Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “casting”

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.

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

At least 1,693 records · Page 94

Electrospun Si and Si/C Fiber Anodes for Li-Ion Batteries

Due to structural changes in silicon during lithiation/delithiation, most Li-ion battery anodes containing silicon show rapid gravimetric capacity fade upon charge/discharge cycling. Herein, we report on a new Si powder anode in the form of electrospun fibers with only poly(acrylic acid) (PAA) binder and no electrically conductive carbon. The performance of this anode was contrasted to a fiber mat composed of Si powder, PAA binder, and a small amount of carbon powder. Fiber mat electrodes were evaluated in half-cells with a Li metal counter/reference electrode. Without the addition of conductive carbon, a stable capacity of about 1500 mAh/g (normalized to the total weight of the anode) was obtained at 1C for 50 charge/discharge cycles when the areal loading of silicon was 0.30 mgSi/cm2, whereas a capacity of 800 mAh/g was obtained when the Si loading was increased to ~1.0 mgSi/cm2. On a Si weight basis, these capacities correspond to >3500 mAh/gSi. The capacities were significantly higher than those found with a slurry-cast powdered Si anode with PAA binder. There was no change in fiber anode performance (gravimetric capacity and constant capacity with cycling) when a small amount of electrically conductive carbon was added to the electrospun fiber anodes when the Si loading was ≤1.0 mgSi/cm2.

Mondal, Abhishek N.↗

Development of a Modular Tissue Phantom for Evaluating Vascular Access Devices

Central vascular access (CVA) may be critical for trauma care and stabilizing the casualty. However, it requires skilled personnel, often unavailable during remote medical situations and combat casualty care scenarios. Automated CVA medical devices have the potential to make life-saving therapeutics available in these resource-limited scenarios, but they must be properly designed. Unfortunately, currently available tissue phantoms are inadequate for this use, resulting in delayed product development. Here, we present a tissue phantom that is modular in design, allowing for adjustable flow rate, circulating fluid pressure, vessel diameter, and vessel positions. The phantom consists of a gelatin cast using a 3D-printed mold with inserts representing vessels and bone locations. These removable inserts allow for tubing insertion which can mimic normal and hypovolemic flow, as well as pressure and vessel diameters. Trauma to the vessel wall is assessed using quantification of leak rates from the tubing after removal from the model. Lastly, the phantom can be adjusted to swine or human anatomy, including modeling the entire neurovascular bundle. Overall, this model can better recreate severe hypovolemic trauma cases and subject variability than commercial CVA trainers and may potentially accelerate automated CVA device development.

59 BASIC BIOLOGICAL SCIENCES↗

Coreset Clustering on Small Quantum Computers

Many quantum algorithms for machine learning require access to classical data in superposition. However, for many natural data sets and algorithms, the overhead required to load the data set in superposition can erase any potential quantum speedup over classical algorithms. Recent work by Harrow introduces a new paradigm in hybrid quantum-classical computing to address this issue, relying on coresets to minimize the data loading overhead of quantum algorithms. We investigated using this paradigm to perform k-means clustering on near-term quantum computers, by casting it as a QAOA optimization instance over a small coreset. We used numerical simulations to compare the performance of this approach to classical k-means clustering. We were able to find data sets with which coresets work well relative to random sampling and where QAOA could potentially outperform standard k-means on a coreset. However, finding data sets where both coresets and QAOA work well—which is necessary for a quantum advantage over k-means on the entire data set—appears to be challenging.

42 ENGINEERING↗

Phosphoric Acid-Doped Ion-Pair Coordinated PEMs with Broad Relative Humidity Tolerance

Proton exchange membrane (PEM) capable of working over a broad operating condition window is critical for successful adoption of PEM-based electrochemical devices. In this work, phosphoric acid (PA)-doped biphenyl-backbone ion-pair coordinated PEMs were prepared by quaternization of BPBr-100, a precursor polymer, with three different tertiary amines including trimethylamine, 1-methylpiperidine, and 1,2-dimethylimidazole followed by membrane casting, ion exchange reaction to hydroxide ion, and doping with PA. The resulting PA-doped ion-pair PEMs were characterized in terms of PA doping level, proton conductivity, relative humidity (RH) tolerance, thermal stability, and mechanical properties. PA doping levels were between six and eight according to acid-base titration. The size and structure of the cation group of ion-pair polymers were found to affect the PA doping level and water uptake. Proton conductivity was studied as a function of RH over a wide range of 5% to 95% RH. Stable conductivity at 80 °C was observed up to 70% RH for 10 h. Mechanical property characterization indicates that the PA doping process resulted in more ductile membranes with significantly increased elongation at break due to the plasticization effect of PA. A combination of high proton conductivity at low RH conditions, and good humidity tolerance makes this new class of PEMs great potential candidates for use in electrochemical devices such as proton exchange membrane fuel cells and electrochemical hydrogen compressors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nickel Hydroxide Nanofluid Cathodes with High Solid Loadings and Low Viscosity for Energy Storage Applications

Nanofluid electrodes with high loading of active solid materials have significant potential as high energy density flow battery electrolytes; however, two key criteria need to be met: they must have a manageable viscosity for pumping and simultaneously exhibit good electrochemical activity. A typical dispersion of nickel hydroxide nanoparticles (~100 nm) is limited to 5–10 wt.% of solids, above which it has a paste-like consistency, incompatible with flow applications. We report on the successful formulation of stable dispersions of a nano-scale nickel hydroxide cathode (β-Ni(OH) 2 ) with up to 60 wt.% of solids and low viscosity (32 cP at 25 °C), utilizing a surface graft of small organic molecules. The fraction of grafting moiety is less than 3 wt.% of the nanoparticle weight, and its presence is crucial for the colloidal stability and low viscosity of suspensions. Electrochemical testing of the pristine and modified β-Ni(OH) 2 nanoparticles in the form of solid casted electrodes were found to be comparable with the latter exhibiting a maximum discharge capacity of ~237 mAh/g over 50 consecutive charge–discharge cycles, close to the theoretical capacity of 289 mAh/g.

25 ENERGY STORAGE↗

Guiding Principles for Geochemical/Thermodynamic Model Development and Validation in Nuclear Waste Disposal: A Close Examination of Recent Thermodynamic Models for H + —Nd 3+ —NO 3 - (—Oxalate) Systems

Development of a defensible source-term model (STM), usually a thermodynamical model for radionuclide solubility calculations, is critical to a performance assessment (PA) of a geologic repository for nuclear waste disposal. Such a model is generally subjected to rigorous regulatory scrutiny. In this article, we highlight key guiding principles for STM model development and validation in nuclear waste management. We illustrate these principles by closely examining three recently developed thermodynamic models with the Pitzer formulism for aqueous H + —Nd 3+ —NO 3 - (—oxalate) systems in a reverse alphabetical order of the authors: the XW model developed by Xiong and Wang, the OWC model developed by Oakes et al., and the GLC model developed by Guignot et al., among which the XW model deals with trace activity coefficients for Nd(III), while the OWC and GLC models are for concentrated Nd(NO 3 ) 3 electrolyte solutions. The principles highlighted include the following: (1) Principle 1. Validation against independent experimental data: A model should be validated against experimental data or field observations that have not been used in the original model parameterization. We tested the XW model against multiple independent experimental data sets including electromotive force (EMF), solubility, water vapor, and water activity measurements. The results show that the XW model is accurate and valid for its intended use for predicting trace activity coefficients and therefore Nd solubility in repository environments. (2) Principle 2. Testing for relevant and sensitive variables: Solution pH is such a variable for an STM and easily acquirable. All three models are checked for their ability to predict pH conditions in Nd(NO 3 ) 3 electrolyte solutions. The OWC model fails to provide a reasonable estimate for solution pH conditions, thus casting serious doubt on its validity for a source-term calculation. In contrast, both the XW and GLC models predict close-to-neutral pH values, in agreement with experimental measurements. (3) Principle 3. Honoring physical constraints: Upon close examination, it is found that the Nd(III)-NO 3 association schema in the OWC model suffers from two shortcomings. Firstly, its second stepwise stability constant for Nd(NO 3 ) 2+ (log K 2 ) is much higher than the first stepwise stability constant for NdNO 3 2+ (log K 1 ), thus violating the general rule of (log K 2 –log K 1 ) < 0, or $\frac{K1}{K2}$>1. Secondly, the OWC model predicts abnormally high activity coefficients for Nd(NO 3 ) 2 + (up to ~900) as the concentration increases. (4) Principle 4. Minimizing degrees of freedom for model fitting: The OWC model with nine fitted parameters is compared with the GLC model with five fitted parameters, as both models apply to the concentrated region for Nd(NO 3 ) 3 electrolyte solutions. The latter appears superior to the former because the latter can fit osmotic coefficient data equally well with fewer model parameters. The work presented here thus illustrates the salient points of geochemical model development, selection, and validation in nuclear waste management.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The Significance of Multi-Size Carbon Fibers on the Mechanical and Fracture Characteristics of Fiber Reinforced Cement Composites

One of the main challenges of using a high fiber volume content in a cement composite is the narrow margin of fiber volume content beyond which fibers can cause an adverse effect on the mechanical properties. In this paper, the significance of fiber size distribution and fiber volume content of different proportions of chopped and milled carbon microfibers are investigated. The mixes’ flowability showed improvement with altering the fiber size distribution despite having a high fiber content. Uniaxial compression cylinders and unnotched and notched beams were cast and then tested at 7 and 28 days of age. It was found that the compressive strength is significantly affected by fiber size distribution more than fiber volume content. On the other hand, the modulus of rupture and fracture toughness are proportional to the fiber volume content with little effect of fiber size distribution. Finally, neither high fiber volume content nor altered fiber size distribution significantly affected the elastic modulus of the fiber cement composites.

Abdellatef, Mohammed↗

Fluorescent CQD-Doped Styrene Acrylic Emulsion Coating Film with Enhanced Optical Properties

Styrene acrylic emulsions (SAEs) have emerged as a promising material for water-based coatings. However, they are still limited by their own defects in practical applications, poor weatherability, and degradation of performance at lower or higher temperatures. Here, we introduce a facile approach to producing fluorescent carbon quantum dots (CQDs) from wood processing residues and fabricating fluorescent CQD/SAE coating films via emulsion-casting. The addition of the fluorescent CQDs enhanced the optical performance of the CQD/SAE coating films. The fluorescent CQDs were prepared via a hydrothermal approach and were obtained after heating at 180 °C for 6 h at a reaction concentration of 50 mg/mL. The synthesized CQDs resulted in a high fluorescence, and the CQDs had an average size of 1.63 nm. Various concentrations of the fluorescent CQDs were doped into the SAE coating film, which improved its optical properties. We also characterized and discussed the products and then explored their optical properties. This study presents the potential of fluorescent CQD/SAE coating films for applications in anti-counterfeiting coatings, fluorescent adhesives, and papermaking.

36 MATERIALS SCIENCE↗

Training Ultrasound Image Classification Deep-Learning Algorithms for Pneumothorax Detection Using a Synthetic Tissue Phantom Apparatus

Ultrasound (US) imaging is a critical tool in emergency and military medicine because of its portability and immediate nature. However, proper image interpretation requires skill, limiting its utility in remote applications for conditions such as pneumothorax (PTX) which requires rapid intervention. Artificial intelligence has the potential to automate ultrasound image analysis for various pathophysiological conditions. Training models require large data sets and a means of troubleshooting in real-time for ultrasound integration deployment, and they also require large animal models or clinical testing. Here, we detail the development of a dynamic synthetic tissue phantom model for PTX and its use in training image classification algorithms. The model comprises a synthetic gelatin phantom cast in a custom 3D-printed rib mold and a lung mimicking phantom. When compared to PTX images acquired in swine, images from the phantom were similar in both PTX negative and positive mimicking scenarios. We then used a deep learning image classification algorithm, which we previously developed for shrapnel detection, to accurately predict the presence of PTX in swine images by only training on phantom image sets, highlighting the utility for a tissue phantom for AI applications.

Boice, Emily N. (ORCID:0000000171802842)↗

Hybrid Manufacturing of Conformal Cooling Channels for Tooling

Computer-aided manufacturing (CAM) techniques for hybrid manufacturing have led to new application areas in the manufacturing industry. In the tooling industry, cooling channels are used to enable specific heating and cooling cycles to improve the performance of the process. These internal cooling channels have been designed with limited manufacturing processes in mind, so, until recently, they were often straight in shape for cross-drilling operations and manufactured from a cast billet. To show a novel application of this common technology, a tool with integrated conformal cooling channels was manufactured using hybrid manufacturing (blown-powder DED and CNC machining) techniques. The computer-aided manufacturing strategy used, and the lessons learned are presented and discussed to enable future work in this industrial application space.

36 MATERIALS SCIENCE↗

Structural Aspects of Neutron Survival Probabilities

The neutron survival probability (and related quantities including probabilities of extinction and initiation) is a central element of the broader stochastic theory of neutron populations and finds application in fields including reactor start-up, analysis of reactor power bursts and criticality accidents, and safeguards. In a full neutron transport formulation, the equation governing the single-neutron survival probability is a backward or adjoint-like integro-partial differential equation with the added complexity of being highly nonlinear. Analogous formulations of this equation exist in the context of many approximate theories of neutron transport, with the point kinetics formulation having received significant theoretical attention since the 1940s. This work continues this tradition by providing a novel analysis of the single-neutron survival probability equation using the tools of boundary layer theory. The analysis reveals that the “fully dynamic” solution of the single-neutron survival probability equation—and some key probability distributions derived from it—may be cast as a singular perturbation around the underlying quasi-static single-neutron probability of initiation. In this perturbation solution, the expansion parameter is the ratio of the neutron generation time to a macroscopic time scale characterizing the overall system evolution; this interpretation illuminates some of the fundamental structural aspects of neutron survival phenomena.

97 MATHEMATICS AND COMPUTING↗

Microstructural Assessment of a Multiple-Intermetallic-Strengthened Aluminum Alloy Produced from Gas-Atomized Powder by Hot Extrusion and Friction Extrusion

An aluminum (Al) matrix with various transition metal (TM) additions is an effective alloying approach for developing high-specific-strength materials for use at elevated temperatures. Conventional fabrication processes such as casting or fusion-related methods are not capable of producing Al–TM alloys in bulk form. Solid phase processing techniques, such as extrusion, have been shown to maintain the microstructure of Al–TM alloys. In this study, extrusions are fabricated from gas-atomized aluminum powders (≈100–400 µm) that contain 12.4 wt % TM additives and an Al-based matrix reinforced by various Al–Fe–Cr–Ti intermetallic compounds (IMCs). Two different extrusion techniques, conventional hot extrusion and friction extrusion, are compared using fabricating rods. During extrusion, the strengthening IMC phases were extensively refined as a result of severe plastic deformation. Furthermore, the quasicrystal approximant IMC phase (70.4 wt % Al, 20.4 wt % Fe, 8.7 wt % Cr, 0.6 wt % Ti) observed in the powder precursor is replaced by new IMC phases such as Al3.2Fe and Al45Cr7-type IMCs. The Al3Ti-type IMC phase is partially dissolved into the Al matrix during extrusion. The combination of linear and rotational shear in the friction extrusion process caused severe deformation in the powders, which allowed for a higher extrusion ratio, eliminated linear voids, and resulted in higher ductility while maintaining strength comparable to that resulting from hot extrusion. Results from equilibrium thermodynamic calculations show that the strengthening IMC phases are stable at elevated temperatures (up to ≈ 600 °C), thus enhancing the high-temperature strength of the extrudates.

36 MATERIALS SCIENCE↗

Effect of Melt-Spinning Parameters on the Structure and Properties of Ni 55.5 Mn 18.8 Ga 24 Si 1.7 Heusler Alloy Ribbons

Ni–Mn-based Heusler alloys are known to demonstrate magnetic shape memory and giant magnetocaloric effect (MCE). These effects depend on the phases, crystallographic and magnetic phase transitions, and the crystallographic texture characteristics. These structural characteristics, in turn, are a function of the processing parameters. In the current work, Ni 55.5 Mn 18.8 Ga 24 Si 1.7 Heusler alloy was processed by melt-spinning under a helium atmosphere. This process results in a fine microstructure. The ribbon that was produced with a narrower nozzle width, faster wheel speed, and higher cast temperature, indicating a faster cooling rate, had double the magnetic entropy change close to room temperature. However, the other ribbon demonstrated a large entropy change over a broader temperature range, extending its usability. The effect of the melt-spinning process parameters on the developing microstructure, crystallographic structure and texture, transformation temperatures, and the magnetic entropy change were studied to explain the difference in magnetocaloric behavior.

36 MATERIALS SCIENCE↗

Atomic Diffusivities of Yttrium, Titanium and Oxygen Calculated by Ab Initio Molecular Dynamics in Molten 316L Oxide-Dispersion-Strengthened Steel Fabricated via Additive Manufacturing

Oxide-dispersion-strengthened (ODS) steels have long been viewed as a prime solution for harsh environments. However, conventional manufacturing of ODS steels limits the final product geometry, is difficult to scale up to large components, and is expensive due to multiple highly involved, solid-state processing steps required. Additive manufacturing (AM) can directly incorporate dispersion elements (e.g., Y, Ti and O) during component fabrication, thus bypassing the need for an ODS steel supply chain, the scale-up challenges of powder processing routes, the buoyancy challenges associated with casting ODS steels, and the joining issues for net-shape component fabrication. In the AM process, the diffusion of the dispersion elements in the molten steel plays a key role in the precipitation of the oxide particles, thereby influencing the microstructure, thermal stability and high-temperature mechanical properties of the resulting ODS steels. In this work, the atomic diffusivities of Y, Ti, and O in molten 316L stainless steel (SS) as functions of temperature are determined by ab initio molecular dynamics simulations. The latest Vienna Ab initio Simulation Package (VASP) package that incorporates an on-the-fly machine learning force field for accelerated computation is used. At a constant temperature, the time-dependent coordinates of the target atoms in the molten 316L SS were analyzed in the form of mean square displacement in order to obtain diffusivity. The values of the diffusivity at multiple temperatures are then fitted to the Arrhenius form to determine the activation energy and the pre-exponential factor. Given the challenges in experimental measurement of atomic diffusivity at such high temperatures and correspondingly the lack of experimental data, this study provides important physical parameters for future modeling of the oxide precipitation kinetics during AM process.

Chemistry↗

Prediction of Silicon Content in a Blast Furnace via Machine Learning: A Comprehensive Processing and Modeling Pipeline

Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.

Chemistry↗

Poly(ionic liquid)s with Dicationic Pendants as Gas Separation Membranes

Poly(norbornene)s and poly(ionic liquid)s are two different classes of attractive materials, which are known for their structural tunability and thermal stabilities, and have been extensively studied as gas separation membranes. The incorporation of ionic liquids (ILs) into the poly(norbornene) through post-polymerization has resulted in unique materials with synergistic properties. However, direct polymerization of norbornene-containing IL monomers as gas separation membranes are limited. To this end, a series of norbornene-containing imidazolium-based mono- and di-cationic ILs (NBM-mIm and NBM-DILs) with different connectivity and spacer lengths were synthesized and characterized spectroscopically. Subsequently, the poly(NBM-mIm) with bistriflimide [Tf2N−] and poly([NBM-DILs][Tf2N]2) comprising homo-, random-, and block- (co)polymers were synthesized via ring-opening metathesis polymerization using the air-stable Grubbs second-generation catalyst. Block copolymers (BCPs), specifically, [NBM-mIM][Tf2N] and [NBM-ImCnmIm] [Tf2N]2 (n = 4 and 6) were synthesized at two different compositions, which generated high molecular weight polymers with decent solubility relative to homo- and random (co)polymers of [NBM-DILs] [Tf2N]2. The prepared BCPs were efficiently analyzed by a host of analytical tools, including 1H-NMR, GPC, and WAXD. The successfully BCPs were cast into thin membranes ranging from 47 to 125 μm and their gas (CO2, N2, CH4, and H2) permeations were measured at 20 °C using a time-lag apparatus. These membranes displayed modest CO2 permeability in a non-linear fashion with respect to composition and a reverse trend in CO2/N2 permselectivity was observed, as a usual trade-off behavior between permeability and permselectivity.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancement of γ/γ’ Microstructured Cobalt Superalloys Produced from Atomized Powder by Creating a Harmonic Structure

A material’s properties must be continuously improved to meet the demands of extreme conditions in high-temperature applications. It is demonstrated that γ-γ’ Co-based superalloys could surpass the yield stress of Ni-based superalloys at high temperature due to the γ-γ’ structure. The powders were subjected to a harmonic modification in order to refine the grain structure on the surface and to activate the sintering process. This study examines how harmonic structure affects microstructure and mechanical properties at high temperatures. Spark Plasma Sintering (SPS) was used for consolidation to maintain the ultrafine grain size microstructure of the powder. Compression tests were conducted from room temperature (RT) to 750 °C to assess the mechanical properties of the material. Yield stress values obtained from harmonic structures are four times higher than those obtained from cast alloys.

36 MATERIALS SCIENCE↗

Processing, Microstructure, and Properties of Bimetallic Steel-Ni Alloy Powder HIP

This work explores technical feasibility in hot isostatic pressing (HIP) manufacturing of an integral bimetallic component using steel and Ni alloy powder for supercritical carbon dioxide (sCO2) turbomachinery. Lab-scale bimetallic HIP specimens using HAYNES® 282® and SS316L or SS415 powder are investigated in powder configuration, heat treatment, microstructure, and tensile properties up to 400 °C. Interdiffusion profiles at dissimilar alloy interfaces caused by HIP cycle is predicted by DICTRA simulations and validated by electron probe microanalysis (EPMA). The interdiffusion distance of most elements is around 100 μm, while C and N have a higher interdiffusion distance. Dense distribution of Ti-rich carbonitrides and alumina particles are found to decorate prior particle boundaries near joining interface on the 282 side, affecting tensile strength across interface as well as tensile failure location. A higher amount of excessive carbonitride formation near interface is observed in SS316L/282 than in SS415/282, which is consistent with the predicted greater degree of interdiffusion effect in SS316L/282. Typical HAYNES® 282® heat treatment condition is applicable to 282/SS316L and 282/SS415 combinations, resulting in a higher strength than cast CF8M and CA6NM. A pilot-scale bimetallic SS415/282 pipe is then demonstrated to show the promise of scaleup.

36 MATERIALS SCIENCE↗