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Results for “Temperature optimization”

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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Design and optimization of high temperature optocouplers as galvanic isolation

The commercial InGaN-based (blue and green) and AlGaInP-based (red) multiple quantum well (MQW) lighting emitting diodes (LEDs) were studied in a wide range of temperatures up to 800 K for their light emission and detection (i.e., LEDs operated under reverse bias as photodiodes (PDs)) characteristics. The results indicate the feasibility of integrating a pair of selected LEDs to fabricate high temperature (HT) optocouplers, which can be utilized as galvanic isolation to replace the bulky isolation transforms in the high-density power modules. A detailed study on LEDs and PDs were performed. The external quantum efficiency (EQE) of the LED and PDs were calculated. Higher relative external quantum efficiency (EQE) and lower efficiency droops with temperatures are obtained from the blue and green LEDs for display compared with the blue one for lighting and red LED for display. The blue for lighting and red for display devices show superior responsivity, specific detectivity (D*), and EQE compared with blue and green for display when operated as PDs. The results suggest that red LED devices for display can be used to optimize HT optocouplers due to the highest wavelength overlapping compared with others.

42 ENGINEERING↗
DOE OSTI2025

Optimizing the critical temperature and superfluid density of a metal-superconductor bilayer

A promising path to realizing higher superconducting transition temperatures 𝑇 c is the strategic engineering of artificial heterostructures. For example, quantum materials could, in principle, be coupled with other materials to produce a more robust superconducting state. Here, in this work, we add numerical support to the hypothesis that a strongly interacting superconductor weakened by phase fluctuations can boost its 𝑇 c by hybridizing the system with a metal. Using determinant quantum Monte Carlo, we simulate a two-dimensional bilayer composed of an attractive Hubbard model and a metallic layer in two regimes of the interaction strength −|𝑈|. In the strongly interacting regime, we find that increasing the interlayer hybridization 𝑡 ⊥ results in a nonmonotonic enhancement of 𝑇 c , with an optimal value comparable to the maximum 𝑇 c observed in the single-layer attractive Hubbard model, confirming trends inferred from other approaches. In the intermediate coupling regime, when −|𝑈| is close to the value associated with the maximum 𝑇 c of the single-layer model, increasing 𝑡 ⊥ tends to decrease 𝑇 c , implying that the correlated layer was already optimally tuned. Importantly, we demonstrate that the mechanism behind these trends is related to enhancement in the superfluid stiffness, as was initially proposed by Kivelson [Phys. B: Condens. Matter 318, 61 (2002)].

Zhang, Yutan [Univ. of California, Davis, CA (Unit↗
DOE OSTI2026

Long-term thermal stability and calibration of Type-II fiber Bragg grating array inscribed in radiation-hardened fibers

This paper investigates the long-term thermal stability of Type-II fiber Bragg grating (FBG) arrays, inscribed by femtosecond laser in radiation-hardened fiber, for potential applications as multiplexed sensors in high-temperature energy systems. The thermal stability of FBG sensors was assessed through 16 thermal cycles from room temperature (RT) to 750 ℃ about two months, involving 100 FBG sensors. The results show that the absolute temperature drift of FBG sensors can be reduced to less than 0.4 pm/day after 54 h thermal annealing process at a constant temperature of 800 ℃. As temperature sensors, the FBGs demonstrated stable performance, achieving a standard deviation (STD) of 1.8 pm (corresponding to a temperature resolution of 0.118 ℃) post-annealing. Repeated thermal cycles revealed a random drift of 2.3 pm in the FBG wavelength at RT. Polynomial fitting was explored as a calibration method to convert FBG wavelength shifts into absolute temperature measurements. By optimizing calibration temperature points (RT, 200 ℃, 400 ℃, and 750 ℃), the study shows that cubic polynomial calibration using four points yields an average R2 of 0.9997 and an RMSE of 3.58 ℃ across the entire temperature range (RT to 750 ℃). This approach represents an 11.53-fold improvement over empirical slope calibration and a 1.34-fold improvement over four-point piecewise fitting. The findings indicate that Type-II FBGs inscribed in radiation-hardened fibers can function as accurate temperature sensors, with performance on par with or exceeding that of thermocouples. With their multiplexing capability, robust signal transmission over long lead cables, and immunity to electromagnetic interference, FBG sensors offer a promising alternative to traditional electronic sensors for energy system monitoring.

Dominguez-Ontiveros, Elvis [ORNL] (ORCID:000000018↗
DOE OSTI2025

Computational Optimization of Room Temperature Usable Capacity for Hydrogen Storage in MFU-4-Type Metal–Organic Frameworks via Pairwise Metal Substitutions

The efficient storage of hydrogen is a critical challenge in the quest for sustainable energy solutions. Current adsorbent-based methods achieve satisfactory storage densities predominantly under cryogenic temperatures and/or high pressures, which imposes problems with cost-efficient and safe implementation of this technology. Materials that can bind hydrogen gas reversibly at ambient temperatures and more moderate pressures could play a pivotal role in enabling hydrogen-powered technologies. In this study, we use reliable computational modeling to investigate two synthetically feasible paths for tuning the enthalpy of H2 binding in MFU-4-type metal–organic frameworks (MOFs), aiming to maximize usable capacity. This study examines MIM4 IICl3(bta)6 (bta– = benzotriazolate) Kuratowski-type clusters as a model for strong binding sites in MFU-4l frameworks. We systematically evaluate the impact of separately tuning the central MII metal ion (which plays a structural role) and the peripheral MI metal ion (which binds the substrate) on the energetics of H2 binding. Our computational study reveals that H2 binding at an MI site mostly follows the trend AgI < CuI < NiI < CoI < AuI while a larger central MII site generally weakens the H2 binding at a MI site. Importantly, we have identified three new combinations of MI and MII to achieve high fractional usable capacities of the total H2 adsorbed under a pressure swing from 5 to 100 bar at room temperature. Additionally, we examine the nature of the binding interaction between the peripheral metal atom and the hydrogen molecule. While charge transfer predominantly induces this interaction, for several atom combinations, a change in the polarization (associated with variations in the ionic radius of the MI binding atom) is another important factor for adjusting the strength of the interaction. We suggest that the proposed compositions of Kuratowski-type clusters are highly desirable synthetic targets for future laboratory study.

Tkachenko, Nikolay V↗
DOE OSTI2020

Laser-heated capillary discharge plasma waveguides for electron acceleration to 8 GeV

A plasma channel created by the combination of a capillary discharge and inverse Bremsstrahlung laser heating enabled the generation of electron bunches with energy up to 7.8 GeV in a laser-driven plasma accelerator. The capillary discharge created an initial plasma channel and was used to tune the plasma temperature, which optimized laser heating. Although optimized colder initial plasma temperatures reduced the ionization degree, subsequent ionization from the heater pulse created a fully ionized plasma on-axis. The heater pulse duration was chosen to be longer than the hydrodynamic timescale of ≈ 1 ns, such that later temporal slices were more efficiently guided by the channel created by the front of the pulse. Here, simulations are presented which show that this thermal self-guiding of the heater pulse enabled channel formation over 20 cm. The post-heated channel had lower on-axis density and increased focusing strength compared to relying on the discharge alone, which allowed for guiding of relativistically intense laser pulses with a peak power of 0.85 PW and wakefield acceleration over 15 diffraction lengths. Electrons were injected into the wake in multiple buckets and times, leading to several electron bunches with different peak energies. To create single electron bunches with low energy spread, experiments using localized ionization injection inside a capillary discharge waveguide were performed. A single injected bunch with energy 1.6 GeV, charge 38 pC, divergence 1 mrad, and relative energy spread below 2% full-width half-maximum was produced in a 3.3 cm-long capillary discharge waveguide. This development shows promise for mitigation of energy spread and future high efficiency staged acceleration experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Simulation-aided characterization of a versatile water-based condensation particle counter for atmospheric airborne research

Capturing the vertical profiles and horizontal variations of atmospheric aerosols often requires accurate airborne measurements. With the advantage of avoiding health and safety concerns related to the use of butanol or other chemicals, water-based condensation particle counters have emerged to provide measurements under various environments. However, airborne deployments are relatively rare due to the lack of instrument characterization under reduced pressure at flight altitudes. This study investigates the performance of a commercial “versatile” water-based condensation particle counter (vWCPC, model 3789, TSI, Shoreview, MN, USA) under various ambient pressure conditions (500–920 hPa) with a wide range of particle total number concentrations (1500–70 000 cm -3 ). The effect of conditioner temperature on vWCPC 3789 performance at low pressure is examined through numerical simulation and laboratory experiments. We show that the default instrument temperature setting of 30 °C for the conditioner is not suitable for airborne measurement and that the optimal conditioner temperature for low-pressure operation is 27°. Under the optimal conditioner temperature (27°), the 7 nm cut-off size is also maintained. Additionally, we show that insufficient droplet growth becomes more significant under the low-pressure operation. The counting efficiency of the vWCPC 3789 can vary up to 20 % for particles of different chemical compositions (e.g., ammonium sulfate and sucrose particles). However, such variation is independent of pressure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Correlating Macro and Atomic Structure with Elastic Properties and Ionic Transport of Glassy Li 2 S‐P 2 S 5 (LPS) Solid Electrolyte for Solid‐State Li Metal Batteries

Abstract A combination of high ionic conductivity and facile processing suggest that sulfide‐based materials are promising solid electrolytes that have the potential to enable Li metal batteries. Although the Li 2 S‐P 2 S 5 (LPS) family of compounds exhibit desirable characteristics, it is known that Li metal preferentially propagates through microstructural defects, such as particle boundaries and/or pores. Herein, it is demonstrated that a near theoretical density (98% relative density) LPS 75‐25 glassy electrolyte exhibiting high ionic conductivity can be achieved by optimizing the molding pressure and temperature. The optimal molding pressure reduces porosity and particle boundaries while preserving the preferred amorphous structure. Moreover, molecular rearrangements and favorable Li coordination environments for conduction are attained. Consequently, the Young's Modulus approximately doubles (30 GPa) and the ionic conductivity increases by a factor of five (1.1 mS cm −1 ) compared to conventional room temperature molding conditions. It is believed that this study can provide mechanistic insight into processing‐structure‐property relationships that can be used as a guide to tune microstructural defects/properties that have been identified to have an effect on the maximum charging current that a solid electrolyte can withstand during cycling without short‐circuiting.

Garcia‐Mendez, Regina↗
DOE OSTI2021

Optimization of direct aging temperature of Ti free grade 300 maraging steel manufactured using laser powder bed fusion (LPBF)

Maraging steels are of interest to the tool and die industry owing to their high strength, toughness and machinability. Additive manufacturing technologies like laser powder bed fusion (LPBF) can result in a paradigm shift in the design of maraging steel tools. Here, the lack of precipitates, in combination with solute segregation and non-equilibrium microstructure in Grade 300 maraging steel fabricated via LPBF makes the steel amenable to strengthening via direct aging post fabrication instead of the conventional solution treatment and aging. In this study we have focused on optimizing the direct aging temperature for a Ti-free Grade 300 maraging steel fabricated via LPBF for two different aging times. Through strain hardening analysis and detailed microstructural characterization, we show that direct aging at a temperature of 440 °C for 6 h resulted in the best strength-ductility combination. Aging samples at a lower temperature or shorter time resulted in no strain hardening prior to necking as a result of lower fraction of reverted austenite, whereas aging samples at a higher temperature resulted in extensive recrystallization of martensite, coarsening of precipitates, and extensive austenite reversion, resulting in softening of the fabricated parts.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Remote Epitaxy of III-V Solar Cells via Hydride Vapor Phase Epitaxy

The promise of remote epitaxy, in which epitaxial registry of a film can still be maintained through two-dimensional layers, has emerged from an advanced understanding of the interactions between two dimensional materials and bulk semiconductors. A promising application of this technology is to facilitate substrate reuse in epitaxial III-V systems, which could significantly reduce material cost and improve commercial viability of this high-efficiency photovoltaic technology. In this process the weak van der Waal bonds between the 2D layer and the III-V substrate make separation of epitaxially-grown layers simple and leaves a smooth substrate that can be reused for cost reduction. Here we present a study of growth parameters of GaAs on AlGaAs through a low dimensional carbon interlayer via hydride vapor phase epitaxy (HVPE). We Investigate the effect of various GaAs nucleation conditions such as V/III ratio, temperature and growth rate on film roughness, crystallinity, and degree of epitaxial alignment. We demonstrate growth of single crystal GaAs layer on top of the low dimensional carbon that follow the crystal orientation of the substrate. Surface roughness measured via AFM found that lower V/III ratios result in smoother III-V films grown on the low dimensional carbon, with a lowest RMS of ~60 nm obtained at a V/III ratio of 5. Growth temperatures are optimized at 650 C, as temperatures below 550 C show non-crystalline growth and higher temperature samples display very rough surfaces. Additionally, we investigate HVPE growth on various forms of low-dimensional carbon including transferred graphene, CVD-grown graphene, and MOCVD-growth amorphous carbon and find the latter to be most well suited for III-V growth as this method results in cleaner interface and potential for direct, large-area coverage. We also identify techniques to mitigate surface degradation in carbon layers as a function of both exposure time and growth environment by analyzing surface changes via x-ray reflectivity. We show growth of heteroepitaxial III-V solar cells on carbon interlayers and preliminary cell results, which are currently limited to 4% efficiency under one sun.

AlGaAs↗
DOE OSTI2023

An Initial Evaluation of the Elevated-Temperature Cyclic Properties of Optimized 316H Stainless Steel Fabricated by Powder Metallurgy Hot Isostatic Pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is a mature advanced manufacturing technology, which can consolidate metallic powder under high temperature and pressure to generate near-net shape components. This process can lower production costs and reduce component lead times for nuclear reactor construction and can be readily deployed in the near term for microreactor components because of their smaller size. The purpose of this work is to continue the evaluation of elevated-temperature cyclic material properties for PM-HIP 316H stainless steel. Prior scoping results have shown that the commercially procured PM-HIP stainless-steel materials have reduced creep-fatigue performance compared to wrought 316 stainless steels. To better understand how PM-HIP processed material properties compare to traditional manufacturing methods, additional billets of PM-HIP 316H stainless steel were procured and tested. This testing is necessary to understand how elevated-temperature properties are influenced by the PM-HIP process and what data are needed for incorporating PM HIP 316H into the American Society of Mechanical Engineers Boiler Pressure Vessel Code, Section III, Division 5 for high temperature reactor construction. Specifically, an additional PM-HIP 316H stainless steel billet with lower oxygen and nitrogen concentrations was fabricated by the Nuclear Advanced Manufacturing Research Centre of the United Kingdom and tested to understand if elevated-temperature cyclic properties can be improved. The creep-fatigue resistance of the material from this new billet did not show appreciable improvement compared to prior testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Machine learning based simultaneous control of air handling unit discharge air and condenser water temperatures set-point for minimized cooling energy in an office building

In this study, an artificial intelligence based real-time prediction and control model to optimize condenser water temperature and discharge air temperature (DAT) set-points in water-cooled air handling unit (AHU) system has been developed. EnergyPlus-MATLAB co-simulation has been conducted to analyze the developed model's effectiveness. Here, to develop artificial neural networks (ANN) model, embedded neural network objects in MATLAB was utilized. The developed model could decide an optimal temperature set-points based on outdoor air wet-bulb temperature to reflect the Korean climate context. As a result, the developed ANN prediction model showed the predictive performance of Cv(RMSE) of approximately 21%. Compared to the conventional fixed temperature algorithm, which fixes AHU DAT at 14°C and condenser water temperature at 32°C, the ANN based optimized control showed a 22% total cooling energy reduction. These results show that significant energy savings can be achieved by simultaneously controlling condenser water temperature and AHU DAT set-points considering Korean climatic characteristics using AI technologies such as ANN models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Development and Experimental Optimization of High-Temperature Modeling Tools and Methods for Concentrated Solar Power Particle - Systems

A novel, open-source radiative modeling toolset was developed to extend the functionality of particle-based modeling software (e.g. discrete element method (DEM)) to environmental conditions relevant to concentrated solar power applications. This toolset was optimized for deployment on desktop workstations instead of high-performance computing systems, to render such tools more accessible to the research community. Both particle-based modeling and radiative exchange modeling are computationally expensive and often require specialized programming expertise, making these methods cumbersome to use. Recent developments in DEM software by DCS Computing have greatly reduced these challenges, providing a graphical-user-interface based platform and modeling optimization for desktop workstations, HPCs, and cloud computing. The University of Dayton leveraged the experience of DCS Computing in developing a user-friendly, open-source radiative heat transfer expansion for DEM modeling. The University of Dayton DEM+ radiative modeling toolset was developed using a combination of fundamental experimental measurements, modeling, and simplified flow experiments over a range of temperatures and flow conditions. The toolset provides researchers with access to multiple radiative models including an accelerated Monte-Carlo Ray Tracing (application agnostic, highly computationally expensive), an expanded database of distance-based approximations (application limited, computationally light), and a weighted blending of the two methods capable of achieving over 90% reduction in computation time with equivalent accuracy compared to Monte-Carlo Ray Tracing. Through a graphical user interface, users can customize the radiative models to match their desired accuracy and available computational resources, improving access to particle based modeling for the research community. Ceramic sintered bauxite proppants were used in modeling and experimentally as a baseline. Both the radiative heat transfer and flow properties for particulate systems were investigated at elevated temperatures up to 800 °C. The major accomplishments for this work include a verified, open-source radiative modeling toolset to be distributed amongst the research community and the fabrication of three small-scale test facilities to investigate particle behavior and tune DEM flow properties for operation up to 800 °C. The findings have been shared with the research community via conference modeling workshops, deployment of the tools in DCS Computing Aspherix®, and open-source access to the developed radiative modeling tool. The development of next-generation CSP facilities and thermal energy storage systems based on ceramic particles requires providing access to computationally efficient and accurate modeling tools. Particles will experience a wide range of environments (20-800 °C) and handling conditions (dilute curtains or dense packing), requiring specially designed and optimized equipment. Optimizing solid particle physics models and establishing best-practices for particle modeling in CSP environments will assist researchers with designing optimized equipment, accelerating the deployment of more economically-competitive CSP facilities.

14 SOLAR ENERGY↗
DOE OSTI2021

Characterization and structural analysis of a thermophilic GH11 xylanase from compost metatranscriptome

Xylanase is efficient for xylan degradation and widely applied in industries. We found a GH11 family xylanase (Xyn11A) with high thermostability and catalytic activity from compost metatranscriptome. This xylanase has the optimal reaction temperature at 80 °C with the activity of 2907.3 U/mg. The X-ray crystallographic structure shows a typical “right hand” architecture, which is the characteristics of the GH11 family enzymes. Comparing it with the mesophilic XYN II, a well-studied GH11 xylanase from Trichoderma reesei, Xyn11A is more compact with more H-bonds. Our mutagenic results show that the electrostatic interactions in the thumb and palm region of Xyn11A could result in its high thermostability and activity. Introducing a disulfide bond at the N-terminus further increased its optimal reaction temperature to 90 °C with augmented activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Application of Artificial Neural Network Model for Optimized Control of Condenser Water Temperature Set-Point in a Chilled Water System

Here, in this study, real-time predictive control and optimization model based on an ANN (artificial neural network) was developed to evaluate the cooling energy saving performance of the optimized control of CndWT (condenser water temperature). For this purpose, the difference in TCEC (total cooling energy consumption) between the conventional control strategy when the CndWT produced by the cooling tower is fixed and the optimized control strategy when real-time control of the CndWT through the optimal ANN model is applied was compared and analyzed. For the modeling of the building to be simulated, the co-simulation of EnergyPlus and MATLAB was built through the middleware Building Controls Virtual Test Bed. For the prediction of TCEC, an ANN model was developed through MATLAB's neural network toolbox. The model accuracy of the ANN was examined through Cv(RMSE) index and as a result, Cv(RMSE) of the optimized ANN model turned out to be approximately 25 %. More importantly, the predictive control technique was able to save TCEC by 5.6 % compared to the conventional control method constantly fixing CndWT set-point to 30 °C. These results showed that the CndWT needs to be dynamically controlled using artificial intelligence technique such as ANN model and that significant energy savings were achievable compared to the conventional fixed control.

42 ENGINEERING↗
DOE OSTI2024

Optimal control of the electron temperature profile in DIII-D using machine learning surrogate models

The viability of the tokamak as a potential fusion reactor depends on the ability to keep the plasma in a stable regime while achieving temperatures, densities, and confinement times that are as high as possible. Tokamak scenario development attempts to find plasma regimes that achieve all of these conditions and are accessible with a given set of hardware constraints. This requires the ability to control plasma properties such as the normalized beta, the internal inductance, safety factor, rotation, etc. One property that has received less attention than some of the others, but is no less critical to achieving high performance, is the electron temperature (T e ) profile. In this work, Linear Quadratic Integral (LQI) control is used to develop a controller for the electron temperature profile in DIII-D. The controller is based on a linearized model derived from the transport equation that describes the evolution of the electron temperature, and includes contributions from the neural network surrogate models NubeamNet and MMMnet. Furthermore, the controller is tested in simulation using COTSIM, and is proven capable of tracking a target T e profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗