (RP) -- an implementation of the Pilot abstraction, addresses these challenges and serves as an effective runtime system to execute workloads comprised of many tasks. In this paper, we characterize the performance of executing many tasks using RP when interfaced with JSM and PRRTE on Summit: RP is responsible for resource management and task scheduling on acquired resource; JSM or PRRTE enact the placement of launching of scheduled tasks. Our experiments provide lower bounds on the performance of RP when integrated with JSM and PRRTE. Specifically, for workloads comprised of homogeneous single-core, 15 minutes-long tasks we find that: PRRTE scales better than JSM for > O(1000) tasks; PRRTE overheads are negligible; and PRRTE supports optimizations that lower the impact of overheads and enable resource utilization of 63% when executing O(16K), 1-core tasks over 404 compute nodes.

Matteo, Turilli↗
DOE OSTI2024

Active Learning for Metamaterial Optimization on HPC and QC Integrated Systems

Active learning algorithms, integrating machine learning, quantum computing and optics simulation in an iterative loop, offer a promising approach to optimizing metamaterials. However, these algorithms can face difficulties in optimizing highly complex structures due to computational limitations. High-performance computing (HPC) and quantum computing (QC) integrated systems can address these issues by enabling parallel computing. In this study, we develop an active learning algorithm working on HPC-QC integrated systems. We evaluate the performance of optimization processes within active learning (i.e., training a machine learning model, problem-solving with quantum computing, and evaluating optical properties through wave-optics simulation) for highly complex metamaterial cases. Our results showcase that utilizing multiple cores on the integrated system can significantly reduce computational time, thereby enhancing the efficiency of optimization processes. Therefore, we expect that leveraging HPC-QC integrated systems helps effectively tackle large-scale optimization challenges in general.

Kim, Seongmin↗
DOE OSTI2018

Core microbiomes for sustainable agroecosystems

In an era of ecosystem degradation and climate change, maximizing microbial functions in agroecosystems has become a prerequisite for the future of global agriculture. Furthermore, managing species-rich communities of plant-associated microbiomes remains a major challenge. Here, we propose interdisciplinary research strategies to optimize microbiome functions in agroecosystems. Informatics now allows us to identify members and characteristics of ‘core microbiomes’, which may be deployed to organize otherwise uncontrollable dynamics of resident microbiomes. Integration of microfluidics, robotics and machine learning provides novel ways to capitalize on core microbiomes for increasing resource-efficiency and stress-resistance of agroecosystems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Petascale Orbital-Free Density Functional Theory Enabled by Small-Box Algorithms

Orbital-free density functional theory (OFDFT) is a quantum-mechanics-based method that utilizes electron density as its sole variable. The main computational cost in OFDFT is the ubiquitous use of the fast Fourier transform (FFT), which is mainly adopted to evaluate the kinetic energy density functional (KEDF) and electron–electron Coulomb interaction terms. We design and implement a small-box FFT (SBFFT) algorithm to overcome the parallelization limitations of conventional FFT algorithms. We also propose real-space truncation of the nonlocal Wang–Teter KEDF kernel. The scalability of the SBFFT is demonstrated by efficiently simulating one full optimization step (electron density, energies, forces, and stresses) of 1,024,000 lithium (Li) atoms on up to 65,536 cores. We perform other tests using Li as a test material, including calculations of physical properties of different phases of bulk Li, geometry optimizations of nanocrystalline Li, and molecular dynamics simulations of liquid Li. All of the tests yield excellent agreement with the original OFDFT results, suggesting that the OFDFT-SBFFT algorithm opens the door to efficient first-principles simulations of materials containing millions of atoms.

Chemistry↗
DOE OSTI2016

Channel Bow Constraint Option in the BWR Loading Pattern Optimization System FINELOAD-3

The boiling water reactor (BWR) loading pattern (LP) optimization system FINELOAD-3 (FL3), has been applied for actual BWR reload core design for over fifteen years in TEPCO Systems Corporation (TEPSYS) and for over ten years in several European utilities. FL3 works in combination with the advanced nodal core simulator SIMULATE-3 (S3) or other core simulators. Recently, the channel bow constraint option has been added in FL3. In the BWR reload core design work, the channel bow management is very important in order to avoid the interference between a channel and a control blade and/or to minimize the effect on critical power ratio during the operation cycle. The channel bow constraint option is applied to eliminate channel bow violation against design target. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Using ARM Measurements to Understand and Reduce the Double ITCZ Biases in the Community Atmospheric Model

1. Understanding of the observed variability of ITCZ in the equatorial eastern Pacific. The annual mean precipitation in the eastern Pacific has a maximum zonal band north of the equator in the ITCZ where the maximum SST is located. During the boreal spring (referring to February, March, and April throughout the present paper), because of the accumulated solar radiation heating and oceanic heat transport, a secondary maximum of SST exists in the southeastern equatorial Pacific. Associated with this warm SST is also a seasonal transitional maximum of precipitation in the same region in boreal spring, exhibited as a weak double ITCZ pattern in the equatorial eastern Pacific. This climatological seasonal variation, however, varies greatly from year to year: double ITCZ in the boreal spring occurs in some years but not in other years; when there a single ITCZ, it can appear either north, south or at the equator. Understanding this observed variability is critical to find the ultimate cause of the double ITCZ in climate models. Seasonal variation of ITCZ south of the eastern equatorial Pacific: By analyzing data from satellites, field measurements and atmospheric reanalysis, we have found that in the region where spurious ITCZ in models occurs, there is a “seasonal cloud transition” — from stratocumulus to shallow cumulus and eventually to deep convection —in the South Equatorial Pacific (SEP) from September to April that is similar to the spatial cloud transition from the California coast to the equator. This seasonal transition is associated with increasing sea surface temperature (SST), decreasing lower tropospheric stability and large-scale subsidence. This finding of seasonal cloud transition points to the same source of model errors in the ITCZ simulations as in simulation of stratocumulus-cumulus-deep convection transition. It provides a test for climate models to simulate the relationships between clouds and large-scale atmospheric fields in a region that features a spurious double Inter-tropical Convergence Zone (ITCZ) in most models. This work is recently published in Yu et al. (2016). Interannual variation of ITCZ south of the eastern equatorial Pacific: By analyzing data from satellites, field measurements and atmospheric reanalysis, we have characterized the interannual variation of boreal spring precipitation in the eastern tropical Pacific and found the cause of the observed interannual variability. We have shown that ITCZ in this region can occur as a single ITCZ along the Equator, single ITCZ north of the Equator, single ITCZ south of the Equator, and double ITCZ on both sides of the Equator. We have found that convective instability only plays a secondary role in the ITCZ interannual variability. Instead, the remote impact of the Pacific basin-wide SST on the horizontal gradient of surface pressure and wind convergence is the primary driver of this interannual variability. Results point to the need to include moisture convergence in convection schemes to improve the simulation of precipitation in the eastern tropical Pacific. This result has been recently submitted for publication (Yu and Zhang 2016). 2. Improvement of model parameterizations to reduce the double ITCZ bias We analyzed the current status of climate model performance in simulating precipitation in the equatorial Pacific. We have found that the double ITCZ bias has not been reduced in CMIP5 models relative to CMIP4 models. We have characterized the dynamic structure of the common bias by using precipitation, sea surface temperature, surface winds and sea-level. Results are published in Zhang et al. (2015): Since cumulus convection plays a significant role in the double ITCZ behavior in models, we have used measurements from ARM and other sources to carry out a systematic analysis of the roles of shallow and deep convection in the CAM. We found that in both CAM4 and CAM5, when the intensity of deep convection decreases as a result of parameterization change, the intensity of shallow convection increases, leading to very different changes in precipitation partitions but little change in the total precipitation. The different precipitation partition however can manifest themselves in other measures of model performances including temperature and humidity. This study points to the need to treat model physical parameterizations as integrated system rather than individual components. Results from this study are published in Wang and Zhang (2013). Since shallow convection interacts with the deep convection scheme and surface turbulence to trigger the double ITCZ, we studied methods to improve the shallow convection scheme in climate models. We investigated the bulk budgets of the vertical velocity and its parameterization in convective cores, convective updrafts, and clouds by using large-eddy simulation (LES) of four shallow convection cases including one from ARM. We proposed optimal forms of the Simpson and Wiggert equation to calculate the vertical velocity in bulk mass flux convection schemes for convective cores, convective updrafts, and convective clouds as parameterization schemes. The new scheme is published in Wang and Zhang (2014). By using long-term radar-based ground measurements from ARM, we derived a scale-aware inhomogeneity parameterization of cloud liquid water in climate models. We found a relationship between the inhomogeneity parameter and the model grid size as well as atmospheric stability. This relationship is implemented in the CESM to describe the subgrid-scale cloud inhomogeneity. Relative to the default CESM with the finite-volume dynamic core at 2-degree resolution, the new parameterization leads to smaller cloud inhomogeneity and larger cloud liquid-water path in high latitudes, and the opposite effect in low latitudes, with the regional impact on shortwave cloud radiation effect of up to 10 W/m 2 . This is due to both the smaller (larger) grid size in high (low) latitudes in the longitude-latitude grid setting of CESM and the more stable (unstable) atmosphere. This parameterization is expected lead to more realistic simulation of tropical precipitation in high-resolution models. Results from this study are reported in Xie and Zhang (2015).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Conceptual design study of neutron detectors for safeguards measurement of an irradiated pebble

Nuclear material control and accounting (MC&A) of pebble-bed reactors (PBRs) is challenging because a PBR utilizes hundreds of thousands of identical, unmarked pebbles that are continuously recirculated through the core. To develop tools that enable the implementation of international safeguards, especially in the context of MC&A of spent pebbles, we designed and simulated three neutron detection concepts to determine fissile content in individual pebbles: a differential die-away (DDA) detector, a californium interrogation prompt neutron (CIPN) detector, and a passive neutron albedo reactivity (PNAR) detector using Monte Carlo calculations. Burnup calculations were performed on the spent pebbles from the PBMR-400 classic PBR. The varying neutron and gamma source terms, and isotopic compositions in the spent pebbles calculated at various burnup levels were used in the neutron detector models. DDA was found to be sensitive to the number of passes a pebble has had through the core and to the fissile content contained in a spent pebble. Optimization in the DDA design further increased the neutron count rates and thus reduced counting uncertainty. Meanwhile, passive neutron counting using the same detector body could distinguish pebbles with different numbers of passes, but its response was dominated by neutron-emitting actinides and was not sensitive to fissile content. On the other hand, the PNAR technique was not viable for a single pebble but performed reasonably for a 27-pebble array, which suggested potential use for verification measurements of containers filled with 27 or more spent pebbles.

CIPN↗
DOE OSTI2024

Liquid lithium divertor analysis using coupled plasma material interaction model

A liquid lithium divertor can improve performance of future fusion devices by creating efficient power exhaust and improving the energy confinement via pumping of the hydrogen isotopes. In addition, significantly higher heat fluxes can be handled if controlled vapor shielding is used to redistribute the divertor heat flux over a wider area. Design and optimization of such a system calls for an analysis model which includes a strong two-way coupling between the plasma and divertor material. The incoming plasma heat and particle flux will affect the divertor surface temperature, which is a defining factor of the lithium evaporative and sputtered flux going into the plasma. Results of the coupled model based on the plasma edge code SOLPS-ITER and the computational fluid dynamics (CFD) code ANSYS-CFX will be presented for different configurations. An analytical slab flow model is used as a heat transfer boundary condition for SOLPS, defining particle flux from the wall via calculation of the surface temperature. At the final step, results of the SOLPS analysis are verified using a 3D CFD magnetohydrodynamics (MHD) analysis which uses heat and particle flux from SOLPS as a boundary condition. In addition to plasma heat flux, both analytical and CFD temperature models include several plasma material interaction effects, such as lithium evaporation, condensation and sputtering based on deuterium target flux. New adatom sputtering model based on the available experimental data is presented. Analytical model is expanded to include free surface axisymmetric configurations. Results of parametric studies of the divertor configurations with different lithium inlet temperature and velocity will be presented leading to the optimal design resulting in the lowest possible lithium contamination in the core.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Surface Segregation of Liquid Metal Plasma-Facing Component Alloys: A ReaxFF Investigation

Engineering liquid metal alloys offers a transformative pathway for plasma-facing components by enabling chemically tailored surfaces that can simultaneously optimize plasma-material interactions, reduce divertor heat flux, and enhance core plasma confinement, thereby advancing the commercial viability of nuclear fusion power plants. This study, employing an atomistic simulation approach, provides direct evidence that incorporating nonmetal surface-active agents (such as O and H, or their combination) enables strong surface segregation. This capability makes tin−aluminum (Sn−Al) and tin−lithium (Sn−Li) alloys, with suitable compositions, good candidates for PFC applications. Specifically, the presence of low-Z solutes (Li, Al) leads to preferential surface enrichment, which imparts low-Z sputtering characteristics, while the Sn solvent maintains thermophysical stability. To systematically examine this behavior, we developed a ReaxFF force field spanning the full Sn/Al/Li/O/H chemistry, validated it against formation energies and elastic constants, and applied it in reactive molecular dynamics simulations at fusion-relevant temperatures. We also introduced an overlapbased segregation index that captures interfacial compositional separation directly from atomistic density distributions. Here, this metric reveals a clear hierarchy of segregation regimes and provides a unified view across all systems studied. Together, these findings establish a mechanistic link between nonmetal chemistry and interfacial structure, providing a predictive framework for designing self-adaptive, low-sputtering liquid metal alloys for fusion applications.

Alloys↗