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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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Temperature modulation was demonstrated as a novel way to control water partitioning during the reaction of silicate minerals with water-saturated supercritical carbon dioxide.
The Co-rich end of the Co–Tb binary phase diagram (Co x Tb 1−x , x = 0.66–0.82) has been investigated to understand the phases which form in the bulk and how they interact to yield magnetic behavior which has been reported to be ideal for use in spintronic devices. Here, this work shows that the phases and phase fractions present across this composition range follow those predicted by the binary phase diagram, and all compounds in this composition range are multiphase. Magnetic measurements show similar behavior in this composition range to related thin film work, and we attribute the observed behavior to the respective binary phases present in each compound. Ideal magnetic behavior of minimized magnetic saturation and maximized coercivity is observed in the range of x= 0.78 − 0.80 related to the majority phase Co 7 Tb 2 in these two compounds. High pressure magnetic measurements show magnetic saturation and coercivity at 300 K change little with respect to external pressure. The extension of the synthesis of these binaries into the bulk allows for specific binary phases to be targeted and analyzed for consideration in future devices.
We report on the effect of epitaxial strain on magnetic and optical properties of perovskite LaCrO 3 (LCO) single crystal thin films. Epitaxial LCO thin films are grown by pulsed laser deposition on proper choice of substrates to impose different strain states. A combined experimental and theoretical approach is used to demonstrate the direct correlation between lattice-strain and functional properties. The magnetization results show that the lattice anisotropy plays a critical role in controlling the magnetic behavior of LCO films. The strain induced tetragonality in the film lattice strongly affects the optical transitions and charge transfer gap in LCO. This study opens possibilities to tailor the functional properties of LCO and related materials by strain engineering in epitaxial growth.
Motivated by recent observations of threefold rotational symmetry breaking in twisted moiré systems, cold-atom optical lattices, quantum Hall systems, and triangular antiferromagnets, we phenomenologically investigate the strain-temperature phase diagram of the electronic 3-state Potts-nematic order. While in the absence of strain the quantum Potts-nematic transition is first-order, quantum critical points (QCP) emerge when uniaxial strain is applied, whose nature depends on whether the strain is compressive or tensile. In one case, the nematic amplitude jumps between two non-zero values while the nematic director remains pinned, leading to a symmetry-preserving metanematic transition that terminates at a quantum critical end-point. For the other type of strain, the nematic director unlocks from the strain direction and spontaneously breaks an in-plane twofold rotational symmetry, which in twisted moiré superlattices triggers an electric polarization. Such a piezoelectric transition changes from first to second-order upon increasing strain, resulting in a quantum tricritical point. Using a Hertz-Millis approach, we show that these QCPs share interesting similarities with the widely studied Ising-nematic QCP. The existence of three minima in the nematic action also leaves fingerprints in the strain-nematic hysteresis curves, which display multiple loops. At non-zero temperatures, because the upper critical dimension of the 3-state Potts model is smaller than three, the Potts-nematic transition is expected to remain first-order in 3D, but to change to second-order in 2D. As a result, the 2D strain-temperature phase diagram displays two first-order transition wings bounded by lines of critical end-points or tricritical points, reminiscent of the phase diagram of metallic ferromagnets. Furthermore, we discuss how our results can be used to unambiguously identify spontaneous Potts-nematic order.
Abstract not provided.
Proportional-integral-derivative (PID) controllers in water resource recovery facilities (WRRFs) feedback control loops are commonplace. While simple to implement, such control loops are rarely tuned optimally or systematically. Heuristic tuning approaches are commonly applied with varying degrees of success using trial-and-error, ad hoc tuning rules, or duplication of tuning values from a similar system. However, there are effective methods, such as lambda tuning, produce acceptable tuning with limited effort. These are based on the step-response method, where a manual process perturbation is used to define the relationship between the manipulated and controlled variables. Based on such an experiment, a simple process model is constructed and used to determine the controller tuning values. In this work, we used the step-response method and lambda tuning for two control systems in full-scale WRRFs. This led to responsive and stable behavior of the controlled system as defined by the absolute average error of the controlled variable to setpoint and standard deviation of the manipulated variable. Tuning of feedback control loops can be completed successfully through a systematic approach, and this work suggests that tuning tools, like lambda, should be part of all wastewater treatment control engineers' toolbox.
Time-dependent density functional theory (TDDFT) combined with range-separated hybrid (RSH) functionals and a tuned range-separation parameter γ offers a computationally economical approach for high-throughput excited- state property predictions. The γ-tuning procedure in the gas phase is well established. However, no agreement on the best γ- tuning procedure has been made when considering the solvent effect with implicit solvent models like the polarizable continuum model (PCM). To answer that question, this study created a diverse dataset with 937 molecules with experimental solutionphase UV/vis absorption spectra. Three γ-tuning methods, the gasphase γ-tuning (GPγT), the partial vertical γ-tuning (PVγT), and the strict vertical γ-tuning (SVγT), were evaluated for the ωPBEh functional over the entire dataset. Additional benchmarks are done for the optimally tuned screened range-separated hybrid combined with the PCM approach (SRSH-PCM) and the solvation-mediated tuning procedure (sol-med-OT). Our findings revealed that the optimal γ-values obtained by the PVγT and the SVγT are significantly smaller than the GPγT. This trend holds consistently across all molecules in our dataset, and we explained the origin of this phenomenon. TDDFT calculations with PVγTand SVγT-tuned γ-values and default global Fock exchange fraction achieve superior performance compared to those using GPγTtuned or default γ and slightly outperform SRSH-PCM and sol-med-OT with similar or lesser computational cost. Furthermore, we found that the smaller γ-values from SVγT captured the expected 1/(εR) asymptotic behavior in the solution phase, resulting in accurate prediction of solution-phase CT excitations, consistent with the screened asymptote behavior encoded in SRSH-PCM. These results show that SVγT is the best scheme for high-throughput UV/vis absorption spectrum calculations using the ωPBEh functional from a data-driven perspective.
The Headquarters Department of the Army (HQDA) sponsored a study to determine the national impact of deploying the Re-tuning™ methodology in 5 buildings types that account for over 40% of the Army’s conditioned building stock. Re-tuning is a systematic process that improves operational efficiency and reduces energy consumption at no- or low-cost through the building automation system (BAS) by correcting operational problems that plague buildings. The study relied on successful demonstration of the re-tuning methodology at 4 pilot US Army installations that informed a holistic effort that included simulating 12 individual re-tuning energy efficiency measures (EEMs) and 6 packages of EEMs in 5 selected Army building prototype models that represent 311 million ft2 (28.9 million m2) of the Army’s conditioned floor space. Both the baseline buildings and the packages were customized to capture the expected outcomes of re-tuning a diverse set of buildings. The study highlighted the benefit of individual re-tuning EEMs and economics of implementing packages of EEMs in applicable Army buildings across 16 climates and 2 building vintages. The average whole-building energy savings ranged from 10.8% to 40.5% by building type, with the company operations facility (COF) building having the highest value proposition from re-tuning. In addition, the study reveals that all large office (LO) buildings in the Army are economical to re-tune. The total modeled cost savings potential for re-tuning the five building types across the US Army is $204/1,000 sf ($220/100 m2), or $64M annually. This cost savings represents 5.6% of all the Army’s energy expenditures.
We present parameter sets corresponding to new underlying event tunes for the H erwig7.3 Monte Carlo event generator. The existing H erwig tunes are in good agreement with LHC data, however, they are not typically designed for center-of-mass energies below $\sqrt{𝑠}$ = 300 GeV. The tunes presented in this study can describe midrapidity data collected at the nominal RHIC energy of $\sqrt{𝑠}$ = 200 GeV as well as higher center-of-mass energies utilized by experiments at the LHC and Tevatron. The base “New Haven” tune is developed by fitting minimum-bias simulations of proton-proton ($𝑝𝑝$) collisions to midrapidity identified hadron and jet data from the STAR experiment. The “Nashville” tune includes a separate set of parameters developed by tuning to Tevatron proton-antiproton ($𝑝\bar{𝑝}$) data at $\sqrt{𝑠}$ = 300, 900 and 1960 GeV from CDF, and LHC $𝑝𝑝$ measurements from CMS at $\sqrt{𝑠}$ =7 TeV, in addition to the STAR measurements. Both new tunes demonstrate significant improvements over the recommended default tune currently included in the latest version of H erwig for minimum bias production. As such, we advocate using these tunes for future simulation studies at midrapidity by experimental collaborations at RHIC (STAR and sPHENIX) and the LHC (ALICE, ATLAS, and CMS).
Plastic tuning of multicell superconducting accelerating cavities is crucial in the development cycle of cavities for particle accelerators. Cavities must meet stringent requirements regarding the operating mode frequency, field flatness, and eccentricity before lining them up in a cryomodule string. After dressing bare cavities with helium vessels, the welded vessel prevents access to individual cavity cells disallowing any further localized tuning. Currently, there is no straightforward way to tune dressed cavities other than cutting the vessel and then tuning the bare cavity and dressing it back, which would significantly impact cost and schedule. In this work, we present a novel tuning technique for already jacketed cavities that is non-invasive and cost-effective. The proposed scheme employs pressurized balloons to be temporarily deployed inside the cavity as a means to localize mechanical deformation in specific cells. The proposed tuning technique was successfully utilized to recover a 9-cell 1.3 GHz tesla-style cavity.
Group-IV color centers in diamond have attracted significant attention as solid-state spin qubits because of their excellent optical and spin properties. Among these color centers, the tin-vacancy (Sn-V - ) center is of particular interest because its large ground-state splitting enables long spin coherence times at temperatures above 1 K. However, color centers typically suffer from inhomogeneous broadening, which can be exacerbated by nanofabrication-induced strain, hindering the implementation of quantum nodes emitting indistinguishable photons. Although strain and Raman tuning have been investigated as promising tuning techniques to overcome the spectral mismatch between distinct group-IV color centers, other approaches need to be explored to find methods that can offer more localized control without sacrificing emission intensity. Here, we study the electrical tuning of Sn-V - centers in diamond via the direct-current Stark effect. We demonstrate a tuning range beyond 1.7 GHz. We observe both quadratic and linear dependence on the applied electric field. Further, we also confirm that the tuning effect we observe is a result of the applied electric field and is distinct from thermal tuning due to Joule heating. Stark tuning is a promising avenue toward overcoming detunings between emitters and enabling the realization of multiple identical quantum nodes.
High-energy physics experiments studying neutrinos rely heavily on simulations of their interactions with atomic nuclei. Limitations in the theoretical understanding of these interactions typically necessitate ad hoc tuning of simulation model parameters to data. Traditional tuning methods for neutrino experiments have largely relied on simple algorithms for numerical optimization. While adequate for the modest goals of initial efforts, the complexity of future neutrino tuning campaigns is expected to increase substantially, and new approaches will be needed to make progress. In this paper, we examine the application of simulation-based inference (SBI) to the neutrino interaction model tuning for the first time. Using a previous tuning study performed by the MicroBooNE experiment as a test case, we find that our SBI algorithm can correctly infer the tuned parameter values when confronted with a mock data set generated according to the MicroBooNE procedure. This initial proof-of-principle illustrates a promising new technique for next-generation simulation tuning campaigns for the neutrino experimental community.
The Mu2E experiment will measure the ratio of the rate of the neutrinoless, coherent conversion of muons into electrons as a measure of Charged Lepton Flavor Violation. As part of the Mu2E experiment, a proton storage ring, called the Delivery Ring, will utilize resonant extraction to slow-spill protons to the experiment. To regulate and optimize the Delivery Ring resonant extraction process, a fast tune measurement scheme will be required. This Mu2E tune meter will measure the average tune and the tune spectrum, in multiple time slices, through the entire resonant extraction cycle of nominally 43 msec. The Mu2E tune meter system utilizes vertical and horizontal 21.4 MHz Schottky detector resonant pickups, taken from the decommissioned Tevatron, high-gain amplifiers and digital down-conversion FPGA logic for its signal processing. This paper will present the design of this Schottky tune meter as well as tune measurements from the Mu2E delivery ring.
High-energy physics experiments studying neutrinos rely heavily on simulations of their interactions with atomic nuclei. Limitations in the theoretical understanding of these interactions typically necessitate ad hoc tuning of simulation model parameters to data. Traditional tuning methods for neutrino experiments have largely relied on simple algorithms for numerical optimization. While adequate for the modest goals of initial efforts, the complexity of future neutrino tuning campaigns is expected to increase substantially, and new approaches will be needed to make progress. In this paper, we examine the application of simulation-based inference (SBI) to the neutrino interaction model tuning for the first time. Using a previous tuning study performed by the MicroBooNE experiment as a test case, we find that our SBI algorithm can correctly infer the tuned parameter values when confronted with a mock data set generated according to the MicroBooNE procedure. This initial proof-of-principle illustrates a promising new technique for next-generation simulation tuning campaigns for the neutrino experimental community.
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.
Polymeric thermal switches that can reversibly tune and significantly enhance their thermal conductivities are desirable for diverse applications in electronics, aerospace, automotives, and medicine; however, they are rarely achieved. Here, we report a polymer-based thermal switch consisting of an end-linked star-shaped thermoset with two independent thermal conductivity tuning mechanisms—strain and temperature modulation—that rapidly, reversibly, and cyclically modulate thermal conductivity. The end-linked star-shaped thermoset exhibits a strain-modulated thermal conductivity enhancement up to 11.5 at a fixed temperature of 60 °C (increasing from 0.15 to 2.1 W m –1 K –1 ). Additionally, it demonstrates a temperature-modulated thermal conductivity tuning ratio up to 2.3 at a fixed stretch of 2.5 (increasing from 0.17 to 0.39 W m –1 K –1 ). When combined, these two effects collectively enable the end-linked star-shaped thermoset to achieve a thermal conductivity tuning ratio up to 14.2. Moreover, the end-linked star-shaped thermoset demonstrates reversible tuning for over 1000 cycles. The reversible two-way tuning of thermal conductivity is attributed to the synergy of aligned amorphous chains, oriented crystalline domains, and increased crystallinity by elastically deforming the end-linked star-shaped thermoset.
Accurate performance calibration of multijunction (MJ) solar cells is critical for advancing this technology toward large-scale terrestrial application, yet existing testing methods developed by photovoltaics calibration laboratories remain prohibitively complex and resource intensive for most research laboratories. Current approaches rely on expensive multisource simulators and/or intricate spectral tuning algorithms, limiting accessibility and hindering standardized comparisons of emerging MJ technologies such as perovskite-based tandems. This paper introduces a streamlined spectral irradiance adjustment method for light-emitting diode (LED)-based solar simulators, which are increasingly adopted in the photovoltaics community due to their versatility and cost-effectiveness. The method we present bins LED channels into groups based on the number of junctions of the MJ photovoltaic device under test (DUT) and their corresponding band gaps and incorporates an automated tuning algorithm that eliminates the need to adjust each channel’s irradiance individually. This tuning algorithm requires the relative spectral responsivities of both the DUT and a broadband reference cell, as well as a calibrated spectroradiometer. Measurement validation across various MJ devices, including III-V and perovskite/silicon tandems, demonstrates excellent agreement within 1% with well-established xenon-tungsten multisource simulators and associated tuning algorithms. By enabling precise spectral tuning with readily available equipment and a simple tuning algorithm, our approach bridges the measurement accuracy gap between research laboratories and accredited testing facilities, fostering more reliable device comparisons and accelerating the translation of MJ technologies into real-world energy systems.
The electromagnetic eigenmodes of the Fermilab Recycler RF cavities were simulated with ACE3P running on NERSC's 'Perlmutter' supercomputer in an attempt to optimize their tuning range to comfortably support slip-stacking. A theory, based on coupled circuits and avoided crossings, was developed to explain the origins of the tuning range for tuner-cavity waveguide systems. This provided a logical, rigorous method to carry out this optimization, although engineering problems due to high voltages in the tuner and the operational $\mu$ range of the garnet had to be carefully implemented. It was shown that the desired goal of 10kHz of tuning was not attainable with the current cavity specifications. The maximum tuning range obtained was 5.59kHz for a single tuner with a coaxial line of length 63in. A double tuner cavity was also studied using the simulation software, although with little improvement in the tuning range. A promising technique to improve the tuning range involving the desynchronization of the garnets' magnetic permeabilities is proposed.