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At least 325 records · Page 18

Computational Modeling of a 3D Printed Recuperator and Subsequent Experimental Loop for Supercritical Carbon Dioxide Cycles

Oak Ridge National Laboratory (ORNL), in collaboration with mechanical-thermal energy storage (mTES) provider EarthEn, a US Department of Energy (DOE) Lab-Embedded Entrepreneurship Program (LEEP) recipient at ORNL’s Innovation Crossroads 2023, is utilizing a state-of-the-art patented 3D printing technique to design an additively manufactured (AM) supercritical CO2 (sCO2) recuperator (REC) for EarthEn’s charge/discharge cycle. The AM REC will be printed at ORNL’s Manufacturing Demonstration Facility using Inconel Alloy 718 and tested on a closed-loop, ∼100 kW scale experimental facility that is under construction. The testing will compare the printed design against a commercial-off-the-shelf Printed Circuit Heat Exchanger (PCHE) REC. The design of the sCO2 facility is guided by a Modelica-based system model which is primarily dependent on the open-source TRANSFORM library developed at ORNL and uses the open-source CoolProp library for thermophysical properties of sCO2 via the External Media library. It is envisioned that an iterative process will be followed between the physical loop and the system model wherein the initial experimental data will be used to tune the model, which in turn will be used to guide future loop operation. Simultaneously, the AM REC is being designed using computer-aided design models, and it is also being analyzed for hydraulic and thermomechanical response using commercial computational fluid dynamics software, Simcenter STAR-CCM+, on highperformance computing resources.1

See, Nate [ORNL] (ORCID:0000000178581202)↗

Soft elasticity optimises dissipation in 3D-printed liquid crystal elastomers

Soft-elasticity in monodomain liquid crystal elastomers (LCEs) is promising for impact-absorbing applications where strain energy is ideally absorbed at constant stress. Conventionally, compressive and impact studies on LCEs have not been performed given the notorious difficulty synthesizing sufficiently large monodomain devices. Here, we use direct-ink writing 3D printing to fabricate bulk (>cm 3 ) monodomain LCE devices and study their compressive soft-elasticity over 8 decades of strain rate. At quasi-static rates, the monodomain soft-elastic LCE dissipated 45% of strain energy while comparator materials dissipated less than 20%. At strain rates up to 3000 s –1 , our soft-elastic monodomain LCE consistently performed closest to an ideal-impact absorber. Drop testing reveals soft-elasticity as a likely mechanism for effectively reducing the severity of impacts – with soft elastic LCEs offering a Gadd Severity Index 40% lower than a comparable isotropic elastomer. Lastly, we demonstrate tailoring deformation and buckling behavior in monodomain LCEs via the printed director orientation.

36 MATERIALS SCIENCE↗

Ink-substrate interactions during 3D printing revealed by time-resolved coherent X-ray scattering

Additive printing techniques are regarded as revolutionary and versatile methods of advanced device manufacturing, stemming from the possibility to pattern materials on a custom-based approach and the potential to create novel microstructures and achieve new functionalities. Despite these advantages, the inherent anisotropy of the printing process is a source of property gradients within the printed materials, often associated with variable and/or poor performance. Up to date, the evolutionary pathways associated with printing have largely remained unaddressed, mainly owing to the difficulty to study the transformations induced in the material during processing. Time-resolved coherent X-ray scattering techniques, such as X-ray photon correlation spectroscopy, enable the in situ study of transient nanoscale and mesoscale states in a large variety of materials, including amorphous ones, by directly accessing the most relevant timescales and length scales of their nanoscale and mesoscale dynamics, self-assembly, and mesostructure evolution. In this work, we conduct in operando studies of continuous-flow direct writing with colloidal inks, focusing on how the ink formulation and ink-substrate interactions affect the processes that determine the macroscopic properties of the printed materials. We find fundamental differences in the ink structural relaxations emerging from the primary colloid properties (monodisperse versus aggregated colloids) and the substrates surface energy and mechanical properties. Our work helps to reveal and quantify the basic science governing the evolution of 3D-printed materials during processing, ultimately improving engineering criteria for the design of printable materials.

36 MATERIALS SCIENCE↗

Monolithic Trace-Contaminant Sorbents Fabricated from 3D-Printed Polymer Precursors

The current trace-contaminant (TC) removal technology for use in Extravehicular Activities (EVAs) involves the use of a packed bed of acid-impregnated granular charcoal, which is difficult to regenerate. In this paper, results are presented on the development of vacuum-regenerable TC sorbents for use in the Portable Life Support System (PLSS). The sorbents are derived from 3D-printed polymer monoliths (e.g., honeycomb structures), which are then carbonized and activated in order to develop porosity, and also to enhance the TC-sorption capacity. Results are presented on the following aspects of carbon-sorbent development: (1) precursor selection; (2) monolith fabrication; (3) shape retention and strength; (4) carbon surface and porosity characterization; (5) TC-sorption capacity and vacuum-regeneration; (6) pressure drop; and (7) sub-scale sorbent prototype. The use of predominantly microporous monolithic carbon is associated with the following benefits: (a) high TC-sorption capacity; (b) low pressure drop; (c) rapid vacuum (pressure-swing) desorption due to thin monolith walls and low pressure drop; (d) good thermal management (high thermal conductivity and low adsorption/desorption thermal effects associated with physisorption); and (e) good resistance to dusty environments.

Portable Life Support System (PLSS)↗

In Situ Synchrotron X-ray Scattering Investigation of Cathodic ZIF-8 Deposition on Graphite Using 3D-Printed Cells

Electrochemical approaches provide unique means to fabricate thin films of metal organic frameworks (MOFs). However, the kinetics of electrochemical MOF deposition has not been quantitatively investigated so far. In this study, we report the first in situ measurements of electrochemical MOF growth using transmission synchrotron X-ray scattering. Electrochemical cells based on poly(lactic acid) with two windows were fabricated using fused-deposition modelling. Here, the resulting 3D-printed cells, the surface of which was coated with paraffin wax to prevent solvent percolation through the polymer material, were used to monitor the cathodic growth of zeolitic imidazolate framework-8 (ZIF-8) on graphite in a methanol solution containing ZnCl 2 and 2-methylimidazole (Hmim) at different cathodic potentials. The resulting time-resolved X-ray diffraction data showed a gradual increase in crystal size with negligible changes in crystal orientation during the cathodic ZIF-8 deposition. More importantly, the time-resolved data provided a means to quantitatively assess the kinetics of the cathodic ZIF-8 growth using the Gualtieri model, revealing that the cathodic potential and Hmim concentration affected crystal growth kinetics, but not nucleation kinetics. These ZIF-8 samples exhibited changes in X-ray diffraction pattern after being washed with methanol and dried in air, indicating that in situ measurements are essential to investigate mechanisms behind MOF electrodeposition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

“Hybridizing heat-integrated 3D printed modules with mass manufacturable, low pressure drop fiber sorbents” (Final Report)

The overall objective of this proposal was to research, develop, and evaluate a modular direct air capture (DAC) system that is simple and scalable. This system was based on the adsorption of CO 2 into commercial polyamines supported by porous fiber sorbents, which can be produced at kilometer per hour scales using our pre-pilot spinning line. We have housed these fiber materials in novel 3D printed modular housing systems that provide easy-to-manufacture and localized heat integration and flow control. This hybridization of fiber sorbent technology with modular housing provided several advantages that led to lower air pressure drops, higher sorbent productivity, as well as ease of manufacturing and assembly unrivaled by existing and emerging heat integrated contactor designs. The modular housing was fabricated with the following features, at a minimum: (i) a tapered air intake to reduce pressure drop related to entrance effects, (ii) a structured network of heat transfer channels to enable localized cooling and heating during adsorption and desorption, respectively, and (iii) low pressure drop supports for the fiber sorbents. This hybrid manufacturing approach provides a facile method for taking fiber sorbents from lab scale to pilot scale as it dramatically simplifies the fabrication of heat integrated contactor structures.

42 ENGINEERING↗

3D printing of architected sulfur cathodes with dual-site atomic catalysts for accelerated polysulfide kinetics and Li-ion transport in high areal-loading lithium–sulfur batteries

The practical deployment of lithium–sulfur batteries (LSBs) is hindered by fundamental limitations in conventional slurry-cast cathodes, including poor sulfur utilization, sluggish ion transport, and low areal capacity, particularly in thick electrodes required for high energy density. To address these challenges, we present direct ink writing (DIW) as an additive manufacturing strategy to fabricate advanced current-collector-free, 3D-printed sulfur cathodes (3DP S@CoNi-DSACs/NC) with hierarchically porous architectures that enhance lithium-ion diffusion, promote electrolyte penetration, and reduce interfacial resistance. The synergistic effects of Co/Ni dual-atom sites accelerate redox kinetics and mitigate polysulfide shuttling. As a result, the optimized 3DP cathode with a sulfur loading of 5.4 mg cm −2 demonstrated excellent rate capability, delivering a high reversible capacity of 1041.4 mAh g −1 at 1C with 85.5% capacity retention after 1000 cycles, significantly outperforming its cast counterpart. Remarkably, even at a higher sulfur loading of 8.1 mg cm −2 , the 3DP cathode maintains outstanding performance, achieving a discharge capacity of 1538.4 mAh g −1 and an areal capacity of 12.5 mAh cm −2 at 0.1C. This study not only demonstrates the functional integration of catalytically active materials into 3D printable sulfur cathode architectures but also offers a scalable and transformative platform for building high-performance LSBs beyond conventional electrode manufacturing methods.

3D electrode↗

Advancing Industry 4.0: Multimodal Sensor Fusion for AI-Based Fault Detection in 3D Printing

Additive manufacturing, particularly fused deposition modeling, is transforming modern production by enabling rapid prototyping and complex part fabrication. However, its layer-by-layer process remains vulnerable to faults such as nozzle clogging, filament runout, and layer misalignment, which compromise print quality and reliability. Traditional inspection methods are costly, time-intensive, and often limited to post-process analysis, making them unsuitable for real-time intervention. In this current study, the authors developed a novel, low-cost, and portable faultdetection system that leverages multimodal sensor fusion and artificial intelligence for real-time monitoring in FDM-based 3D printing. The system integrates acoustic, vibration, and thermal sensing into a non-intrusive architecture, capturing complementary data streams that reflect both mechanical and process-related anomalies. Acoustic and thermal sensors operate in a fully contactless manner, while the vibration sensor requires minimal attachment such that it will not interfere with printer hardware, thereby preserving portability and ease of deployment. The multimodal signals are processed into spectrograms and time-frequency features, which are classified using convolutional neural networks for intelligent fault detection. The proposed system advances Industry 4.0 objectives by offering an affordable, scalable, and practical monitoring solution that improves faultdetection accuracy, reduces waste, and supports sustainable, adaptive manufacturing.

42 ENGINEERING↗

Development of Additive Manufacturing Technologies for 3D Printing of Spacecraft Heat Shields

Ablative heat shields are an enabling technology for entry into planetary atmospheres. From the PICA heatshields used for several Mars rovers to the carbon phenolic material used for Galileo’s Jupiter entry probe, the heat shield manages the heat load transferred to the payload, protecting the sensitive scientific instruments carried on entry probes. The Additive Manufacturing of Thermal Protection Systems (AMTPS) project, an Early Career Initiative (ECI) funded by NASA’s Space Technology Mission Directorate and led by NASA Johnson Space Center, seeks to develop materials and processes for 3D printing ablative heat shields for spacecraft. Current methods for producing ablative heat shields are extremely labor intensive and require extensive hands-on processes and quality control characterization. Additive manufacturing (AM) offers the possibility of reduced production times, improved reliability, and enhanced performance via graded compositions. Costs will also be reduced by reducing the time and labor required for heat shield production. Direct integration of the heat shield onto the structure during processing simplifies integration and reduces risk.

Nathaniel Olson↗

Development of Additive Manufacturing Technologies for 3D Printing of Spacecraft Heat Shields

Ablative heat shields are an enabling technology for entry into planetary atmospheres. From the PICA heatshields used for several Mars rovers to the carbon phenolic material used for Galileo’s Jupiter entry probe, the heat shield manages the heat load transferred to the payload, protecting the sensitive scientific instruments carried on entry probes. The Additive Manufacturing of Thermal Protection Systems (AMTPS) project, an Early Career Initiative (ECI) funded by NASA’s Space Technology Mission Directorate and led by NASA Johnson Space Center, seeks to develop materials and processes for 3D printing ablative heat shields for spacecraft. Current methods for producing ablative heat shields are extremely labor intensive and require extensive hands-on processes and quality control characterization. Additive manufacturing (AM) offers the possibility of reduced production times, improved reliability, and enhanced performance via graded compositions. Costs will also be reduced by reducing the time and labor required for heat shield production. Direct integration of the heat shield onto the structure during processing simplifies integration and reduces risk.

Nathaniel Olson↗

Fast-, Light-Cured Scintillating Plastic for 3D-Printing Applications

Additive manufacturing techniques enable a wide range of possibilities for novel radiation detectors spanning simple to highly complex geometries, multi-material composites, and metamaterials that are either impossible or cost prohibitive to produce using conventional methods. The present work identifies a set of promising formulations of photocurable scintillator resins capable of neutron-gamma pulse shape discrimination (PSD) to support the additive manufacturing of fast neutron detectors. The development of these resins utilizes a step-by-step, trial-and-error approach to identify different monomer and cross-linker combinations that meet the requirements for 3D printing followed by a 2-level factorial parameter study to optimize the radiation detection performance, including light yield, PSD, optical clarity, and hardness. The formulations resulted in hard, clear, PSD-capable plastic scintillators that were cured solid within 10 s using 405 nm light. The best-performing scintillator produced a light yield 83% of EJ-276 and a PSD figure of merit equaling 1.28 at 450–550 keVee.

Frandsen, Brian G. (ORCID:0000000319964320)↗

Summary Report on Phase I Results from the 3D Printing in Zero G Technology Demonstration Mission, Volume I

Human space exploration to date has been confined to low-Earth orbit and the Moon. The International Space Station (ISS) provides a unique opportunity for researchers to prove out the technologies that will enable humans to safely live and work in space for longer periods of time and venture beyond the Earth/Moon system. The ability to manufacture parts in-space rather than launch them from Earth represents a fundamental shift in the current risk and logistics paradigm for human spaceflight. In September 2014, NASA, in partnership with Made In Space, Inc., launched the 3D Printing in Zero-G technology demonstration mission to explore the potential of additive manufacturing for in-space applications and demonstrate the capability to manufacture parts and tools on orbit using fused deposition modeling. This Technical Publication summarizes the results of testing to date of the ground control and flight prints from the first phase of this ISS payload.

in-space manufacturing↗

Computed Tomography (CT) Analysis of 3D Printed Lattice Structures

LATTICE structures are increasingly used in product design across different industries, including the Department of Energy (DOE), due to their high strength and lightweight properties. These structures possess qualities such as high stiffness, energy absorption, large surface area, and structural support. To ensure lattice structures' quality and symmetry, it is crucial to have defect-free structures. However, in some cases, traditional non-destructive evaluation methods may not be practical due to encasing lattice structures in material. To analyze the lattice structures' quality, this project will employ CT imaging to gain access to the encased structures and perform a detailed analysis of each section. Three 3D printed complex lattice cubes were created, with two exposed and one encased in material, for this project. The CT X-ray cabinet will be used to scan all three cubes, and the data collected will be reconstructed and evaluated using complex interpretation software. This analysis will allow for a detailed examination of the structure's porosity, inclusions, cracks, wall thickness, and symmetry in each section.

36 MATERIALS SCIENCE↗

Utilizing computer vision and artificial intelligence algorithms to predict and design the mechanical compression response of direct ink write 3D printed foam replacement structures

Additive Manufacturing (AM) of porous polymeric materials, such as foams, recently became a topic of intensive research due their unique combination of low density, impressive mechanical properties, and stress dissipation capabilities. Conventional methods for fabricating foams rely on complex and stochastic processes, making it challenging to achieve precise architectural control of structured porosity. In contrast, AM provides access to a wide range of printable materials, where precise spatial control over structured porosity can be modulated during the fabrication process enabling the production of foam replacement structures (FRS). Current approaches for designing FRS are based on intuitive understanding of their properties or an extensive number of finite element method (FEM) simulations. These approaches, however, are computationally expensive and time consuming. As such, in this work, we present a novel methodology for determining the mechanical compression response of direct ink write (DIW) 3D printed FRS using a simple cross-sectional image. By obtaining measurement data for a relatively small number of samples, an artificial neural network (ANN) was trained, and a computer vision algorithm was used to make inferences about foam compression characteristics from a single cross-sectional image. Finally, a genetic algorithm (GA) was used to solve the inverse design problem, generating the AM printing parameters that an engineer should use to achieve a desired compression response from a DIW printed FRS. The methods developed herein present an avenue for entirely autonomous design and analysis of additively manufactured structures using artificial intelligence.

36 MATERIALS SCIENCE↗

Slides for MS&T2022: Carbon-Carbon Composites from 3D Printed Preforms Graphitized by Electric Field Assisted Sintering

Formation of Carbon-Carbon (C-C) composite materials requires putting a carbon fiber preform through a cycle of densification, carbonization, and graphitization. This cycle is then repeated until the desired properties are achieved. The graphitization phase is particularly energy demanding as it involves heating the components to in excess of 2000°C. In traditional furnaces this is also quite time consuming as typical heating rates are low, and the actual heat treatment may be limited by component dimensions, as heat is conducted throughout the part primarily by thermal diffusion. Joule heating by means of Electric Field Assisted Sintering (EFAS) systems enables high heating rates and causes the part to be heated from the inside, which eliminates the thermal diffusion time constraint. In our process, C-C composites are formed by pyrolyzation of 3D-printed carbon fiber preforms, vacuum infiltration of naphthalene based mesophase pitch, and carbonization. The part is then graphitized in the EFAS system. By this method graphitization of the composite matrix was achieved in less than an hour. A part density of greater than 1.6g/cc (up to 1.9g/cc demonstrated) was achieved after only two rounds of infiltration and a single graphitization. Overall the process took less than a week which is significantly faster than traditional methods. Optical microscopy and XRD results are discussed to elucidate the internal porosity and characterize the degree of graphitization. Testing was performed showing the impact on fiber direction to electrical and thermal properties of the final part.

36 MATERIALS SCIENCE↗

The Application of Convolutional Neural Networks (CNNs) to Recognize Defects in 3D-Printed Parts

Cracks and pores are two common defects in metallic additive manufacturing (AM) parts. In this paper, deep learning-based image analysis is performed for defect (cracks and pores) classification/detection based on SEM images of metallic AM parts. Three different levels of complexities, namely, defect classification, defect detection and defect image segmentation, are successfully achieved using a simple CNN model, the YOLOv4 model and the Detectron2 object detection library, respectively. The tuned CNN model can classify any single defect as either a crack or pore at almost 100% accuracy. The other two models can identify more than 90% of the cracks and pores in the testing images. In addition to the application of static image analysis, defect detection is also successfully applied on a video which mimics the AM process control images. The trained Detectron2 model can identify almost all the pores and cracks that exist in the original video. This study lays a foundation for future in situ process monitoring of the 3D printing process.

36 MATERIALS SCIENCE↗

Melt compounding of spray-dried cellulose nanofibrils/polypropylene and their application in 3D printing

Abstract Micro- and nano-scale cellulosic fillers exhibit excellent dispersion and distribution within a thermoplastic matrix during the process of melt compounding or injection molding. In this study, spray-dried cellulose nanofiber (SDCNF) powders were manufactured using a pilot-scale rotating disk atomizer spray dryer. Bleached Kraft pulp (BKP), unbleached Kraft pulp (UKP), and old corrugated cardboard pulp (OCC) fibrillated at a fines level of 90% were used as feedstock materials for spray-drying. BKP-, UKP-, and OCC- SDCNFs were compounded with polypropylene using a twin screw co-rotating extruder. Maleic anhydride grafted polypropylene (MAPP) was used as a coupling agent in the composite formulations. The tensile, flexural, and impact properties of SDCNF-filled PP composites increased at 10 wt% SDCNF loading. The presence of SDCNFs in the PP matrix resulted in faster crystallization and a 12% reduction in the degree of crystallinity of the neat PP. The coefficient of thermal expansion (CTE) of neat PP was reduced by up to 31% attributable to the presence of the SDCNFs. Application of the SDCNF-reinforced PP composites in 3D printing reduced the shrinkage rate of the printed neat PP by 39%, and the printability of the PP was significantly improved with the addition of the SDCNFs.

Materials Science↗