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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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At least 181 records · Page 10

WaterTAP 0.4 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.5 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.6 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.7 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.8 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.10 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.11 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 0.12 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗

WaterTAP 1.0 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

AS↗

Non-smooth Bayesian optimization in tuning scientific applications

Tuning algorithmic parameters to optimize the performance of large, complicated computational codes is an important problem involving finding the optima and identifying regimes defined by non-smooth boundaries in black-box functions. Within the Bayesian optimization framework, the Gaussian process surrogate model produces smooth mean functions, but functions in the tuning problem are often non-smooth, which is exacerbated by the fact that we usually have limited sequential samples from the black-box function. Here, motivated by these issues encountered in tuning, we propose a novel Gaussian process model called a clustered Gaussian process (cGP), where the components are dynamically updated by clustering. In our studies, the performance of cGP can be better than stationary GPs in nearly 90% of the experiments and better than non-stationary GPs in nearly 70% of the repeated experiments while requiring less computational cost. cGP provides a novel approach for dynamic GP, computes more efficiently than recursive partitioning, and discovers non-smoothness regimes. We provide extensive experiments including high-performance computing (HPC) and industrial simulation functions to show the effectiveness of our methods.

97 MATHEMATICS AND COMPUTING↗

Material and Interface Engineering Strategies to Mitigate Decoherence in Superconducting Qubits

While significant strides have been made to increase the coherence time of superconducting qubits, further advancements are essential for realizing scalable quantum computing. Decoherence is often a result of loss and noise stemming from two-level systems and excess quasiparticles, arising due to material defects, fabrication processes, and ambient exposure, particularly at surfaces and interfaces. Our recent efforts to mitigate these decoherence mechanisms have employed a variety of strategies, including low-loss surface encapsulation materials, advanced substrate preparation techniques, modifications to metal film growth, and the development of novel fabrication processes. The structural and chemical properties of materials, surfaces, and interfaces are studied using scanning probe microscopy, electron microscopy, photoelectron spectroscopy, mass spectrometry, and X-ray diffraction, which is correlated to device performance metrics, including superconducting resonator internal quality factor and qubit T1 time. This information is used to identify and understand material sources of loss and their origins in the device fabrication process. Through multi-institution efforts within SQMS we have identified the loss mechanism of interstitial hydrogen in niobium-based devices and shown how standard fabrication processes introduce these hydrides, developing strategies to mitigate their formation.1 Furthermore, we have characterized the metal-substrate interface, including the loss of niobium-silicides formed at that interface, and developed silicon surface treatments that reduce atomic scale roughness and oxygen content at the metal-substrate and Josephson junction interfaces.2-4 By developing the connection between materials properties and the overall performance of superconducting quantum circuitry, we can develop fabrication strategies to mitigate material losses, thus supporting the ongoing efforts to enhance coherence time in superconducting quantum devices. 1. Torres-Castanedo, C. G.*, Goronzy, D. P.*, et al., Adv. Funct. Mater., 2401365 (2024) 2. Lu, X., et al., Phys. Rev. Materials 6, 064402 (2022) 3. Berti, G., Appl. Phys. Lett. 122, 192605 (2023) 4. Kopas, C. J., Goronzy, D. P., et al., arXiv:2408.02863 (2024)

Goronzy, Dominic P.↗

Sampling and Characterization of Coal Basins as an Alternative Rare-Earth Element Resource

Conference presentation at TechConnect World Innovation Conference & Expo, Washington, D.C., June 13–15, 2022. The University of North Dakota (UND) through the Energy & Environmental Research Center (EERC) and the Institute for Energy Studies teamed with the University of Kentucky Center for Applied Energy Research, Microbeam Technologies Inc., the Kentucky Geological Survey (KGS), the North Dakota Geological Survey (NDGS), and the mining industry to execute a contract with the U.S. Department of Energy National Energy Technology Laboratory (NETL) to obtain and characterize samples of U.S. domestic precombustion coal and coal-related materials with a minimum concentration of 300 parts per million (ppm) total rare-earth elements (TREEs) as the material is removed from the ground, with no processing other than drying.

01 COAL, LIGNITE, AND PEAT↗

Investigations Towards Ultra-Low Cost Nb 3 Sn SRF Fabrication via Melt Casted Bronze Route Processing

Here, a novel approach to fabricating Nb 3 Sn SRF cavities and other RF components using an ultra-low-cost melt casting fabrication process has been investigated. This simple, low cost melt casting technique has the potential to be used to fabricate nearly any superconducting Nb3Sn structure using either the Bronze Route (BR), Internal Tin (IT), External Tin (ET) processes as well as normal conducting pure copper (Cu) cavities. Most of the heat treated samples that were examined using SEM/EDX seemed to show a reasonable correlation of T c onset and transition width (ΔT c ) of the ingots initial/starting Sn content to the desired stoichiometric Nb 3 Sn phase, where the lower starting Sn content coupons resulted in lower T c 's with broader transition widths and the higher starting Sn coupons resulted in higher T c 's with narrower ΔT c ’s. The best samples had T c onsets ~17-18 K and ΔT c 's < 2 K. Two samples were further tested for RF surface resistance (R s ) and Quality Factor (Q) at JLAB. Here, these RF measurements were performed at 7.4 GHz using a calorimetric technique and showed two transitions, one at ~ 8 K and another at ~ 14 K; values of R s were at least two orders of magnitude higher than similar high quality Nb 3 Sn films directly deposited substrates by JLAB and with another superconducting transition close to the superconducting transition temperature of niobium. Substantial improvements in the processing variables ranging from higher quality of the initial ingots with higher Sn content, to better electropolishing and reaction heat treatment regimens will be necessary to realize improved RF performance metrics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Genesis of a novel high-rate composite manufacturing process using large-scale additive manufacturing – compression molding (AM-CM) system: Possibilities and limitations

Oak Ridge National Laboratory (ORNL) has developed a highly automated manufacturing process for thermoplastic composites that combines the benefits of Additive Manufacturing and Compression Molding (AM-CM) to produce high-performance functional composite structures at automotive production rates. Here, the AM-CM process creates highly precise preforms by additively placing extruded fiber-filled polymers (with controlled fiber orientations and multi-material configurations) in the desired mold location before undergoing a secondary compression molding process immediately before the preform cools down. Preforms can be in the form of short, long-chopped, or continuous fiber-filled thermoplastic polymers (e.g., CF/GF-filled ABS, PC, LM-PAEK, etc.). The AM-CM process combines the benefits of controlled fiber alignment, that is only achievable in AM-printed parts with the classical CM process, which eliminates porosity and good surface finish. A preform created using AM-CM can integrate various materials to enable additional architectural functionalities, including over-molding, selective stiffening, and the incorporation of electrically or thermally conductive channels. All these advantages come with a fast part production cycle time. The AM-CM process can manufacture multi-material, multi-functional parts in under 3 min, starting from raw material (pellets) to the final product. The novel AM-CM process offers superior microstructural control and enhanced multi-functionality previously unattainable with any other traditional high-rate thermoplastic composite manufacturing method. This work covers the manufacturing concept, system development, materials and applications of AM-CM process in detail.

Kumar, Vipin [Oak Ridge National Laboratory (ORNL)↗

Additively manufactured novel Al-Cu-Sc-Zr alloy: Microstructure and mechanical properties

An in-depth understanding of microstructure and resultant properties is paramount in the design of a novel alloy system, especially for additive manufacturing (AM). The present investigation aims to characterize a prototypical AM Al alloy with great potential for structural applications. An Al-1.5Cu-0.8Sc-0.4Zr alloy designed using integrated computational material engineering was printed using the laser powder bed fusion AM process. This novel alloy shows promising combination of strength and ductility in as-built and peak-aged conditions. This improvement in the tensile properties is attributed to the presence of both coherent L1 2 Al 3 Sc/Al 3 (Sc,Zr) precipitates and Cu-rich regions. The microstructures were studied via extensive microscopy at different length scales using X-ray microscopy, scanning electron microscopy, and transmission electron microscopy. Fractography revealed that the columnar grain boundaries in as-built condition allow easy slip transfer as compared to the equiaxed grains, with the apex of the melt pool acting as the crack nucleation site. Furthermore, the peak aged condition resulted in improved strength while marginally sacrificing ductility due to precipitates decorating dislocations, grain boundaries and melt pool boundaries thus acting as obstacles to slip transfer.

36 MATERIALS SCIENCE↗

An experimental and modeling study of the application of membrane contactor reactors to methanol synthesis using pure CO 2 feeds

We describe here a post-combustion CO 2 capture and utilization (CCU) technology that converts the CO 2 into methanol (MeOH), a valuable chemical, thus providing a way to monetize the carbon captured to offset process costs. Methanol synthesis (MeS) has been discussed recently for application to CCU, but thermodynamic limitations make it difficult to convert in a single pass a large CO 2 fraction. Conventional catalysts show slow kinetics in converting CO 2 -rich syngas (or pure CO 2 ) into MeOH. Our Group developed a novel MeS process, employing a membrane contactor reactor (MCR) system that attains carbon conversions significantly higher than equilibrium. Our focus here is to process pure CO 2 streams by combining the MCR with a separate reactor, which converts the CO 2 into a syngas via the reverse water gas shift (RWGS) reaction. In this preliminary effort, the RWGS reactor (RWGSR) is assumed to reach equilibrium. Additional MeS kinetic rate data are generated validating experimentally the ability of the MeS-MCR to process as a feed the RWGSR exit stream. The performance of the combined (RWGSR/MeS-MCR) system is then simulated using a recently developed MeS-MCR model. In conclusion, the findings are encouraging, and research is currently ongoing to experimentally validate the RWGSR/MeS-MCR system performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Separation and Recovery of High-Purity Dysprosium from Electric Vehicle Scrap Permanent Magnets Using Cyanex 572, a Cationic Extractant in a Membrane Solvent Extraction Process

Rare earth elements (REEs), especially heavy rare earth elements such as dysprosium (Dy), have gained immense attention globally due to their widespread use in many state-of-the-art technologies. Consequently, demand for REEs is increasing rapidly in comparison to their supply. Recycling of REEs from end-of-life (EoL) electronic waste (e-waste) can help to mitigate the increasing gap between the demand and supply of REEs. This study reports the separation and recovery of high-purity Dy from various feedstocks such as scrap permanent magnets (SPMs), electric vehicle (EV) magnets, and mixed rare earth oxides (REOs) using an economically viable and scalable membrane solvent extraction (MSX) process. First, the optimized conditions (organic phase composition and feed solution acid concentration) for the separation of Dy from light REEs such as neodymium (Nd) and praseodymium (Pr) were evaluated using liquid–liquid extraction. Thereafter, a multistage MSX process was developed to separate high purity (>99.5 wt %) Dy from Nd and Pr using Cyanex 572, a cationic extractant. Using feedstocks with varying initial compositions, the MSX process obtained 100% pure Dy with 63–96% Dy recovery in three to six stages with a maximum extraction rate of 2.9 g m–2 h –1 . Purity of the recovered Dy was confirmed via additional characterization such as scanning electron microscopy, energy dispersive X-ray spectroscopy, and X-ray diffraction. This novel MSX process holds immense potential for industry deployment for the separation of heavy and light rare REEs from a wide range of e-waste.

electrical vehicle magnets↗

Restorable Neutralization of Poly(acrylic acid) Binders toward Balanced Processing Properties and Cycling Performance for Silicon Anodes in Lithium-Ion Batteries

Neutralization of poly(acrylic acid) (PAA)-based binders using lithium hydroxide is a common strategy for fabricating silicon anode laminates, which improves rheological properties of slurries toward high-quality electrode laminates. However, the significantly increased basicity causes degradation of Si particles while the irreversible conversion of carboxylic acid groups to lithium carboxylates undermines the binding strength, collectively leading to adverse cycling performance of the fabricated Si anodes. Herein, a novel neutralization process for PAA binders is developed. A weak base, ammonia (NH 3 ), was discovered as a neutralizing agent that still promotes rheological response of binder solutions but results in a reduced pH increase. Interestingly, the resulting ammonium carboxylate groups may cleave during the drying process to restore the neutralized PAA (PAA-NH 3 ) binders to their pristine states. The best-performing composition of 50% neutralization (PAA-50%NH 3 ) provides comparable rheological response as a PAA-Li binder as well as much improved cycling performance. Additionally, the half-cells using the PAA-50%NH 3 binder can deliver 60% capacity retention over 100 cycles at C/3 rate, affording a 23.8% increase compared to PAA-Li half-cells. This restorable neutralization process of PAA binders represents an innovative strategy of mitigating issues from slurry processing of Si particles to achieve concurrent improvements in high-quality lamination and cycling performance.

25 ENERGY STORAGE↗