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NASA NTRSDate not supplied

Comprehensive 3D Multiphysics Model on Electrochemical Recovery of O 2 from Metabolic CO 2 at the International Space Station (ISS)

The International Space Station (ISS) is presently equipped with an elaborate, heavy, and high-power consuming system that recovers approximately 50% of O 2 from metabolic CO 2 as part of the atmospheric revitalization (AR) at the ISS habitat. Future long-duration missions will require a sustainable and efficient system capable of yielding a minimum of 75% O 2 recovery to reach the self-sufficiency required for long space missions beyond earth’s low orbit. A Macrofluidic Electrochemical Reactor (MFECR) technology development effort is currently underway at NASA Marshall Space Flight Center (MSFC) to not only increase significantly current O 2 recovery efficiency, improving self-sufficiency on AR at the ISS habitat and future long missions, but also reduce the complexity of the system. The authors have developed and deployed a comprehensive 3D multiphysics model that thoroughly replicates the actual configuration and fluid/material domains of the MFECR. The coupled physics in this multiphysics model include multicomponent-multiphase electrochemical-driven reactions, non-ideal mass transport mechanism, free and porous flow, heat transfer, CO 2 solubility on alkaline electrolyte, water condensation on porous medium, and DC electrical current generation along with Joule heating effect. This model is aimed to conduct quantitive benchmark on three different MFECR’s layouts, one without serpentine paths (plain) and two with serpentines leading to four and twelve paths respectively. Once experimental data is generated via a test matrix of 200 tests, the model will be validated to conduct MFECR’s process optimization and revalidate the quantitive benchmark on three different MFECR’s layouts.

Jesus A. Dominguez↗
NASA NTRS2019

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)↗
DOE OSTI2024

Ultrastrong magnon-magnon coupling and chiral spin-texture control in a dipolar 3D multilayered artificial spin-vortex ice

Strongly-interacting nanomagnetic arrays are ideal systems for exploring reconfigurable magnonics. They provide huge microstate spaces and integrated solutions for storage and neuromorphic computing alongside GHz functionality. These systems may be broadly assessed by their range of reliably accessible states and the strength of magnon coupling phenomena and nonlinearities. Increasingly, nanomagnetic systems are expanding into three-dimensional architectures. This has enhanced the range of available magnetic microstates and functional behaviours, but engineering control over 3D states and dynamics remains challenging. Here, we introduce a 3D magnonic metamaterial composed from multilayered artificial spin ice nanoarrays. Comprising two magnetic layers separated by a non-magnetic spacer, each nanoisland may assume four macrospin or vortex states per magnetic layer. This creates a system with a rich 16 N microstate space and intense static and dynamic dipolar magnetic coupling. The system exhibits a broad range of emergent phenomena driven by the strong inter-layer dipolar interaction, including ultrastrong magnon-magnon coupling with normalised coupling rates of $\frac{Δf}{v}$ = 0.57, GHz mode shifts in zero applied field and chirality-control of magnetic vortex microstates with corresponding magnonic spectra.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2023

The Gmao Hybrid 4d-Envar Observing System Simulation Experiment Framework.

This work describes the extension of the Global Modeling and Assimilation Office (GMAO) Observing System Simulation Experiment (OSSE) framework to use a hybrid 4D-EnVar scheme instead of 3D-Var. The original 3D-Var and hybrid 4D-EnVar OSSEs use the same version of the data assimilation system (DAS) so that a direct comparison is possible in terms of the validation with respect to their corresponding real cases. Rather than quantifying the differences between the two data assimilation methodologies, a short inter-comparison of upgrading from a 3D- to a 4D-OSSE is provided to highlight aspects where this change matters to the OSSE community and to identify features of data assimilation that can only be explored in a four-dimensional OSSE framework. A short validation of the hybrid 4D-EnVar OSSE shows that conclusions from previous assessments of the 3D-Var OSSE in its ability to mimic the behavior of the real system still hold with the same caveats. Furthermore, some aspects of the ensemble configuration and behavior are discussed along with forecast sensitivity to observation impacts (FSOI). Estimates of error standard deviations are shown to be smaller in the hybrid 4D-EnVar OSSE but with little impact on the character of the error. A discussion on future work directions focuses on exploring the four-dimensional aspect such as the error distribution within the assimilation window or four-dimensional handling of high-temporal density observations.

Data assimilation↗
DOE OSTI2025

Progress Towards the Validation of a new RELAP5-3D model of the High Temperature Test Facility

Validation is a key step in the development of any type of systems model. As the next generation of reactors approaches, the need for codes that have been validated for these new types of systems continues to grow. An example of a prominent option is the Reactor Excursion Leak Analysis Program (RELAP5-3D), developed by Idaho National Laboratory. This code was developed for the purpose of systems level thermal-hydraulic modeling of light water reactors (LWRS) and postulated transients that can occur in LWRS.RELAP5-3D has been substantially validated against LWR data. Due to its long history as a reactor safety analysis tool, there has been an effort to adapt RELAP5-3D for the purposes of advanced reactor concepts such as prismatic high-temperature gas-cooled reactors (HTGRs). However, RELAP5-3D has not nearly been validated and verified for HTGRs to the degree of LWRs, warranting verification and validation opportunities with computational benchmarks and existing experimental facilities. Examples of such facilities include the modular high-temperature gas-cooled reactor (MHTGR) 350 and the high temperature engineering test reactor (HTTR) from Japan. The MHTGR 350 is a benchmark design concept for code-to-code verification purposes; therefore, it does not provide any experimental data for validation opportunities The HTTR provides useful multiphysics validation data but does not have the in-core instruments to generate thermal-hydraulic experimental data to help with RELAP5-3D validation. Consequently, a facility that could provide key in-core temperatures for thermal-hydraulic validation was still needed. The High Temperature Test Facility (HTTF) is an integral effects facility for HTGR thermal hydraulics developed and operated by Oregon State University. HTTF represents ¼ length scale of the General Atomics MHTGR and is rated for a total power of 2.2 MW. Axially, the core consists of an upper and lower reflector and 10 blocks, numbered from bottom to top (Block 1 is right above lower reflector). The core is heated via graphite resistive heater rods, with respective channels distributed throughout the core. The primary coolant is helium and heat can radiate out of the core to the reactor cavity cooling system (RCCS), which is cooled by water. The primary purpose of the facility is to investigate pressurized conduction cooldown (PCC) and depressurized conduction cooldown (DCC) transients, which are also referred to as the pressurized and depressurized loss of forced cooling respectively. Two experiments were chosen to perform the validation study with a RELAP5-3D model of HTTF. These experiments are PG-27 (PCC) and PG-29 (DCC). These were chosen based off of the quality of available experimental data before and during the experiment which led to their inclusion in the HTGR Thermal Hydraulics Benchmark.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Validation of Photovoltaic Modeling Tool Solargraf Against Measured Data

Solargraf is a cloud-based 3D design tool by Enphase Energy that allows users to design solar and storage systems with a variety of elements. Through a Cooperative Research and Development Agreement (CRADA), Enphase Energy collaborated with the National Renewable Energy Laboratory (NREL) to validate Solargraf's 3D design simulation against measured PV system performance. This study follows the same methodology of similar validation studies completed at NREL. The predicted performance results from simulations in both Solargraf and NREL's System Advisor Model (SAM) tool were compared with measured data to evaluate performance predictions.

14 SOLAR ENERGY↗
NASA NTRS2021

Recent Improvements in the Dart Model for Atmosphere, Topography, Large Landscape, Chlorophyll Fluorescence, Satellite Image Inversion

Physical models simulating the radiative budget (RB) and remote sensing (RS) observation of three-dimensional (3D) landscapes are critical to better understand human and natural components of the Earth system and further develop RS technology. DART is one of the most comprehensive 3D models of Earth-atmosphere optical radiative transfer (RT), from ultraviolet (UV) to thermal infrared (TIR). It simulates the optical signal of proximal, aerial and satellite imaging spectrometers and laser scanners, the 3D RB and solar induced chlorophyll fluorescence (SIF) signal, for any urban or natural landscape and any experimental or instrument configuration. It is freely available for research and teaching activities (https://dart.omp.eu). Here, five recent advances are presented. 1) Atmosphere RT. 2) RT in non repetitive topography. 3) Monte Carlo modelling for fast RS image simulation of large landscapes. 4) SIF modelling for vegetation simulated as facets and turbid cells. 5) RS image inversion for mapping the optical properties of urban material and the urban radiative budget.

DART↗
NASA NTRS1993

Rapid prototyping 3D virtual world interfaces within a virtual factory environment

On-going work into user requirements analysis using CLIPS (NASA/JSC) expert systems as an intelligent event simulator has led to research into three-dimensional (3D) interfaces. Previous work involved CLIPS and two-dimensional (2D) models. Integral to this work was the development of the University of Massachusetts Lowell parallel version of CLIPS, called PCLIPS. This allowed us to create both a Software Bus and a group problem-solving environment for expert systems development. By shifting the PCLIPS paradigm to use the VEOS messaging protocol we have merged VEOS (HlTL/Seattle) and CLIPS into a distributed virtual worlds prototyping environment (VCLIPS). VCLIPS uses the VEOS protocol layer to allow multiple experts to cooperate on a single problem. We have begun to look at the control of a virtual factory. In the virtual factory there are actors and objects as found in our Lincoln Logs Factory of the Future project. In this artificial reality architecture there are three VCLIPS entities in action. One entity is responsible for display and user events in the 3D virtual world. Another is responsible for either simulating the virtual factory or communicating with the real factory. The third is a user interface expert. The interface expert maps user input levels, within the current prototype, to control information for the factory. The interface to the virtual factory is based on a camera paradigm. The graphics subsystem generates camera views of the factory on standard X-Window displays. The camera allows for view control and object control. Control or the factory is accomplished by the user reaching into the camera views to perform object interactions. All communication between the separate CLIPS expert systems is done through VEOS.

Kosta, Charles Paul↗
DOE OSTI2024

Visualizing an Exascale Data Center Digital Twin: Considerations, Challenges and Opportunities

Digital twins are an excellent tool to model, visualize, and simulate complex systems, to understand and optimize their operation. In this work, we present the technical challenges of real-time visualization of a digital twin of the Frontier supercomputer.We show the initial prototype and current state of the twin and highlight technical design challenges of visualizing such a large High Performance Computing (HPC) system. The goal is to understand the use of augmented reality as a primary way to extract information and collaborate on digital twins of complex systems. This leverages the spatio-temporal aspect of a 3D representation of a digital twin, with the ability to view historical and real-time telemetry, triggering simulations of a system state and viewing the results, which can be augmented via dashboards for details. Finally, we discuss considerations and opportunities for augmented reality of digital twins of large-scale, parallel computers.

Maiterth, Matthias↗
NASA NTRS1998

Coulomb Crystallization of Charged Microspheres Levitated in a Gas Discharge Plasma

The technical topic of the project was the experimental observation of Coulomb crystallization of charged microspheres levitated in a gas discharge plasma. This suspension, sometimes termed a dusty plasma, is closely analogous to a colloidal suspension, except that it has a much faster time response, is more optically thin, and has no buoyancy forces to suspend the particles. The particles are levitated by electric fields. Through their collective Coulomb repulsions, the particles arrange themselves in a lattice with a crystalline symmetry, which undergoes an order-disorder phase transition analogous to melting when the effective temperature of the system is increased. Due to gravitational sedimentation, the particles form a thin layer in the laboratory, so that the experimental system is nearly 2D, whereas in future microgravity experiments they are expected to fill a larger volume and behave like a 3D solid or liquid. The particles are imaged using a video camera by illuminating them with a sheet of laser light. Because the suspension is optically thin, this imaging method will work as well in a 3D microgravity experiment as it does in a 2D laboratory system.

Goree, John↗
DOE OSTI2023

Electronic structure, dimer physics, orbital-selective behavior, and magnetic tendencies in the bilayer nickelate superconductor $\mathrm{La_3Ni_2O_7}$under pressure

Motivated by the recently reported high-temperature superconductivity in the bilayer La 3 Ni 2 O 7 (LNO) under pressure, we comprehensively study this system using ab initio techniques. The Ni 3d orbitals have a large bandwidth at ambient pressure, increasing by ~22% at 29.5 GPa. Without electronic interactions, the Ni d 3z 2 -r 2 orbitals form a bonding-antibonding molecular orbital state via the O p z inducing a “dimer” lattice in the LNO bilayers. The Fermi surface consists of two-electron sheets with mixed e g orbitals and a hole pocket defined by the d 3z 2 -r 2 orbital, suggesting a Ni two-orbital minimum model. Different from the infinite-layer nickelate, we obtained a large interorbital hopping between d 3z 2 -r 2 and d x 2 -y 2 states in LNO, caused by the ligand “bridge” of in-plane O p x or p y orbitals connecting those two orbitals, inducing d-p σ-bonding characteristics. The competition between the intraorbital and interorbital hoppings leads to an interesting dominant spin stripe (π,0) order because of bond ferromagnetic tendencies via the recently discussed “half-empty” mechanism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Tension-free Dirac strings and steered magnetic charges in 3D artificial spin ice

3D nano-architectures presents a new paradigm in modern condensed matter physics with numerous applications in photonics, biomedicine, and spintronics. They are promising for the realization of 3D magnetic nano-networks for ultra-fast and low-energy data storage. Frustration in these systems can lead to magnetic charges or magnetic monopoles, which can function as mobile, binary information carriers. However, Dirac strings in 2D artificial spin ices bind magnetic charges, while 3D dipolar counterparts require cryogenic temperatures for their stability. Here, we present a micromagnetic study of a highly frustrated 3D artificial spin ice harboring tension-free Dirac strings with unbound magnetic charges at room temperature. We use micromagnetic simulations to demonstrate that the mobility threshold for magnetic charges is by 2 eV lower than their unbinding energy. By applying global magnetic fields, we steer magnetic charges in a given direction omitting unintended switchings. The introduced system paves the way toward 3D magnetic networks for data transport and storage.

36 MATERIALS SCIENCE↗
DOE OSTI2022

X-ray-imaging spectrometer (XRIS) for studies of residual kinetic energy and low-mode asymmetries in inertial confinement fusion implosions at OMEGA (invited)

A system of x-ray imaging spectrometer (XRIS) has been implemented at the OMEGA Laser Facility and is capable of spatially and spectrally resolving x-ray self-emission from 5 to 40 keV. The system consists of three independent imagers with nearly orthogonal lines of sight for 3D reconstructions of the x-ray emission region. The distinct advantage of the XRIS system is its large dynamic range, which is enabled by the use of tantalum apertures with radii ranging from 50 μm to 1 mm, magnifications of 4 to 35×, and image plates with any filtration level. In addition, XRIS is capable of recording 1–100’s images along a single line of sight, facilitating advanced statistical inference on the detailed structure of the x-ray emitting regions. Properties such as P0 and P2 of an implosion are measured to 1% and 10% precision, respectively. Furthermore, T e can be determined with 5% accuracy.

Adrian, P. J.↗
DOE OSTI2020

LiDAR-Aided Interior Orientation Parameters Refinement Strategy for Consumer-Grade Cameras Onboard UAV Remote Sensing Systems

Unmanned aerial vehicles (UAVs) are quickly emerging as a popular platform for 3D reconstruction/modeling in various applications such as precision agriculture, coastal monitoring, and emergency management. For such applications, LiDAR and frame cameras are the two most commonly used sensors for 3D mapping of the object space. For example, point clouds for the area of interest can be directly derived from LiDAR sensors onboard UAVs equipped with integrated global navigation satellite systems and inertial navigation systems (GNSS/INS). Imagery-based mapping, on the other hand, is considered to be a cost-effective and practical option and is often conducted by generating point clouds and orthophotos using structure from motion (SfM) techniques. Mapping with photogrammetric approaches requires accurate camera interior orientation parameters (IOPs), especially when direct georeferencing is utilized. Most state-of-the-art approaches for determining/refining camera IOPs depend on ground control points (GCPs). However, establishing GCPs is expensive and labor-intensive, and more importantly, the distribution and number of GCPs are usually less than optimal to provide adequate control for determining and/or refining camera IOPs. Moreover, consumer-grade cameras with unstable IOPs have been widely used for mapping applications. Therefore, in such scenarios, where frequent camera calibration or IOP refinement is required, GCP-based approaches are impractical. To eliminate the need for GCPs, this study uses LiDAR data as a reference surface to perform in situ refinement of camera IOPs. The proposed refinement strategy is conducted in three main steps. An image-based sparse point cloud is first generated via a GNSS/INS-assisted SfM strategy. Then, LiDAR points corresponding to the resultant image-based sparse point cloud are identified through an iterative plane fitting approach and are referred to as LiDAR control points (LCPs). Finally, IOPs of the utilized camera are refined through a GNSS/INS-assisted bundle adjustment procedure using LCPs. Seven datasets over two study sites with a variety of geomorphic features are used to evaluate the performance of the developed strategy. The results illustrate the ability of the proposed approach to achieve an object space absolute accuracy of 3–5 cm (i.e., 5–10 times the ground sampling distance) at a 41 m flying height.

47 OTHER INSTRUMENTATION↗
NASA NTRS1996

A convertor and user interface to import CAD files into worldtoolkit virtual reality systems

Virtual Reality (VR) is a rapidly developing human-to-computer interface technology. VR can be considered as a three-dimensional computer-generated Virtual World (VW) which can sense particular aspects of a user's behavior, allow the user to manipulate the objects interactively, and render the VW at real-time accordingly. The user is totally immersed in the virtual world and feel the sense of transforming into that VW. NASA/MSFC Computer Application Virtual Environments (CAVE) has been developing the space-related VR applications since 1990. The VR systems in CAVE lab are based on VPL RB2 system which consists of a VPL RB2 control tower, an LX eyephone, an Isotrak polhemus sensor, two Fastrak polhemus sensors, a folk of Bird sensor, and two VPL DG2 DataGloves. A dynamics animator called Body Electric from VPL is used as the control system to interface with all the input/output devices and to provide the network communications as well as VR programming environment. The RB2 Swivel 3D is used as the modelling program to construct the VW's. A severe limitation of the VPL VR system is the use of RB2 Swivel 3D, which restricts the files to a maximum of 1020 objects and doesn't have the advanced graphics texture mapping. The other limitation is that the VPL VR system is a turn-key system which does not provide the flexibility for user to add new sensors and C language interface. Recently, NASA/MSFC CAVE lab provides VR systems built on Sense8 WorldToolKit (WTK) which is a C library for creating VR development environments. WTK provides device drivers for most of the sensors and eyephones available on the VR market. WTK accepts several CAD file formats, such as Sense8 Neutral File Format, AutoCAD DXF and 3D Studio file format, Wave Front OBJ file format, VideoScape GEO file format, Intergraph EMS stereolithographics and CATIA Stereolithographics STL file formats. WTK functions are object-oriented in their naming convention, are grouped into classes, and provide easy C language interface. Using a CAD or modelling program to build a VW for WTK VR applications, we typically construct the stationary universe with all the geometric objects except the dynamic objects, and create each dynamic object in an individual file.

Wang, Peter Hor-Ching↗
DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗
DOE OSTI2020

Modeling, analysis, and code/data validation of DIII-D tokamak divertor experiments on ELM and non-ELM plasma tungsten sputtering erosion

Abstract We analyzed recent DIII-D tokamak tungsten divertor probe experiments using advanced, coupled, sputter erosion/redeposition, plasma, and surface response code packages. Modeling is done for ELMing H-mode, and L-mode plasmas, impinging on various size tungsten deposits on Divertor Material Evaluation System (DiMES) carbon probes. The simulations compute 3D, full kinetic, sub-gyromotion, impurity sputtering and transport, including changes in tungsten surface composition and response due to mixed deuterium and carbon ions irradiation. Per our analysis, ELM (edge localized mode) plasma sputtering in DIII-D mostly involves free-streaming high energy (∼500–1000 eV) D + and C +6 ions, with high near-surface plasma density. L-Mode sputtering is due to impurity sputtering (C, W) only, with lower density. All cases show complete redeposition of tungsten on the divertor, with significant redeposition on the tungsten spots themselves, and low self-sputtering. Comparison of ELM plasma gross tungsten erosion simulation results with in-situ spectroscopic data is good, as are code/data comparisons of net erosion using post-exposure Rutherford backscattering (RBS) data for the L-mode probes. The analysis, extrapolated to a full tungsten divertor, implies low net erosion and negligible plasma contamination from sputtering. These results support the use of high-Z plasma facing surfaces in ITER and beyond.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Understanding and mitigating process drift in aerosol jet printing

Aerosol jet printing offers a versatile, high-resolution prototyping capability for flexible and hybrid electronics. Despite its rapid growth in recent years, persistent problems such as process drift hinder the adoption of this technology in production environments. Here we explore underlying causes of process drift during aerosol jet printing and introduce an engineered solution to improve deposition stability. In this work it is shown that the ink level within the cartridge is a critical factor in determining atomization efficiency, such that the reduction in ink volume resulting from printing itself can induce significant and systematic process drift. By integrating a custom 3D-printed cartridge with an ink recirculation system, ink composition and level within the cartridge are better maintained. This strategy allows extended duration printing with improved stability, as evidenced by 30 h of printing over 5 production runs. This provides an important tool for extending the duration and improving reliability for aerosol jet printing, a key factor for integration in practical manufacturing operations.

36 MATERIALS SCIENCE↗