SEARCH · Engineering Papers

Results for “potential yield”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54

All sources NASA NTRS DOE OSTI

DOE OSTI2026

Optimization of the FRIB beam dump: a hybrid genetic algorithm and reinforcement learning approach

The operational envelope of high-power-density systems, such as particle accelerators and advanced nuclear energy systems, is critically constrained by the need to manage extreme thermal loads. To address this, we present a novel hybrid optimization framework combining a genetic algorithm (GA) with a soft actor-critic (SAC) deep reinforcement learning agent. This framework was applied to a practical high-heat-flux problem: redesigning the beam dump at the Facility for Rare Isotope Beams (FRIB) for a power upgrade from 20 kW to 50 kW. The resulting design, validated by three-dimensional conjugate heat transfer simulations, suppresses hazardous hot spots and yields a markedly more uniform temperature distribution. This provides a robust operating margin, increasing the average power-handling capability by 72% relative to the current design, demonstrating the framework’s potential to solve complex thermal management challenges in both accelerator technology and advanced nuclear systems.

Accelerator↗

DOE OSTI2022

Ferric chloride aided peracetic acid pretreatment for effective utilization of sugarcane bagasse

The synergetic impacts of ferric chloride aided peracetic acid (FPA) pretreatment were investigated to enhance the total biomass utilization through effective cellulose conversion and high-quality lignin production. The sugarcane bagasse pretreatment with 2% peracetic acid (PAA) and 0.1 mol/L ferric chloride (FeCl 3 ) effectively removed 57.3% of lignin and 72.2% of xylan while preserving ~ 97% of cellulose from sugarcane bagasse under mild temperature (90 °C). The FPA pretreated sugarcane bagasse was effectively hydrolyzed with a glucose yield of 313.0 mg/g-biomass, which was 4.5 times higher than the yield of untreated biomass (69.75 mg/g-biomass) and 1.6 and 3.6 times higher than that of individual PAA and FeCl 3 pretreated sugarcane bagasse, respectively. The regenerated lignin (FPA lignin) showed great potential for further valorization by preserving the major interunit linkage (up to 86% of β-O-4) without significant carbohydrate contamination and lignin condensation due to its mild reaction conditions. In this paper, the combination of PAA and FeCl 3 synergistically enhanced the pretreatment efficiency on sugarcane bagasse and resulted in high fermentable sugar and high-quality lignin production.

09 BIOMASS FUELS↗

DOE OSTI2024

Martensitic transformation induced strength-ductility synergy in additively manufactured maraging 250 steel by thermal history engineering

Maraging steels are known for their exceptional strength but suffer from limited work hardening and ductility. Here, in this study, we report an intermittent printing strategy to tailor the microstructure and mechanical properties of maraging 250 steel via tuning the thermal history during wire-arc directed energy deposition. By introducing a dwell time between adjacent layers, the maraging 250 steel is cooled below the martensite start temperature, triggering thermally-driven martensitic transformation during the printing process. Thermal cycling during subsequent layer deposition results in the formation of reverted austenite which shows a refined microstructure and induces elemental segregation between martensite and reverted austenite. The Ni enrichment in the austenite promotes stabilization of the reverted austenite upon cooling to room temperature. The reverted austenite is metastable during deformation, leading to strain-induced martensitic transformation under loading. Specifically, a 3 min interlayer dwell time produces a maraging 250 steel with approximately 8% reverted austenite, resulting in improved work hardening via martensitic transformation induced plasticity during deformation. Meanwhile, the higher cooling rate and refined prior austenite grains lead to substantially refined martensitic grains (by approximately fivefold) together with an increased dislocation density. With 3 min interlayer dwell time, the yield strength of the printed maraging 250 steel increases from 836 MPa to 990 MPa, and the uniform elongation is doubled from 3.2% to 6.5%. This intermittent deposition strategy demonstrates the potential to tune the microstructure of maraging steels for achieving strength-ductility synergy by engineering the thermal history during additive manufacturing.

Additive manufacturing↗

DOE OSTI2023

The 12-layer trimer-based hexagonal perovskite Cs 4 Ca 0.7 Mn 3.3 Cl 12

Here, we describe the crystal structure and basic magnetic properties of Cs 4 Ca 0.7 Mn 3.3 Cl 12 , a previously unreported twelve layer (12L-) hexagonal (R-3m) chloride perovskite. Its crystal structure features face sharing MnCl 6 octahedra that form Mn 3 Cl 12 trimers. The trimers, which form a triangular array, are separated by corner sharing to layers of disordered single Ca(Mn)Cl 6 octahedra. The decreased intratrimer Mn–Mn distance yields stronger magnetic coupling within trimers than between trimers. The dominant magnetic interactions are antiferromagnetic (θ CW = –105 K), the effective magnetic moment per Mn 2+ is 6.5 μ B , and potential signatures of magnetic frustration are observed. Behavior consistent with short- and long-range magnetic order is exhibited at approximately 37 and 0.7 K, respectively.

12L-hexagonal perovskite↗

DOE OSTI2024

Microstructural refinement of an Al-Ce-Mg alloy via Shear Assisted Processing and Extrusion

Al-Ce alloys have attracted recent interest because of their high thermal stability due to the low solubility of Ce in the Al matrix. The Al 11 Ce 3 eutectic phase gives excellent strain hardening behavior and moderate high-temperature strength in the as-cast state. However, its strengthening effect is limited by its coarse as-cast structure. Therefore, alternative manufacturing methods such as additive manufacturing or equal channel angular pressing have been applied to refine the Al 11 Ce 3 phase to good effect. However, these techniques are both expensive and time-consuming. Therefore, this study aims to use Shear Assisted Processing and Extrusion (ShAPE), an emerging solid phase processing technique that is more easily scalable than the previously mentioned methods. ShAPE can produce useful cross-sections of an Al-8Ce-4Mg alloy while refining the Al 11 Ce 3 phase to produce a higher strength material. It was found that a low temperature ShAPE process can improve the room temperature yield strength by ~60 % compared to a binary Al-4Mg alloy. Additionally, the high-temperature yield strength of the Al-Ce alloys increased by 20%, with a simultaneous 15% improvement in ductility compared to the binary Al-Mg alloy. Finally, these results highlight the potential for ShAPE as a processing technique for Al-Ce alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Evaluating Ru-RuO 2 @BN as a Bifunctional Electrocatalyst for the Nitrogen Reduction Reaction and the Hydrogen Evolution Reaction

Electrochemical approaches toward clean energy production have been the focus of significant attention. Here, the nitrogen (N 2 ) reduction reaction (NRR) and the hydrogen (H 2 ) evolution reaction (HER) offer a promising method for producing NH 3 and H 2 , respectively. Nevertheless, practical obstacles that must be overcome in creating optimal catalysts are the sluggish kinetics and low selectivity of NRR and HER. Herein, we report on the synthesis of a Ru-RuO 2 -decorated boron nitride (BN) catalyst that shows excellent activity toward NRR. A rate of NH3 formation (V NH3 ) of 16.8 μg h -1 mg -1 and a corresponding Faradaic efficiency (FE) of 52.9% were noted at a potential of −0.5 V in 0.1 M HCl. However, the HER activity of Ru-RuO 2 @BN was found to be highly suppressed in 0.1 M HCl and did not yield a reasonable overpotential value. Thus, the capability of this material toward NRR suggests its viability as a promising catalyst for clean NH 3 production.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2022

Luminescent MOFs (LMOFs): recent advancement towards a greener WLED technology

The replacement of traditional incandescent, halogen and fluorescent lamps by white light emitting diodes (WLEDs) is expected to reduce the global electricity consumption by one-third by 2030, according to the US Department of Energy. The current WLED technology uses rare-earth element (REE) based phosphor materials, which, not only is cost-intensive but also constitutes an environmental concern. Hence, researchers are in a quest for a new-generation of opto-electronic materials that can replace the conventional phosphors in WLEDs and thus aim towards a cleaner and more energy efficient lighting technology for the future. Luminescent metal–organic frameworks (LMOFs) have recently emerged as a new sub-class of MOFs which have demonstrated enormous potential for applications in sensing, imaging, optoelectronics and in solid-state lighting (SSL) technology. LMOFs could be game changers as lighting phosphors due to advantages such as high luminescence quantum yield, tunable excitation and emission which can be achieved by rational design and optimization of metal centers, linkers, and the guest molecules, facile fabrication into devices, and structural robustness. These clear advantageous features of LMOFs make them score over other contemporary materials, and enable them to be futuristic phosphor materials for WLED technology. Here, in this feature article, we will provide an overview of the most recent developments of LMOF-based phosphor materials for SSL with a special focus on WLED technology. The emphasis will be centered around REE-free LMOFs, as the aim is to direct the attention of the readers towards a more viable and greener lighting technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Real-space solution to the electronic structure problem for nearly a million electrons

We report a Kohn–Sham density functional theory calculation of a system with more than 200 000 atoms and 800 000 electrons using a real-space high-order finite-difference method to investigate the electronic structure of large spherical silicon nanoclusters. Our system of choice was a 20 nm large spherical nanocluster with 202 617 silicon atoms and 13 836 hydrogen atoms used to passivate the dangling surface bonds. To speed up the convergence of the eigenspace, we utilized Chebyshev-filtered subspace iteration, and for sparse matrix–vector multiplications, we used blockwise Hilbert space-filling curves, implemented in the PARSEC code. For this calculation, we also replaced our orthonormalization + Rayleigh–Ritz step with a generalized eigenvalue problem step. We utilized all of the 8192 nodes (458 752 processors) on the Frontera machine at the Texas Advanced Computing Center. We achieved two Chebyshev-filtered subspace iterations, yielding a good approximation of the electronic density of states. Our work pushes the limits on the capabilities of the current electronic structure solvers to nearly 106 electrons and demonstrates the potential of the real-space approach to efficiently parallelize large calculations on modern high-performance computing platforms.

Chemistry↗

DOE OSTI2020

Light element ($$Z=1,2$$) production from spontaneous ternary fission of $$^{252}$$Cf

Abstract The yields of light elements ( $$Z=1,2$$ Z = 1 , 2 ) obtained from spontaneous ternary fission of $$^{252}$$ 252 Cf are treated within a nonequilibrium approach, and the contribution of unstable nuclei and excited bound states is taken into account. These light cluster yields may be used to probe dense matter, and to infer in-medium corrections such as Pauli blocking which is determined by the nucleon density. Continuum correlations are calculated from scattering phase shifts using the Beth-Uhlenbeck formula, and the effect of medium modification is estimated. The relevant distribution is reconstructed from the measured yields of isotopes. This describes the state of the nucleon system at scission and cluster formation, using only three Lagrange parameters which are the nonequilibrium counterparts of the temperature and chemical potentials, as defined in thermodynamic equilibrium. We concluded that a simple nuclear statistical equilibrium model neglecting continuum correlations and medium effects is not able to describe the measured distribution of H and He isotopes. Moreover, the freeze-out concept may serve as an important ingredient to the nonequilibrium approach using the relevant statistical operator concept.

Röpke, G.↗

DOE OSTI2023

Advancing the central role of non-model biorepositories in predictive modeling of emerging pathogens

The COVID-19 pandemic demonstrated the insufficiency of a reactive approach to emerging zoonotic pathogens. With spillover increasing in frequency as environments change and the human footprint continues to grow, pandemic prevention will require predictive models that can identify (i) potential zoonoses with a high likelihood of emergence and (ii) environmental or other features that may trigger a shift in host, vector, or pathogen baselines associated with emergence and/or spillover. Artificial intelligence (AI), and particularly its machine learning and deep learning branches, holds enormous potential for detecting shifts in large-scale biodiversity and disease datasets (genomic, ecological, geospatial, etc.). Such algorithms can be trained to identify subtle patterns in large volumes of data to yield insights into complex phenomena for which we have limited knowledge of the true cause(s) or predictor(s), as is the case for emerging infectious diseases.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Economic, Greenhouse Gas, and Resource Assessment for Fuel and Protein Production from Microalgae: 2022 Algae Harmonization Update

This report presents an updated "harmonization study" documenting the collaborative analysis of microalgae cultivation and conversion to fuels and products. Four national laboratory modeling teams reconvened to investigate the resource, economic, and environmental sustainability implications of integrated systems encompassing large-scale algae farms and conversion biorefineries. Relative to prior harmonization analyses conducted by these partners, the present effort focuses on more near-term deployment potential based on the use of nutrient-replete, high-protein algal biomass compositions (more readily achievable today without sacrificing cultivation productivity), though this also incurs challenges in lower fuel yields and accordingly higher costs and carbon intensities for the overall integrated systems. Additionally, the present assessment adds further granularity around carbon dioxide (CO 2 ) sourcing and transport via carbon capture of nearby point sources, as well as handling of high-saline cultivation media and resultant blowdown/disposal processing. Finally, this assessment focuses on conversion opportunities to produce both fuel (prioritizing sustainable aviation fuel, in this case via hydrothermal liquefaction) and protein products for the food and feed markets, recognizing growing needs for such products.

09 BIOMASS FUELS↗

DOE OSTI2024

Machine Learning for DUNE Supernova Trigger

One of the major scientific goals of the Deep Underground Neutrino Experiment (DUNE) is to detect and measure the neutrino flux from galactic core-collapse supernovae. These neutrinos, which exist in the low energy range of up to a few tens of MeV and are responsible for carrying away over 99% of the gravitational binding energy of the supernova, provide an opportunity to study the end of life evolution of massive stars, as well as unique properties and interactions of neutrinos. Because galactic supernovae are expected to occur only on the timespan of every few decades, it is crucial that DUNE is able to detect supernova neutrino interactions when they occur. However, detecting these supernova interactions requires sifting through a large amount of data, and DUNE detectors require a trigger to signal when supernova neutrino events occur. Machine learning provides a potential approach to creating this trigger. This project generates ADC and ground truth images of neutrino interactions in a LArTPC detector as simulated by the Model of Argon Reaction Low Energy Yields (MARLEY) to be used for machine learning. The eventual goal of this work is to facilitate DUNE s detection of supernova neutrino interactions by building a machine learning pipeline that will train the trigger algorithm.

Damish, Stephanie↗

DOE OSTI2023

Bioproduction and Evaluation of Renewable Butyl Acetate as a Desirable Bioblendstock for Diesel Fuel

The objective of this project was to develop an integrated bioprocess for efficient butyl acetate (BA) production through strain development using systematic genome engineering and MicroNiche Engineering™ technology (MNE). BA's potential as a bioblendstock for diesel fuel was evaluated through droplet experiments and Mixing Controlled Compression Ignition (MCCI) engine testing. The project aimed to achieve 30 g/L BA production with a yield of 0.4 g/g and a productivity of 0.6 g/L/h. The suitable composition of the blended fuel (BA/biodiesel) would be determined for MCCI engine application.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Conversion Of Coal To Li-Ion Battery Grade (Potato) Graphite (Final Technical Report)

It was previously shown that biomass could be readily transformed to Li-ion battery grade graphite with performance that is equivalent to commercial graphite. This project extended that result to lignite coal, an abundant and inexpensive resource in the United States. It was found that lignite from North Dakota (ND), following charring and exposure to near-infrared light from a laser in the presence of an iron metal catalyst, graphitizes with high yield, crystallinity and purity. Furthermore, spheroidal (“potato”) shaped graphite agglomerates can be produced from ND lignite with performance that rivals that of commercial graphite. Finally, the process was found to be potentially economical, to that extent that it may be able to disrupt the current market, if the laboratory results obtained under this project can be successfully translated to industrial scale.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2024

Exploiting Modern C++ for Portable Parallel Programming in Lattice QCD Applications

The evolution of ISO C++ standards increasingly serves the needs of scientific computing, offering potential benefits for developing portable applications. The recent revisions of C++ programming language, for instance, introduces a suite of algorithms capable of being executed on accelerators. Although this approach may not yield best performance, it can present a viable balance between code productivity and computational efficiency. In this report, we discuss the implementation of the HISQ operator utilizing a range of features from the C++17/20/23 standards and include an assessment of their performance.

Strelchenko, Alexei↗

DOE OSTI2024

Randomized measurement protocols for lattice gauge theories

Randomized measurement protocols, including classical shadows, entanglement tomography, and randomized benchmarking are powerful techniques to estimate observables, perform state tomography, or extract the entanglement properties of quantum states. While unraveling the intricate structure of quantum states is generally difficult and resource-intensive, quantum systems in nature are often tightly constrained by symmetries. Furthermore, this can be leveraged by the symmetry-conscious randomized measurement schemes we propose, yielding clear advantages over symmetry-blind randomization such as reducing measurement costs, enabling symmetry-based error mitigation in experiments, allowing differentiated measurement of (lattice) gauge theory entanglement structure, and, potentially, the verification of topologically ordered states in existing and near-term experiments. Crucially, unlike symmetry-blind randomized measurement protocols, these latter tasks can be performed without relearning symmetries via full reconstruction of the density matrix.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Machine Learning for DUNE Supernova Trigger

Damish, Stephanie↗

DOE OSTI2025

Electrochemical stability and corrosion behavior of Ni-Cr alloy in molten LiCl-KCl salt

This study investigated the electrochemical properties and potential-dependent stability of Cr(II) and Ni(II) in a eutectic LiCl-KCl molten salt at 500 °C under an argon atmosphere using a three-electrode cell configuration with a glassy carbon working electrode, Ag/Ag + reference electrode, and graphite counter electrode. Cyclic voltammetry was employed to characterize the Cr(0)/Cr(II)/Cr(III) and Ni(0)/Ni(II) redox transitions, yielding diffusion coefficients of 0.50 (±0.01) × 10 −5 cm 2 s −1 for Cr(II) and 0.91 (±0.16) × 10 −5 cm 2 s −1 for Ni(II) at 500 °C. The redox stability domains of these species provided insight into the corrosion mechanisms of a Ni-Cr alloy (80–20 wt %) in LiCl-KCl salt. The measured open circuit potential of the alloy corresponded to the range of potentials where the Ni(0) and Cr(II) species are stable, indicating a preferential dissolution of Cr. Immersion testing of the alloy for 336 h confirmed significant Cr depletion (or Ni-enrichment) at the surface layer, corroborating Cr dealloying as the dominant corrosion reaction under open circuit conditions. Additionally, the application of a small anodic overpotential (0.11 V) resulted in selective Cr dissolution while a large anodic overpotential (0.25 V) resulted in co-dissolution of both Cr and Ni. Furthermore, these results demonstrate that the corrosion mechanisms of a Ni-Cr alloy in LiCl-KCl depend upon the applied potential, and thus the redox conditions of the molten salt should be carefully controlled in the design of a redox buffer to mitigate corrosion in molten salt environments.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗