2023 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2023): Poster Session
Program Organizers: Joseph Beaman, University of Texas at Austin
Tuesday 4:00 PM
August 15, 2023
Room: Salon JK
Location: Hilton Austin
A Pilot Study on Temperature Monitoring and Morphology of the Meltpool in EB-PBF of Copper using Numerical and Analytical Models: Elmira Sharabian1; 1UTEP University
In this research, a pilot study on temperature monitoring of electron-beam powder bed fusion of copper has been investigated. Two different methods including an analytical model and a numerical simulation were tested to estimate the temperature and morphology of the meltpool. The analytical model was developed based on process parameters (beam power and speed) and thermophysical properties of the material. The analytical heat transfer model was developed for copper and the results were compared with numerical outcomes. Experimental tests were used to verify both the analytical and numerical models. Results demonstrated that the developed analytical model containing the conduction of the material has great accuracy. Statistical analysis showed process parameters have a significant effect on morphology of meltpool and temperature. The proposed model and simulation can be useful to predict the meltpool morphology which drives the bonding quality of the subsequent layer and the overall quality of the printed parts.
Data Pipelines for Direct Ink Write Digital Twins: Alex Caviness1; 1LLNL
We present on automated data capture and storage for machine learning-aided digital twins, with a focus on mechanical test data streams. Our pipeline connects mechanical test measurement data using a web interface, test hardware API, and a database, allowing for efficient and accurate data collection for our digital twin platform. These digital twins can then be used for process and part evaluation, which can help optimize the design and performance of parts. We present the benefits of using automated data capture and storage, including improved data quality, reduced time and resources required for data collection, and improved accuracy and consistency of data. Though rooted in Direct Ink Write, this work is extendable to other additive manufacturing techniques in which data science can establish a link between the fabrication process and part performance.
Design of Lightweight 3D Printed Structures for the 7th Annual 3D Printed Aircraft Competition: Robert Taylor1; Orie Nzere1; Son Pham1; Andy Huynh1; Thomas Allsup1; Emma Yang1; 1University of Texas Arlington
The University of Texas at Arlington (UTA) hosts the 7th Annual 3D Printed Aircraft Competition on July 8, 2023, to provide undergraduate and graduate student teams from a range of universities a competitive event to learn and apply principles of aircraft design, lightweight structural design, and effective design for additive manufacture. The competition requirement for a fully 3D printed airframe and a limitation on power duration during the flight motivates students to develop lightweight designs that effectively integrate knowledge of structural mechanics with 3D printing process mechanics. This poster discusses fixed and rotary wing aircraft designs from student teams at the University of Texas at Arlington using Fused Filament Fabrication (FFF), Continuous Fiber Fabrication (CFF), and MultiJet Fusion (MJF) 3D printing technologies. Design and process considerations are discussed as well as lessons learned. The poster also presents competition results.
Development of Joint Manufacturing and In-line Metrology System for the Patterning of 3D Holographic Structures in Roll-to-roll Processes: Barbara Groh1; Cody Lee1; 1University of Texas at Austin
Roll-to-roll (R2R) fabrication at the micro and nano scales promises to increase manufacturing throughput and reduce unit cost while providing avenues for unique product applications. By exploring the potential of creating 3D structures with a single pattern and being able to confirm pattern success in-situ, existing overlay error can be mitigated. This paper demonstrates steps being taken to combine a R2R 3D nanolithography tool and an AFM-based in-line metrology tool into a functional system for patterning precise 3D structures. The existing manufacturing system will be adapted to pattern complex structures with a flexible PDMS mask currently being proven on stationary substrates. Modifications to the AFM system will include a focus on imaging patterns with varying mechanical properties and tailoring the system to include gathering mechanical information as well as imaging. By mapping surface features, the AFM tool will identify surface imperfections and predict failures occurring within the 3D structure.
Dissimilar Vacuum Brazing of Additive Manufactured 17-4PH Stainless Steel to Conventional 304 and 17-4 Stainless Steel by BNi-2 Brazing Filler Material: Tansu Göynük1; Orkun Umur Önem1; Evren Yasa2; İshak Karakaya3; 1ROKETSAN A.S.; 2AMRC; 3Middle East Technical University
With the development of technology, it has become critical to be able to produce parts with complex geometry at once without using other production technology. Additive manufacturing methods have taken their place in the competitive market saving both time and cost. Vacuum brazing of additive manufactured 17-4PH stainless, conventional AISI304 and 17-4PH stainless steel alloys were examined. In this work, parts were brazed under 10-6 Torr, at 1050°C for 20 minutes using BNi-2 filler material. Vacuum brazed parts were examined in terms of microstructure, wetting, and mechanical strength. Wetting behaviour of brazing on different materials was evaluated by measurement of contact angle and wetted area using optical microscopy on different materials. Microstructures were examined by SEM and EDS. Finally, tensile testing was done on joints to evaluate whether the surface roughness and brazing of different materials affects strength of brazed parts.
Fabrication of Solid-state Electrolytes Using 3D Printing for Lithium Metal Batteries: John Obielodan1; Jacob Ferguson1; Josh Beyer1; Zhezhen Fu2; 1University of Wisconsin-Platteville; 2Penn State Harrisburg
3D printing offers several benefits including the capabilities for flexible battery architectures. Solid-state batteries are being developed to overcome the drawbacks of lithium-ion batteries such as low energy density and fire safety concerns. In this work, colloidal pastes of ceramic type Li-garnet solid-state electrolyte (Li6.75La3Zr1.75Ta0.25O12) mixed with photocurable resin were used to 3D print test samples. The pastes demonstrated promising printing behaviors that allow the fabrication of various structures. The samples were sintered at temperatures between 900oC and 1250oC for durations ranging from 1 to 12 hours. X-ray diffraction shows that they maintain single cubic Li-garnet phase. They were densifiable to high relative densities based on SEM observations. The ionic conductivities of the samples were obtained. The results shows that 3D printing is a promising route for fabricating solid-state batteries.
Influence of In-process Layer-wise Surface Property on the Mechanical Properties of Laser Powder Bed Fusion Products: Haolin Zhang1; Heyang Zhang1; Alexander Caputo2; Chaitanya Krishna Vallabh3; Richard Neu2; Xiayun Zhao1; 1University of Pittsburgh; 2Georgia Institute of Technology; 3Stevens Institute of Technology
Laser powder bed fusion (LPBF) additive manufacturing has the potential of efficiently producing components with high resolution and complex geometry. However, during LPBF the as-manufactured layers usually possess rough surfaces that lead to porosity formation and unsatisfactory mechanical properties, necessitating extensive post-processing prior to being deployed for practical applications. Fringe projection profilometry (FPP) is a cost-effective, non-invasive technology that has been developed for in-situ LPBF surface measurement. In this work, we first develop a FPP measurement data analytics framework to extract in-process layer surface features, which can serve as implications of potential defects that could be caused by spatters, balling, or shrinkage. Then, we conduct different regression analyses to correlate the inferred layer-wise surface defects and the FPP-measured thickness profiles with the ex-situ characterized part properties including hardness, fatigue life, and critical crack locations. The proposed FPP-based framework can help optimize or control LPBF processes for achieving improved mechanical properties.
Modifying Glass Surface Morphology via Temperature-controlled Laser Melting: Andre Bos1; Douglass Meredith1; Robert Landers2; Edward Kinzel2; John Bernardin1; 1Los Alamos National Laboratory; 2University of Notre Dame
Glass Laser Additive Manufacturing is an emerging technology with a wide range of applications in chemistry, biology, optical science, and engineering. A custom printer was developed utilizing a 4-axis motion system, infrared radiation-based thermal sensors, and a CO2 laser to heat glass filaments above their working temperatures and deposit them into various shapes. Complex path planning is needed to deposit the glass to maintain a constant pulling action with the rod and maintain a melt pool between the rod and substrate or previous layer for printing. Similar path planning algorithms along with a feedback control system are used to alter the surface morphology of the deposited glass. To mitigate undesirable defects from overheating the glass, a closed-loop feedback algorithm automatically modifies the laser duty cycle given IR camera measurements to maintain a constant melt area temperature.
PEEK Parameter Optimization for Fused Deposition Modeling: Quang Ha1; Deborah Hagen1; Evan Hagin1; 1Sandia National Laboratory
Polyetheretherketone (PEEK) is an engineering grade thermoplastic with high performance and high reliability. PEEK has excellent mechanical properties and chemical compatibility. Another desirable property of PEEK includes the ability to operate in much higher temperature environments compared to other commonly used additive manufacturing polymers. However, PEEK can be very difficult manufacture through Fused Deposition Modeling (FDM) due to the properties mentioned above and requires high nozzle temperature and a heated build chamber. Some printing defects of FDM PEEK include inaccurate dimension, poor layer adhesion, varying surface topography, and excessive warping. To minimize the defects during the printing process, we optimized print parameters which include print speed, extrusion/retraction rates, and print process temperature. This resulted in improved part characteristics while benefitting from FDM style additive manufacturing to create complex structures.
Wide-field Low-coherence Interferometry for Keyhole Depth Measurements in Laser Powder Bed Fusion: Matthias Beuting1; Kayvan Samimi1; Sayed Hojjatzadeh1; Erick Oberstar1; Melissa Skala1; Lianyi Chen1; Scott Sanders1; 1University of Wisconsin-Madison
We present a method for measuring keyhole depth and high-frequency melt pool fluctuations in laser powder bed fusion using optical interferometry. Previous studies utilized a technique called inline coherent imaging (ICI) based on the same principle involving scanning a focused interrogation beam across the area of interest to measure melt pool topography. In contrast, our proposed approach uses an enlarged beam fixed in position relative to the process laser to cover the entire keyhole area. We demonstrate that depth information can be reconstructed from this signal, enabling the identification of the lowest point within the keyhole. Eliminating the need for precise mechanical beam steering can improve time resolution while reducing the complexity and cost of on-machine sensors.
Photoinhibition Aided Vat Photopolymerization (PinVPP) Additive Manufacturing: Yue Zhang1; Yousra Bensouda1; Xiayun Zhao1; 1University of Pittsburgh
Vat photopolymerization (VPP) among other additive manufacturing processes have a great potential to rapidly print complex 3D components out of a matrix of photo-curable resin. Photoinhibition has been demonstrated by leading research groups to be able to form a thicker deadzone that enables faster print and vertical micro-topography. However, the potential application of photoinhibition to improve VPP can be extended for lateral over-curing control. In general, photoinhibition aided VPP (PinVPP) employs two simultaneously projected optical masks for initiating and inhibiting the polymerization, respectively, at disparate wavelengths. In this work, we present two study cases of PinVPP – one general VPP print for polymeric parts and one VPP of ceramic slurry. Our initial experiment aims to understand the correlation of the two-wavelength exposure intensities with the inhibition zone thickness, the working curve thus the critical energy and depth of penetration, and the effects on print speed and geometric properties in PinVPP.
Comparative Success of EBM and SLM for Fabrication of Lattice Structures in Metal Orthopaedic Implants: Zeynep Kirimlier1; Ece Tutsak1; Onur Demirak2; Alptuğ Öztaşkın3; İpek Döş3; 1Trabtech Advanced Implant Technologies; 2Ankara University; 3Middle East Technical University
Lattices are applied to the surface of implants to create the trabecular intersection that mimicks cancellous bone. The producibility of lattice structures with EBM and SLM are still being investigated since these PBF-AM methods have differences in principle and operation. The objective of this study is to conduct comprehensive analysis of different types of lattices manufactured by EBM and SLM in terms of producibility, quality, mechanical and biological characteristics.Eight different lattice unit cells available in the nTopology were selected to design lattices considering porosity, strut thickness, and cell size. A Python wrapper script was implemented, a finite element analysis has been conducted. Similar lattices to the cancellous bone were selected. To obtain optimum process parameters, bulk samples were produced for both SLM and EBM. Density test and microstructural analysis were performed. With the optimum process parameters, lattice samples were produced. SEM examination, compression, cytotoxicity and osseointegration tests were conducted.
Investigation of Electrical Properties in TPU/CNT Conductive Composites: Hansol Kim1; Jongho Jeon1; Sangmin Lee1; Jungho Cho1; Sang-Woo Han1; 1Chungbuk National University
Conductive composites used in flexible circuits have a wide range of applications, such as wearable sensors, proximity sensors, and pressure sensors. Polymers and carbon nanotubes (CNTs) are representative materials in conductive composites. Polymers provide flexibility, while CNTs impart electrical properties, making them suitable for this purpose. In this study, conductive composites were produced by blending thermoplastic polyurethane (TPU) with CNTs and investigating their electrical properties using fused filament fabrication (FFF). The melting mixing method was used for composite fabrication. As the wt% of CNTs increased, the electrical resistance decreased, and the resistance showed a decreasing trend with increasing applied voltage. In cases where the wt% of CNTs was low, the resistance decrease with increasing voltage was relatively high, which can be explained by the tunneling conduction mechanism in the conductive composite.
Mechanical and Corrosion Response of Minor and Trace Elements in CoCrMo Alloy Powders on Additively Manufactured Dental Crowns and Bridges: Ipek Dös1; Ece Tutsak1; Zeynep Kırımlıer1; 1TraBtech
SLM is an additive manufacturing method for producing dental crown and bridges (DCB) using CoCrMo alloy powders. The powder composition plays a crucial role in the mechanical and chemical bonding of metal and ceramic materials. This study investigates the effect of minor and trace percentage in the composition on CoCrMo powder alloys. Three CoCrMo alloy powders that have different minor and trace component weight percentages have been analyzed. Density and microstructural analysis were carried out to determine the optimal SLM process parameters and heat treatment for bulk specimens. Tensile, corrosion and de-bonding crack initiation tests were performed on the samples. Results show that slight differences in chemical composition can impact the mechanical and corrosion responses, highlighting the importance of carefully selecting the powder composition for successful SLM manufacturing of dental parts.
3D Bio Printed Biodegradable Composite Material for Pediatric Craniomaxillofacial Implants: Ipek Dös1; Ece Tutsak1; Zeynep Kırımlıer1; Onur Demirak1; 1TraBtech
Developing an ideal bone substitute material for repairing bone deformities is a challenge in clinical orthopedics. Conventional methods are inadequate for creating complex anatomical geometries. Additive manufacturing is a growing field in bone tissue engineering due to its reproducibility, high accuracy, and rapid production of patient-specific scaffolds. (PLGA)- based artificial bone substitutes show promise in biocompatibility, mechanical properties, degradability, and ability to promote bone regeneration. This study is dedicated to pediatric craniomaxillofacial implant treatments using PLGA and hydroxyapatite nanoparticles (nHA) to fabricate 3D porous scaffolds by Fused Deposition Modelling. Gyroid lattice geometries were chosen for osteointegration and self-supporting features. Optimum nHA weight percentages and production parameters were determined, and mechanical and biological tests were completed. The producibility of innovative patient-specific geometry design with this biodegradable composite material is discussed. This study provides a solution for CMF implant treatments that do not hinder the physical growth of developing children.
Development of Soft Gripper Pneumatic Control System Based on Deep Reinforcement Learning: Seongyeon Kim1; Kiseong Kim1; Jongho Shin1; 1ChungbukNationalUniversity
As interest in soft grippers soared, many studies have been performed to control the soft gripper. For the soft gripper control, a soft gripper model is required first. Usually the soft gripper modeling has been done through finite element analysis, which takes lots of time and is effective only in limited situations. Therefore, research on deep learning-based modeling with a small amount of FEM results has been extensively conducted, and some satisfactory results have been reported. However, since the model is expressed in the form of a neural network, it is difficult to utilize general control methods, so research on optimal control or deep reinforcement learning is being attempted. In this study, we propose a pneumatic control system for the soft gripper control based on the DRL. To this end, the soft gripper and DRL-based controller are directly developed, and experiments are performed and the results are analyzed.
Distortion and Residual Stress Mitigation of Large Parts for Wire-arc Additive Manufacturing: Wen Dong1; Xavier Jimenez1; Carter Gassler1; Albert To1; 1University of Pittsburgh
Wire arc additive manufacturing (WAAM) has drawn increasing attention due to its ability to print large metal parts. However, thermal gradients during the process can result in significant residual stress and distortion, negatively affecting product quality and making post-processing more difficult. In the present work, we have implemented several strategies when printing a part ~900 mm long to mitigate these issues. Firstly, a fixture designed based on topology optimization is attached to the baseplate to reduce distortion. However, cracks were observed in the baseplate near the deposit ends after the first trial. Then, we carefully examined and modified the deposit and baseplate shapes to further reduce the residual stress. The second trial successfully printed a part that met the required specifications. Due to its high accuracy and low cost, the modified inherent strain (MIS) method is employed to predict the distortion and residual stress for fixture design and shape modification.
Efficient Thermomechanical Simulation for WAAM using Automated GPU-based Modeling: Xavier Jimenez1; Albert To1; Florian Dugast1; Alaa Olleak1; 1University of Pittsburgh
Simulating the wire arc additive manufacturing (WAAM) process can be challenging due to the large part size. An improved workflow that combines automation and GPU accelerated modeling using the Pittsburgh Additive Manufacturing Simulator (PAMSIM) has been implemented. Although thermal simulations are very fast, thermomechanical simulations can take 10 to 20 times more time and thus become impractical to implement before every print. This work focuses on implementation of an automated computational framework for the flash heating network combined with the temperature dependent inherent strain. The improved workflow helps to accelerate the manufacturing process of new parts using WAAM, through thermal and residual stress results at the part scale level.
A Data-driven Distortion Compensation Method and the Necessity to Consider Spatial Effects in Binder Jet Parts: Basil Paudel1; Albert To1; 1University of Pittsburgh
Binder jet parts undergo significant deformation during the sintering, a process that facilitates densification. This process-induced sintering distortion may result in parts with unacceptable geometric accuracy with the extent heavily dependent on the initial green density of the part. The current work investigates the effect of part size and location within the print build on the green density and proposes an approach to compensate input geometry based on mechanistic simulations using a data-driven method. Finally, the proposed approach's efficacy is validated both numerically and experimentally by comparing the deformed sintered shape against the target.
Electrochemical Stability of 3D Printed Separators and Gaskets for Shape-conformable Lithium-ion Batteries: Christian Fernandez1; Eva Schiaffino Bustamante1; Ana Aranzola1; Ana Martinez1; Alexis Maurel1; Eric MacDonald1; 1The University of Texas at El Paso
As the demand for rechargeable batteries increases, the concept of utilizing 3D printing technologies to produce tailored battery components with complex geometries that can be customized for a specific application has gained relevance. This work focuses on 3D printing via vat polymerization of separator and gasket components using commercially available and laboratory-made photocurable resins as material feedstock. In-depth electrochemical, rheological, and mechanical characterization steps are performed. In particular, the 3D printed samples are tested by means of linear sweep voltammetry, a common stability analysis, to ensure their electrochemical inertness during the charge and discharge of a classical lithium-ion battery. This work paves the way towards the development of shape-conformable battery individual components and fully 3D printed energy storage devices.
Elucidating the Role of Local Preheat Temperature on Multi-track Melt Pool Morphology Variation for Inconel 718 Laser Powder Bed Fusion via CIFEM: Seth Strayer1; William Frieden Templeton2; Alaaeldin Olleak1; Florian Dugast1; Sneha Narra2; Albert To1; 1University of Pittsburgh; 2Carnegie Mellon University
Despite advancements in finite element (FE) thermal simulation techniques for laser powder bed fusion (L-PBF), these models employ an effective heat source model, which invokes a tedious calibration process and provides inaccurate thermal fields compared to high-fidelity computational fluid dynamics (CFD) simulations. Accordingly, the driving force behind melt pool size variation, especially in the multi-track case, has remained enigmatic up to this point. In this work, the authors extend CIFEM to multi-track scenarios for Inconel 718 L-PBF to help address these issues. CIFEM's data-driven heat source model is trained to predict the thermal fields from multi-track CFD simulations with different scan lengths to establish the role of a local preheat temperature metric. By imposing these fields on the desired FE solution domain, the simulated melt pool sizes are within 10% error regarding experimental measurements up to five consecutive tracks while providing substantially more accurate thermal fields to traditional FE models.
Enabling Part-scale Melt Pool Prediction in Laser Powder Bed Fusion via a Global-local Thermal Process Simulation Model: Shawn Hinnebusch1; William Templeton2; Alaa Olleak1; Praveen Vulimiri1; Florian Dugast1; Sneha Narra2; Albert To1; 1University of Pittsburgh; 2Carnegie Mellon University
Predicting accurate thermal history in laser powder bed fusion (LPBF) is a challenging problem. Layerwise simulations are geometry dependent for calibration and cannot capture the local heat accumulation due to the laser scanning process. Scanwise simulations are far more accurate but are restricted in size to just a few millimeters. An infrared (IR) camera is mounted on an LPBF system to calibrate and validate the interpass temperatures. Using a GPU-accelerated finite element based solver, the geometry-agnostic layerwise calibration was completed with less than 6% mean absolute percentage error. The layerwise simulation provides an accurate thermal boundary condition for the local scanwise simulations at a reduced computational cost. Melt pool width and depth can be predicted in any location before printing. Integrating high-speed layerwise simulations with scanwise simulations results in a low-cost yet accurate thermal history that identifies problematic regions before costly builds.
Fabrication of 3-Dimensional Flexible Tactile Sensor using Pressure Sensitive Material: Chae Young Park1; Ho-Chan Kim2; Chiyen Kim3; In Hwan Lee1; 1Chungbuk National University; 2Andong National University; 3Cheongju Campus of Korea Polytechnics
In this study, sensors of various shapes were fabricated through the additive manufacturing process using pressure sensitive material. Furthermore, various response characteristics were observed with several 3-dimensional shapes. The flexible tactile sensors were fabricated by stacking Multi walled carbon nanotube-based pressure sensitive materials in layer-by-layer manner. The response characteristics according to shape and the number of layers were studied for given mechanical stimuli. In the case of curved sensors, the initial resistance and resistance change decreased as the number of layers increased. However, there was no significant difference in response time and recovery time depending on the number of layers.
A Local Preheat Temperature Dependent Stochastic Finite Element Heat Source Model for Inconel 718 Laser Powder Bed Fusion: Seth Strayer1; Albert To1; 1University Of Pittsburgh
Thermal field prediction of laser powder bed fusion (L-PBF) via the finite element method can help optimize the process while avoiding the cost of experiments. However, these models abstract critical physics into an effective heat source model that does not readily capture the experimentally-measured melt pool size magnitude and variance, especially for multi-track cases. This work presents a novel local preheat temperature dependent stochastic heat source model to help address these issues. First, the heat source parameters are calibrated to the mean melt pool sizes for Inconel 718 L-PBF multi-track experiments. These parameters are predicted during the simulation to establish the role of a local preheat temperature metric. Second, random sampling techniques are employed to match the experimentally-measured variance within each track. Accordingly, the simulated melt pool sizes are within 10% error regarding experimental measurements up to five consecutive tracks while more closely matching the measured melt pool size variance.
Accelerating Design and Additive Manufacturing of Polymer Matrix Composites: Olivia Fulkerson1; Akash Deep1; Srikanthan Ramesh1; Hadi Noori1; Erik Inman1; 1Oklahoma State University
Polymer matrix composites (PMCs) offer exceptional mechanical performance and low weight, making them ideal for various applications. 3D printing enables the efficient production of functional composite parts with customized mechanical properties. However, the current optimization process for 3D printing PMCs involves trial-and-error, which is time-consuming and costly. To address this, a Bayesian optimization (BO) framework is proposed in this project to accelerate the design and production of high-strength, low-weight 3D printed PMCs. The BO framework models the 3D printing process as a black-box function using minimal experimental data. A probabilistic model is developed to recommend the next set of experiments iteratively until the optimized process parameters are reached. Our results demonstrate that the proposed method can efficiently find the global optima for black-box functions, such as 3D printing. This research has potential to benefit the additive manufacturing industry by providing a scalable approach that can accelerate the process workflow.
Mechanical Test Plan of Niobium Alloy C103 for Laser Powder - Direct Energy Deposition: Hugo Garcia1; Brandon Colón1; Kurtis Watanabe1; Francisco Medina2; 1University of Texas at El Paso; 2W.M. Keck Center for 3D Innovation
Niobium Alloy C103 is a material with a shorter background in Laser Powder - Directed Energy Deposition when compared to other materials. However, C103 stands out in having relatively strong mechanical properties at high temperatures. Thus, making it a great candidate for applications such as propulsion, hypersonics, nuclear and more. This poster will present a test plan for quasi-static testing of thin wall specimens to better understand the mechanical response of C103. Thin wall geometries were printed using RPM Innovations’ 222XR LP-DED with a single pass beam. There are several tensile specimens proposed with their corresponding finite element analysis which are discussed in detail in the poster. A total of 4 specimen conditions are proposed: as built, stress relieved (SR), and 2 different hot isostatic press (HIP) heat treatment to then be later subjected to a tensile test.
Additively Manufactured LiCoO2-based Photocurable Resin as Positive Electrode for Lithium-ion Batteries: Ana Aranzola1; Eva Schiaffino1; Alexis Maurel1; Ana Martinez Maciel1; Eric MacDonald1; 1University of Texas at El Paso
Rapidly advancing technology demands equally advanced subcomponents. Multi-material additive manufacturing (AM) has the potential to transform the production of lithium-ion batteries by enhancing the battery structural design to enable three-dimensional ion diffusion, as opposed to the one-dimensional diffusion observed in commercial lithium-ion batteries. In turn, 3D diffusion allows to maximize the battery power performances. This work focuses on the development and 3D printing of a novel photosensitive material loaded with lithium cobalt oxide (LiCoO2) electroactive active material to act as the positive electrode. Using the Vat Photopolymerization (VPP) printing technique, the material was successfully printed at varying battery material loadings. After thermal post-processing that did not compromise mechanical integrity, promising electrochemical specific capacity values were obtained, approaching commercial values of lithium-ion batteries. These results pave the way towards newly designed 3D printed batteries promising better performance and non-obtrusive, conforming shapes to specific designs for different applications.
Monitoring of Process Stability in Laser Wire Directed Energy Deposition using Machine Vision: Anis Asad1; Benjamin Bevans1; Jakob Hamilton2; Iris Rivero2; Prahalada Rao1; 1Virginia Tech; 2Rochester Institute of Technology
The goal of this work is to mitigate flaw formation in parts made using the laser wire directed energy deposition (LW-DED) additive manufacturing process. As a step towards this goal, the objective of this work is to use real-time data from a meltpool imaging sensor to detect process instabilities. This is an important area of research, as LW-DED process tends to incessantly drift due to poorly understood thermophysical phenomena and stochastic effects. To realize the foregoing objective, we developed a machine learning model that acquires real-time imaging data, and automatically classifies the process state into one of four possible regimes: stable, dripping, stubbing, and incomplete melting. Through single track experiments conducted over 128 conditions, we show that the approach is capable of accurately classifying the process state with a statistical fidelity approaching 90% (F-score).
Monitoring of Single-track Quality in Laser Powder Bed Fusion using In-situ Thermionic Sensing: Benjamin Bevans1; Philip DePond2; Aiden Martin2; Nick Calta2; J-B Forien2; Gabe Guss2; Brian Giera2; Prahalada Rao1; 1Virginia Tech; 2Lawrence Livermore National Laboratory
This work concerns the laser powder bed fusion (LPBF) additive manufacturing process. In this work track quality was monitored in-situ using a novel thermionic sensing approach. It is important to monitor the quality of the track in LPBF as it is the basic building block of the part. In this work, track quality is defined as track width and the percent continuity of the track. The objective of this work is to detect the onset of track deviations using signatures extracted from a novel thermionic sensor. This thermionic sensor is attached to the substrate and measures the voltage response of the electrons released when the laser interacts with the build plate. The signals from the thermionic sensor are analyzed using empirical mode decomposition, and the derived signatures are used subsequently within elementary machine learning models to predict the quality of track.
Building Blocks for Understanding Triply Periodic Surfaces: A Visual and Tactile Learning Aid: Joseph Fisher1; Simon Miller1; Joseph Bartolai1; Michael Yukish1; Timothy Simpson1; 1Pennsylvania State University
We present an additively manufactured visual and tactile teaching aid to show how Triply Periodic Minimal Surfaces (TPMS) divide space and how we can generate multiple unique lattice structures from one surface. TPMS can be used as the basis for the design of lattice structures for additive manufacturing, and they divide space into two interwoven volumes that remain separate throughout three-dimensional space. The surface itself can be offset and used as a lattice structure and the interwoven volumes are also of interest because they can act as the fluid domains in a heat exchanger or can be modeled on their own to be used as unique lattice topologies. To produce this aid, we have subdivided lattice structures based on the IWP TPMS into regions that can be assembled separately or together without geometric interference. We use keyed patterns of magnets to make assembly of the lattices faster and easier.
Structural Analysis and Design of Mantis Shrimp-inspired Composites for Enhanced Impact Resistance: Ailin Chen1; Ran Tao2; Alexander Landauer2; Sangryun Lee3; Jiyoung Jung1; Daniel Lim1; Ukamaka Ezimora4; Grace Gu1; 1University of California Berkeley; 2National Institute of Standards and Technology; 3Ewha Womans University; 4University of California Merced
The mantis shrimp's club possesses both destructive power and exceptional energy-absorbing properties. It has attracted the interest of researchers seeking to develop protective systems with leap-ahead properties. The club’s unique microstructure includes a tough, fibrous interlayer that exhibits a sinusoidal periodicity. Prior research has primarily focused on mimicking either the material composition or fiber orientation of the mantis shrimp, typically under static loading conditions. Here we merge the club’s sinusoidal interlayer design into a composite microstructure and fabricate it using a dual-material 3D printer. A computational model is developed to reveal the structure’s failure mechanism under low-velocity impact loading. Experimental drop-tower testing is used to validate model predictions. Using this model, we further investigate the structure's response to high-velocity impact and optimize its components for enhanced energy absorption. This work improves our understanding of the shrimp’s crack propagation mechanisms under dynamic loading, enabling the development of better amphibious protective systems.
Characterization of Thermoset Feedstocks for Laser Powder Bed Fusion: Malik Blackman1; Meisha Shofner1; Camden Chatham2; 1Georgia Institute of Technology; 2Savannah River National Laboratory
As additive manufacturing (AM) technology has developed and progressed, a constant topic of research in the area has been to expand the library of materials that may be used with these techniques. Among AM methods that use polymers, laser powder bed fusion (L-PBF) has preferentially used thermoplastic polymers as its starting materials, but the deposition and material joining method employed in L-PBF may be compatible with powdered thermoset polymer precursors as feedstocks. Therefore, the objective of this work is to examine how thermosetting polymers may be used more widely with L-PBF. Specifically, materials characterization experiments are designed to assess how aspects of L-PBF processing will affect curing behavior, part formation, and material properties. The outcomes of this work will establish a methodology for evaluating candidate thermosetting polymer feedstocks for use with L-PBF and an understanding of the sensitivity of material behavior and properties to different L-PBF process parameters.
Data-driven Local Porosity Prediction in Laser Powder Bed Fusion via In-situ Monitoring: Berkay Bostan1; Shawn Hinnebusch1; David Anderson1; Albert To1; 1University of Pittsburgh
In this study, the geometry-agnostic deep learning scheme has been developed for defect detection during the laser powder bed fusion (LPBF) process. DNNs model has been trained that gives +90% accuracy with a relatively smaller dataset. Inputs to DNNs include various thermal signatures (interpass temperatures, heat intensities, and cooling rates) and spatter locations. At the same time, when making predictions, the DNNs architecture considers the features of not only the relevant pixel, but also neighboring pixels in all directions (desired order of neighbors in the current, upper, and lower layers). The potential outcomes of this study are simultaneous defect prediction during manufacturing and repairing the defects by rescanning the concerned region. Furthermore, defect formation mechanisms have been investigated by SHAP (SHapley Additive exPlanations) feature importance analysis method, and it is observed that spattering is the most dominant factor for defect formation until the melt pool reaches a certain size.
Metal Additive Manufacturing of A36 Steel to Improve Techno-economic Performance of Marine Renewable Energy Technology: Hyein Choi1; Jesse Adamczyk1; Kasandra Herrera1; Erin Karasz1; Michael Melia1; Shaun Whetten1; Michael Heiden1; 1Sandia National Laboratories
Marine renewable energy has the potential to bolster clean energy production on a global scale. However, these technologies need to be more economical to counter traditional energy generation. Wave energy converters (WEC) are one facet within this realm that have high costs associated with fabricating heavy, structural A36 steel parts. Additive manufacturing (AM) methods such as wire arc additive manufacturing (WAAM) have the potential to produce more cost-effective marine energy components by producing higher complexity, lightweight parts and reducing lead time. In this study, WAAM and wrought A36 steel tensile coupons were produced, and mechanical properties were compared under dry and wet conditions. WAAM-produced A36 steel retained significantly higher mechanical properties in both dry and long-term corrosion conditions. The solidification microstructure was investigated to better understand how WAAM’s manufacturing route improved performance for renewable energy applications.SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.
Computer Vision for Powder Mass Flow Rate Measurement in Blown Powder Directed Energy Deposition: Callan Herberger1; Alan Burl2; Erik LaNeave1; Janely Villela1; Juan Villela1; Lauren Heinrich3; James Haley3; Thomas Feldhausen3; Chris Saldana2; Eric MacDonald1; 1The University of Texas at El Paso; 2Georgia Tech; 3Oak Ridge National Laboratory
Laser Powder Directed Energy Deposition can deliver metallic powder to a structure coincident with the focused beam of a laser to deposit metal with 3D control. Monitoring the mass flow rates of these powders is crucial to ensure quality and yield. Moreover, although less explored, the ability to combine two or more powders in the delivery system can enable in situ alloying with compositional changes throughout a structure. The present work explores an unobtrusive method to measure mass flow rate of a single type of metal powder through a delivery system to the deposition head. With high-speed imaging through a transparent tube inserted in the delivery system prior to reaching the deposition head, computer vision can verify the mass flow rates to avoid over or under building of the intended geometry. Furthermore, the potential exists to distinguish different metal powders to ensure correct metallurgical composition just prior to deposition.
Layer-wise Prediction of Microstructure Evolution in Laser Powder Bed Fusion Additive Manufacturing using Physics-based Machine Learning: Alexander Riensche1; Benjamin Bevans1; Grant King2; Ajay Krishnan3; Kevin Cole2; Prahalada Rao3; 1Virginia Tech; 2University of Nebraska-Lincoln; 3Edison Welding Institute
In this work we developed a framework to predict microstructure formation in the laser powder bed fusion (LPBF) of Inconel 718 parts. The microstructure is predicted as a function of sub-surface cooling rate estimated from a rapid part-level computational thermal model within elementary machine learning models. In this work, the microstructure evolved is quantified layer-by-layer in terms of three aspects: meltpool depth, grain size (primary dendritic arm spacing), and microhardness. The approach predicts the microstructure evolved with statistical fidelity exceeding 85% (R2). This is substantial improvement over existing microstructure prediction which are only able to predict the microstructure of a small region (~1 mm3) and not of the entire part.
Enhancement of Profile Data for Repetitive Process Control Measurements in DED Additive Manufacturing: Kyle Saake1; Elias Snider1; Douglas Bristow1; 1Missouri University of Science and Technology
Layer-to-layer repetitive process control (RPC) is a powerful tool in minimizing defects for direct energy deposition (DED) additive manufacturing, specifically for blown powder systems. Layer-to-layer feedback control structures require a profile scanner (a Keyence profilometer in this work) to be integrated between layers for error measurements. Obtaining quality scans while minimizing scanning downtime is important for reducing cost in such control structures. An approach for collecting quality scanner data by combining multiple scans is presented. Fitting optimizations are discussed which align scans to produce high-fidelity profiles of printed parts. Example datasets are presented with relevant analysis of data confidence and validation metrics. Integration of the scanning algorithm into the existing RPC structure is discussed with implications on the build process.
Increasing Precision Towards NiTi Lattice Structure using PBF-EB: Zeyu Lin1; Sasan Dadbakhsh1; Amir Rashid1; 1KTH
The electron beam powder bed fusion (PBF-EB) is limitedly used to manufacture complex structures such as delicate lattices. Nickel-titanium (NiTi) has been chosen for fabricating the lattice structure due to its wide utilization in the biomedical sector. However, issues may arise when manufacturing angled trusses while the dimensional inaccuracy increases with the increase of the angle between the truss member and the vertical build direction. Therefore, two different scan strategies: spot melting and linear melting were used to manufacture the lattice structures respectively to compare the dimensional accuracy of different structures. This investigation highlights that linear melting is prone to maintain the geometrical accuracy of line-based structures with a limited influence from the scan speed while spot melting is more capable of manufacturing the point-based structure with a higher geometrical resolution.
Data Management for Additive Manufacturing Process Monitoring: Matthew Roach1; Dominik Kozjek2; Clayton Cooper3; Kathy Babusci4; Bradley Jared1; 1University of Tennessee, Knoxville; 2Northwestern University; 3Case Western Reserve University; 4Ohio State University
Managing process monitoring data generated from additive manufacturing presents multiple challenges. These challenges come from every step in the workflow including acquisition, transfer, storage, archive, standardization, analysis, and visualization. Acquisition systems need to be robust to collect different data formats while maintaining a synchronized timeline. Data transfer needs to be reliable, secure, and fast. Data storage and archive needs to be secure and maintain redundant. Once the data is collected, it must be processed and visualized quickly and in a method that is easily available for a wide audience of users. Many of these aspects should work autonomously and if done well can expedite research discoveries and promote conversations on analysis and visualization results. This project aims to begin a collaborative effort among researchers to solve these AM specific challenges and design information organization structures and methods that are easy to use and standardized across laboratories.
Development of Flexible Circuits using Epoxy-based Flexible Electrical Conductors: Jongho Jeon1; Kim Hansol1; Lee Sangmin1; Han Sang-Woo1; Lee In Hwan1; Cho Jungho1; 1Chungbuk National University
In this study, we fabricated flexible circuits using a Direct Writing system based on a silver epoxy-based conductive material developed in previous studies, and evaluated their electrical properties for potential applications. As a result, we confirmed that the flexible circuits fabricated using the Direct Writing system are suitable for wearable applications, as they are able to maintain their structural integrity and electrical conductivity even while flexing and bending. Our findings suggest that Direct Writing technology has the potential to be used as a method for producing wearable electronics due to its ability to create precise and intricate circuits with minimal material waste. Furthermore, these results may have significant implications for the future development and advancement of flexible electronics, particularly in the field of biomedical applications.
Fabrication of Superhydrophobic Surfaces using Waste PET: Tae Gyun Kim1; Na Kyoung Kim1; Geon Hwee Kim1; 1Chungbuk National University
Superhydrophobicity means that a water contact angle is greater than 150°, and many materials and manufacturing techniques have been conducted for superhydrophobic surfaces. Methods for making superhydrophobic surfaces include lithography, electroplating, chemical etching, spray coating, but they have environmental issues and process complexity. Electrospinning is a process of making superhydrophobic surfaces, which is fast and simple method, and a large amount of nanostructures can be made with a small amount of polymer solution. In this study, nanostructures were created through electrospinning and electrospraying of PET(Polyethylene Terephthalate), and superhydrophobic surfaces were successfully manufactured. It is meaningful that waste PET was used as an electrospinning solution and no additional process was required for superhydrophobic implementation. The fabricated PET membrane’s water contact angle was confirmed about 151°, and this technology can be used for hydrophobic films, electronics such as solar panels, and building windows.
Robot-aided selective embedding of a spatially steered fiber in polymer composite parts made using vat photopolymerization: Vivek Khatua1; G. K. Ananthasuresh1; B. Gurumoorthy1; 1Indian Institute of Science
Fiber-Reinforced Polymer Composite (FRPC) parts are predominantly laminates, shells, or surfaces wound with 2+D fiber patterns even after the emergence of additive manufacturing. Making FRPC parts with embedded continuous fibers in 3D is not reported previously even though topology optimization demonstrates that such designs are optimal. Earlier attempts in 3D fiber reinforcement include making parts with channels into which fibers are inserted or co-extruding fiber with resin. In this work, we developed a 3D printer and a process for concurrent embedding of spatially steered continuous fibers inside the matrix by extending vat photopolymerization. We embed a single continuous fiber spatially by using a robot to gradually steer the fiber as the part is built layer upon layer. We also show that multiple continuous fibers can be steered in a part. We tested a few parts for strength and stiffness to illustrate the importance of spatially embedding fibers in specific patterns.
Spreading and Packing of Ceramic Powder Using a Displacement-controlled Roller in SLFS: Kaya Bayazitoglu1; Matthew Cassoli1; Joseph Beaman1; Desiderio Kovar1; 1The University of Texas at Austin
Selective Laser Flash Sintering (SLFS) combines aspects of Selective Laser Sintering (SLS) and Flash Sintering to neck ceramic particles together. A traditional ceramic sintering process is then used to densify the necked particles. The density of the ceramic powder bed impacts attainable density of the final part. To achieve the required density in the powder bed a packing method using a displacement-controlled roller is tested and compared to a traditional method of pressing ceramic powder into a pellet using a die and hydraulic press. Packed regions were sintered to final densities to evaluate the efficacy of a roller-based packing process.
3D Printing of Gel Polymer Electrolytes via Vat Photopolymerization for Lithium-ion Batteries: Eva Schiaffino Bustamante1; Christian Fernandez Soria1; Ana Aranzola1; Alexis Maurel1; Ana Martinez Maciel1; Eric MacDonald1; 1The University of Texas at El Paso
As classical lithium-ion batteries are based on a planar architecture consisting of the 2D stacking of components (current collectors, electrodes, separator/electrolyte), 3D printing technologies have the potential to revolutionize the production of shape-conformable batteries, with increased specific surface area, ion diffusion, and improved power performances. This study presents the preparation of several UV photocurable resins with different liquid electrolyte-to-polymer matrix ratios, designed to act as gel polymer electrolytes (GPE) once printed by the vat photopolymerization (VPP) 3D printing process. Printing parameters are optimized to ensure print quality and accuracy. The 3D-printed GPE is examined through electrochemical impedance spectroscopy to maximize the ionic conductivity while ensuring satisfactory printability. Finally, electrochemical testing of the 3D-printed GPEs is performed to demonstrate their functionality in a classical lithium-ion battery. This work seeks to achieve the 3D printing via VPP of a complete lithium-ion battery, a world first.
A Data Driven-based Geometric Compensation Method for Laser Powder Bed Fusion: Wen Dong1; Basil Paudel1; Albert To1; 1University of Pittsburgh
The residual stress and deformation induced during the laser powder bed fusion (L-PBF) process can degrade the performance and quality of the products and increase the difficulty of post-processing like machining and cutting. The present work develops a data driven-based geometric compensation method to reduce the part distortion in L-PBF processes. The method includes four steps: (1) collect distortion data based on both numerical simulations and experimental measurement; (2) implement principal component analysis to reduce the data size and extract features that account for 99.99% of the total energy; (3) train the Gaussian process model for each feature to establish relationships between the initial and as-built shape of a part; (4) apply the trained model to generate the compensated geometry so that the as-built shape is the desired one. The experimental validation shows that the proposed approach is able to effectively improve the geometric accuracy of the as-built part.
FE Predictions of Residual Stresses in L-PBF Generated Ti-6Al-4V NIST Bridges: Caitlin Luke1; Courtney Morgan-Barnes1; Brad Sampson1; Haley Doude1; Matthew Priddy1; 1Mississippi State University
The ability to characterize and predict residual stresses in parts produced via additive manufacturing (AM) methods is vital in both the understanding and performance of as-built structures. Currently, there is a need for improving the modeling and prediction of residual stresses in as-built samples for the purposes of toolpath optimization. This work studied the residual stresses in laser powder bed fusion (L-PBF) structures with a sequentially coupled thermo-mechanical finite element (FE) modeling framework for the prediction of residual stresses in as-built Ti-6Al-4V NIST bridges. Nine variations of layer thickness, scan strategy, and scan speed were examined for parameter variation effects on residual stress formation. Thermal history data collected from the experimental builds was used to perform thermal calibration/validation of the FE models. This investigation of NIST bridge residual stress formation will provide greater insight to the process-property relationship for Ti-6Al-4V L-PBF structures.
Towards Large-scale Grain Growth Modeling in Powder Bed Fusion: Michael Paleos1; Albert To1; 1University of Pittsburgh
Grain growth models in the context of additive manufacturing are dealing with both the inherent complexity of the process and the computational expense of thermal process simulations. Cellular automata models have been successful in approximating the true physics of melt pool solidification, but they are typically confined to relatively small spatial domains. Building on recent advances in powder bed fusion process and microstructure modeling, we propose an integration framework based on several computational schemes that can lead to accurate simulations on unprecedented scales. For that purpose, we leverage and properly combine both the recently developed matrix-free FEM-based PAMSIM process simulator and the open-source ExaCA software. Our work centers around efficiently capturing information about several thermal signatures that would then guide grain growth in a decoupled manner. This framework would enable the computational study of microstructure (and property) heterogeneity and of the effect of unconventional scanning strategies.
Experimental Evaluation of Hierarchical Functionally Graded Lattices Using Digital Image Correlation and Micro-CT: Junyang Ye1; Ata Babazadeh-Naseri1; Benjamin Fregly1; C. Higgs1; 1Rice University
Hierarchical meta-materials based on functionally-graded lattices (FGLs) have the benefit of customizable material properties. However, the effects of sharp transitions on the effective properties of FGLs have yet to be evaluated. This experimental study focused on characterizing the compressive properties of hierarchical FGLs built with smooth or sharp gradings. A total of 12 samples were 3D-printed in Ti6Al4V alloy and tested in axial compressive loading. Digital image correlation (DIC) was used to measure displacements and deformations. The 3D-printing quality of FGLs was also evaluated by micro-CT imaging of 5 samples. The results showed that the cross-sectional areas of struts in FGLs with sharp transitions were 26% smaller than uniform lattices and FGLs with smooth transitions. Compression testing also confirmed a lower average elastic modulus in FGLs with sharp gradings. These results will provide insights for incorporating adjustment factors to account for the loss of strength in FGLs.
Characterization and Validation Experiments for a Binder Jet 3D Printing Modeling Framework: Wesley Combs1; Joshua Wagner1; C.Fred Higgs III2; 1Rice University; 2Rice Univ
Binder jet 3D printing (BJ3DP) is an additive manufacturing (AM) process that is based on the selective joining of powder particles by precision jetting of liquid binder droplets. Recently, we’ve developed a computational framework that resolves the coupled fluid-particle interaction that occurs between the binder and powder during jetting. Supplementary experiments are required for this numerical model to (1) calibrate the powder material properties such that the behavior of the modeled particles represents the physical powder in question, and (2) to validate the overall simulation results with direct experimental comparisons. For the former, we present a methodology for calibrating the cohesion behavior of metal AM powder using angle of repose experiments. For the latter, we introduce a dedicated experimental apparatus that isolates the fundamental physics of binder-powder interactions in BJ3DP. This apparatus employs high-speed, microscopic imaging for real time observation of the binder deposition event.
Exploring Capillary Suspension Technique to Develop 3D Printable Oxide Based Lithium Electrolytes for All Solid-state Batteries by Direct Ink Writing: Siri Vaishnavi Thummalapalli1; Venkat Kamavaram2; Ganesh Kumar Arumugam2; Arunachala Kannan1; Kenan Song1; 1Arizona State University; 2Oceanit Laboratories
The development of solid-state batteries is a bottleneck to replacing the current lithium-ion batteries with liquid electrolytes for enhancing safety and energy density. Lithium garnet materials such as Li7La3Zr2O12(LLZO), are ceramic lithium conductors that have several unique properties. The challenge for developing a Solid-State Electrolyte (SSE) for Lithium-ion batteries is the limitation of relatively low ionic conductivity and high interfacial resistance between electrolyte and electrode. Although SSE has shown significant improvements in performance in recent years, they still face dendrite propagation issues due to planar geometries and random porosities. Herein, we present all solid-state 3D printable electrolytes using Ta-doped LLZTO garnet material using Direct Ink Writing (DIW) technique. Direct Ink Write (DIW) involves a controlled selective deposition of material according to a pattern. DIW techniques are capable of single or multi-layer patterning of material onto flat as well as conformal surfaces. Furthermore, multiple ink formulations have been developed with optimized rheological behavior using the capillary suspension technique. Compared to conventional methods, printable electrolytes can be tailored with different structural hierarchies (e.g., surface patterning) for diffused interface between electrode-electrolyte to block the dendrite and achieve a more stable battery performance. The major objective of this study is to optimize printable electrolyte ink composition and rheology, electrolyte conductivity, interfacial resistance, and energy density of solid-state battery through systematic materials characterization and cell testing.
Laser Synthesized Molybdenum Trioxide (MoO3) Nanoparticles for Energy Storage Applications: Amiri Thorpe1; Gracie Boyer2; Jonghyun Park2; 1Florida A&M University; 2Missouri University of Science and Technology
Transition metal oxide nanomaterials, such as Molybdenum trioxide (MoO3), offer a high theoretical specific capacity and are proving to be a promising material to replace full carbon anodes for lithium-ion batteries. However, they suffer from high volumetric expansion during cycling, poor electrical conductivity, and synthesis methods are commonly time consuming and can require toxic precursors. By utilizing an ultrafast laser ablation in liquid method, MoO3 nanosheets can be produced in a one step process without the need of hazardous materials. Through the combination of carbon nanomaterials and the laser synthesized MoO3 nanosheets, composite electrodes with high specific capacities and improved mechanical stability and electrical conductivity can be fabricated.
Analysis of Porosity in LPBF SS316L by X-Ray Computed Tomography: Tasrif Ul Anwar1; Patrick Merighe1; Nadia Kouraytem1; 1Utah State University
Laser Powder Bed Fusion (LPBF) is a widely utilized additive manufacturing process for fabricating small parts with complex features. However, one notable drawback of LPBF is the potential variation in mechanical properties caused by the influence of key process parameters on the underlying structures. Thus, understanding the relationships between process and defect structure in printed components is crucial. In this study, Stainless Steel 316L (SS316L) test coupons were produced using LPBF with different laser parameters. To examine porosity and its spatial distribution, X-ray computed tomography (XCT) was utilized. Lack of fusion (LOF), sintering (an extreme of LOF), near dense, and keyhole defects were identified using the XCT data. These discoveries make it possible to print nearly dense samples, which are expected to exhibit superior mechanical properties compared to their porous counterparts. The results of this study will facilitate the widespread use of LPBF SS316L components, particularly in the energy industry.
Molybdenum Trioxide (MoO3) Nanosheets Imbedded Carbon Nanofibers for Lithium-ion
Batteries: Kevin Lantz1; Kiernan O'Boyle2; Jonghyun Park2; 1Miami Dade College; 2Missouri University of Science and Technology
Molybdenum trioxide (MoO3), a layered transition metal oxide electrode material, possesses unique properties and a high theoretical capacity. However, it encounters challenges such as volume change, poor conductivity, and limited ion diffusion during deintercalation. To address these limitations, we have explored embedding MoO3 nanosheets into interconnected carbon nanofibers. This integration improves the diffusion rate within the material. The synthesis of carbon nanofibers is accomplished through the electrospinning technique, known for its simplicity and cost-effectiveness. The resulting composite, MoO3@CNF, has shown promising performance when incorporated into lithium-ion batteries.
Dual-curing 3D Formation of Continuous Fiber Thermoset Composites: Kaiyue Deng1; Kelvin Fu1; 1University of Delaware