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At least 19 records

Additively Reinforced Thermoformable PETG Composite Sheets for Improved Structural Efficiency

Thermoforming of short-fiber reinforced thermoplastic sheets offers a viable pathway for producing lightweight composite components; however, inherent anisotropy in fiber-reinforced sheets can limit structural performance under multidirectional loading. In this work, short carbon fiber, glass fiber, and hybrid fiber–reinforced PETG sheets were evaluated as candidate feedstock materials for thermoforming, with flexural and tensile testing performed both along the primary fiber direction and in the off-axis orientation to establish baseline stiffness, strength, and anisotropy. As expected, short carbon fiber PETG exhibited the highest stiffness and strength in the primary fiber direction, while all systems showed reduced performance in the off-axis direction. This off-axis performance reduction provides clear justification for the use of additive reinforcement when such thermoformed sheets are intended for structural applications. The intended manufacturing sequence involves thermoforming the reinforced sheet first, followed by the application of additively manufactured lattice reinforcement; therefore, the reinforcement strategy does not impose limitations on sheet formability during thermoforming. Post-forming lattice reinforcement significantly reduced load-normalized displacement by approximately 95–99% relative to non-reinforced sheets and improved weight-normalized stiffness by ~70%. These findings demonstrate that geometry-driven additive reinforcement can effectively compensate for off-axis property reductions in thermoformed PETG composites, enabling enhanced multidirectional structural performance without compromising manufacturability.

Talabi, Isaac [ORNL] (ORCID:0000000340215594)

Behaviors of Polymer Additives Under EHL and Influences of Interactions Between Additives on Friction Modification

Polymer additives have become requisite for the formulation of multigrade engine oils. The behavior of polymethacrylate (PMA)-thickened oils as lubricants in concentrated contacts under nominal rolling and pure sliding conditions was investigated by conventional optical interferometry. The PMA thickened oils behaved differently from the base oil in the formation of elastohydrodynamic (EHL) films. The higher the elastohydrodynamic molecular weight of the PMA contained in the lubricant, the thinner was the oil film under EHL conditions. The film thickness of shear-degraded PMA-thickened oils was also investigated. The behavior of graphite particles dispersed in both the base oil and the PMA-thickened oil was studied under pure sliding by taking photomicrographs. Many kinds of additives are contained in lubricating oil and the interactions between additives are considered. The interactions of zinc-organodithiophosphates (ZDP) with other additives is discussed.

Sakurai, T.

Improved digital construction binder solution utilizing calcium aluminate additive for Infrastructure Scale Additive Manufacturing

Oak Ridge National Laboratory (ORNL) worked with Kerneos Inc., a Division of Imerys USA, Inc. to develop an improved digital construction binder using calcium aluminate additives produced by Kerneos along with locally available concrete materials. When the two-stage (2K) binder formulation was added to commercially available Portland Limestone Cement and sand to form a digital construction mortar, its strength exceeded a number of commercially available digital construction binders both at early and later ages. At the same time, the developed formulation showed precise control of setting time after addition and showed very low shrinkage making it a strong, reliable, and easily customizable alternative to fixed proprietary digital construction binders.

36 MATERIALS SCIENCE

High Temperature Additive Architectures for 65% Efficiency (Final Technical Report)

This project aimed to develop advanced high-temperature additive components that contribute towards the DOE’s goal for advanced gas turbines that are capable of at least 65% efficiency in combined cycle application. The objective was to leverage state-of-the-art additive manufacturing to develop an innovative stage 1 turbine nozzle (S1N) that can provide cooling flow savings while maintaining the component durability expected in today’s gas turbines. The program had two phases. Phase I was a conceptual phase for novel advanced cooling designs enabled by additive manufacturing, as well as proposals for validation. Phase II included execution of the Phase I conceptual design, including manufacturing of prototype hardware and validation within an environment that is similar to engine operation. During Phase I of the program, the team devised a concept to reduce cooling air usage. The cooling air used in the side walls is filmed out along the side walls, while the cooling air used in the airfoil is eventually directed to near-wall channels and exits holes along the airfoil trailing end. During this program, the team performed additive trials to analyze the geometric limitations of additive manufacturing. This helped the team understand minimum wall thicknesses, hole sizes, and cooling channel dimensions among other limits. Phase II of this program pushed GE Vernova beyond its previous experience of designing and manufacturing an additively manufactured hot gas path component. Modern hot gas path components utilize material chemistries that are traditionally hard to weld, such as cast Renè 108, and exhibit solidification cracking when additively manufactured using Direct Metal Laser Melting (DMLM). Note that AM108 is a powder form of Renè 108. A S1N with advanced cooling is larger and more complex than parts previously built by additive manufacturing and required new learnings to resolve risks around solidification cracking. Finally, the team validated the design in a combustion rig that replicated operation in a gas turbine. In order to properly quantify the benefits of the new additive design, a baseline was also tested in the rig and operated under the same conditions. In addition, an uncertainty analysis was done to quantify any sources of error that could impact the results. At the end of the validation effort, it was determined that the additive nozzle exceeded the 15% reduction in cooling flow goal even with the worst-case assumptions for uncertainty.

03 NATURAL GAS

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE

Effects of litter addition on ectomycorrhizal associates of a lodgepole pine (Pinus contorta) stand in Yellowstone National Park

Increasing soil nutrients through litter manipulation, pollution, or fertilization can adversely affect ectomycorrhizal (EM) communities by inhibiting fungal growth. In this study, we used molecular genetic methods to determine the effects of litter addition on the EM community of a Pinus contorta stand in Yellowstone National Park that regenerated after a stand-replacing fire. Two controls were used; in unmodified control plots nothing was added to the soil, and in perlite plots perlite, a chemically neutral substance, was added to maintain soil moisture and temperature at levels similar to those under litter. We found that (i) species richness did not change significantly following perlite addition (2.6 +/- 0.3 species/core in control plots, compared with 2.3 +/- 0.3 species/core in perlite plots) but decreased significantly (P < 0.05) following litter addition (1.8 +/- 0.3 species/core); (ii) EM infection was not affected by the addition of perlite but increased significantly (P < 0.001) in response to litter addition, and the increase occurred only in the upper soil layer, directly adjacent to the added litter; and (iii) Suillus granulatus, Wilcoxina mikolae, and agaricoid DD were the dominant organisms in controls, but the levels of W. mikolae and agaricoid DD decreased significantly in response to both perlite and litter addition. The relative levels of S. granulatus and a fourth fungus, Cortinariaceae species 2, increased significantly (P < 0.01 and P < 0.05, respectively) following litter addition. Thus, litter addition resulted in some negative effects that may be attributable to moisture-temperature relationships rather than to the increased nutrients associated with litter. Some species respond positively to litter addition, indicating that there are differences in their physiologies. Hence, changes in the EM community induced by litter accumulation also may affect ecosystem function.

Fungi/classification/growth & development

Minimizing Energy Loss by Designing Multifunctional Solid Additives to Independent Regulation of Donor and Acceptor Layers for Efficient LBL Polymer Solar Cells

Solid additives are crucial in layer-by-layer (LBL) polymer solar cells (PSCs). Despite its importance, the simultaneous application of solid additives into both donor and acceptor layers has been largely overlooked. In this work, two multifunctional solid additives are actively designed, and investigated the synergistic effect on both donor and acceptor layers. Incorporating the multifunctional solid additives into the donor layer could effectively enhance the aggregation and molecular stacking of the donor polymer, leading to reduced energy disorder and minimizing ΔE 2 . When the multifunctional solid additives are introduced into the acceptor layer, they just play a role in optimizing the morphology, thereby reducing the ΔE 3 . Excitedly, the simultaneous addition of the multifunctional solid additives into both donor and acceptor layers produced a synergistic effect for decreasing ΔE 2 and ΔE 3 simultaneously, especially adding SA2, thus enabling an excellent power conversion efficiency (PCE) of 19.95% (certified as 19.68%) with an open-circuit voltage (V oc ) of 0.921 V, a short circuit current density (J sc ) of 27.08 mA cm -2 and a fill factor (FF) of 79.98%. The work highlights the potential of multifunctional solid additives in independently regulating the properties of donor and acceptor layers, which is expected as a promising approach for further developing higher performance PSCs.

36 MATERIALS SCIENCE

Impact of Lithium‐Free Borate Additives on the Cycle Life and Calendar Aging of Silicon‐Based Lithium‐Ion Batteries

Silicon-anode lithium-ion batteries (LIBs) suffer from limited cycle life and poor calendar life, constraining their large-scale commercialization. Integrating additives into electrolytes is a simple and cost-effective strategy to improve these aspects. The effects of lithium-free boron-based additives on cycling and calendar performance of high-loading Si-anode LIBs remain largely unexplored. In this work, the influence of five Li-free borate additives, each with distinct molecular structures and elemental compositions, is systematically investigated. All additives enhance cycle life to varying extents. Notably, the addition of 1 v/v% tri(2,2,2-trifluoroethyl) borate to the baseline electrolyte nearly doubles the cycle life at 50% state of health. This enhancement is attributed to three key factors. Specifically, borate additives 1) improve electrochemical activity, 2) act as anion receptors that interact with [PF6]- anions and carbonate solvents to reduce electrolyte decomposition, and 3) promote the formation of a stable and polymeric solid electrolyte interphase layer. Furthermore, these additives exhibited negligible impact in mitigating leakage current during a 180 h voltage-hold calendar-aging test, indicating their limited effect in calendar life. These findings provide insight into the role of Li-free borate additives in improving cycle life while addressing the knowledge gap regarding their influence on calendar aging.

Li, Defu

Influence of functional additives, fillers, and pigments on thermal and catalytic pyrolysis of polyethylene for waste plastic upcycling

Pyrolysis offers a relatively green and economical method to convert waste plastics into valuable chemicals and fuels without the need for harmful solvents, toxic chemicals, or costly high-pressure reactors. Despite its popularity among chemical upcycling technologies, industrial adoption suffers from feedstock heterogeneity, low-quality products, and catalyst deactivation. Most plastics in our daily lives are formulated with functional additives, fillers, and colorants. These additives remaining in end-of-life waste streams increase feedstock heterogeneity, creating a challenging issue in recycling plastics. Still, the potential impacts of additives on the chemical upcycling of plastics have been poorly understood. In this study, polyethylene compounded with a range of widely used additives (antioxidants, stabilizers, pigments, fillers, slip agents, and flame retardants) was subjected to both thermal pyrolysis and catalytic pyrolysis in different catalyst-to-feedstock contact modes. It showed that many inorganic additives, such as talc, kaolin, CaCO 3 , TiO 2 , carbon black, and zinc stearate, facilitated polymer decomposition during pyrolysis, increasing light hydrocarbons while also promoting aromatic and carbon residue formation. Conversely, antioxidants and stabilizers inhibited depolymerization, favoring heavier hydrocarbons. During catalytic pyrolysis with HZSM-5 zeolite, additives strongly enhanced aromatic and catalytic coke formation, especially when there was direct contact between plastics and catalysts. Although certain additives seem beneficial in the short term by promoting polymer cracking and improving the selectivity of aromatics, the transport of the additives and their degradation products and increased carbon coking can contaminate products, deactivate or modify catalysts, and foul reactors. These findings address a critical knowledge gap in effectively converting waste plastics via a greener route.

42 ENGINEERING

Analysis and Evaluation of Supersonic Underwing Heat Addition

The linearized theory for heat addition under a wing has been developed to optimize wing geometry, heat addition, and angle of attack. The optimum wing has all of the thickness on the underside of the airfoil, with maximum-thickness point well downstream, has a moderate thickness ratio, and operates at an optimum angle of attack. The heat addition is confined between the fore Mach waves from under the trailing surface of the wing. By linearized theory, a wing at optimum angle of attack may have a range efficiency about twice that of a wing at zero angle of attack. More rigorous calculations using the method of characteristics for particular flow models were made for heating under a flat-plate wing and for several wings with thickness, both with heat additions concentrated near the wing. The more rigorous calculations yield in practical cases efficiencies about half those estimated by linear theory. An analysis indicates that distributing the heat addition between the fore waves from the undertrailing portion of the wing is a way of improving the performance, and further calculations appear desirable. A comparison of the conventional ramjet-plus wing with underwing heat addition when the heat addition is concentrated near the wing shows the ramjet to be superior on a range basis up to Mach number of about B. The heat distribution under the wing and the assumed ramjet and airframe performance may have a marked effect on this conclusion. Underwing heat addition can be useful in providing high-altitude maneuver capability at high flight Mach numbers for an airplane powered by conventional ramjets during cruise.

wings

Carbon availability, soil pH, and microbial allocation to nitrogen acquisition shape grassland heterotrophic respiration in response to a decade of nitrogen addition

Previous work has found that anthropogenic inputs of nitrogen (N) and phosphorus (P) impact heterotrophic respiration during soil organic matter decomposition in grasslands, a critical pathway through which carbon (C) is lost from soil to the atmosphere. While N addition typically reduces heterotrophic respiration, why the strength and direction of this N effect varies among sites is unclear. Here, to address this, we conducted a 339-day laboratory incubation to measure heterotrophic respiration from nine grasslands across North America that have received 10 years of factorial N and P fertilization. N addition reduced cumulative respiration most at sites with low pH, low microbial allocation towards N acquisition, and high soil C concentration and availability. However, N addition had neutral rather than positive effects on heterotrophic respiration in sites with high pH and decomposer allocation towards N acquisition. Across sites, a decade of N addition reduced heterotrophic respiration by ∼24 %, driven by reductions in microbial biomass. Heterotrophic respiration was less sensitive to P addition, despite its increasing microbial biomass. However, simultaneous N and P addition did ameliorate negative N effects. These results show that previously observed variation in the response of heterotrophic respiration to N addition can be explained by soil C availability and pH status, widely measured factors which can be used to predict how grassland C fluxes may change under continuing nutrient deposition.

N addition

SiC Receiver/Reactor by Additive Manufacturing for Concentrated Solar Thermocatalysis with Thermal Energy Storage (Final Technical Report - Public)

The direct use of solar thermal energy provides opportunities for low-cost heating sources for a variety of applications. Ultra-high temperatures around 1000°C are high value and highly useful for energy-demanding industries. Many materials cannot withstand these conditions. In the area of Sustainable Chemicals, further limitations on material stability exist. Combining state-of-the-art materials with new designs provides a promising pathway for harvesting solar thermal energy and performing high temperature chemical processes. However, conventional manufacturing limits the potential for design flexibility. In this project, Additive Manufacturing was combined with advanced materials and new chemical reactor designs. In addition, 24/7 energy is necessary for chemical processing, and designs for ultra-high temperature thermal storage were devised. Specifically, preliminary design of a novel solar thermal receiver was developed in this project and designed to work with thermocatalytic reactors for producing sustainable chemicals and fuels. An ultra-high temperature particle storage system and heat exchangers were proposed to transport ultra-hot air as thermal fluid for the system. On a broader scale, this system could be used to tap solar thermal energy for a centralized facility with capability of transferring that heat to various segments at a full range of temperatures to 1000°C. The project pushed the temperature boundaries past those in current use, and Additive Manufacturing was envisaged for fabricating the receiver to meet requirements of extreme environments. An extensive analysis of silicon carbide additive manufacturing was performed to compare the thermal and mechanical properties of complex geometries compared to conventional material and those manufactured via other methods. The Additive Manufacturing via Binder-Jet printing was optimized and characterized to provide high quality and reproducible components capable of withstanding the proposed extreme environments. The designs for the concentrating solar thermal cavity with ultra-hot air thermal fluid showed high performance in simulations, attributable to the complex optimized geometries of the 3D printed systems. The bright future of Additive Manufacturing with advanced materials developments should provide more options and even higher quality as the technology further develops. Current costs for Additive Manufacturing of advanced ceramics is relatively low, however post-processing of the materials for extreme environments is currently high. There is little industrial-scale infrastructure for these, but it is growing as niche applications become more mainstream. The results of the project can be translated into similar extreme environments for concentrating solar thermal energy as well as its integration with ultra-hot air thermal fluids. A number of industries that require ultra-high temperatures need to electrify or otherwise decarbonize for climate goals, and this project showed that theoretically there is a pathway to do so with direct concentrated solar thermal power.

10 SYNTHETIC FUELS

Effect of Nb2O5 and V2O5 addition on the superconducting properties of YBa2Cu3O(y) thin films

The effect of Nb2O5 and V2O5 addition on the superconducting properties and microstructure of YBa2Cu3O(y) has been studied in thin films. Polycrystalline targets for laser ablation were prepared by mixing high purity V2O5 or Nb2O5 powders with a well characterized YBa2Cu3O(y) powder in the range 0 to 4 wt percent by solid state reaction method. Thin films (approximately 1500 A thickness) of the above targets were grown on (100) SrTiO3 (STO) and (100) LaAlO3 (LAO) substrates at 700 C temperature by pulsed laser deposition (PLD) technique. In the case of Nb2O5 addition we have noticed an increase in J(sub c) up to 0.5 wt percent and higher additive concentration (greater than 0.5 wt percent) have degraded the superconducting properties. However, in the case of V2O3 addition, there is an improvement in current density and microstructural properties up to 1 wt percent and the superconducting properties degrade for concentrations greater than 1 wt percent. The best J(sub c) for 0.5 wt percent of Nb2O5 added YBCO thin film is 1.6 x 10(exp 6) A/sq cm and for that of V2O5 added sample is 3.4 x 10(exp 6) A/sq cm at 77 K as compared to the pure YBa2Cu3O(y) (YBCO) film J(sub c) (1.2 x 10(exp 6) A/sq cm) observed on STO substrates. The reason for improvement in J(sub c) and microstructural properties in the case of V2O5 addition could be due to the low melting of V2O5 (690 C) which can act as a very good surfactant during deposition. Over all, we have realized that Nb2O5 addition or V2O5 addition to YBCO have shown significant improvement over the undoped YBa2Cu3O(7-x) films grown under identical conditions.

Srinivas, S.

Part distortion monitoring in additive manufacturing using machining

In additive manufacturing, accumulation of residual stresses can result in severe part distortion from the desired preform shape. Current methods for in-situ part distortion monitoring in additive manufacturing typically require expensive sensors, or capital equipment, and require time-consuming post-processing to understand the shape deviation. This paper presents an in-situ method, in the context of hybrid manufacturing, for part distortion detection using machining of additively manufactured parts. As a surrogate, three test artifacts were used to represent different distorted geometries. The tool axis positions from the machine tool controller and the cutting power were monitored during a facing operation. Cutting power data was used to detect the tool entry and exit in the workpiece using a novel approach with power standard deviation metric. The workpiece geometry and distorted configuration was subsequently predicted for positional and rotational deviations to within 2 mm accuracy using synchronized tool position data with cutting power. The proposed method can be used in a hybrid (additive and subtractive) machine tool to periodically check part distortion in the additive build. The method is applicable for any additive process and is low-cost and computationally inexpensive.

36 MATERIALS SCIENCE