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DOE OSTI2023

Neutrino signatures of 100 2D Axisymmetric Core-Collapse Supernova Simulations

ABSTRACT We present in this paper a public data release of an unprecedentedly large set of core-collapse supernova (CCSN) neutrino emission models, comprising 100 detailed 2D axisymmetric radiation-hydrodynamic simulations evolved out to as late as ∼5 s post-bounce and spanning an extensive range of massive-star progenitors. The motivation for this paper is to provide a physically and numerically uniform benchmark data set to the broader neutrino detection community to help it characterize and optimize subsurface facilities for what is likely to be a once-in-a-lifetime galactic supernova burst event. With this release, we hope to (1) help the international experiment and modelling communities more efficiently optimize the retrieval of physical information about the next galactic CCSN, (2) facilitate the better understanding of core-collapse theory and modelling among interested experimentalists, and (3) help further integrate the broader supernova neutrino community.

Astronomy & Astrophysics↗

DOE OSTI2024

Dopant Segregation in Single-Crystal Optical Fiber Grown via the Laser-Heated Pedestal Growth Technique

Single crystal (SC) optical fiber has promising potential to be used for optical fiber sensing applications in harsh conditions due to its robustness to high temperature, high radioactivity, and resistance to chemical corrosion as compared to optical sensors using silica fiber. However, SC fiber grown via the laser-heated pedestal growth (LHPG) technique innately does not have a core-cladding structure found in standard optical fiber, resulting in optical losses. In this work we investigate optimization of the growth parameters of a two LHPG process used to grow SC fiber with a graded index via introduction of dopants to the feedstock material. Feedstock material is fabricated with the first LHPG device, then sol-gel dip-coated to create outer films of dopant material. The dip-coated feedstock is used to grow SC fiber in which segregation of the dopant constituents occurs, resulting in a graded index of refraction across the fiber, and an effective core-cladding structure. Hardware and software improvements to both LHPG systems are presented and the growth parameters for short pieces of ~320-330 μm diameter YAG fiber has been established. Characterization techniques/procedures have also been established for future grown SC fiber. These improvements and preparations are anticipated to result in a significant increase in grown fiber quality with a similar growth rate to that previously established.

Lander, Gary↗

DOE OSTI2024

Dopant Segregation in Single-Crystal Optical Fiber Grown via the Laser-Heated Pedestal Growth Technique

Lander, Gary↗

DOE OSTI2020

Electronic structure and oxophilicity optimization of mono-layer Pt for efficient electrocatalysis

The slow kinetics of the anodic hydrogen oxidation reaction (HOR) in alkaline medium is one of the limitations for anion exchange membrane fuel cells (AEMFCs). Hence, accurately regulate and understand catalytic interface structure are essential to solve this bottleneck and reveal the structure-activity relationship. In this work, a novel trimetal core-shell model with mono-layer Pt-shell is employed for hydrogen electrooxidation to avoid thermodynamic driven bulk/surface composition deviation. On account of the atomic radius discrepancies of 3d-transition metals M (M = Fe, Co and Cu), the electronic structure of mono-layer Pt is regulated by the strain-engineered Pd-M core and the electrocatalytic activity for HOR is tuned accordingly. Nevertheless, step-by-step electrochemical monitoring and surface-treatment experiments indicate that the oxophilicity optimization by low-valence M(OH) x species, rather than the hydrogen binding energy (HBE) optimization caused by strain engineering, influence the activity obviously. It is mainly derived from the enhanced adsorption of OH ad and accelerated desorption of the H ad . The trimetal core-shell model breathes new life into the low-Pt catalyst design for hydrogen electrooxidation reaction.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2019

Optimizing multi-modal, non-axisymmetric plasma response metrics with additional coil rows on DIII-D

The expansion of the DIII-D tokamak operational space via the addition of new non-axisymmetric coil rows is investigated using the linear MHD plasma response code MARS-F. The plasma response to magnetic perturbations imposed by five distinct low- and high-field side coil geometries is modeled for toroidal mode numbers up to n = 6. A set of linear (~δB^2: resonant, kink mode amplitude) and quadratic (~δB: core and edge integrated NTV torque) plasma metrics are defined and compared directly for the various coil geometries. Coil size is also scanned as a secondary optimization variable. An in-vessel coil located at the low-field side midplane is identified as the most efficient plasma response actuator across all metrics and toroidal mode numbers. The multi-row combination of this new midplane (M) coil with the existing DIII-D non-axisymmetric coil set is considered in numerical optimization studies to quantify the impact of this new coil on modeled plasma response metrics. The addition of the M coil is shown to significantly increase the actuator efficiency in maximizing individual plasma response metrics as well as maximizing multi-modal ratios of response metrics, e.g. maximizing resonant modes or edge NTV torque while minimizing kink modes or core NTV torque. The ex-vessel midplane (C) coil is also observed to have an outsize effect on multi-modal optimization due to its uniquely narrow poloidal spectra, and the expansion of optimization space due to the combined use of the two existing in-vessel coil rows with both the M and C coils is notably larger than either coil's individual contribution even though both share similar poloidal locations. This four-row system is expected to greatly extend abilities to understand and optimize the control of transients and rotation on the DIII-D tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

ParaOpt: Automated Application Parameterization and Optimization for the Cloud

The variety of instance types available on cloud platforms offers enormous flexibility to match the requirements of applications with available resources. However, selecting the most suitable instance type and configuring an application to optimally execute on that instance type can be complicated and time-consuming. For example, application parallelism flags must match available cores and problem sizes must be tuned to match available memory. As the search space of application configurations can be enormous, we propose an automated approach, called ParaOpt, to automatically explore and tune application configurations on arbitrary cloud instances. ParaOpt supports arbitrary applications, enables use of custom optimization methods, and can be configured with different optimization targets such as runtime and cost. We evaluate ParaOpt by optimizing genomics, molecular dynamics, and machine learning applications with four types of optimizers. We show with as few as 15 parameterized executions of an application, representing between 1.2%-26.7% of the search space, that ParaOpt is able to identify the optimal configuration in 32.7% of experiments and a near-optimal configuration in 83.2% of cases. As a result of using near-optimal configurations, ParaOpt reduces overall execution time by up to 85.8% when compared with using the default configuration.

Wu, Chaofeng↗

DOE OSTI2017

Block-Parallel Data Analysis with DIY2

DIY2 is a programming model and runtime for block-parallel analytics on distributed-memory machines. Its main abstraction is block-structured data parallelism: data are decomposed into blocks; blocks are assigned to processing elements (processes or threads); computation is described as iterations over these blocks, and communication between blocks is defined by reusable patterns. By expressing computation in this general form, the DIY2 runtime is free to optimize the movement of blocks between slow and fast memories (disk and flash vs. DRAM) and to concurrently execute blocks residing in memory with multiple threads. This enables the same program to execute in-core, out-of-core, serial, parallel, single-threaded, multithreaded, or combinations thereof. This paper describes the implementation of the main features of the DIY2 programming model and optimizations to improve performance. DIY2 is evaluated on benchmark test cases to establish baseline performance for several common patterns and on larger complete analysis codes running on large-scale HPC machines.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Studsvik R2 materials test reactor Ad Hoc depletion strategy for the derivation of the fuel isotopic composition of the MPCMIV benchmark

The Ad Hoc Depletion Strategy elaborated by the NINE company, developed in support of the organization of the MPCMIV (Multi-physics Pellet Cladding Mechanical Interaction Validation) benchmark input and output specifications, is presented. This work aims at illustrating the strategy itself and then showing the results obtained with its application over the Studsvik R2 Testing Reactor, which is analyzed in the benchmark. The objective of the application of the strategy is to compute the fuel elements isotopic compositions at the beginning of some core loadings of interest for the benchmark. To this objective, it is necessary to implement first the simulation model of the three single assembly types and perform the infinite lattice depletions, then, to build the full core model and to perform the simulation of the core cycle. All the models and simulations were carried out with the use of the Monte Carlo particle transport code Serpent 2. Finally, the simulations results are assessed against Studsvik isotopic compositions of the fuel elements discharged from the R2 Reactor at the end of the core loading. Several assumptions were necessary during all the steps of the strategy, to overcome the lack of information regarding the core management. For this reason, the solution found at the end of the current analysis may not be completely optimized and further improvements regarding the model assumptions will be tested in a future work. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Parallel simulated annealing with embedded machine learning and multifidelity models for reactor core design

This paper presents extensions to a penalty-free, parallel simulated annealing (SA) algorithm for multi-constrained combinatorial optimization with the aim of embedding multi-fidelity physics models into the annealing procedure. The method uses a low-fidelity, quickly executing model for rapid design space exploration and a high-fidelity model for detailed constraint resolution and on-the-fly bias correction. Machine learning models updated within the annealing procedure were used to bridge the gap between the multi-fidelity models, which led to accurate rapid exploration and efficient detailed constraint resolution. A software implementation of the new multi-fidelity optimization methods, called ML-PSA, was demonstrated on a continuous multi-fidelity optimization problem and a constrained combinatorial PWR lattice design problem. These problems demonstrate some of the features, parallel performance characteristics, and extensible nature of the multi-fidelity SA methods. This paper shows that the developed software and procedure are a general optimization tool that can be applied to a wide variety of scientific and engineering design optimization applications. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Optimizing spectral phase transfer in four-wave mixing with gas-filled capillaries

Four-wave mixing (FWM) in gas-filled hollow-core capillaries, a nonlinear optical process that mixes signal and pump photon frequencies to generate idler frequency photons, offers a method for precise spectral phase transfer from signal to idler at ultrashort timescales and extreme powers. However, this regime is challenged by competing linear and nonlinear dynamics, leading to significant trade-offs between spectral phase transfer and conversion efficiency. Our computational investigation focuses on the upconversion of femtosecond pulses from the infrared (IR) to the ultraviolet (UV), a range notoriously difficult to manipulate. We explore an intermediate energy regime that strikes an optimal balance between FWM-mediated phase-transfer fidelity and nonlinear conversion efficiency. By adjusting the energy ratios and spectral phase profiles of the input signal, we achieve conversion efficiencies of approximately 5-15% while maintaining an effective quasi-linear spectral phase transfer. These findings will contribute to establishing first-principles and scaling laws essential for applications such as high-precision imaging, spectroscopy, quantum transduction, and distributed entangled interconnects, facilitating advanced control of ultrafast photonic and electronic wavepackets in quantum materials with unprecedented spatial and temporal precision.

Zhang, Hao↗

DOE OSTI2025

From Structure to Function: Zn/Mn-Modified Maghemite as an Advanced Nanoplatform for Magnetic Hyperthermia and Radionuclide Therapy

The development of nanoplatforms capable of efficient heat generation and stable radionuclide delivery is essential for effective bimodal cancer therapy. Here, in this study, binary (Fe–M) and ternary (Fe–M–M′) metal oxide nanoparticles were synthesized via a polyol method optimized to produce flower-like γ-Fe 2 O 3 (maghemite) structures, with M and M′ representing Zn and/or Mn. Comprehensive structural and magnetic characterization was conducted to explain the relationship between composition, defect structure, and hyperthermic performance. The analyses revealed that cation substitution induced an Fe-site vacancy, primarily at octahedral positions, leading to local structural distortions, as confirmed by powder X-ray diffraction and pair distribution function analysis. The optimized composition, with Zn/Mn/Fe = 0.040:0.182:1, exhibited the highest concentration of vacancies and structural disorder. These vacancies altered the bonding environment, enhancing magnetic interactions at tetrahedral sites while weakening those at the octahedral positions. The resulting multicore nanoflowers (20–63 nm; core size 13–18 nm) displayed strong heating performance, with intrinsic loss power ranging from 0.34 to 5.77 nHm 2 kg –1 . The optimized sample achieved a temperature increase of 30 °C within 2 min and a specific absorption rate of 369 W g –1 . This composition was further coated with citrate (CA) and successfully radiolabeled with 177 Lu, achieving a radiolabeling yield of 92.7% and excellent stability, thus forming a robust nanoplatform for combined magnetic hyperthermia and radionuclide therapy. Biological evaluation of the optimized S5 composition revealed selective cytotoxicity toward HeLa and LS174 cells, while toxicity was significantly lower to A549, A375, and normal MRC-5 cells. Citrate coating of S5 nanoparticles (S5@CA) drastically reduced their cytotoxicity across all tested cell lines (IC 50 > 200 μg mL –1 ), confirming their enhanced biocompatibility for therapeutic applications. In HeLa cells subjected to magnetic hyperthermia, the viability decreased to approximately 84% after 30 min and 61% after 60 min of treatment, demonstrating the sustained hyperthermic effect at a controlled working temperature of 48 °C. These results underscore the effectiveness of cation substitution and vacancy engineering in tailoring the functional properties of maghemite-based nanomaterials for advanced multimodal cancer therapies.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Dragonfly Rotor Optimization using Machine Learning Applied to an OVERFLOW Generated Airfoil Database

NASA’s 4th New Frontiers Mission is the Titan Dragonfly relocatable lander. This coaxial quadrotor vehicle will be launched on a rocket to Titan in 2028. Following a gravity assisted Earth flyby and an approximate 6-year transit, Dragonfly will enter the Titan atmosphere around 2034 with the goal of exploring Titan’s pre-biotic chemistry and habitability. The multirotor design for this unique application has continually evolved since 2016 with constraints such as Titan’s cryogenic atmosphere at 95 Kelvin (-288 F), gravity 14% that of Earth’s, atmospheric density 440% of standard sea-level air, and the inability to test the entire system together under all these conditions until the first flight on Titan. This paper focuses on rotor design aspects of the Dragonfly lander and introduces a novel framework for multirotor design optimization considering multiple flight conditions. The methodology leverages machine learning methods and is demonstrated in the context of Dragonfly. A new OVERFLOW Machine Learning Airfoil Performance (PALMO) database is first presented. PALMO is then wrapped inside a Bayesian optimization framework and applied to a 4-rotor system (one side of the Dragonfly lander). Training data is generated on each iteration of the optimization using the CAMRAD-II comprehensive analysis software to evaluate successive rotor designs in multiple relevant flight conditions. An optimal design for the 4-rotor system was found with approximately 900 rotor designs analyzed in CAMRAD-II, which required 9 million queries of the PALMO surrogate models. This demonstration case evaluated 10,000,000 potential candidate rotor designs in 5.5 hours on 114 CPU cores using uniform inflow, and in 27.8 hours using the prescribed wake model. This work thus enables mid-fidelity rotor design optimization without requiring access to high-performance computing.

Dragonfly↗

DOE OSTI2025

Design and Analysis of a Mutual Inductance Level Sensor for Liquid Metals

Here, this article describes the design and analysis of an electromagnetic level sensor for use in high-temperature liquid metal systems. The mutual inductance level sensor (MILS) described in this work was fabricated using two single-conductor mineral insulated cables wrapped in a bifilar fashion around a stainless steel tube core and was housed in an isolating thimble that preserved the pressure boundary of the test vessel. Two sensor variations were fabricated that differ only in active length, 1016 and 1778 mm. Experimental data were collected using the 1016-mm sensor (MILS-MKII-040) that demonstrated a sensitivity of 9.2 μ V/mm in a room temperature testing stand that used solid aluminum as a surrogate for liquid metal. Experimental data were collected using the 1778-mm sensor (MILS-MKII-070) that demonstrated a sensitivity of 6.9 μ V/mm in the high-temperature (300 ° C) liquid sodium environment at the mechanisms engineering test loop (METL) of Argonne National Laboratory. The sensor performance was found to be repeatable over the course of several months, with roughly ±1% deviation from nominal output. Finite element models were developed in COMSOL Multiphysics that fully describe each test setup, and the models were validated using experimental data. The validated COMSOL models were used to perform an array of analyses that examined the performance of the sensor in differing environments. Maximizing the coil diameter inside the isolating thimble was found to maximize the signal and sensitivity of the sensor. An optimal operating frequency was found near 1000 Hz using both experimental data and COMSOL. The influence of a metallic thimble surrounding the sensor and a metallic sensor core was quantified and found to be negligible at the optimal operating frequency. The sensitivity of the sensor was quantified when monitoring the level of additional liquid metals. These include lead, lead-bismuth eutectic (LBE), sodium-potassium alloy (NaK), and lithium (in addition to sodium). The sensitivities were quantified using liquid metal properties at 350 ° C and 650 ° C. The geometry of the test stand model, all material properties used in the model, and the results are presented in a manner that allows the reader can replicate the model and perform additional analyses.

COMSOL↗

DOE OSTI2023

Tuning the Intermolecular Electrostatic Interaction toward High-Efficiency and Low-Cost Organic Solar Cells

Organic solar cells (OSCs) have achieved much progress with rapidly increasing power conversion efficiencies (PCEs). It should be noted that the top-performance OSCs are generally consisted of active materials with complex chemical structures, resulting in high costs. Here, combining the material design and morphology control, high-efficiency OSCs are fabricated by a low-cost donor: acceptor blend. A completely non-fused electron acceptor named Tz is designed and synthesized via introducing thiazole units on both sides of a bithiophene core, which shows an outstanding PCE of 13.3% with a typical polythiophene donor. More importantly, optimization guidelines are presented to get excellent morphology for low-cost donor:acceptor systems. Three polythiophenes are selected, poly(3-hexylthiophene) and its two derivatives with electron-withdrawing substitutions (PDCBT and PDCBT-2F), as donors to fabricate the cell devices. The computational and experimental data reveal that decreasing the electrostatic interaction between polythiophene and Tz is the key to getting a suppressed miscibility and thus a high phase purity. Finally, this study provides insight into the molecular design and donor:acceptor matching requirements for high-efficiency and low-cost OSCs.

14 SOLAR ENERGY↗

DOE OSTI2017

Controlled 3D Carbon Nanotube Architecture Coated with MoO x Material by ALD Technique: A High Energy Density Lithium‐Ion Battery Electrode

Due to its high theoretical capacity, energy density, and excellent reversibility with Li/Li + , molybdenum oxide is one of the vastly studied electrode material in lithium‐ion batteries. However, like most of the oxides, it also suffers from poor cyclic stability because of its low electrical conductivity. In 3D core–shell structure prepared by atomic layer deposition coating, it can provide superiority in nanoscale decoration than other deposition methods because of its extreme conformality and precise thickness control on high aspect ratio surfaces. This report illustrates the electrochemical activity of 3D core–shell type amorphous MoO x material coated by atomic layer deposition technique on conducting carbon nanotubes (CNT) scaffold which exhibits excellent overall cell capacity. The obtained capacity is manifold higher than its planar 2D counterpart and that can become an advanced nanoscale fabrication methodology of such 3D nanostructures for electrode preparation. Such binder free MoO x /CNT core–shell electrode structure shows very high and stable electrochemical activity toward Li/Li + system. An optimal thickness of MoO x on CNT is also found out in order to attain the most stable cyclic performance of this nanostructure. A stable reversible areal capacity of 645 µAh cm −2 with specific capacity of 915 mAh g −1 is achieved from optimized MoO x /CNT assembly.

Dhara, Arpan↗

DOE OSTI2019

Simulation and analysis of different approaches towards fiber optic plasmonic sensing for detection of human-liver tissues

Three types of plasmonic sensors are applied for the detection of five types of human-liver tissues (normal N, metastatic MET, non-cancerous metastatic NMET, hepatocellular carcinoma HCC and non-cancerous hepatocellular carcinoma NHCC). The first type of the fiber with seven layers is made by a ZBLAN core surrounded by NaF, silicon, silver, graphene, Al{sub 2}O{sub 3} and liver layers. The second type of the fiber with six layers is similar to the first one but without the graphene layer. The third type of the fiber with five layers is made by a SiO{sub 2} core surrounded by GaP, gold, Al{sub 2}O{sub 3} and liver layers. For optimized thicknesses of the interior layers at a laser wavelength (1.53 μm) one obtains large values of the figure of merit and amplitude sensitivity at an angle very close to the resonance angle. The advantage of the third (second) type of the fiber for normal liver is a large figure of merit (maximum amplitude sensitivity) in comparison with that for the second (third) type of the sensor. For all variants of the sensors, the figure of merit and maximum of the amplitude sensitivity are decreasing in the same order (N, MET, NMET, NHCC and HCC) for the liver tissues.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2017

Cross-scale efficient tensor contractions for coupled cluster computations through multiple programming model backends

Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts to extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

3D field phase-space control in tokamak plasmas

Here, a small relaxation of the axisymmetric magnetic field of a tokamak into a non-axisymmetric three-dimensional (3D) configuration can be effective to control magnetohydrodynamic instabilities, such as edge-localized modes. However, a major challenge to the concept of 3D tokamaks is that there are virtually unlimited possible choices for a 3D magnetic field, and most of them will only destabilize or degrade plasmas by symmetry breaking. Here, we demonstrate the phase-space visualization of the full 3D field-operating windows of a tokamak, which allows us to predict which configurations will maintain high confinement without magnetohydrodynamic instabilities in an entire region of plasmas. We test our approach at the Korean Superconducting Tokamak Advanced Research (KSTAR) facility, whose 3D coils with many degrees of freedom in the coil space make it unique for this purpose. Our experiments show that only a small subset of coil configurations can accomplish edge-localized mode suppression without terminating the discharge with core magnetohydrodynamic instabilities, as predicted by the perturbative 3D expansion of plasma equilibrium and the optimizing principle of local resonance. The prediction provided excellent guidance, implying that our method can substantially improve the efficiency and fidelity of the 3D optimization process in tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗