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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Multimode Strong Coupling in Cavity Optomechanics

Optomechanical systems show great potential as quantum transducers and information storage devices for use in future hybrid quantum networks. In this context, optomechanical strong coupling can enable efficient, high-bandwidth, and deterministic transfer of quantum states. While optomechanical strong coupling has been realized at optical frequencies, it has proven difficult to identify a robust optomechanical system that features the low loss and high coupling rates required for more sophisticated control of mechanical motion. In this paper, we demonstrate strong coupling in a Brillouin-based bulk cavity optomechanical system in both the single-mode and the multimode strong-coupling regime, which leads to a useful device both for applications in quantum information and for investigating decoherence phenomena in bulk acoustic wave resonators. Using nontrivial mode hybridizations in the strong-coupling regime, we create hybridized photonic-phononic modes with lifetimes that are significantly longer than those of the uncoupled system. This surprising lifetime enhancement, which results from the interference of decay channels, showcases the use of multimode strong coupling as a general strategy to control extrinsic decoherence mechanisms. Moreover, phonons supported by such bulk-acoustic-wave resonators have a collection of properties, including high frequencies, long coherence times, and robustness against thermal decoherence, that make this optomechanical system particularly enticing for applications such as quantum transduction and memories. Hence, this system provides access to phenomena in a previously unexplored regime of optomechanical interactions and could serve as an important building block for future quantum devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Windowed multipole representation of R -matrix cross sections

Nuclear cross sections are basic inputs to any nuclear computation. Campaigns of experiments are fitted with the parametric R-matrix model of quantum nuclear interactions, and the resulting cross sections are documented—both pointwise and as resonance parameters (with uncertainties)—in standard evaluated nuclear data libraries (ENDF, JEFF, BROND, JENDL, CENDL, TENDL): these constitute our common knowledge of fundamental low-energy nuclear cross sections. In the past decade, a collaborative effort has been deployed to establish a new nuclear cross-section library format—the Windowed Multipole Library—with the goal of considerably reducing the computational cost of cross-section calculations in nuclear transport simulations. This work lays the theoretical foundations underpinning these efforts. From general R-matrix scattering theory, we derive the windowed multipole representation of nuclear cross sections. Though physically and mathematically equivalent to R-matrix cross sections, the windowed multipole representation is particularly well suited for subsequent temperature treatment of angle-integrated cross sections, in particular Doppler broadening, which is the averaging of cross sections over the thermal motion of the target atoms. Doppler broadening is of critical importance in neutron transport applications, as it ensures the stability of many nuclear reactors (negative thermal reactivity). Yet, Doppler broadening of nuclear cross sections has been a considerable bottleneck for nuclear transport computations, often requiring memory-costly pretabulations. We show that the windowed multipole representation can perform accurate Doppler broadening analytically (up to the first reaction threshold), from which we derive cross-section temperature derivatives to any order—all computable on the fly (without precalculations stored in memory). Furthermore, we here establish a way of converting the R-matrix resonance parameters uncertainty (covariance matrices) into windowed multipole parameters uncertainty. We show that generating stochastic nuclear cross sections by sampling from the resulting windowed multipole covariance matrix can reproduce the cross-section uncertainty in the original nuclear data file. The windowed multipole representation is therefore a novel nuclear physics formalism able to generate Doppler broadened stochastic nuclear cross sections on the fly, unlocking breakthrough computational gains for nuclear computations. Through this foundational paper, we hope to make the windowed multipole representation accessible, reproducible, and usable for the nuclear physics community, as well as provide the theoretical basis for future research on expanding its capabilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Interfacial magnetic characteristics of nearly compensated gadolinium iron garnet

Reports on spin Hall magnetoresistance, magnonic spin currents from thermal gradients, and spin transfertorque magnetic random-access memory using compensated ferrimagnets largely discuss bulk magnetization but lack consideration of depth profiles or interfacial characteristics. Here, magnetic and structural characterization of profiles and interfaces was performed for nearly compensated gadolinium iron garnet (GdIG) thin films. X-ray diffraction and reciprocal space maps show that sputter deposited GdIG on Si is polycrystalline with the desired cubic garnet phase, and GdIG on gadolinium gallium garnet (GGG) is epitaxial with <0.06% compressive strain. Temperature-dependent magnetometry confirms the compensation temperatures of GGG/GdIG and Si/GdIG to be 285 and 260 K, respectively, both near room temperature. Interestingly, these measurements suggest the presence of unsaturated rare-earth moments, which result in a characteristic hysteresis between heating and cooling sequences in the magnetization-temperature curves at zero field. Depth-profile measurements from polarized neutron reflectometry (PNR) indicate up to 91% volume fraction in GdIG on Si. At the interface, PNR reveals a region containing magnetized Fe-doped GGG, a low-density GdIG at the GGG/GdIG interface, and a thin magnetically dead layer at the Si/GdIG interface. Cross-sectional transmission electron microscopy and energy dispersive x-ray spectroscopy confirm the assessment of PNR. In conclusion, the magnetic characteristics of interfacial regions are attributed to intermixing of Fe-Ga at the GGG/GdIG interface and the presence of amorphous Fe-Si at the Si/GdIG interface.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High-throughput phase-field simulations and machine learning of resistive switching in resistive random-access memory

Metal oxide-based Resistive Random-Access Memory (RRAM) exhibits multiple resistance states, arising from the activation/deactivation of a conductive filament (CF) inside a switching layer. Understanding CF formation kinetics is critical to achieving optimal functionality of RRAM. Here a phase-field model is developed, based on materials properties determined by ab initio calculations, to investigate the role of electrical bias, heat transport and defect-induced Vegard strain in the resistive switching behavior, using MO 2- x systems such as HfO 2- x as a prototypical model system. It successfully captures the CF formation and resultant bipolar resistive switching characteristics. High-throughput simulations are performed for RRAMs with different material parameters to establish a dataset, based on which a compressed-sensing machine learning is conducted to derive interpretable analytical models for device performance (current on/off ratio and switching time) metrics in terms of key material parameters (electrical and thermal conductivities, Vegard strain coefficients). These analytical models reveal that optimal performance (i.e., high current on/off ratio and low switching time) can be achieved in materials with a low Lorenz number, a fundamental material constant. This work provides a fundamental understanding to the resistive switching in RRAM and demonstrates a computational data-driven methodology of materials selection for improved RRAM performance, which can also be applied to other electro-thermo-mechanical systems.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Mixing antiferromagnets to tune NiFe-[IrMn/FeMn] interfacial spin-glasses, grains thermal stability, and related exchange bias properties

Spintronics devices and in particular thermally assisted magnetic random access memories require a wide range of ferromagnetic/antiferromagnetic (F/AF) exchange bias (EB) properties and subsequently of AF materials to fulfil diverse functionality requirements for the reference and storage. For the reference layer, large EB energies and high blocking temperature (T{sub B}) are required. In contrast, for the storage layer, mostly moderate T{sub B} are needed. One of the present issues is to find a storage layer with properties intermediate between those of IrMn and FeMn and in particular: (i) with a T{sub B} larger than FeMn for better stability at rest-T but lower than IrMn to reduce power consumption at write-T and (ii) with improved magnetic interfacial quality, i.e., with reduced interfacial glassy character for lower properties dispersions. To address this issue, the EB properties of F/AF based stacks were studied for various mixed [IrMn/FeMn] AFs. In addition to EB loop shifts, the F/AF magnetic interfacial qualities and the AF grains thermal stability are probed via measurements of the low- and high-temperature contributions to the T{sub B} distributions, respectively. A tuning of the above three parameters is observed when evolving from IrMn to FeMn via [IrMn/FeMn] repetitions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Over 50% reduction in the formation energy of Co-based Heusler alloy films by two-dimensional crystallisation

Crystalline formation of high magnetic-moment thin films through low-temperature annealing processes compatible with current semiconductor technologies is crucial for the development of next generation devices, which can utilise the spin degree of freedom. Utilising in-situ aberration corrected electron microscopy, we report a 235 °C crystallisation process for a Co-based ternary Heusler-alloy film whose initial nucleation is initiated by as few as 27 unit cells. The crystallisation occurs preferentially in the 〈111〉 crystalline directions via a two-dimensional (2D) layer-by-layer growth mode; resulting in grains with [110] surface normal and [111] plane facets. This growth process was found to reduce the crystallisation energy by more than 50% when compared to bulk samples whilst still leading to the growth of highly ordered grains expected to give a high degree of spin-polarisation. Our findings suggest that the 2D layer-by-layer growth minimises the crystallisation energy allowing for the possible implementation of highly spin-polarised alloy films into current chip and memory technologies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Radiation Dose–Dependent Hippocampal Atrophy Detected With Longitudinal Volumetric Magnetic Resonance Imaging

Purpose: After radiation therapy (RT) to the brain, patients often experience memory impairment, which may be partially mediated by damage to the hippocampus. Hippocampal sparing in RT planning is the subject of recent and ongoing clinical trials. Calculating appropriate hippocampal dose constraints would be improved by efficient in vivo measurements of hippocampal damage. In this study we sought to determine whether brain RT was associated with dose-dependent hippocampal atrophy. Methods and Materials: Hippocampal volume was measured with magnetic resonance imaging (MRI) in 52 patients who underwent fractionated, partial brain RT for primary brain tumors. Study patients had high-resolution, 3-dimensional volumetric MRI before and 1 year after RT. Images were processed using software with clearance from the US Food and Drug Administration and Conformité Européene marking for automated measurement of hippocampal volume. Automated results were inspected visually for accuracy. Tumor and surgical changes were censored. Mean hippocampal dose was tested for correlation with hippocampal atrophy 1 year after RT. Average hippocampal volume change was also calculated for hippocampi receiving high (>40 Gy) or low (<10 Gy) mean RT dose. A multivariate analysis was conducted with linear mixed-effects modeling to evaluate other potential predictors of hippocampal volume change, including patient (random effect), age, hemisphere, sex, seizure history, and baseline volume. Statistical significance was evaluated at α = 0.05. Results: Mean hippocampal dose was significantly correlated with hippocampal volume loss (r=−0.24, P=.03). Mean hippocampal volume was significantly reduced 1 year after high-dose RT (mean −6%, P=.009) but not after low-dose RT. In multivariate analysis, both RT dose and patient age were significant predictors of hippocampal atrophy (P<.01). Conclusions: The hippocampus demonstrates radiation dose–dependent atrophy after treatment for brain tumors. Quantitative MRI is a noninvasive imaging technique capable of measuring radiation effects on intracranial structures. This technique could be investigated as a potential biomarker for development of reliable dose constraints for improved cognitive outcomes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Operator evolution from the similarity renormalization group and the Magnus expansion

The Magnus expansion is an efficient alternative to solving similarity renormalization group (SRG) flow equations with high-order, memory-intensive ordinary differential equation solvers. The numerical simplifications it offers for operator evolution are particularly valuable for in-medium SRG calculations, though challenges remain for difficult problems involving intruder states. Here we test the Magnus approach in an analogous but more accessible situation, which is the free-space SRG treatment of the spurious bound states arising from a leading-order chiral effective field theory (EFT) potential with very high cutoffs. In this work, we show that the Magnus expansion passes these tests and then use the investigations as a springboard to address various aspects of operator evolution that have renewed relevance in the context of the scale and scheme dependence of nuclear processes. These aspects include SRG operator flow with band- versus block-diagonal generators, universality for chiral EFT Hamiltonians and associated operators with different regularization schemes, and the impact of factorization arising from scale separation. Implications for short-range correlations physics and the possibilities for reconciling high- and low-resolution treatments of nuclear structure and reactions are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

NRC Multiphysics Analysis Capability Deployment FY21: Part 3

This report details the progress and activities of Idaho National Laboratory (INL) on the Nuclear Regulatory Commission (NRC) project “Development and Modeling Support for Advanced Non-Light Water Reactors.” The deliverables completed for this report are: Deliverable 1c: the capability to model gas mixtures was added to Pronghorn. A test problem mimicking the conditions achieved in a depressurized loss of forced cooling (DLOFC) event was solved with both RELAP-5 and Pronghorn. Pronghorn employed a finite vol ume method with the Kurganov-Tadmor discretization. The comparison between the mass fraction spatial profiles computed with RELAP-5 and Pronghorn clearly shows the presence of numerical artifacts (i.e., overly diffusive behavior at low Mach numbers). We confirmed that the problem disappears at higher Mach numbers. We recommend future work on the implementation of a low Mach finite volume formulation to better treat low Mach number problems. Deliverable 2a: we demonstrated two approaches to model the radiation/conduction/natural convection heat transfer across a stagnant gas for the PBMR-400 design using Pronghorn. The first approach is based on the net radiation method, which relies on the computation of view factors with the Multiphysics Object-Oriented Simulation Environment (MOOSE) ray tracing capability. The second method is a traditional thermal resistance approach. The test problems include both 2D and 3D geometries. In all cases, the results show very good agreement during a DLOFC transient. This confirms that the faster thermal resistance method produces solutions that are equivalent to the net radiation method for this geometry. Deliverable 3d: we demonstrated the use of the advection kernel for the delayed neutron precursor equation in Griffin with a 2D MSFR model. The results appear physical but further verification is recommended. We also recommend the addition of conjugate heat transfer to compute the temperatures and model the thermomechanic behavior of the reflectors and other structures. Significant memory and performance issues were encountered in the 3D axisymmetric model. Future work is recommended in this area. Task 8g: this task allows multidimensional MOOSE applications to be coupled to system codes (RELAP-7 and SAM). We implemented a faster multiphysics iteration coupling algorithm, which provides an overall 6× acceleration of the 3D-1D coupling of the core multidi- mensional fluid flow solver and the 1D primary and secondary loop model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Domain Texture of the Orthorhombic Phase of La 2-x Ba x CuO 4

Bragg Coherent Diffraction Imaging (BCDI) experiments have been carried out at the Advanced Photon Source using a new cryostat system developed to achieve high mechanical stability and low vibrations. Here, we measured the (012) LTO Bragg peak which is unique to the low-temperature orthorhombic (LTO) phase of micron-sized crystals of the High-temperature Superconductor La 2-x Ba x CuO 4 (LBCO) to study the formation of structural domains. Each time the sample was cooled into the orthorhombic phase, the diffraction pattern of domains was different. Finally, this confirms the interpretation of pinning of the lower-temperature Charge Density Wave domains observed in coherent resonant X-ray speckle correlation analysis experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Analyzing and modeling the kinetics of amyloid beta pores associated with Alzheimer’s disease pathology

Amyloid beta (Aβ) oligomers associated with Alzheimer’s disease (AD) form Ca 2+ -permeable plasma membrane pores, leading to a disruption of the otherwise well-controlled intracellular calcium (Ca 2+ ) homeostasis. The resultant up-regulation of intracellular Ca 2+ concentration has detrimental implications for memory formation and cell survival. The gating kinetics and Ca 2+ permeability of Aβ pores are not well understood. We have used computational modeling in conjunction with the ability of optical patch-clamping for massively parallel imaging of Ca 2+ flux through thousands of pores in the cell membrane of Xenopus oocytes to elucidate the kinetic properties of Aβ pores. The fluorescence time-series data from individual pores were idealized and used to develop data-driven Markov chain models for the kinetics of the Aβ pore at different stages of its evolution. Our study provides the first demonstration of developing Markov chain models for ion channel gating that are driven by optical-patch clamp data with the advantage of experiments being performed under close to physiological conditions. As a result, we demonstrate the up-regulation of gating of various Ca 2+ release channels due to Aβ pores and show that the extent and spatial range of such up-regulation increases as Aβ pores with low open probability and Ca 2+ permeability transition into those with high open probability and Ca 2+ permeability.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2013

A Mars Sample Return Sample Handling System

We present a sample handling system, a subsystem of the proposed Dragon landed Mars Sample Return (MSR) mission [1], that can return to Earth orbit a significant mass of frozen Mars samples potentially consisting of: rock cores, subsurface drilled rock and ice cuttings, pebble sized rocks, and soil scoops. The sample collection, storage, retrieval and packaging assumptions and concepts in this study are applicable for the NASA's MPPG MSR mission architecture options [2]. Our study assumes a predecessor rover mission collects samples for return to Earth to address questions on: past life, climate change, water history, age dating, understanding Mars interior evolution [3], and, human safety and in-situ resource utilization. Hence the rover will have "integrated priorities for rock sampling" [3] that cover collection of subaqueous or hydrothermal sediments, low-temperature fluidaltered rocks, unaltered igneous rocks, regolith and atmosphere samples. Samples could include: drilled rock cores, alluvial and fluvial deposits, subsurface ice and soils, clays, sulfates, salts including perchlorates, aeolian deposits, and concretions. Thus samples will have a broad range of bulk densities, and require for Earth based analysis where practical: in-situ characterization, management of degradation such as perchlorate deliquescence and volatile release, and contamination management. We propose to adopt a sample container with a set of cups each with a sample from a specific location. We considered two sample cups sizes: (1) a small cup sized for samples matching those submitted to in-situ characterization instruments, and, (2) a larger cup for 100 mm rock cores [4] and pebble sized rocks, thus providing diverse samples and optimizing the MSR sample mass payload fraction for a given payload volume. We minimize sample degradation by keeping them frozen in the MSR payload sample canister using Peltier chip cooling. The cups are sealed by interference fitted heat activated memory alloy caps [5] if the heating does not affect the sample, or by crimping caps similar to bottle capping. We prefer cap sealing surfaces be external to the cup rim to prevent sample dust inside the cups interfering with sealing, or, contamination of the sample by Teflon seal elements (if adopted). Finally the sample collection rover, or a Fetch rover, selects cups with best choice samples and loads them into a sample tray, before delivering it to the Earth Return Vehicle (ERV) in the MSR Dragon capsule as described in [1] (Fig 1). This ensures best use of the MSR payload mass allowance. A 3 meter long jointed robot arm is extended from the Dragon capsule's crew hatch, retrieves the sample tray and inserts it into the sample canister payload located on the ERV stage. The robot arm has capacity to obtain grab samples in the event of a rover failure. The sample canister has a robot arm capture casting to enable capture by crewed or robot spacecraft when it returns to Earth orbit

Wilson, David↗
DOE OSTI2012

Program Development Tools and Infrastructures: Activities by ASC CSSE/CCE and Partners

Exascale class machines will exhibit a new level of complexity: they will feature an unprecedented number of cores and threads, will most likely be heterogeneous and deeply hierarchical, and offer a range of new hardware techniques (such as speculative threading, transactional memory, programmable prefetching, and programmable accelerators), which all have to be utilized for an application to realize the full potential of the machine. Additionally, users will be faced with less memory per core, fixed total power budgets, and sharply reduced MTBFs. At the same time, it is expected that the complexity of applications will rise sharply for exascale systems, both to implement new science possible at exascale and to exploit the new hardware features necessary to achieve exascale performance. This is particularly true for many of the NNSA codes, which are large and often highly complex integrated simulation codes that push the limits of everything in the system including language features. To overcome these limitations and to enable users to reach exascale performance, users will expect a new generation of tools that address the bottlenecks of exascale machines, that work seamlessly with the (set of) programming models on the target machines, that scale with the machine, that provide automatic analysis capabilities, and that are flexible and modular enough to overcome the complexities and changing demands of the exascale architectures. Further, any tool must be robust enough to handle the complexity of large integrated codes while keeping the user's learning curve low. With the ASC program, in particular the CSSE (Computational Systems and Software Engineering) and CCE (Common Compute Environment) projects, we are working towards a new generation of tools that fulfill these requirements and that provide our users as well as the larger HPC community with the necessary tools, techniques, and methodologies required to make exascale performance a reality.

43 PARTICLE ACCELERATORS↗
NASA NTRS2009

Initial Results from the Vector Electric Field Investigation on the C/NOFS Satellite

Initial results are presented from the Vector Electric Field Investigation (VEFI) on the Air Force Communication/Navigation Outage Forecasting System (C/NOFS) satellite, a mission designed to understand, model, and forecast the presence of equatorial ionospheric irregularities. The VEFI instrument includes a vector DC electric field detector, a fixed-bias Langmuir probe operating in the ion saturation regime, a flux gate magnetometer, an optical lightning detector, and associated electronics including a burst memory. The DC electric field detector has revealed zonal and meridional electric fields that undergo a diurnal variation, typically displaying eastward and outward-directed fields during the day and westward and downward-directed fields at night. In general, the measured DC electric field amplitudes are in the 0.5-2 mV/m range, corresponding to I3 x B drifts of the order of 30-150 m/s. What is surprising is the high degree of large-scale (10's to 100's of km) structure in the DC electric field, particularly at night, regardless of whether well-defined spread-F plasma density depletions are present. The spread-F density depletions and corresponding electric fields that have been detected thus far have displayed a preponderance to appear between midnight and dawn. Associated with the narrow plasma depletions that are detected are broad spectra of electric field and plasma density irregularities for which a full vector set of measurements is available for detailed study. On some occasions, localized regions of low frequency (< 8 Hz) magnetic field broadband irregularities have been detected, suggestive of filamentary currents, although there is no one-to-one correspondence of these waves with the observed plasma density depletions, at least within the data examined thus far. Finally, the data set includes a wide range of ELF/VLF/HF waves corresponding to a variety of plasma waves, in particular banded ELF hiss, whistlers, and lower hybrid wave turbulence triggered by lightning-induced sferics. The VEFI data set represents a treasure trove of measurements that are germane to numerous fundamental aspects of the electrodynamics and irregularities inherent to the Earth's low latitude ionosphere.

Pfaff, R.↗
DOE OSTI2020

Normal or abnormal? Machine learning for the leakage detection in carbon sequestration projects using pressure field data

The international commitments for atmospheric carbon reduction will require a rapid increase in carbon capture and storage (CCS) projects. The key to any successful CCS project lies in the long term storage and prevention of leakage of stored carbon dioxide (CO 2 ). In addition to being a greenhouse gas, CO 2 leaks reaching the surface can accumulate in low-lying areas resulting in a serious health risk. Among several alternatives, some of the more promising CCS storage formations are depleted oil and gas reservoirs, where the reservoirs had good geological seals prior to hydrocarbon extraction. With more CCS wells coming online, it is imperative to implement permanent, automated monitoring tools. We apply machine learning models to automate the leakage detection process in carbon storage reservoirs using rates of (CO 2 ) injection and pressure data measured by simple harmonic pulse testing (HPT). To validate the feasibility of this machine learning based workflow, we use data from HPT experiments carried out in the Cranfield oil field, Mississippi, USA. The data consist of a series of pulse tests conducted with baseline parameters and with an artificially introduced leak. Here, in this study, we pose the leakage detection task as an anomaly detection problem where deviation from the predicted behavior indicates leaks in the reservoir. Results show that different machine learning architectures such as multi-layer feed forward network, Long Short-Term Memory, and convolutional neural network are able to identify leakages and can provide early warning. These warnings can then be used to take remedial measures.

58 GEOSCIENCES↗
DOE OSTI2014

Charging and Heating Dynamics of Nanoparticles in Nonthermal Plasmas

The focus of this award was to understand the interactions of nanometer-sized particles with ionized gases, also called plasmas. Plasmas are widely used in the fabrication of electronic circuits such as microprocessors and memory devices, in plasma display panels, as well as in medical applications. Recently, these ionized gases are finding applications in the synthesis of advanced nanomaterials with novel properties, which are based on nanometer-sized particulate (nanoparticles) building blocks. As these nanoparticles grow in the plasma environment, they interact with the plasmas species such as electrons and ions which critically determines the nanoparticle properties. The University of Minnesota researchers conducting this project performed numerical simulations and developed analytical models that described the interaction of plasma-bound nanoparticles with the plasma ions. The plasma ions bombard the nanoparticle surface with substantial energy, which can result in the rearrangement of the nanoparticles’ atoms, giving them often desirable structures at the atomic scale. Being able to tune the ion energies allows to control the properties of nanoparticles produced in order to tailor their attributes for certain applications. For instance, when used in high efficiency light emitting devices, nanoparticles produced under high fluxes of highly energetic ions may show superior light emission to particles produced under low fluxes of less energetic ions. The analytical models developed by the University of Minnesota researchers enable the research community to easily determine the energy of ions bombarding the nanoparticles. The researchers extensively tested the validity of the analytical models by comparing them to sophisticated computer simulations based on stochastic particle modeling, also called Monte Carlo modeling, which simulated the motion of hundreds of thousands of ions and their interaction with the nanoparticle surfaces. Beyond the scientific intellectual merits, this award had significant broader impacts. Two graduate students received their doctoral degrees and both have joined a U.S. manufacturer of plasma-based semiconductor processing equipment. Four undergraduate students participated in research conducted under this grant and gained valuable hands-on laboratory experience. A middle school science teacher observed research conducted under this grant and developed three new course modules that introduce middle school students to the concepts of nanometer scale, the atomic structure of matter, and the composition of matter of different chemical elements.

42 ENGINEERING↗
DOE OSTI2025

ChatPORT: Fine-Tuned LLM for Easy Code {PORT}ing

Fine-tuning existing LLMs for specialized tasks has become a very attractive alternative due to its low cost and quick development cycle. With many pre-trained LLMs available, it is an increasingly complex task to choose the correct model as the starting point or base model. In this work we discuss ChatPORT - a specialized fine-tuned LLM geared towards providing correctly translated codes from one programming model to another. We evaluate a number of base models and compare and contrast their features and characteristics that make them a viable starting point. In this paper, we focus on the OpenMP offload porting capabilities of ChatPORT. We build our training data using kernels from the Heterogeneous Computing Benchmarks (HeCBench) [12] and the OpenMP Validation and Verification suite [5] to fine-tune the base models. We then test the model using unseen kernels extracted from the HeCBench benchmark suite. Our results show that: (1) not all open LLMs geared towards HPC are aware of programming models like OpenMP, (2) although all base models benefit from fine-tuning they learn differently and produce different correctness rates, (3) depending on the memory size and compute resource available, different base models can be used for fine-tuning without significantly affecting the quality of transpiled code they generate, (4) fine-tuning improved the correctness rate of the LLM by an average of 43.2%, and (5) feedback-based training data further increased the correctness rate by an average of 6% over the LLMs tested.

Pophale, Swaroop [ORNL] (ORCID:0000000185446367)↗
DOE OSTI2019

Giant enhancement of the magnetocaloric response in Ni–Co–Mn–Ti by rapid solidification

Magnetocaloric refrigeration is a solid-state cooling approach that assures high energy efficiency and low environmental impact. It remains uncompetitive with conventional vapor-compression technologies due to lack of high-performing materials that exhibit large magnetocaloric effects in low magnetic fields. In this work we report a game-changing enhancement of the magnetocaloric response in a transition-metal-based Ni–Co–Mn–Ti. Mechanically and chemically stable rapidly solidified ribbons exhibit magnetic entropy changes as high as ~27J·kg –1 K –1 for a moderate field change of 2T, comparable to or larger than the best known materials for near-room temperature applications. The ribbons can be easily manufactured in large quantities and the transition temperature can be adjusted by varying Co concentration.

36 MATERIALS SCIENCE↗